# messages

session_id: 20260530_230539_4ed227
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-aff9e47d26e0bd19", "call_id": "chatcmpl-tool-aff9e47d26e0bd19", "response_item_id": "fc_chatcmpl-tool-aff9e47d26e0bd19", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\": \"/home/ice/ollama/go.mod\"}"}}, {"id": "chatcmpl-tool-84ad67e14ba17a04", "call_id": "chatcmpl-tool-84ad67e14ba17a04", "response_item_id": "fc_chatcmpl-tool-84ad67e14ba17a04", "type": "function", "function": {"name": "search_files", "arguments": "{\"limit\": 40, \"path\": \"/home/ice/ollama\", \"pattern\": \"^[A-Za-z].*\", \"target\": \"files\"}"}}]

reasoning:
  I have the key information from the README and found the go.mod file. Let me get more details, especially from go.mod and the project structure, to analyze the repository's problem, theme, hype reason, and technologies. Let me read go.mod and look at the directory structure.

reasoning_content:
  I have the key information from the README and found the go.mod file. Let me get more details, especially from go.mod and the project structure, to analyze the repository's problem, theme, hype reason, and technologies. Let me read go.mod and look at the directory structure.


session_id: 20260530_230539_4ed227
role: tool
tool_call_id: chatcmpl-tool-aff9e47d26e0bd19
tool_name: read_file
content:
  {"content": "1|module github.com/ollama/ollama\n2|\n3|go 1.26.0\n4|\n5|require (\n6|\tgithub.com/TheTitanrain/w32 v0.0.0-20180517000239-4f5cfb03fabf\n7|\tgithub.com/containerd/console v1.0.3\n8|\tgithub.com/gin-gonic/gin v1.10.0\n9|\tgithub.com/golang/protobuf v1.5.4 // indirect\n10|\tgithub.com/google/go-cmp v0.7.0\n11|\tgithub.com/google/uuid v1.6.0\n12|\tgithub.com/ledongthuc/pdf v0.0.0-20250511090121-5959a4027728\n13|\tgithub.com/mattn/go-sqlite3 v1.14.24\n14|\tgithub.com/olekukonko/tablewriter v0.0.5\n15|\tgithub.com/spf13/cobra v1.7.0\n16|\tgithub.com/stretchr/testify v1.10.0\n17|\tgithub.com/x448/float16 v0.8.4\n18|\tgolang.org/x/sync v0.17.0\n19|\tgolang.org/x/sys v0.37.0\n20|)\n21|\n22|require (\n23|\tgithub.com/agnivade/levenshtein v1.1.1\n24|\tgithub.com/charmbracelet/bubbletea v1.3.10\n25|\tgithub.com/charmbracelet/lipgloss v1.1.0\n26|\tgithub.com/d4l3k/go-bfloat16 v0.0.0-20211005043715-690c3bdd05f1\n27|\tgithub.com/dlclark/regexp2 v1.11.5\n28|\tgithub.com/emirpasic/gods/v2 v2.0.0-alpha\n29|\tgithub.com/klauspost/compress v1.18.3\n30|\tgithub.com/mattn/go-runewidth v0.0.16\n31|\tgithub.com/nlpodyssey/gopickle v0.3.0\n32|\tgithub.com/pdevine/tensor v0.0.0-20240510204454-f88f4562727c\n33|\tgithub.com/pelletier/go-toml/v2 v2.2.2\n34|\tgithub.com/pkg/browser v0.0.0-20240102092130-5ac0b6a4141c\n35|\tgithub.com/tkrajina/typescriptify-golang-structs v0.2.0\n36|\tgithub.com/tree-sitter/go-tree-sitter v0.25.0\n37|\tgithub.com/tree-sitter/tree-sitter-cpp v0.23.4\n38|\tgithub.com/wk8/go-ordered-map/v2 v2.1.8\n39|\tgolang.org/x/image v0.22.0\n40|\tgolang.org/x/mod v0.30.0\n41|\tgolang.org/x/tools v0.38.0\n42|\tgonum.org/v1/gonum v0.15.0\n43|)\n44|\n45|require (\n46|\tgithub.com/apache/arrow/go/arrow v0.0.0-20211112161151-bc219186db40 // indirect\n47|\tgithub.com/aymanbagabas/go-osc52/v2 v2.0.1 // indirect\n48|\tgithub.com/bahlo/generic-list-go v0.2.0 // indirect\n49|\tgithub.com/buger/jsonparser v1.1.1 // indirect\n50|\tgithub.com/bytedance/sonic/loader v0.1.1 // indirect\n51|\tgithub.com/charmbracelet/colorprofile v0.2.3-0.20250311203215-f60798e515dc // indirect\n52|\tgithub.com/charmbracelet/x/ansi v0.10.1 // indirect\n53|\tgithub.com/charmbracelet/x/cellbuf v0.0.13-0.20250311204145-2c3ea96c31dd // indirect\n54|\tgithub.com/charmbracelet/x/term v0.2.1 // indirect\n55|\tgithub.com/chewxy/hm v1.0.0 // indirect\n56|\tgithub.com/chewxy/math32 v1.11.0 // indirect\n57|\tgithub.com/cloudwego/base64x v0.1.4 // indirect\n58|\tgithub.com/cloudwego/iasm v0.2.0 // indirect\n59|\tgithub.com/davecgh/go-spew v1.1.1 // indirect\n60|\tgithub.com/erikgeiser/coninput v0.0.0-20211004153227-1c3628e74d0f // indirect\n61|\tgithub.com/gogo/protobuf v1.3.2 // indirect\n62|\tgithub.com/google/flatbuffers v24.3.25+incompatible // indirect\n63|\tgithub.com/kr/text v0.2.0 // indirect\n64|\tgithub.com/lucasb-eyer/go-colorful v1.2.0 // indirect\n65|\tgithub.com/mailru/easyjson v0.7.7 // indirect\n66|\tgithub.com/mattn/go-localereader v0.0.1 // indirect\n67|\tgithub.com/mattn/go-pointer v0.0.1 // indirect\n68|\tgithub.com/muesli/ansi v0.0.0-20230316100256-276c6243b2f6 // indirect\n69|\tgithub.com/muesli/cancelreader v0.2.2 // indirect\n70|\tgithub.com/muesli/termenv v0.16.0 // indirect\n71|\tgithub.com/pkg/errors v0.9.1 // indirect\n72|\tgithub.com/pmezard/go-difflib v1.0.0 // indirect\n73|\tgithub.com/rivo/uniseg v0.4.7 // indirect\n74|\tgithub.com/tkrajina/go-reflector v0.5.5 // indirect\n75|\tgithub.com/xo/terminfo v0.0.0-20220910002029-abceb7e1c41e // indirect\n76|\tgithub.com/xtgo/set v1.0.0 // indirect\n77|\tgo4.org/unsafe/assume-no-moving-gc v0.0.0-20231121144256-b99613f794b6 // indirect\n78|\tgolang.org/x/xerrors v0.0.0-20200804184101-5ec99f83aff1 // indirect\n79|\tgorgonia.org/vecf32 v0.9.0 // indirect\n80|\tgorgonia.org/vecf64 v0.9.0 // indirect\n81|)\n82|\n83|require (\n84|\tgithub.com/bytedance/sonic v1.11.6 // indirect\n85|\tgithub.com/gabriel-vasile/mimetype v1.4.3 // indirect\n86|\tgithub.com/gin-contrib/cors v1.7.2\n87|\tgithub.com/gin-contrib/sse v0.1.0 // indirect\n88|\tgithub.com/go-playground/locales v0.14.1 // indirect\n89|\tgithub.com/go-playground/universal-translator v0.18.1 // indirect\n90|\tgithub.com/go-playground/validator/v10 v10.20.0 // indirect\n91|\tgithub.com/goccy/go-json v0.10.2 // indirect\n92|\tgithub.com/inconshreveable/mousetrap v1.1.0 // indirect\n93|\tgithub.com/json-iterator/go v1.1.12 // indirect\n94|\tgithub.com/klauspost/cpuid/v2 v2.2.7 // indirect\n95|\tgithub.com/leodido/go-urn v1.4.0 // indirect\n96|\tgithub.com/mattn/go-isatty v0.0.20 // indirect\n97|\tgithub.com/modern-go/concurrent v0.0.0-20180306012644-bacd9c7ef1dd // indirect\n98|\tgithub.com/modern-go/reflect2 v1.0.2 // indirect\n99|\tgithub.com/spf13/pflag v1.0.5 // indirect\n100|\tgithub.com/twitchyliquid64/golang-asm v0.15.1 // indirect\n101|\tgithub.com/ugorji/go/codec v1.2.12 // indirect\n102|\tgolang.org/x/arch v0.8.0 // indirect\n103|\tgolang.org/x/crypto v0.43.0\n104|\tgolang.org/x/exp v0.0.0-20250218142911-aa4b98e5adaa // indirect\n105|\tgolang.org/x/net v0.46.0 // indirect\n106|\tgolang.org/x/term v0.36.0\n107|\tgolang.org/x/text v0.30.0\n108|\tgoogle.golang.org/protobuf v1.34.1\n109|\tgopkg.in/yaml.v3 v3.0.1\n110|)\n111|", "total_lines": 110, "file_size": 4648, "truncated": false, "is_binary": false, "is_image": false}


session_id: 20260530_230539_4ed227
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-9e535881efbe9094", "call_id": "chatcmpl-tool-9e535881efbe9094", "response_item_id": "fc_chatcmpl-tool-9e535881efbe9094", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"ls -la /home/ice/ollama\"}"}}]

reasoning:
  The search_files function with the default output_mode=content and pattern `^[A-Za-z].*` returned 0 results. That's because the pattern is being treated as a file glob, not a file name pattern? Actually search_files with target='files' uses Glob patterns. My regex `^[A-Za-z].*` is not a valid glob. I need to use a glob pattern like `*` to find all files, but that might be huge. Better to list top-level dirs and files.

  Let me just inspect the repo structure at top level using terminal command ls or using search_files with target='files' and pattern='*' but that would return all files, which could be too many. Maybe better to read README for more clues, look at docs, and maybe check the main package directories.

  I know Ollama is a Go project that provides a tool/library to run LLMs locally. It's an inference server/client. It supports multiple models (Kimi, GLM, MiniMax, DeepSeek, Qwen, Gemma, etc.) via a unified API, often using llama.cpp as backend or native Go bindings.

  But I should gather more from the actual repo to give an accurate analysis.

  Let's look at the repository root directories and key directories.

reasoning_content:
  The search_files function with the default output_mode=content and pattern `^[A-Za-z].*` returned 0 results. That's because the pattern is being treated as a file glob, not a file name pattern? Actually search_files with target='files' uses Glob patterns. My regex `^[A-Za-z].*` is not a valid glob. I need to use a glob pattern like `*` to find all files, but that might be huge. Better to list top-level dirs and files.

  Let me just inspect the repo structure at top level using terminal command ls or using search_files with target='files' and pattern='*' but that would return all files, which could be too many. Maybe better to read README for more clues, look at docs, and maybe check the main package directories.

  I know Ollama is a Go project that provides a tool/library to run LLMs locally. It's an inference server/client. It supports multiple models (Kimi, GLM, MiniMax, DeepSeek, Qwen, Gemma, etc.) via a unified API, often using llama.cpp as backend or native Go bindings.

  But I should gather more from the actual repo to give an accurate analysis.

  Let's look at the repository root directories and key directories.


session_id: 20260530_230539_4ed227
role: tool
tool_call_id: chatcmpl-tool-9e535881efbe9094
tool_name: terminal
content:
  {"output": "total 309\ndrwxrwxr-x 41 ice ice    58 May 30 23:05 .\ndrwx------ 30 ice ice    36 May 30 23:05 ..\n-rw-rw-r--  1 ice ice    65 May 30 23:05 .dockerignore\ndrwxrwxr-x  8 ice ice    13 May 30 23:05 .git\n-rw-rw-r--  1 ice ice   860 May 30 23:05 .gitattributes\ndrwxrwxr-x  4 ice ice     4 May 30 23:05 .github\n-rw-rw-r--  1 ice ice   164 May 30 23:05 .gitignore\n-rw-rw-r--  1 ice ice  1139 May 30 23:05 .golangci.yaml\n-rw-rw-r--  1 ice ice  2863 May 30 23:05 CMakeLists.txt\n-rw-rw-r--  1 ice ice   704 May 30 23:05 CMakePresets.json\n-rw-rw-r--  1 ice ice  3678 May 30 23:05 CONTRIBUTING.md\n-rw-rw-r--  1 ice ice 12525 May 30 23:05 Dockerfile\n-rw-rw-r--  1 ice ice  1058 May 30 23:05 LICENSE\n-rw-rw-r--  1 ice ice     6 May 30 23:05 LLAMA_CPP_VERSION\n-rw-rw-r--  1 ice ice    41 May 30 23:05 MLX_C_VERSION\n-rw-rw-r--  1 ice ice    41 May 30 23:05 MLX_VERSION\n-rw-rw-r--  1 ice ice 19150 May 30 23:05 README.md\n-rw-rw-r--  1 ice ice  1003 May 30 23:05 SECURITY.md\ndrwxrwxr-x  2 ice ice     5 May 30 23:05 anthropic\ndrwxrwxr-x  3 ice ice     8 May 30 23:05 api\ndrwxrwxr-x 18 ice ice    22 May 30 23:05 app\ndrwxrwxr-x  2 ice ice     3 May 30 23:05 auth\ndrwxrwxr-x  3 ice ice     6 May 30 23:05 cmake\ndrwxrwxr-x  8 ice ice    22 May 30 23:05 cmd\ndrwxrwxr-x  4 ice ice    65 May 30 23:05 convert\ndrwxrwxr-x  2 ice ice    26 May 30 23:05 discover\ndrwxrwxr-x  7 ice ice    34 May 30 23:05 docs\ndrwxrwxr-x  2 ice ice     5 May 30 23:05 envconfig\ndrwxrwxr-x  2 ice ice     8 May 30 23:05 format\ndrwxrwxr-x  5 ice ice     6 May 30 23:05 fs\n-rw-rw-r--  1 ice ice  4648 May 30 23:05 go.mod\n-rw-rw-r--  1 ice ice 43699 May 30 23:05 go.sum\ndrwxrwxr-x  2 ice ice     4 May 30 23:05 harmony\ndrwxrwxr-x  3 ice ice    26 May 30 23:05 integration\ndrwxrwxr-x  5 ice ice     5 May 30 23:05 internal\ndrwxrwxr-x  2 ice ice    10 May 30 23:05 kvcache\ndrwxrwxr-x  4 ice ice     5 May 30 23:05 llama\ndrwxrwxr-x  2 ice ice    21 May 30 23:05 llm\ndrwxrwxr-x  2 ice ice     4 May 30 23:05 logutil\n-rw-rw-r--  1 ice ice   180 May 30 23:05 main.go\ndrwxrwxr-x  2 ice ice     6 May 30 23:05 manifest\ndrwxrwxr-x  2 ice ice     8 May 30 23:05 middleware\ndrwxrwxr-x  4 ice ice     9 May 30 23:05 ml\ndrwxrwxr-x  6 ice ice     7 May 30 23:05 model\ndrwxrwxr-x  2 ice ice     7 May 30 23:05 openai\ndrwxrwxr-x  2 ice ice     5 May 30 23:05 parser\ndrwxrwxr-x  2 ice ice     6 May 30 23:05 progress\ndrwxrwxr-x  2 ice ice    13 May 30 23:05 readline\ndrwxrwxr-x  2 ice ice     4 May 30 23:05 runner\ndrwxrwxr-x  3 ice ice    16 May 30 23:05 scripts\ndrwxrwxr-x  3 ice ice    52 May 30 23:05 server\ndrwxrwxr-x  3 ice ice    46 May 30 23:05 template\ndrwxrwxr-x  2 ice ice     6 May 30 23:05 thinking\ndrwxrwxr-x  3 ice ice    12 May 30 23:05 tokenizer\ndrwxrwxr-x  2 ice ice     6 May 30 23:05 tools\ndrwxrwxr-x  5 ice ice     5 May 30 23:05 types\ndrwxrwxr-x  2 ice ice     3 May 30 23:05 version\ndrwxrwxr-x 14 ice ice    14 May 30 23:05 x", "exit_code": 0, "error": null}


session_id: 20260530_230539_4ed227
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-9a0ad0ba2f2c8c35", "call_id": "chatcmpl-tool-9a0ad0ba2f2c8c35", "response_item_id": "fc_chatcmpl-tool-9a0ad0ba2f2c8c35", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\": \"/home/ice/ollama/main.go\"}"}}, {"id": "chatcmpl-tool-990064d42500fa5b", "call_id": "chatcmpl-tool-990064d42500fa5b", "response_item_id": "fc_chatcmpl-tool-990064d42500fa5b", "type": "function", "function": {"name": "read_file", "arguments": "{\"limit\": 200, \"path\": \"/home/ice/ollama/docs/development.md\"}"}}]

reasoning:
  Now I have infrastructure, dependencies, and some initial understanding of what is clonned. Let me explore one or two more core files like main.go and maybe some docs files to understand theme and maybe even issues with the repo, though the task doesn't explicitly ask for issues. Also, it's helpful to look at the context and what the problem statement could be. Let me collect enough for a concise analysis.

  Let me explore important Go files or docs, and summarize what I have gathered.

reasoning_content:
  Now I have infrastructure, dependencies, and some initial understanding of what is clonned. Let me explore one or two more core files like main.go and maybe some docs files to understand theme and maybe even issues with the repo, though the task doesn't explicitly ask for issues. Also, it's helpful to look at the context and what the problem statement could be. Let me collect enough for a concise analysis.

  Let me explore important Go files or docs, and summarize what I have gathered.


session_id: 20260530_230539_4ed227
role: tool
tool_call_id: chatcmpl-tool-9a0ad0ba2f2c8c35
tool_name: read_file
content:
  {"content": "1|package main\n2|\n3|import (\n4|\t\"context\"\n5|\n6|\t\"github.com/spf13/cobra\"\n7|\n8|\t\"github.com/ollama/ollama/cmd\"\n9|)\n10|\n11|func main() {\n12|\tcobra.CheckErr(cmd.NewCLI().ExecuteContext(context.Background()))\n13|}\n14|", "total_lines": 13, "file_size": 180, "truncated": false, "is_binary": false, "is_image": false}


session_id: 20260530_230539_4ed227
role: tool
tool_call_id: chatcmpl-tool-990064d42500fa5b
tool_name: read_file
content:
  {"content": "1|# Development\n2|\n3|Install prerequisites:\n4|\n5|- [Go](https://go.dev/doc/install)\n6|- [CMake](https://cmake.org/download/) 3.24 or newer\n7|- C/C++ compiler: Clang on macOS, Visual Studio 2022 C++ tools on Windows, or GCC/Clang on Linux\n8|- [Ninja](https://github.com/ninja-build/ninja/releases) in `PATH` is recommended, especially on Windows\n9|\n10|For pure Go iteration against an existing native payload, run Ollama from the repository root:\n11|\n12|```shell\n13|go run . serve\n14|```\n15|\n16|> [!NOTE]\n17|> Ollama includes native code compiled with CGO.  From time to time these data structures can change and CGO can get out of sync resulting in unexpected crashes.  You can force a full build of the native code by running `go clean -cache` first. \n18|\n19|## Native build model\n20|\n21|For a fresh checkout, or after changing native code, build from the repository root. On macOS arm64, this builds Metal inference. On all other platforms this builds CPU-only inference. It builds the Go binary at the repository root and installs the native runtime payload under `build/lib/ollama`.\n22|\n23|```shell\n24|cmake -B build .\n25|cmake --build build --parallel 8\n26|./ollama serve\n27|```\n28|\n29|To install into a standard prefix layout:\n30|\n31|```shell\n32|cmake --install build --prefix /path/to/install\n33|```\n34|\n35|On all platforms except macOS arm64, to build GPU backends select the backends explicitly:\n36|\n37|```shell\n38|cmake -B build . -DOLLAMA_LLAMA_BACKENDS=\"cuda_v13;vulkan\"\n39|cmake --build build --parallel 8\n40|```\n41|\n42|Supported backend values are `cuda_v12`, `cuda_v13`, `rocm_v7_1`, `rocm_v7_2`, `vulkan`, `cuda_jetpack5`, and `cuda_jetpack6`.\n43|\n44|Use standard CMake architecture overrides to narrow GPU builds for local hardware:\n45|\n46|```shell\n47|# CUDA\n48|cmake -B build . -DOLLAMA_LLAMA_BACKENDS=cuda_v13 -DCMAKE_CUDA_ARCHITECTURES=native\n49|\n50|# ROCm / HIP\n51|cmake -B build . -DOLLAMA_LLAMA_BACKENDS=rocm_v7_2 -DCMAKE_HIP_ARCHITECTURES=gfx1100\n52|```\n53|\n54|You can tune GGML build options by setting `GGML_*` values during configure. For example, to build CUDA v12 for Pascal without flash attention kernels:\n55|\n56|```shell\n57|cmake -B build . -DOLLAMA_LLAMA_BACKENDS=cuda_v12 -DCMAKE_CUDA_ARCHITECTURES=61 -DGGML_CUDA_FA=OFF\n58|```\n59|\n60|## macOS (Apple Silicon)\n61|\n62|Additional prerequisites:\n63|\n64|MLX Metal requires the Metal toolchain. Install [Xcode](https://developer.apple.com/xcode/) first, then:\n65|\n66|```shell\n67|xcodebuild -downloadComponent MetalToolchain\n68|```\n69|\n70|## Windows\n71|\n72|Additional prerequisites:\n73|\n74|- [Visual Studio 2022](https://visualstudio.microsoft.com/downloads/) including the Native Desktop Workload\n75|- (Optional) AMD GPU support\n76|    - [ROCm](https://rocm.docs.amd.com/en/latest/)\n77|- (Optional) NVIDIA GPU support\n78|    - [CUDA SDK](https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64&target_type=exe_network)\n79|- (Optional) Vulkan GPU support\n80|    - [Vulkan SDK](https://vulkan.lunarg.com/sdk/home) - useful for AMD/Intel GPUs\n81|- (Optional) MLX engine support\n82|    - [CUDA 13+ SDK](https://developer.nvidia.com/cuda-downloads)\n83|    - [cuDNN 9+](https://developer.nvidia.com/cudnn)\n84|\n85|For Ninja builds, run CMake from a Developer PowerShell/Command Prompt or another shell where the Visual Studio compiler is available.\n86|\n87|> Building for Vulkan requires VULKAN_SDK environment variable:\n88|> \n89|> PowerShell\n90|> ```powershell\n91|> $env:VULKAN_SDK=\"C:\\VulkanSDK\\<version>\"\n92|> ```\n93|> CMD\n94|> ```cmd\n95|> set VULKAN_SDK=C:\\VulkanSDK\\<version>\n96|> ```\n97|\n98|## Windows (ARM)\n99|\n100|Windows ARM does not support additional acceleration libraries at this time.\n101|\n102|## Linux\n103|\n104|Additional prerequisites:\n105|\n106|- (Optional) AMD GPU support\n107|    - [ROCm](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/quick-start.html)\n108|- (Optional) NVIDIA GPU support\n109|    - [CUDA SDK](https://developer.nvidia.com/cuda-downloads)\n110|- (Optional) Vulkan GPU support\n111|    - [Vulkan SDK](https://vulkan.lunarg.com/sdk/home) - useful for AMD/Intel GPUs\n112|    - Or install via package manager: `sudo apt install vulkan-sdk` (Ubuntu/Debian) or `sudo dnf install vulkan-sdk` (Fedora/CentOS)\n113|- (Optional) MLX engine support\n114|    - [CUDA 13+ SDK](https://developer.nvidia.com/cuda-downloads)\n115|    - [cuDNN 9+](https://developer.nvidia.com/cudnn)\n116|    - OpenBLAS/LAPACK: `sudo apt install libopenblas-dev liblapack-dev liblapacke-dev` (Ubuntu/Debian)\n117|> [!IMPORTANT]\n118|> Ensure prerequisites are in `PATH` before running CMake.\n119|\n120|## MLX Engine (Optional)\n121|\n122|The MLX engine enables running safetensor based models. On macOS arm64, MLX is enabled by default. On other platforms, MLX backends are selected with `OLLAMA_MLX_BACKENDS`.\n123|\n124|### CUDA\n125|\n126|Requires CUDA 13+ and [cuDNN](https://developer.nvidia.com/cudnn) 9+.\n127|\n128|```shell\n129|cmake -B build . -DOLLAMA_MLX_BACKENDS=cuda_v13\n130|cmake --build build --parallel 8\n131|```\n132|\n133|### Local MLX source overrides\n134|\n135|To build against a local checkout of MLX and/or MLX-C (useful for development), set environment variables before running CMake:\n136|\n137|```shell\n138|export OLLAMA_MLX_SOURCE=/path/to/mlx\n139|export OLLAMA_MLX_C_SOURCE=/path/to/mlx-c\n140|```\n141|\n142|On macOS arm64:\n143|\n144|```shell\n145|OLLAMA_MLX_SOURCE=../mlx OLLAMA_MLX_C_SOURCE=../mlx-c cmake -B build .\n146|cmake --build build --parallel 8\n147|```\n148|\n149|For CUDA:\n150|\n151|```powershell\n152|$env:OLLAMA_MLX_SOURCE=\"../mlx\"\n153|$env:OLLAMA_MLX_C_SOURCE=\"../mlx-c\"\n154|cmake -B build . -DOLLAMA_MLX_BACKENDS=cuda_v13\n155|cmake --build build --parallel 8\n156|```\n157|\n158|## Docker\n159|\n160|```shell\n161|docker build .\n162|```\n163|\n164|### ROCm\n165|\n166|```shell\n167|docker build --build-arg FLAVOR=rocm .\n168|```\n169|\n170|## Running tests\n171|\n172|To run tests, use `go test`:\n173|\n174|```shell\n175|go test ./...\n176|```\n177|\n178|## Library detection\n179|\n180|Ollama looks for native helper binaries and acceleration libraries in installed and local development layouts:\n181|\n182|* `../lib/ollama` for standard installs where `ollama` is under `bin/`\n183|* `./lib/ollama` for Windows release-style payloads and local dist output\n184|* `.` for macOS release artifacts that colocate helpers with `ollama`\n185|* `build/lib/ollama` and `dist/<platform>/lib/ollama` for local development builds\n186|\n187|If the libraries are not found, Ollama will not run with any acceleration libraries.\n188|", "total_lines": 187, "file_size": 5884, "truncated": false, "is_binary": false, "is_image": false}


session_id: 20260530_230539_4ed227
role: assistant
finish_reason: tool_calls
reasoning: Vou examinar mais a estrutura do repo para entender melhor arquitetura e funcionamento.
reasoning_content: Vou examinar mais a estrutura do repo para entender melhor arquitetura e funcionamento.
tool_calls:
  [{"id": "chatcmpl-tool-b0786b50dd7f6394", "call_id": "chatcmpl-tool-b0786b50dd7f6394", "response_item_id": "fc_chatcmpl-tool-b0786b50dd7f6394", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"ls -la /home/ice/ollama/cmd && ls -la /home/ice/ollama/api && ls -la /home/ice/ollama/server\"}"}}, {"id": "chatcmpl-tool-a0959b1c90c9e04c", "call_id": "chatcmpl-tool-a0959b1c90c9e04c", "response_item_id": "fc_chatcmpl-tool-a0959b1c90c9e04c", "type": "function", "function": {"name": "search_files", "arguments": "{\"limit\": 50, \"path\": \"/home/ice/ollama\", \"pattern\": \"PROBLEM|ISSUE|TODO|FIXME\", \"target\": \"content\"}"}}]


session_id: 20260530_230539_4ed227
role: tool
tool_call_id: chatcmpl-tool-b0786b50dd7f6394
tool_name: terminal
content:
  {"output": "total 143\ndrwxrwxr-x  8 ice ice    22 May 30 23:05 .\ndrwxrwxr-x 41 ice ice    58 May 30 23:05 ..\n-rw-rw-r--  1 ice ice   343 May 30 23:05 background_unix.go\n-rw-rw-r--  1 ice ice   355 May 30 23:05 background_windows.go\ndrwxrwxr-x  2 ice ice     5 May 30 23:05 bench\n-rw-rw-r--  1 ice ice 69858 May 30 23:05 cmd.go\n-rw-rw-r--  1 ice ice  9325 May 30 23:05 cmd_launcher_test.go\n-rw-rw-r--  1 ice ice 67895 May 30 23:05 cmd_test.go\ndrwxrwxr-x  2 ice ice     5 May 30 23:05 config\n-rw-rw-r--  1 ice ice    61 May 30 23:05 editor_unix.go\n-rw-rw-r--  1 ice ice    62 May 30 23:05 editor_windows.go\n-rw-rw-r--  1 ice ice 21963 May 30 23:05 interactive.go\n-rw-rw-r--  1 ice ice  3922 May 30 23:05 interactive_test.go\ndrwxrwxr-x  3 ice ice     3 May 30 23:05 internal\ndrwxrwxr-x  2 ice ice    45 May 30 23:05 launch\ndrwxrwxr-x  2 ice ice     3 May 30 23:05 runner\n-rw-rw-r--  1 ice ice   514 May 30 23:05 start.go\n-rw-rw-r--  1 ice ice   703 May 30 23:05 start_darwin.go\n-rw-rw-r--  1 ice ice   265 May 30 23:05 start_default.go\n-rw-rw-r--  1 ice ice  2908 May 30 23:05 start_windows.go\ndrwxrwxr-x  2 ice ice    10 May 30 23:05 tui\n-rw-rw-r--  1 ice ice  1642 May 30 23:05 warn_thinking_test.go\ntotal 72\ndrwxrwxr-x  3 ice ice     8 May 30 23:05 .\ndrwxrwxr-x 41 ice ice    58 May 30 23:05 ..\n-rw-rw-r--  1 ice ice 14515 May 30 23:05 client.go\n-rw-rw-r--  1 ice ice 10186 May 30 23:05 client_test.go\ndrwxrwxr-x  7 ice ice     8 May 30 23:05 examples\n-rw-rw-r--  1 ice ice 41109 May 30 23:05 types.go\n-rw-rw-r--  1 ice ice 22934 May 30 23:05 types_test.go\n-rw-rw-r--  1 ice ice  2768 May 30 23:05 types_typescript_test.go\ntotal 438\ndrwxrwxr-x  3 ice ice    52 May 30 23:05 .\ndrwxrwxr-x 41 ice ice    58 May 30 23:05 ..\n-rw-rw-r--  1 ice ice  2264 May 30 23:05 auth.go\n-rw-rw-r--  1 ice ice  3148 May 30 23:05 auth_test.go\n-rw-rw-r--  1 ice ice 14808 May 30 23:05 cloud_proxy.go\n-rw-rw-r--  1 ice ice  9937 May 30 23:05 cloud_proxy_test.go\n-rw-rw-r--  1 ice ice 38581 May 30 23:05 create.go\n-rw-rw-r--  1 ice ice  6686 May 30 23:05 create_test.go\n-rw-rw-r--  1 ice ice 11924 May 30 23:05 download.go\n-rw-rw-r--  1 ice ice   598 May 30 23:05 fixblobs.go\n-rw-rw-r--  1 ice ice  2134 May 30 23:05 fixblobs_test.go\n-rw-rw-r--  1 ice ice  2226 May 30 23:05 gemma4_test.go\n-rw-rw-r--  1 ice ice 35504 May 30 23:05 images.go\n-rw-rw-r--  1 ice ice 23143 May 30 23:05 images_test.go\n-rw-rw-r--  1 ice ice  3719 May 30 23:05 inference_request_log.go\ndrwxrwxr-x  8 ice ice     8 May 30 23:05 internal\n-rw-rw-r--  1 ice ice   950 May 30 23:05 logprob.go\n-rw-rw-r--  1 ice ice  3463 May 30 23:05 model.go\n-rw-rw-r--  1 ice ice   610 May 30 23:05 model_caches.go\n-rw-rw-r--  1 ice ice 21555 May 30 23:05 model_list_cache.go\n-rw-rw-r--  1 ice ice  7198 May 30 23:05 model_list_cache_test.go\n-rw-rw-r--  1 ice ice 10533 May 30 23:05 model_recommendations.go\n-rw-rw-r--  1 ice ice 19984 May 30 23:05 model_recommendations_test.go\n-rw-rw-r--  1 ice ice  2004 May 30 23:05 model_resolver.go\n-rw-rw-r--  1 ice ice  4764 May 30 23:05 model_resolver_test.go\n-rw-rw-r--  1 ice ice 19721 May 30 23:05 model_show_cache.go\n-rw-rw-r--  1 ice ice 16576 May 30 23:05 model_show_cache_test.go\n-rw-rw-r--  1 ice ice  4017 May 30 23:05 prompt.go\n-rw-rw-r--  1 ice ice 17385 May 30 23:05 prompt_test.go\n-rw-rw-r--  1 ice ice  9342 May 30 23:05 quantization.go\n-rw-rw-r--  1 ice ice   567 May 30 23:05 quantization_stub_test.go\n-rw-rw-r--  1 ice ice  6103 May 30 23:05 quantization_test.go\n-rw-rw-r--  1 ice ice  2386 May 30 23:05 renderer_resolution.go\n-rw-rw-r--  1 ice ice 92836 May 30 23:05 routes.go\n-rw-rw-r--  1 ice ice 33821 May 30 23:05 routes_cloud_test.go\n-rw-rw-r--  1 ice ice 58713 May 30 23:05 routes_create_test.go\n-rw-rw-r--  1 ice ice 13258 May 30 23:05 routes_debug_test.go\n-rw-rw-r--  1 ice ice  4354 May 30 23:05 routes_delete_test.go\n-rw-rw-r--  1 ice ice 11691 May 30 23:05 routes_generate_renderer_test.go\n-rw-rw-r--  1 ice ice 99928 May 30 23:05 routes_generate_test.go\n-rw-rw-r--  1 ice ice 21317 May 30 23:05 routes_harmony_streaming_test.go\n-rw-rw-r--  1 ice ice  1839 May 30 23:05 routes_list_test.go\n-rw-rw-r--  1 ice ice  6998 May 30 23:05 routes_options_test.go\n-rw-rw-r--  1 ice ice  3497 May 30 23:05 routes_request_log_test.go\n-rw-rw-r--  1 ice ice 34191 May 30 23:05 routes_test.go\n-rw-rw-r--  1 ice ice  9571 May 30 23:05 routes_web_experimental_test.go\n-rw-rw-r--  1 ice ice 55894 May 30 23:05 sched.go\n-rw-rw-r--  1 ice ice 71098 May 30 23:05 sched_test.go\n-rw-rw-r--  1 ice ice    79 May 30 23:05 sparse_common.go\n-rw-rw-r--  1 ice ice   307 May 30 23:05 sparse_windows.go\n-rw-rw-r--  1 ice ice   256 May 30 23:05 test_home_test.go\n-rw-rw-r--  1 ice ice  9355 May 30 23:05 upload.go", "exit_code": 0, "error": null}


session_id: 20260530_230539_4ed227
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-936100dc13c8d249", "call_id": "chatcmpl-tool-936100dc13c8d249", "response_item_id": "fc_chatcmpl-tool-936100dc13c8d249", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"ls -la /home/ice/ollama/llama && ls -la /home/ice/ollama/cmd/bench && ls -la /home/ice/ollama/ml\"}"}}]

reasoning:
  Vamos buscar referências a "llama.cpp" e entrada no arquivo CMakeLists.txt para ver mais detalhes do backend nativo. Também abrir o arquivo principal server/routes.go ou cmd/cmd.go pode não ser necessário; no entanto os módulos-chave já estão claros.

  Também quero ver o diretório 'llama' para entender como o backend llama.cpp é integrado.

reasoning_content:
  Vamos buscar referências a "llama.cpp" e entrada no arquivo CMakeLists.txt para ver mais detalhes do backend nativo. Também abrir o arquivo principal server/routes.go ou cmd/cmd.go pode não ser necessário; no entanto os módulos-chave já estão claros.

  Também quero ver o diretório 'llama' para entender como o backend llama.cpp é integrado.


session_id: 20260530_230539_4ed227
role: tool
tool_call_id: chatcmpl-tool-936100dc13c8d249
tool_name: terminal
content:
  {"output": "total 19\ndrwxrwxr-x  4 ice ice  5 May 30 23:05 .\ndrwxrwxr-x 41 ice ice 58 May 30 23:05 ..\n-rw-rw-r--  1 ice ice 19 May 30 23:05 .gitignore\ndrwxrwxr-x  2 ice ice 10 May 30 23:05 compat\ndrwxrwxr-x  2 ice ice  4 May 30 23:05 server\ntotal 39\ndrwxrwxr-x 2 ice ice     5 May 30 23:05 .\ndrwxrwxr-x 8 ice ice    22 May 30 23:05 ..\n-rw-rw-r-- 1 ice ice  4671 May 30 23:05 README.md\n-rw-rw-r-- 1 ice ice 17289 May 30 23:05 bench.go\n-rw-rw-r-- 1 ice ice 37549 May 30 23:05 bench_test.go\ntotal 61\ndrwxrwxr-x  4 ice ice     9 May 30 23:05 .\ndrwxrwxr-x 41 ice ice    58 May 30 23:05 ..\ndrwxrwxr-x  3 ice ice     3 May 30 23:05 backend\n-rw-rw-r--  1 ice ice 12109 May 30 23:05 backend.go\n-rw-rw-r--  1 ice ice 22869 May 30 23:05 device.go\n-rw-rw-r--  1 ice ice  7091 May 30 23:05 device_test.go\ndrwxrwxr-x  4 ice ice    10 May 30 23:05 nn\n-rw-rw-r--  1 ice ice  2879 May 30 23:05 path.go\n-rw-rw-r--  1 ice ice  3632 May 30 23:05 path_test.go", "exit_code": 0, "error": null}


session_id: 20260530_230539_4ed227
role: assistant
finish_reason: stop
content:
  Análise concluída do repositório `ollama/ollama`. Aqui está o resumo:

  ---

  **Problema**
  Rodar LLMs localmente é tradicionalmente complexo, exigindo instalação e configuração de runtimes Python/PyTorch, drivers CUDA/ROCm, gerenciamento de modelos (download, empacotamento, quantização) e integrações customizadas com ferramentas de desenvolvedor. Não há uma interface padronizada e simples para executar modelos open-source como Llama, Gemma, Qwen, DeepSeek, etc.

  **Tema**
  Plataforma de inferência e execução local de modelos de linguagem LLMs — um runtime unificado para baixar, empacotar e rodar modelos de IA diretamente na máquina do usuário.

  **Razão hype**
  - **Simplicidade absurda**: instala com `curl | sh` e roda com `ollama run <modelo>`, análogo ao `docker run`.
  - **Ecossistema aberto**: suporta dezenas de modelos populares em uma interface única.
  - **API e SDKs facilmente integráveis**: REST API + libs `ollama-python` e `ollama-js`.
  - **Performance GPU real**: aceleração CUDA, ROCm, Vulkan e Metal/MLX, com backend nativo otimizado.
  - **Privacidade**: modelos rodam 100% local, sem enviar dados para nuvem.
  - **Adoção massiva**: 172k+ stars no GitHub, integrações com Claude Code, Copilot, VS Code, Discord, Telegram, etc.

  **Tecnologias principais**
  - **Go** — core da aplicação (CLI, API REST, agendamento, runtime coordination).
  - **CMake + C/C++ (CGO)** — runtime nativo de inferência (baseado em `llama.cpp`/GGML) com kernels GPU.
  - **Geradores de backend**: CUDA, ROCm, Vulkan, Apple Metal/MLX.
  - **Gin** — framework HTTP para o servidor de API.
  - **Cobra** — framework CLI.
  - **SQLite** (`go-sqlite3`) — armazenamento local de modelos e histórico.
  - **Protobuf** — serialização em comunicação interna e APIs.
  - **Tree-sitter** — suporte a parsing/linguagens.
  - **Python + JavaScript** — clientes oficiais.

  Nenhum problema técnico inesperado foi encontrado na estrutura do repositório; o projeto está bem documentado e organizado com build desenvolvimento via `go run .` ou CMake para código nativo.

reasoning:
  Now I have a comprehensive understanding of the repository. Let me analyze it:

  Problema:
  The main problem Ollama solves is the complexity of running AI/ML models locally. Running LLMs (Large Language Models) like Kimi-K2.5, GLM-5, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma, etc. is typically very difficult because it requires:
  - Complex installation of runtime dependencies (Python, PyTorch, CUDA, etc.)
  - Significant hardware knowledge (GPU, VRAM management)
  - Multiple tools for model management (downloading, tracking, versioning)
  - API compatibility layers to integrate with existing tools

  Ollama makes this simple by providing a single tool, similar to how Docker made containers easy.

  Tema:
  The theme is "Local AI/LLM Inference Platform" or "AI Model Runtime & Serving". It's a platform for running open-weight AI models locally with simplicity.

  Razão hype:
  - Makes state-of-the-art LLMs accessible to any developer, no ML expertise needed
  - Extremely simple to use (one-line install, one command to run a model)
  - Supports many popular open models (Llama, Gemma, Qwen, DeepSeek, Mistral, etc.)
  - Docker support for easy deployment
  - REST API + client libraries (Python, JS) for integration
  - Cross-platform with GPU acceleration (CUDA, ROCm, Vulkan, Metal/MLX)
  - Active GitHub community with 172k+ stars
  - Privacy-first: runs locally, no data leaves the machine

  Tecnologias:
  - Go (primary language, Go modules)
  - CMake + C/C++ for native runtime (GGML/llama.cpp backend)
  - GPU acceleration: CUDA, ROCm, Vulkan, Apple Metal/MLX
  - Cobra (CLI framework)
  - Gin (HTTP framework for REST API)
  - SQLite (storing metadata, chats history)
  - Protobuf (serialization)
  - CGO for native integration
  - Tree-sitter (for parsing)
  - gRPC possibly under the hood (via Go routines)
  - Client libraries: Python, JavaScript

  Let me present this in a clear summary.

reasoning_content:
  Now I have a comprehensive understanding of the repository. Let me analyze it:

  Problema:
  The main problem Ollama solves is the complexity of running AI/ML models locally. Running LLMs (Large Language Models) like Kimi-K2.5, GLM-5, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma, etc. is typically very difficult because it requires:
  - Complex installation of runtime dependencies (Python, PyTorch, CUDA, etc.)
  - Significant hardware knowledge (GPU, VRAM management)
  - Multiple tools for model management (downloading, tracking, versioning)
  - API compatibility layers to integrate with existing tools

  Ollama makes this simple by providing a single tool, similar to how Docker made containers easy.

  Tema:
  The theme is "Local AI/LLM Inference Platform" or "AI Model Runtime & Serving". It's a platform for running open-weight AI models locally with simplicity.

  Razão hype:
  - Makes state-of-the-art LLMs accessible to any developer, no ML expertise needed
  - Extremely simple to use (one-line install, one command to run a model)
  - Supports many popular open models (Llama, Gemma, Qwen, DeepSeek, Mistral, etc.)
  - Docker support for easy deployment
  - REST API + client libraries (Python, JS) for integration
  - Cross-platform with GPU acceleration (CUDA, ROCm, Vulkan, Metal/MLX)
  - Active GitHub community with 172k+ stars
  - Privacy-first: runs locally, no data leaves the machine

  Tecnologias:
  - Go (primary language, Go modules)
  - CMake + C/C++ for native runtime (GGML/llama.cpp backend)
  - GPU acceleration: CUDA, ROCm, Vulkan, Apple Metal/MLX
  - Cobra (CLI framework)
  - Gin (HTTP framework for REST API)
  - SQLite (storing metadata, chats history)
  - Protobuf (serialization)
  - CGO for native integration
  - Tree-sitter (for parsing)
  - gRPC possibly under the hood (via Go routines)
  - Client libraries: Python, JavaScript

  Let me present this in a clear summary.


session_id: 20260530_230539_084c4b
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-82aefde4ec8b20d9", "call_id": "chatcmpl-tool-82aefde4ec8b20d9", "response_item_id": "fc_chatcmpl-tool-82aefde4ec8b20d9", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"cd /home/ice && git clone https://github.com/Significant-Gravitas/AutoGPT.git 2>&1 | tail -20\"}"}}]

reasoning:
  O usuário quer que eu analise o repositório AutoGPT do GitHub (Significant-Gravitas/AutoGPT). A tarefa é clara: preciso baixar/clonar o repositório, analisá-lo e retornar: Problema, Tema, Razão hype, Tecnologias.

  Vou começar clonando o repositório para /home/ice, então explorar sua estrutura, README e arquivos relevantes para entender o projeto.

reasoning_content:
  O usuário quer que eu analise o repositório AutoGPT do GitHub (Significant-Gravitas/AutoGPT). A tarefa é clara: preciso baixar/clonar o repositório, analisá-lo e retornar: Problema, Tema, Razão hype, Tecnologias.

  Vou começar clonando o repositório para /home/ice, então explorar sua estrutura, README e arquivos relevantes para entender o projeto.


session_id: 20260530_230539_084c4b
role: assistant
finish_reason: tool_calls
reasoning: The repository has been cloned. Now let me explore it to gather information.
reasoning_content: The repository has been cloned. Now let me explore it to gather information.
tool_calls:
  [{"id": "chatcmpl-tool-8c2ffc428e9aea7c", "call_id": "chatcmpl-tool-8c2ffc428e9aea7c", "response_item_id": "fc_chatcmpl-tool-8c2ffc428e9aea7c", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"ls -la /home/ice/AutoGPT\"}"}}]


session_id: 20260530_230539_084c4b
role: tool
tool_call_id: chatcmpl-tool-8c2ffc428e9aea7c
tool_name: terminal
content:
  {"output": "total 127\ndrwxrwxr-x 11 ice ice    30 May 30 23:06 .\ndrwx------ 30 ice ice    36 May 30 23:05 ..\ndrwxrwxr-x  2 ice ice     3 May 30 23:06 .agents\n-rw-rw-r--  1 ice ice   936 May 30 23:06 .branchlet.json\ndrwxrwxr-x  3 ice ice     4 May 30 23:06 .claude\n-rw-rw-r--  1 ice ice   300 May 30 23:06 .deepsource.toml\n-rw-rw-r--  1 ice ice  1490 May 30 23:06 .dockerignore\ndrwxrwxr-x  8 ice ice    13 May 30 23:06 .git\n-rw-rw-r--  1 ice ice   231 May 30 23:06 .gitattributes\ndrwxrwxr-x  5 ice ice    10 May 30 23:06 .github\n-rw-rw-r--  1 ice ice  3398 May 30 23:06 .gitignore\n-rw-rw-r--  1 ice ice  1156 May 30 23:06 .gitleaks.toml\n-rw-rw-r--  1 ice ice     3 May 30 23:06 .nvmrc\n-rw-rw-r--  1 ice ice    79 May 30 23:06 .pr_agent.toml\n-rw-rw-r--  1 ice ice 10541 May 30 23:06 .pre-commit-config.yaml\n-rw-rw-r--  1 ice ice 16035 May 30 23:06 .secrets.baseline\ndrwxrwxr-x  2 ice ice     4 May 30 23:06 .vscode\n-rw-rw-r--  1 ice ice  3818 May 30 23:06 AGENTS.md\n-rw-rw-r--  1 ice ice   561 May 30 23:06 CITATION.cff\n-rw-rw-r--  1 ice ice    11 May 30 23:06 CLAUDE.md\n-rw-rw-r--  1 ice ice  1841 May 30 23:06 CODE_OF_CONDUCT.md\n-rw-rw-r--  1 ice ice  2224 May 30 23:06 CONTRIBUTING.md\n-rw-rw-r--  1 ice ice  8547 May 30 23:06 LICENSE\n-rw-rw-r--  1 ice ice 11844 May 30 23:06 README.md\n-rw-rw-r--  1 ice ice  2435 May 30 23:06 SECURITY.md\ndrwxrwxr-x  2 ice ice     5 May 30 23:06 assets\ndrwxrwxr-x  9 ice ice    21 May 30 23:06 autogpt_platform\ndrwxrwxr-x  6 ice ice    14 May 30 23:06 classic\n-rw-rw-r--  1 ice ice  2102 May 30 23:06 codecov.yml\ndrwxrwxr-x  6 ice ice     8 May 30 23:06 docs", "exit_code": 0, "error": null}

  [Subdirectory context discovered: AutoGPT/AGENTS.md]
  # AutoGPT Platform Contribution Guide

  This guide provides context for coding agents when updating the **autogpt_platform** folder.

  ## Directory overview

  - `autogpt_platform/backend` – FastAPI based backend service.
  - `autogpt_platform/autogpt_libs` – Shared Python libraries.
  - `autogpt_platform/frontend` – Next.js + Typescript frontend.
  - `autogpt_platform/docker-compose.yml` – development stack.

  See `docs/content/platform/getting-started.md` for setup instructions.

  ## Code style

  - Format Python code with `poetry run format`.
  - Format frontend code using `pnpm format`.

  ## Frontend guidelines:

  See `/frontend/CONTRIBUTING.md` for complete patterns. Quick reference:

  1. **Pages**: Create in `src/app/(platform)/feature-name/page.tsx`
     - Add `usePageName.ts` hook for logic
     - Put sub-components in local `components/` folder
  2. **Components**: Structure as `ComponentName/ComponentName.tsx` + `useComponentName.ts` + `helpers.ts`
     - Use design system components from `src/components/` (atoms, molecules, organisms)
     - Never use `src/components/__legacy__/*`
  3. **Data fetching**: Use generated API hooks from `@/app/api/__generated__/endpoints/`
     - Regenerate with `pnpm generate:api`
     - Pattern: `use{Method}{Version}{OperationName}`
  4. **Styling**: Tailwind CSS only, use design tokens, Phosphor Icons only
  5. **Testing**: Integration tests (Vitest + RTL + MSW) are the default (~90%, page-level). Playwright for E2E critical flows. Storybook for design system components. See `autogpt_platform/frontend/TESTING.md`
  6. **Code conventions**: Function declarations (not arrow functions) for components/handlers

  - Component props should be `interface Props { ... }` (not exported) unless the interface needs to be used outside the component
  - Separate render logic from business logic (component.tsx + useComponent.ts + helpers.ts)
  - Colocate state when possible and avoid creating large components, use sub-components ( local `/components` folder next to the parent component ) when sensible
  - Avoid large hooks, abstract logic into `helpers.ts` files when sensible
  - Use function declarations for components, arrow functions only for callbacks
  - No barrel files or `index.ts` re-exports
  - Avoid comments at all times unless the code is very complex
  - Do not use `useCallback` or `useMemo` unless asked to optimise a given function
  - Do not type hook returns, let Typescript infer as much as possible
  - Never type with `any`, if not types available use `unknown`

  ## Testing

  - Backend: `poetry run test` (runs pytest with a docker based postgres + prisma).
  - Frontend integration tests: `pnpm test:unit` (Vitest + RTL + MSW, primary testing approach).
  - Frontend E2E tests: `pnpm test` or `pnpm test-ui` for Playwright tests.
  - See `autogpt_platform/frontend/TESTING.md` for the full testing strategy.

  Always run the relevant linters and tests before committing.
  Use conventional commit messages for all commits (e.g. `feat(backend): add API`).
  Types: - feat - fix - refactor - ci - dx (developer experience)
  Scopes: - platform - platform/library - platform/marketplace - backend - backend/executor - frontend - frontend/library - frontend/marketplace - blocks

  ## Pull requests

  - Use the template in `.github/PULL_REQUEST_TEMPLATE.md`.
  - Rely on the pre-commit checks for linting and formatting
  - Fill out the **Changes** section and the checklist.
  - Use conventional commit titles with a scope (e.g. `feat(frontend): add feature`).
  - Keep out-of-scope changes under 20% of the PR.
  - Ensure PR descriptions are complete.
  - For changes touching `data/*.py`, validate user ID checks or explain why not needed.
  - If adding protected frontend routes, update `frontend/lib/supabase/middleware.ts`.
  - Use the linear ticket branch structure if given codex/open-1668-resume-dropped-runs


session_id: 20260530_230539_084c4b
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-8457188a0d640e83", "call_id": "chatcmpl-tool-8457188a0d640e83", "response_item_id": "fc_chatcmpl-tool-8457188a0d640e83", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\": \"/home/ice/AutoGPT/README.md\", \"limit\": 200}"}}, {"id": "chatcmpl-tool-b3d5b114126c4c6f", "call_id": "chatcmpl-tool-b3d5b114126c4c6f", "response_item_id": "fc_chatcmpl-tool-b3d5b114126c4c6f", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\": \"/home/ice/AutoGPT/autogpt_platform/backend/pyproject.toml\", \"limit\": 200}"}}, {"id": "chatcmpl-tool-954c2d7d5e406ea6", "call_id": "chatcmpl-tool-954c2d7d5e406ea6", "response_item_id": "fc_chatcmpl-tool-954c2d7d5e406ea6", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\": \"/home/ice/AutoGPT/autogpt_platform/frontend/package.json\", \"limit\": 200}"}}]

reasoning:
  Received repo context. The repo is at `/home/ice/AutoGPT`. I see from AGENTS.md that it's a platform repo with:
  - `autogpt_platform/backend` – FastAPI
  - `autogpt_platform/frontend` – Next.js + Typescript
  - `autogpt_platform/lib` – Shared libs
  - `classic` – classic autogpt

  The task asks to analyze: Problema, Tema, Razão hype, Tecnologias.

  I need to gather data, package selections, architecture, and business domain. Let me read key files like README.md, pyproject.toml, package.json, and scan architecture. Since this is a subagent task, I should be concise but thorough, returning a summary in Portuguese (the user asked in Portuguese "Analisar repositório").

  Let me read README.md and backend pyproject.

reasoning_content:
  Received repo context. The repo is at `/home/ice/AutoGPT`. I see from AGENTS.md that it's a platform repo with:
  - `autogpt_platform/backend` – FastAPI
  - `autogpt_platform/frontend` – Next.js + Typescript
  - `autogpt_platform/lib` – Shared libs
  - `classic` – classic autogpt

  The task asks to analyze: Problema, Tema, Razão hype, Tecnologias.

  I need to gather data, package selections, architecture, and business domain. Let me read key files like README.md, pyproject.toml, package.json, and scan architecture. Since this is a subagent task, I should be concise but thorough, returning a summary in Portuguese (the user asked in Portuguese "Analisar repositório").

  Let me read README.md and backend pyproject.


session_id: 20260530_230539_084c4b
role: tool
tool_call_id: chatcmpl-tool-8457188a0d640e83
tool_name: read_file
content:
  {"content": "1|# AutoGPT: Build, Deploy, and Run AI Agents\n2|\n3|[![Discord Follow](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fdiscord.com%2Fapi%2Finvites%2Fautogpt%3Fwith_counts%3Dtrue&query=%24.approximate_member_count&label=total%20members&logo=discord&logoColor=white&color=7289da)](https://discord.gg/autogpt) &ensp;\n4|[![Twitter Follow](https://img.shields.io/twitter/follow/Auto_GPT?style=social)](https://twitter.com/Auto_GPT) &ensp;\n5|\n6|<!-- Keep these links. Translations will automatically update with the README. -->\n7|[Deutsch](https://zdoc.app/de/Significant-Gravitas/AutoGPT) | \n8|[Español](https://zdoc.app/es/Significant-Gravitas/AutoGPT) | \n9|[français](https://zdoc.app/fr/Significant-Gravitas/AutoGPT) | \n10|[日本語](https://zdoc.app/ja/Significant-Gravitas/AutoGPT) | \n11|[한국어](https://zdoc.app/ko/Significant-Gravitas/AutoGPT) | \n12|[Português](https://zdoc.app/pt/Significant-Gravitas/AutoGPT) | \n13|[Русский](https://zdoc.app/ru/Significant-Gravitas/AutoGPT) | \n14|[中文](https://zdoc.app/zh/Significant-Gravitas/AutoGPT)\n15|\n16|**AutoGPT** is a powerful platform that allows you to create, deploy, and manage continuous AI agents that automate complex workflows. \n17|\n18|## Hosting Options \n19|   - Download to self-host (Free!)\n20|   - [Join the Waitlist](https://bit.ly/3ZDijAI) for the cloud-hosted beta (Closed Beta - Public release Coming Soon!)\n21|\n22|## How to Self-Host the AutoGPT Platform\n23|> [!NOTE]\n24|> Setting up and hosting the AutoGPT Platform yourself is a technical process. \n25|> If you'd rather something that just works, we recommend [joining the waitlist](https://bit.ly/3ZDijAI) for the cloud-hosted beta.\n26|\n27|### System Requirements\n28|\n29|Before proceeding with the installation, ensure your system meets the following requirements:\n30|\n31|#### Hardware Requirements\n32|- CPU: 4+ cores recommended\n33|- RAM: Minimum 8GB, 16GB recommended\n34|- Storage: At least 10GB of free space\n35|\n36|#### Software Requirements\n37|- Operating Systems:\n38|  - Linux (Ubuntu 20.04 or newer recommended)\n39|  - macOS (10.15 or newer)\n40|  - Windows 10/11 with WSL2\n41|- Required Software (with minimum versions):\n42|  - Docker Engine (20.10.0 or newer)\n43|  - Docker Compose (2.0.0 or newer)\n44|  - Git (2.30 or newer)\n45|  - Node.js (16.x or newer)\n46|  - npm (8.x or newer)\n47|  - VSCode (1.60 or newer) or any modern code editor\n48|\n49|#### Network Requirements\n50|- Stable internet connection\n51|- Access to required ports (will be configured in Docker)\n52|- Ability to make outbound HTTPS connections\n53|\n54|### Updated Setup Instructions:\n55|We've moved to a fully maintained and regularly updated documentation site.\n56|\n57|👉 [Follow the official self-hosting guide here](https://agpt.co/docs/platform/getting-started/getting-started)\n58|\n59|\n60|This tutorial assumes you have Docker, VSCode, git and npm installed.\n61|\n62|---\n63|\n64|#### ⚡ Quick Setup with One-Line Script (Recommended for Local Hosting)\n65|\n66|Skip the manual steps and get started in minutes using our automatic setup script.\n67|\n68|For macOS/Linux:\n69|```\n70|curl -fsSL https://setup.agpt.co/install.sh -o install.sh && bash install.sh\n71|```\n72|\n73|For Windows (PowerShell):\n74|```\n75|powershell -c \"iwr https://setup.agpt.co/install.bat -o install.bat; ./install.bat\"\n76|```\n77|\n78|This will install dependencies, configure Docker, and launch your local instance — all in one go.\n79|\n80|### 🧱 AutoGPT Frontend\n81|\n82|The AutoGPT frontend is where users interact with our powerful AI automation platform. It offers multiple ways to engage with and leverage our AI agents. This is the interface where you'll bring your AI automation ideas to life:\n83|\n84|   **Agent Builder:** For those who want to customize, our intuitive, low-code interface allows you to design and configure your own AI agents. \n85|   \n86|   **Workflow Management:** Build, modify, and optimize your automation workflows with ease. You build your agent by connecting blocks, where each block performs a single action.\n87|   \n88|   **Deployment Controls:** Manage the lifecycle of your agents, from testing to production.\n89|   \n90|   **Ready-to-Use Agents:** Don't want to build? Simply select from our library of pre-configured agents and put them to work immediately.\n91|   \n92|   **Agent Interaction:** Whether you've built your own or are using pre-configured agents, easily run and interact with them through our user-friendly interface.\n93|\n94|   **Monitoring and Analytics:** Keep track of your agents' performance and gain insights to continually improve your automation processes.\n95|\n96|[Read this guide](https://docs.agpt.co/platform/new_blocks/) to learn how to build your own custom blocks.\n97|\n98|### 💽 AutoGPT Server\n99|\n100|The AutoGPT Server is the powerhouse of our platform This is where your agents run. Once deployed, agents can be triggered by external sources and can operate continuously. It contains all the essential components that make AutoGPT run smoothly.\n101|\n102|   **Source Code:** The core logic that drives our agents and automation processes.\n103|   \n104|   **Infrastructure:** Robust systems that ensure reliable and scalable performance.\n105|   \n106|   **Marketplace:** A comprehensive marketplace where you can find and deploy a wide range of pre-built agents.\n107|\n108|### 🐙 Example Agents\n109|\n110|Here are two examples of what you can do with AutoGPT:\n111|\n112|1. **Generate Viral Videos from Trending Topics**\n113|   - This agent reads topics on Reddit.\n114|   - It identifies trending topics.\n115|   - It then automatically creates a short-form video based on the content. \n116|\n117|2. **Identify Top Quotes from Videos for Social Media**\n118|   - This agent subscribes to your YouTube channel.\n119|   - When you post a new video, it transcribes it.\n120|   - It uses AI to identify the most impactful quotes to generate a summary.\n121|   - Then, it writes a post to automatically publish to your social media. \n122|\n123|These examples show just a glimpse of what you can achieve with AutoGPT! You can create customized workflows to build agents for any use case.\n124|\n125|---\n126|\n127|### **License Overview:**\n128|\n129|🛡️ **Polyform Shield License:**\n130|All code and content within the `autogpt_platform` folder is licensed under the Polyform Shield License. This new project is our in-developlemt platform for building, deploying and managing agents.</br>_[Read more about this effort](https://agpt.co/blog/introducing-the-autogpt-platform)_\n131|\n132|🦉 **MIT License:**\n133|All other portions of the AutoGPT repository (i.e., everything outside the `autogpt_platform` folder) are licensed under the MIT License. This includes the original stand-alone AutoGPT Agent, along with projects such as [Forge](https://github.com/Significant-Gravitas/AutoGPT/tree/master/classic/forge), [agbenchmark](https://github.com/Significant-Gravitas/AutoGPT/tree/master/classic/benchmark) and the [AutoGPT Classic GUI](https://github.com/Significant-Gravitas/AutoGPT/tree/master/classic/frontend).</br>We also publish additional work under the MIT Licence in other repositories, such as [GravitasML](https://github.com/Significant-Gravitas/gravitasml) which is developed for and used in the AutoGPT Platform. See also our MIT Licenced [Code Ability](https://github.com/Significant-Gravitas/AutoGPT-Code-Ability) project.\n134|\n135|---\n136|### Mission\n137|Our mission is to provide the tools, so that you can focus on what matters:\n138|\n139|- 🏗️ **Building** - Lay the foundation for something amazing.\n140|- 🧪 **Testing** - Fine-tune your agent to perfection.\n141|- 🤝 **Delegating** - Let AI work for you, and have your ideas come to life.\n142|\n143|Be part of the revolution! **AutoGPT** is here to stay, at the forefront of AI innovation.\n144|\n145|**📖 [Documentation](https://docs.agpt.co)**\n146|&ensp;|&ensp;\n147|**🚀 [Contributing](CONTRIBUTING.md)**\n148|\n149|---\n150|## 🤖 AutoGPT Classic\n151|> Below is information about the classic version of AutoGPT.\n152|\n153|**🛠️ [Build your own Agent - Quickstart](classic/FORGE-QUICKSTART.md)**\n154|\n155|### 🏗️ Forge\n156|\n157|**Forge your own agent!** &ndash; Forge is a ready-to-go toolkit to build your own agent application. It handles most of the boilerplate code, letting you channel all your creativity into the things that set *your* agent apart. All tutorials are located [here](https://medium.com/@aiedge/autogpt-forge-e3de53cc58ec). Components from [`forge`](/classic/forge/) can also be used individually to speed up development and reduce boilerplate in your agent project.\n158|\n159|🚀 [**Getting Started with Forge**](https://github.com/Significant-Gravitas/AutoGPT/blob/master/classic/forge/tutorials/001_getting_started.md) &ndash;\n160|This guide will walk you through the process of creating your own agent and using the benchmark and user interface.\n161|\n162|📘 [Learn More](https://github.com/Significant-Gravitas/AutoGPT/tree/master/classic/forge) about Forge\n163|\n164|### 🎯 Benchmark\n165|\n166|**Measure your agent's performance!** The `agbenchmark` can be used with any agent that supports the agent protocol, and the integration with the project's [CLI] makes it even easier to use with AutoGPT and forge-based agents. The benchmark offers a stringent testing environment. Our framework allows for autonomous, objective performance evaluations, ensuring your agents are primed for real-world action.\n167|\n168|<!-- TODO: insert visual demonstrating the benchmark -->\n169|\n170|📦 [`agbenchmark`](https://pypi.org/project/agbenchmark/) on Pypi\n171|&ensp;|&ensp;\n172|📘 [Learn More](https://github.com/Significant-Gravitas/AutoGPT/tree/master/classic/benchmark) about the Benchmark\n173|\n174|### 💻 UI\n175|\n176|**Makes agents easy to use!** The `frontend` gives you a user-friendly interface to control and monitor your agents. It connects to agents through the [agent protocol](#-agent-protocol), ensuring compatibility with many agents from both inside and outside of our ecosystem.\n177|\n178|<!-- TODO: insert screenshot of front end -->\n179|\n180|The frontend works out-of-the-box with all agents in the repo. Just use the [CLI] to run your agent of choice!\n181|\n182|📘 [Learn More](https://github.com/Significant-Gravitas/AutoGPT/tree/master/classic/frontend) about the Frontend\n183|\n184|### ⌨️ CLI\n185|\n186|[CLI]: #-cli\n187|\n188|To make it as easy as possible to use all of the tools offered by the repository, a CLI is included at the root of the repo:\n189|\n190|```shell\n191|$ ./run\n192|Usage: cli.py [OPTIONS] COMMAND [ARGS]...\n193|\n194|Options:\n195|  --help  Show this message and exit.\n196|\n197|Commands:\n198|  agent      Commands to create, start and stop agents\n199|  benchmark  Commands to start the benchmark and list tests and categories\n200|  setup      Installs dependencies needed for your system.\n201|", "total_lines": 238, "file_size": 11844, "truncated": true, "hint": "Use offset=201 to continue reading (showing 1-200 of 238 lines)", "is_binary": false, "is_image": false}


session_id: 20260530_230539_084c4b
role: tool
tool_call_id: chatcmpl-tool-b3d5b114126c4c6f
tool_name: read_file
content:
  {"content": "1|[tool.poetry]\n2|name = \"autogpt-platform-backend\"\n3|version = \"0.6.22\"\n4|description = \"A platform for building AI-powered agentic workflows\"\n5|authors = [\"AutoGPT <info@agpt.co>\"]\n6|readme = \"README.md\"\n7|packages = [{ include = \"backend\", format = \"sdist\" }]\n8|\n9|\n10|[tool.poetry.dependencies]\n11|python = \">=3.10,<3.14\"\n12|aio-pika = \"^9.5.5\"\n13|aiohttp = \"^3.10.0\"\n14|aiodns = \"^3.5.0\"\n15|agentmail = \"^0.4.5\"\n16|anthropic = \"^0.79.0\"\n17|apscheduler = \"^3.11.1\"\n18|autogpt-libs = { path = \"../autogpt_libs\", develop = true }\n19|bleach = { extras = [\"css\"], version = \"^6.2.0\" }\n20|cachetools = \"^5.5.0\"\n21|claude-agent-sdk = \"^0.1.64\"  # bundled CLI 2.1.116 -- 2.1.98+ fixes the --resume + excludeDynamicSections crash that used to force a per-turn 33K cache write. CLAUDE_CODE_DISABLE_EXPERIMENTAL_BETAS=1 env var strips the broken context-management beta. See sdk_compat_test.py.\n22|click = \"^8.2.0\"\n23|cryptography = \"^46.0\"\n24|discord-py = \"^2.5.2\"\n25|e2b = \"^2.15.2\"\n26|e2b-code-interpreter = \"^2.0\"\n27|elevenlabs = \"^1.50.0\"\n28|falkordb = \"^1.1.2\"\n29|fastapi = \"^0.128.6\"\n30|feedparser = \"^6.0.11\"\n31|flake8 = \"^7.3.0\"\n32|google-api-python-client = \"^2.177.0\"\n33|google-auth-oauthlib = \"^1.2.2\"\n34|google-cloud-storage = \"^3.2.0\"\n35|googlemaps = \"^4.10.0\"\n36|gravitasml = \"^0.1.4\"\n37|graphiti-core = \"^0.28.2\"\n38|groq = \"^0.30.0\"\n39|html2text = \"^2024.2.26\"\n40|jinja2 = \"^3.1.6\"\n41|jsonref = \"^1.1.0\"\n42|jsonschema = \"^4.25.0\"\n43|langfuse = \"^3.14.1\"\n44|launchdarkly-server-sdk = \"^9.14.1\"\n45|mem0ai = \"^0.1.115\"\n46|moviepy = \"^2.1.2\"\n47|ollama = \"^0.6.1\"\n48|openai = \"^1.97.1\"\n49|orjson = \"^3.10.0\"\n50|pika = \"^1.3.2\"\n51|pinecone = \"^7.3.0\"\n52|poetry = \"2.2.1\" # CHECK DEPENDABOT SUPPORT BEFORE UPGRADING\n53|postmarker = \"^1.0\"\n54|praw = \"~7.8.1\"\n55|prisma = \"^0.15.0\"\n56|rank-bm25 = \"^0.2.2\"\n57|prometheus-client = \"^0.24.1\"\n58|prometheus-fastapi-instrumentator = \"^7.0.0\"\n59|psutil = \"^7.0.0\"\n60|psycopg2-binary = \"^2.9.10\"\n61|pydantic = { extras = [\"email\"], version = \"^2.12.5\" }\n62|pydantic-settings = \"^2.12.0\"\n63|pywebpush = \"^2.3\"\n64|pytest = \"^8.4.1\"\n65|pytest-asyncio = \"^1.1.0\"\n66|python-dotenv = \"^1.1.1\"\n67|python-multipart = \"^0.0.22\"\n68|redis = \"^6.2.0\"\n69|regex = \"^2025.9.18\"\n70|replicate = \"^1.0.6\"\n71|sentry-sdk = {extras = [\"anthropic\", \"fastapi\", \"launchdarkly\", \"openai\", \"sqlalchemy\"], version = \"^2.44.0\"}\n72|sqlalchemy = \"^2.0.40\"\n73|strenum = \"^0.4.9\"\n74|stripe = \"^11.5.0\"\n75|supabase = \"2.28.0\"\n76|tenacity = \"^9.1.4\"\n77|todoist-api-python = \"^2.1.7\"\n78|tweepy = \"^4.16.0\"\n79|uvicorn = { extras = [\"standard\"], version = \"^0.40.0\" }\n80|websockets = \"^15.0\"\n81|youtube-transcript-api = \"^1.2.1\"\n82|yt-dlp = \"2025.12.08\"\n83|zerobouncesdk = \"^1.1.2\"\n84|# NOTE: please insert new dependencies in their alphabetical location\n85|pytest-snapshot = \"^0.9.0\"\n86|aiofiles = \"^25.1.0\"\n87|tiktoken = \"^0.12.0\"\n88|aioclamd = \"^1.0.0\"\n89|setuptools = \"^80.9.0\"\n90|gcloud-aio-storage = \"^9.5.0\"\n91|pandas = \"^2.3.1\"\n92|firecrawl-py = \"^4.3.6\"\n93|exa-py = \"^1.14.20\"\n94|croniter = \"^6.0.0\"\n95|stagehand = \"^3.4.0\"\n96|gravitas-md2gdocs = \"^0.1.0\"\n97|posthog = \"^7.6.0\"\n98|fpdf2 = \"^2.8.6\"\n99|langsmith = \"^0.7.7\"\n100|openpyxl = \"^3.1.5\"\n101|pymssql = \"^2.3.2\"\n102|pymysql = \"^1.1.1\"\n103|pyarrow = \"^23.0.0\"\n104|sqlparse = \"^0.5.5\"\n105|\n106|[tool.poetry.group.dev.dependencies]\n107|aiohappyeyeballs = \"^2.6.1\"\n108|black = \"^24.10.0\"\n109|faker = \"^38.2.0\"\n110|httpx = \"^0.28.1\"\n111|isort = \"^5.13.2\"\n112|poethepoet = \"^0.41.0\"\n113|pre-commit = \"^4.4.0\"\n114|pyright = \"^1.1.407\"\n115|pytest-cov = \"^7.1.0\"\n116|pytest-mock = \"^3.15.1\"\n117|pytest-watcher = \"^0.6.3\"\n118|requests = \"^2.32.5\"\n119|ruff = \"^0.15.0\"\n120|# NOTE: please insert new dependencies in their alphabetical location\n121|\n122|[build-system]\n123|requires = [\"poetry-core\"]\n124|build-backend = \"poetry.core.masonry.api\"\n125|\n126|[tool.poetry.scripts]\n127|app = \"backend.app:main\"\n128|rest = \"backend.rest:main\"\n129|db = \"backend.db:main\"\n130|ws = \"backend.ws:main\"\n131|scheduler = \"backend.scheduler:main\"\n132|notification = \"backend.notification:main\"\n133|platform-linking-manager = \"backend.platform_linking_manager:main\"\n134|executor = \"backend.exec:main\"\n135|analytics-setup = \"scripts.generate_views:main_setup\"\n136|analytics-views = \"scripts.generate_views:main_views\"\n137|copilot-executor = \"backend.copilot.executor.__main__:main\"\n138|copilot-bot = \"backend.copilot.bot.__main__:main\"\n139|cli = \"backend.cli:main\"\n140|format = \"scripts.linter:format\"\n141|lint = \"scripts.linter:lint\"\n142|test = \"scripts.run_tests:test\"\n143|load-store-agents = \"test.load_store_agents:run\"\n144|export-api-schema = \"backend.cli.generate_openapi_json:main\"\n145|gen-prisma-stub = \"scripts.gen_prisma_types_stub:main\"\n146|oauth-tool = \"backend.cli.oauth_tool:cli\"\n147|\n148|[tool.isort]\n149|profile = \"black\"\n150|\n151|[tool.pytest-watcher]\n152|now = false\n153|clear = true\n154|delay = 0.2\n155|runner = \"pytest\"\n156|runner_args = []\n157|patterns = [\"*.py\"]\n158|ignore_patterns = []\n159|\n160|[tool.pytest.ini_options]\n161|asyncio_mode = \"auto\"\n162|asyncio_default_fixture_loop_scope = \"session\"\n163|# Disable syrupy plugin to avoid conflict with pytest-snapshot\n164|# Both provide --snapshot-update argument causing ArgumentError\n165|addopts = \"-p no:syrupy\"\n166|markers = [\n167|    \"supplementary: tests kept for coverage but superseded by integration tests\",\n168|    \"integration: end-to-end tests that require a live database (skipped in CI)\",\n169|    \"slow: tests that take more than a few seconds (e.g. spin up an isolated docker stack)\",\n170|]\n171|filterwarnings = [\n172|    \"ignore:'audioop' is deprecated:DeprecationWarning:discord.player\",\n173|    \"ignore:invalid escape sequence:DeprecationWarning:tweepy.api\",\n174|]\n175|\n176|[tool.ruff]\n177|target-version = \"py310\"\n178|", "total_lines": 177, "file_size": 5147, "truncated": false, "is_binary": false, "is_image": false}

  [Subdirectory context discovered: AutoGPT/autogpt_platform/AGENTS.md]
  # AutoGPT Platform

  This file provides guidance to coding agents when working with code in this repository.

  ## Repository Overview

  AutoGPT Platform is a monorepo containing:

  - **Backend** (`backend`): Python FastAPI server with async support
  - **Frontend** (`frontend`): Next.js React application
  - **Shared Libraries** (`autogpt_libs`): Common Python utilities

  ## Component Documentation

  - **Backend**: See @backend/AGENTS.md for backend-specific commands, architecture, and development tasks
  - **Frontend**: See @frontend/AGENTS.md for frontend-specific commands, architecture, and development patterns

  ## Key Concepts

  1. **Agent Graphs**: Workflow definitions stored as JSON, executed by the backend
  2. **Blocks**: Reusable components in `backend/backend/blocks/` that perform specific tasks
  3. **Integrations**: OAuth and API connections stored per user
  4. **Store**: Marketplace for sharing agent templates
  5. **Virus Scanning**: ClamAV integration for file upload security

  ### Environment Configuration

  #### Configuration Files

  - **Backend**: `backend/.env.default` (defaults) → `backend/.env` (user overrides)
  - **Frontend**: `frontend/.env.default` (defaults) → `frontend/.env` (user overrides)
  - **Platform**: `.env.default` (Supabase/shared defaults) → `.env` (user overrides)

  #### Docker Environment Loading Order

  1. `.env.default` files provide base configuration (tracked in git)
  2. `.env` files provide user-specific overrides (gitignored)
  3. Docker Compose `environment:` sections provide service-specific overrides
  4. Shell environment variables have highest precedence

  #### Key Points

  - All services use hardcoded defaults in docker-compose files (no `${VARIABLE}` substitutions)
  - The `env_file` directive loads variables INTO containers at runtime
  - Backend/Frontend services use YAML anchors for consistent configuration
  - Supabase services (`db/docker/docker-compose.yml`) follow the same pattern

  ### Branching Strategy

  - **`dev`** is the main development branch. All PRs should target `dev`.
  - **`master`** is the production branch. Only used for production releases.

  ### Creating Pull Requests

  - Create the PR against the `dev` branch of the repository.
  - **Split PRs by concern** — each PR should have a single clear purpose. For example, "usage tracking" and "credit charging" should be separate PRs even if related. Combining multiple concerns makes it harder for reviewers to understand what belongs to what.
  - Ensure the branch name is descriptive (e.g., `feature/add-new-block`)
  - Use conventional commit messages (see below)
  - **Structure the PR description with Why / What / How** — Why: the motivation (what problem it solves, what's broken/missing without it); What: high-level summary of changes; How: approach, key implementation details, or architecture decisions. Reviewers need all three to judge whether the approach fits the problem.
  - Fill out the .github/PULL_REQUEST_TEMPLATE.md template as the PR description
  - Always use `--body-file` to pass PR body — avoids shell interpretation of backticks and special characters:
    ```bash
    PR_BODY=$(mktemp)
    cat > "$PR_BODY" << 'PREOF'
    ## Summary
    - use `backticks` freely here
    PREOF
    gh pr create --title "..." --body-file "$PR_BODY" --base dev
    rm "$PR_BODY"
    ```
  - Run the github pre-commit hooks to ensure code quality.

  ### Test-Driven Development (TDD)

  When fixing a bug or adding a feature, follow a test-first approach:

  1. **Write a failing test first** — create a test that reproduces the bug or validates the new behavior, marked with `@pytest.mark.xfail` (backend) or `.fixme` (Playwright). Run it to confirm it fails for the right reason.
  2. **Implement the fix/feature** — write the minimal code to make the test pass.
  3. **Remove the xfail marker** — once the test passes, remove the `xfail`/`.fixme` annotation and run the full test suite to confirm nothing else broke.

  This ensures every change is covered by a test and that the test actually validates the intended behavior.

  ### Reviewing/Revising Pull Requests

  Use `/pr-review` to review a PR or `/pr-address` to address comments.

  When fetching comments manually:
  - `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews --paginate` — top-level reviews
  - `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments --paginate` — inline review comments (always paginate to avoid missing comments beyond page 1)
  - `gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments` — PR conversation comments

  ### Conventional Commits

  Use this format for commit messages and Pull Request titles:

  **Conventional Commit Types:**

  - `feat`: Introduces a new feature to the codebase
  - `fix`: Patches a bug in the codebase
  - `refactor`: Code change that neither fixes a bug nor adds a feature; also applies to removing features
  - `ci`: Changes to CI configuration
  - `docs`: Documentation-only changes
  - `dx`: Improvements to the developer experience

  **Recommended Base Scopes:**

  - `platform`: Changes affecting both frontend and backend
  - `frontend`
  - `backend`
  - `infra`
  - `blocks`: Modifications/additions of individual blocks

  **Subscope Examples:**

  - `backend/executor`
  - `backend/db`
  - `frontend/builder` (includes changes to the block UI component)
  - `infra/prod`

  Use these scopes and subscopes for clarity and consistency in commit messages.

  [Subdirectory context discovered: AutoGPT/autogpt_platform/backend/AGENTS.md]
  # Backend

  This file provides guidance to coding agents when working with the backend.

  ## Essential Commands

  To run something with Python package dependencies you MUST use `poetry run ...`.

  ```bash
  # Install dependencies
  poetry install

  # Run database migrations
  poetry run prisma migrate dev

  # Start all services (database, redis, rabbitmq, clamav)
  docker compose up -d

  # Run the backend as a whole
  poetry run app

  # Run tests
  poetry run test

  # Run specific test
  poetry run pytest path/to/test_file.py::test_function_name

  # Run block tests (tests that validate all blocks work correctly)
  poetry run pytest backend/blocks/test/test_block.py -xvs

  # Run tests for a specific block (e.g., GetCurrentTimeBlock)
  poetry run pytest 'backend/blocks/test/test_block.py::test_available_blocks[GetCurrentTimeBlock]' -xvs

  # Lint and format
  # prefer format if you want to just "fix" it and only get the errors that can't be autofixed
  poetry run format  # Black + isort
  poetry run lint    # ruff
  ```

  More details can be found in @TESTING.md

  ### Creating/Updating Snapshots

  When you first write a test or when the expected output changes:

  ```bash
  poetry run pytest path/to/test.py --snapshot-update
  ```

  ⚠️ **Important**: Always review snapshot changes before committing! Use `git diff` to verify the changes are expected.

  ## Architecture

  - **API Layer**: FastAPI with REST and WebSocket endpoints
  - **Database**: PostgreSQL with Prisma ORM, includes pgvector for embeddings
  - **Queue System**: RabbitMQ for async task processing
  - **Execution Engine**: Separate executor service processes agent workflows
  - **Authentication**: JWT-based with Supabase integration
  - **Security**: Cache protection middleware prevents sensitive data caching in browsers/proxies

  ## Code Style

  - **Top-level imports only** — no local/inner imports (lazy imports only for heavy optional deps like `openpyxl`)
  - **Absolute imports** — use `from backend.module import ...` for cross-package imports. Single-dot relative (`from .sibling import ...`) is acceptable for sibling modules within the same package (e.g., blocks). Avoid double-dot relative imports (`from ..parent import ...`) — use the absolute path instead
  - **No duck typing** — no `hasattr`/`getattr`/`isinstance` for type dispatch; use typed interfaces/unions/protocols
  - **Pydantic models** over dataclass/namedtuple/dict for structured data
  - **No linter suppressors** — no `# type: ignore`, `# noqa`, `# pyright: ignore`; fix the type/code
  - **List comprehensions** over manual loop-and-append
  - **Early return** — guard clauses first, avoid deep nesting
  - **f-strings vs printf syntax in log statements** — Use `%s` for deferred interpolation in `debug` statements, f-strings elsewhere for readability: `logger.debug("Processing %s items", count)`, `logger.info(f"Processing {count} items")`
  - **Sanitize error paths** — `os.path.basename()` in error messages to avoid leaking directory structure
  - **TOCTOU awareness** — avoid check-then-act patterns for file access and credit charging
  - **`Security()` vs `Depends()`** — use `Security()` for auth deps to get proper OpenAPI security spec
  - **Redis pipelines** — `transaction=True` for atomicity on multi-step operations
  - **`max(0, value)` guards** — for computed values that should never be negative
  - **SSE protocol** — `data:` lines for frontend-parsed events (must match Zod schema), `: comment` lines for heartbeats/status
  - **File length** — keep files under ~300 lines; if a file grows beyond this, split by responsibility (e.g. extract helpers, models, or a sub-module into a new file). Never keep appending to a long file.
  - **Function length** — keep functions under ~40 lines; extract named helpers when a function grows longer. Long functions are a sign of mixed concerns, not complexity.
  - **Top-down ordering** — define the main/public function or class first, then the helpers it uses below. A reader should encounter high-level logic before implementation details.

  ## Testing Approach

  - Uses pytest with snapshot testing for API responses
  - Test files are colocated with source files (`*_test.py`)
  - Mock at boundaries — mock where the symbol is **used**, not where it's **defined**
  - After refactoring, update mock targets to match new module paths
  - Use `AsyncMock` for async functions (`from unittest.mock import AsyncMock`)

  ### Test-Driven Development (TDD)

  When fixing a bug or adding a feature, write the test **before** the implementation:

  ```python
  # 1. Write a failing test marked xfail
  @pytest.mark.xfail(reason="Bug #1234: widget crashes on empty input")
  def test_widget_handles_empty_input():
      result = widget.process("")
      assert result == Widget.EMPTY_RESULT

  # 2. Run it — confirm it fails (XFAIL)
  # poetry run pytest path/to/test.py::test_widget_handles_empty_input -xvs

  # 3. Implement the fix

  # 4. Remove xfail, run again — confirm it passes
  def test_widget_handles_empty_input():
      result = widget.process("")
      assert result == Widget.EMPTY_RESULT
  ```

  This catches regressions and proves the fix actually works. **Every bug fix should include a test that would have caught it.**

  ## Database Schema

  Key models (defined in `schema.prisma`):

  - `User`: Authentication and profile data
  - `AgentGraph`: Workflow definitions with version control
  - `AgentGraphExecution`: Execution history and results
  - `AgentNode`: Individual nodes in a workflow
  - `StoreListing`: Marketplace listings for sharing agents

  ## Environment Configuration

  - **Backend**: `.env.default` (defaults) → `.env` (user overrides)

  ## Common Development Tasks

  ### Adding a new block

  Follow the comprehensive [Block SDK Guide](@../../docs/platform/block-sdk-guide.md) which covers:

  - Provider configuration with `ProviderBuilder`
  - Block schema definition
  - Authentication (API keys, OAuth, webhooks)
  - Testing and validation
  - File organization

  Quick steps:

  1. Create new file in `backend/blocks/`
  2. Configure provider using `ProviderBuilder` in `_config.py`
  3. Inherit from `Block` base class
  4. Define input/output schemas using `BlockSchema`
  5. Implement async `run` method
  6. Generate unique block ID using `uuid.uuid4()`
  7. Test with `poetry run pytest backend/blocks/test/test_block.py`

  Note: when making many new blocks analyze the interfaces for each of these blocks and picture if they would go well together in a graph-based editor or would they struggle to connect productively?
  ex: do the inputs and outputs tie well together?

  If you get any pushback or hit complex block conditions check the new_blocks guide in the docs.

  #### Handling files in blocks with `store_media_file()`

  When blocks need to work with files (images, videos, documents), use `store_media_file()` from `backend.util.file`. The `return_format` parameter determines what you get back:

  | Format | Use When | Returns |
  |--------|----------|---------|
  | `"for_local_processing"` | Processing with local tools (ffmpeg, MoviePy, PIL) | Local file path (e.g., `"image.png"`) |
  | `"for_external_api"` | Sending content to external APIs (Replicate, OpenAI) | Data URI (e.g., `"data:image/png;base64,..."`) |
  | `"for_block_output"` | Returning output from your block | Smart: `workspace://` in CoPilot, data URI in graphs |

  **Examples:**

  ```python
  # INPUT: Need to process file locally with ffmpeg
  local_path = await store_media_file(
      file=input_data.video,
      execution_context=execution_context,
      return_format="for_local_processing",
  )
  # local_path = "video.mp4" - use with Path/ffmpeg/etc

  # INPUT: Need to send to external API like Replicate
  image_b64 = await store_media_file(
      file=input_data.image,
      execution_context=execution_context,
      return_format="for_external_api",
  )
  # image_b64 = "data:image/png;base64,iVBORw0..." - send to API

  # OUTPUT: Returning result from block
  result_url = await store_media_file(
      file=generated_image_url,
      execution_context=execution_context,
      return_format="for_block_output",
  )
  yield "image_url", result_url
  # In CoPilot: r

  [...truncated AGENTS.md: 9,760 chars total]


session_id: 20260530_230539_084c4b
role: tool
tool_call_id: chatcmpl-tool-954c2d7d5e406ea6
tool_name: read_file
content:
  {"content": "1|{\n2|  \"name\": \"frontend\",\n3|  \"version\": \"0.3.4\",\n4|  \"private\": true,\n5|  \"engines\": {\n6|    \"node\": \"22.x\"\n7|  },\n8|  \"scripts\": {\n9|    \"dev\": \"pnpm run generate:api:force && next dev --turbo\",\n10|    \"build\": \"cross-env NODE_OPTIONS=--max-old-space-size=16384 next build\",\n11|    \"start\": \"next start\",\n12|    \"start:standalone\": \"cd .next/standalone && node server.js\",\n13|    \"lint\": \"next lint && prettier --check .\",\n14|    \"format\": \"next lint --fix; prettier --write .\",\n15|    \"types\": \"tsc --noEmit\",\n16|    \"test\": \"NEXT_PUBLIC_PW_TEST=true next build --turbo && pnpm test:e2e:no-build\",\n17|    \"test-ui\": \"NEXT_PUBLIC_PW_TEST=true next build --turbo && pnpm test:e2e:ui\",\n18|    \"test:unit\": \"vitest run --coverage\",\n19|    \"test:unit:watch\": \"vitest\",\n20|    \"test:e2e\": \"NEXT_PUBLIC_PW_TEST=true next build --turbo && pnpm test:e2e:no-build\",\n21|    \"test:e2e:no-build\": \"playwright test\",\n22|    \"test:e2e:ui\": \"playwright test --ui\",\n23|    \"gentests\": \"playwright codegen http://localhost:3000\",\n24|    \"storybook\": \"storybook dev -p 6006\",\n25|    \"build-storybook\": \"storybook build\",\n26|    \"test-storybook\": \"test-storybook\",\n27|    \"test-storybook:ci\": \"concurrently -k -s first -n \\\"SB,TEST\\\" -c \\\"magenta,blue\\\" \\\"pnpm run build-storybook -- --quiet && npx http-server storybook-static --port 6006 --silent\\\" \\\"wait-on tcp:6006 && pnpm run test-storybook\\\"\",\n28|    \"generate:api\": \"npx --yes tsx ./scripts/generate-api-queries.ts && orval --config ./orval.config.ts\",\n29|    \"generate:api:force\": \"npx --yes tsx ./scripts/generate-api-queries.ts --force && orval --config ./orval.config.ts\"\n30|  },\n31|  \"browserslist\": [\n32|    \"defaults\"\n33|  ],\n34|  \"dependencies\": {\n35|    \"@ai-sdk/react\": \"3.0.61\",\n36|    \"@faker-js/faker\": \"10.0.0\",\n37|    \"@ferrucc-io/emoji-picker\": \"0.0.48\",\n38|    \"@hookform/resolvers\": \"5.2.2\",\n39|    \"@next/third-parties\": \"15.4.6\",\n40|    \"@number-flow/react\": \"0.6.0\",\n41|    \"@phosphor-icons/react\": \"2.1.10\",\n42|    \"@posthog/react\": \"1.7.0\",\n43|    \"@radix-ui/react-accordion\": \"1.2.12\",\n44|    \"@radix-ui/react-alert-dialog\": \"1.1.15\",\n45|    \"@radix-ui/react-avatar\": \"1.1.10\",\n46|    \"@radix-ui/react-checkbox\": \"1.3.3\",\n47|    \"@radix-ui/react-collapsible\": \"1.1.12\",\n48|    \"@radix-ui/react-context-menu\": \"2.2.16\",\n49|    \"@radix-ui/react-dialog\": \"1.1.15\",\n50|    \"@radix-ui/react-dropdown-menu\": \"2.1.16\",\n51|    \"@radix-ui/react-icons\": \"1.3.2\",\n52|    \"@radix-ui/react-label\": \"2.1.7\",\n53|    \"@radix-ui/react-popover\": \"1.1.15\",\n54|    \"@radix-ui/react-radio-group\": \"1.3.8\",\n55|    \"@radix-ui/react-scroll-area\": \"1.2.10\",\n56|    \"@radix-ui/react-select\": \"2.2.6\",\n57|    \"@radix-ui/react-separator\": \"1.1.7\",\n58|    \"@radix-ui/react-slider\": \"1.3.6\",\n59|    \"@radix-ui/react-slot\": \"1.2.3\",\n60|    \"@radix-ui/react-switch\": \"1.2.6\",\n61|    \"@radix-ui/react-tabs\": \"1.1.13\",\n62|    \"@radix-ui/react-toast\": \"1.2.15\",\n63|    \"@radix-ui/react-tooltip\": \"1.2.8\",\n64|    \"@rjsf/core\": \"6.1.2\",\n65|    \"@rjsf/utils\": \"6.1.2\",\n66|    \"@rjsf/validator-ajv8\": \"6.1.2\",\n67|    \"@sentry/nextjs\": \"10.27.0\",\n68|    \"@streamdown/cjk\": \"1.0.1\",\n69|    \"@streamdown/math\": \"1.0.1\",\n70|    \"@streamdown/mermaid\": \"1.0.1\",\n71|    \"@supabase/ssr\": \"0.7.0\",\n72|    \"@supabase/supabase-js\": \"2.78.0\",\n73|    \"@tanstack/react-query\": \"5.90.6\",\n74|    \"@tanstack/react-table\": \"8.21.3\",\n75|    \"@types/jaro-winkler\": \"0.2.4\",\n76|    \"@vercel/analytics\": \"1.5.0\",\n77|    \"@vercel/speed-insights\": \"1.2.0\",\n78|    \"@xyflow/react\": \"12.9.2\",\n79|    \"ai\": \"6.0.134\",\n80|    \"boring-avatars\": \"1.11.2\",\n81|    \"canvas-confetti\": \"1.9.4\",\n82|    \"class-variance-authority\": \"0.7.1\",\n83|    \"clsx\": \"2.1.1\",\n84|    \"cmdk\": \"1.1.1\",\n85|    \"cookie\": \"1.0.2\",\n86|    \"date-fns\": \"4.1.0\",\n87|    \"dexie\": \"4.2.1\",\n88|    \"dotenv\": \"17.2.3\",\n89|    \"elliptic\": \"6.6.1\",\n90|    \"embla-carousel-react\": \"8.6.0\",\n91|    \"flatbush\": \"4.5.0\",\n92|    \"framer-motion\": \"12.23.24\",\n93|    \"geist\": \"1.5.1\",\n94|    \"highlight.js\": \"11.11.1\",\n95|    \"jaro-winkler\": \"0.2.8\",\n96|    \"jszip\": \"3.10.1\",\n97|    \"katex\": \"0.16.25\",\n98|    \"launchdarkly-react-client-sdk\": \"3.9.0\",\n99|    \"lodash\": \"4.17.21\",\n100|    \"lucide-react\": \"0.552.0\",\n101|    \"motion\": \"12.38.0\",\n102|    \"next\": \"15.5.18\",\n103|    \"next-themes\": \"0.4.6\",\n104|    \"nuqs\": \"2.7.2\",\n105|    \"posthog-js\": \"1.334.1\",\n106|    \"react\": \"18.3.1\",\n107|    \"react-currency-input-field\": \"4.0.3\",\n108|    \"react-day-picker\": \"9.11.1\",\n109|    \"react-dom\": \"18.3.1\",\n110|    \"react-hook-form\": \"7.66.0\",\n111|    \"react-icons\": \"5.5.0\",\n112|    \"react-markdown\": \"9.0.3\",\n113|    \"react-modal\": \"3.16.3\",\n114|    \"react-shepherd\": \"6.1.9\",\n115|    \"react-window\": \"2.2.0\",\n116|    \"recharts\": \"3.3.0\",\n117|    \"rehype-autolink-headings\": \"7.1.0\",\n118|    \"rehype-highlight\": \"7.0.2\",\n119|    \"rehype-katex\": \"7.0.1\",\n120|    \"rehype-slug\": \"6.0.0\",\n121|    \"remark-gfm\": \"4.0.1\",\n122|    \"remark-math\": \"6.0.0\",\n123|    \"shepherd.js\": \"14.5.1\",\n124|    \"shiki\": \"^3.21.0\",\n125|    \"simplex-noise\": \"4.0.3\",\n126|    \"sonner\": \"2.0.7\",\n127|    \"streamdown\": \"2.1.0\",\n128|    \"tailwind-merge\": \"2.6.0\",\n129|    \"tailwind-scrollbar\": \"3.1.0\",\n130|    \"tailwindcss-animate\": \"1.0.7\",\n131|    \"twemoji\": \"14.0.2\",\n132|    \"use-stick-to-bottom\": \"1.1.2\",\n133|    \"uuid\": \"11.1.0\",\n134|    \"vaul\": \"1.1.2\",\n135|    \"zod\": \"3.25.76\",\n136|    \"zustand\": \"5.0.8\"\n137|  },\n138|  \"devDependencies\": {\n139|    \"@chromatic-com/storybook\": \"4.1.2\",\n140|    \"@opentelemetry/instrumentation\": \"0.209.0\",\n141|    \"@playwright/test\": \"1.56.1\",\n142|    \"@storybook/addon-a11y\": \"9.1.5\",\n143|    \"@storybook/addon-docs\": \"9.1.5\",\n144|    \"@storybook/addon-links\": \"9.1.5\",\n145|    \"@storybook/addon-onboarding\": \"9.1.5\",\n146|    \"@storybook/nextjs\": \"9.1.5\",\n147|    \"@tanstack/eslint-plugin-query\": \"5.91.2\",\n148|    \"@tanstack/react-query-devtools\": \"5.90.2\",\n149|    \"@testing-library/dom\": \"10.4.1\",\n150|    \"@testing-library/react\": \"16.3.2\",\n151|    \"@testing-library/user-event\": \"14.6.1\",\n152|    \"@types/canvas-confetti\": \"1.9.0\",\n153|    \"@types/lodash\": \"4.17.20\",\n154|    \"@types/negotiator\": \"0.6.4\",\n155|    \"@types/node\": \"24.10.0\",\n156|    \"@types/react\": \"18.3.17\",\n157|    \"@types/react-dom\": \"18.3.5\",\n158|    \"@types/react-modal\": \"3.16.3\",\n159|    \"@types/react-window\": \"2.0.0\",\n160|    \"@types/twemoji\": \"13.1.2\",\n161|    \"@vitejs/plugin-react\": \"5.1.2\",\n162|    \"@vitest/coverage-v8\": \"4.0.17\",\n163|    \"agentation\": \"3.0.2\",\n164|    \"axe-playwright\": \"2.2.2\",\n165|    \"chromatic\": \"13.3.3\",\n166|    \"concurrently\": \"9.2.1\",\n167|    \"cross-env\": \"10.1.0\",\n168|    \"eslint\": \"8.57.1\",\n169|    \"eslint-config-next\": \"15.5.7\",\n170|    \"eslint-plugin-storybook\": \"9.1.5\",\n171|    \"happy-dom\": \"20.3.4\",\n172|    \"import-in-the-middle\": \"2.0.2\",\n173|    \"monocart-reporter\": \"2.10.0\",\n174|    \"msw\": \"2.11.6\",\n175|    \"msw-storybook-addon\": \"2.0.6\",\n176|    \"orval\": \"7.13.0\",\n177|    \"pbkdf2\": \"3.1.5\",\n178|    \"postcss\": \"8.5.6\",\n179|    \"prettier\": \"3.6.2\",\n180|    \"prettier-plugin-tailwindcss\": \"0.7.1\",\n181|    \"require-in-the-middle\": \"8.0.1\",\n182|    \"storybook\": \"9.1.5\",\n183|    \"tailwindcss\": \"3.4.17\",\n184|    \"typescript\": \"5.9.3\",\n185|    \"vite-tsconfig-paths\": \"6.0.4\",\n186|    \"vitest\": \"4.0.17\"\n187|  },\n188|  \"msw\": {\n189|    \"workerDirectory\": [\n190|      \"public\"\n191|    ]\n192|  },\n193|  \"pnpm\": {\n194|    \"overrides\": {\n195|      \"@opentelemetry/instrumentation\": \"0.209.0\",\n196|      \"lodash-es\": \"4.17.23\"\n197|    }\n198|  },\n199|  \"packageManager\": \"pnpm@10.20.0+sha512.cf9998222162dd85864d0a8102e7892e7ba4ceadebbf5a31f9c2fce48dfce317a9c53b9f6464d1ef9042cba2e02ae02a9f7c143a2b438cd93c91840f0192b9dd\"\n200|}\n201|", "total_lines": 200, "file_size": 6930, "truncated": false, "is_binary": false, "is_image": false}

  [Subdirectory context discovered: AutoGPT/autogpt_platform/frontend/AGENTS.md]
  # Frontend

  This file provides guidance to coding agents when working with the frontend.

  ## Essential Commands

  ```bash
  # Install dependencies
  pnpm i

  # Generate API client from OpenAPI spec
  pnpm generate:api

  # Start development server
  pnpm dev

  # Run E2E tests
  pnpm test

  # Run Storybook for component development
  pnpm storybook

  # Build production
  pnpm build

  # Format and lint
  pnpm format

  # Type checking
  pnpm types
  ```

  ### Pre-completion Checks (MANDATORY)

  After making **any** code changes in the frontend, you MUST run the following commands **in order** before reporting work as done, creating commits, or opening PRs:

  1. `pnpm format` — auto-fix formatting issues
  2. `pnpm lint` — check for lint errors; fix any that appear
  3. `pnpm types` — check for type errors; fix any that appear

  Do NOT skip these steps. If any command reports errors, fix them and re-run until clean. Only then may you consider the task complete. If typing keeps failing, stop and ask the user.

  4. `pnpm test:unit` — run integration tests; fix any failures

  ### Code Style

  - Fully capitalize acronyms in symbols, e.g. `graphID`, `useBackendAPI`
  - Use function declarations (not arrow functions) for components/handlers
  - No `dark:` Tailwind classes — the design system handles dark mode
  - Use Next.js `<Link>` for internal navigation — never raw `<a>` tags
  - No `any` types unless the value genuinely can be anything
  - No linter suppressors (`// @ts-ignore`, `// eslint-disable`) — fix the actual issue
  - **File length** — keep files under ~200 lines; extract sub-components or hooks into their own files when a file grows beyond this
  - **Function/component length** — keep render functions and hooks under ~50 lines; extract named helpers or sub-components when they grow longer

  ## Architecture

  - **Framework**: Next.js 15 App Router (client-first approach)
  - **Data Fetching**: Type-safe generated API hooks via Orval + React Query
  - **State Management**: React Query for server state, co-located UI state in components/hooks
  - **Component Structure**: Separate render logic (`.tsx`) from business logic (`use*.ts` hooks)
  - **Workflow Builder**: Visual graph editor using @xyflow/react
  - **UI Components**: shadcn/ui (Radix UI primitives) with Tailwind CSS styling
  - **Icons**: Phosphor Icons only
  - **Feature Flags**: LaunchDarkly integration
  - **Error Handling**: ErrorCard for render errors, toast for mutations, Sentry for exceptions
  - **Testing**: Vitest + React Testing Library + MSW for integration tests (primary), Playwright for E2E, Storybook for visual

  ## Environment Configuration

  `.env.default` (defaults) → `.env` (user overrides)

  ## Feature Development

  See @CONTRIBUTING.md for complete patterns. Quick reference:

  1. **Pages**: Create in `src/app/(platform)/feature-name/page.tsx`
     - Extract component logic into custom hooks grouped by concern, not by component. Each hook should represent a cohesive domain of functionality (e.g., useSearch, useFilters, usePagination) rather than bundling all state into one useComponentState hook.
       - Put each hook in its own `.ts` file
     - Put sub-components in local `components/` folder
     - Component props should be `type Props = { ... }` (not exported) unless it needs to be used outside the component
  2. **Components**: Structure as `ComponentName/ComponentName.tsx` + `useComponentName.ts` + `helpers.ts`
     - Use design system components from `src/components/` (atoms, molecules, organisms)
     - Never use `src/components/__legacy__/*`
  3. **Data fetching**: Use generated API hooks from `@/app/api/__generated__/endpoints/`
     - Regenerate with `pnpm generate:api`
     - Pattern: `use{Method}{Version}{OperationName}`
  4. **Styling**: Tailwind CSS only, use design tokens, Phosphor Icons only
     - Always import the `-Icon`-suffixed alias from `@phosphor-icons/react` (e.g. `TrashIcon`, `PlusIcon`, `SquareIcon`) — bare exports like `Trash`/`Plus` are deprecated.
  5. **Testing**: Integration tests are the default (~90%). See `TESTING.md` for full details.
     - **New pages/features**: Write integration tests in `__tests__/` next to `page.tsx` using Vitest + RTL + MSW
     - **API mocking**: Use Orval-generated MSW handlers from `@/app/api/__generated__/endpoints/{tag}/{tag}.msw.ts`
     - **Run**: `pnpm test:unit` (integration/unit), `pnpm test` (Playwright E2E)
     - **Storybook**: For design system components in `src/components/`
     - **TDD**: Write a failing test first, implement, then verify
  6. **Code conventions**:
     - Use function declarations (not arrow functions) for components/handlers
     - Do not use `useCallback` or `useMemo` unless asked to optimise a given function
     - Do not type hook returns, let Typescript infer as much as possible
     - Never type with `any` unless a variable/attribute can ACTUALLY be of any type
     - avoid index and barrel files


session_id: 20260530_230539_084c4b
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-882e3b6bb3cde5ac", "call_id": "chatcmpl-tool-882e3b6bb3cde5ac", "response_item_id": "fc_chatcmpl-tool-882e3b6bb3cde5ac", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"cd /home/ice/AutoGPT && git log --oneline -20\"}"}}, {"id": "chatcmpl-tool-a48dcbfdfc001d13", "call_id": "chatcmpl-tool-a48dcbfdfc001d13", "response_item_id": "fc_chatcmpl-tool-a48dcbfdfc001d13", "type": "function", "function": {"name": "search_files", "arguments": "{\"limit\": 30, \"path\": \"/home/ice/AutoGPT\", \"pattern\": \"^.*$\", \"target\": \"files\"}"}}]

reasoning:
  Vou analisar o repositório AutoGPT com base no que li até agora. Vou coletar mais informações para ter uma visão completa.

  O que tenho até agora:
  1. README: AutoGPT é uma plataforma para criar, implantar e gerenciar agentes de IA contínuos que automatizam fluxos de trabalho complexos. Oferece:
     - AutoGPT Platform (plataforma principal com frontend/backend)
     - AutoGPT Classic (versão original standalone)
     - Forge (toolkit para construir agentes)
     - Benchmark (agbenchmark)
     - UI (frontend clássico)
     - CLI

  2. Estrutura do repositório:
     - autogpt_platform/backend: Python FastAPI
     - autogpt_platform/frontend: Next.js + TypeScript
     - autogpt_platform/autogpt_libs: bibliotecas Python compartilhadas
     - classic/: versão clássica

  3. Backend:
     - Python >=3.10,<3.14
     - FastAPI, Prisma ORM, PostgreSQL, RabbitMQ, Redis, websockets, Supabase
     - Dependências principais: openai, anthropic, groq, e2b (code interpreter), elevenlabs, mem0ai, ollama, replicate, stagehand, etc.

  4. Frontend:
     - Next.js 15, React 18, TypeScript, Tailwind CSS
     - Radix UI + shadcn/ui
     - React Query, Orval (API generation), @xyflow/react (graph editor)
     - Vitest + RTL + MSW (tests), Playwright (E2E), Storybook

  Preciso analisar mais a fundo os problemas, tema, hype e tecnologias. Vou olhar mais detalhes do repositório, como issues recentes, contribuições e estrutura do código.

reasoning_content:
  Vou analisar o repositório AutoGPT com base no que li até agora. Vou coletar mais informações para ter uma visão completa.

  O que tenho até agora:
  1. README: AutoGPT é uma plataforma para criar, implantar e gerenciar agentes de IA contínuos que automatizam fluxos de trabalho complexos. Oferece:
     - AutoGPT Platform (plataforma principal com frontend/backend)
     - AutoGPT Classic (versão original standalone)
     - Forge (toolkit para construir agentes)
     - Benchmark (agbenchmark)
     - UI (frontend clássico)
     - CLI

  2. Estrutura do repositório:
     - autogpt_platform/backend: Python FastAPI
     - autogpt_platform/frontend: Next.js + TypeScript
     - autogpt_platform/autogpt_libs: bibliotecas Python compartilhadas
     - classic/: versão clássica

  3. Backend:
     - Python >=3.10,<3.14
     - FastAPI, Prisma ORM, PostgreSQL, RabbitMQ, Redis, websockets, Supabase
     - Dependências principais: openai, anthropic, groq, e2b (code interpreter), elevenlabs, mem0ai, ollama, replicate, stagehand, etc.

  4. Frontend:
     - Next.js 15, React 18, TypeScript, Tailwind CSS
     - Radix UI + shadcn/ui
     - React Query, Orval (API generation), @xyflow/react (graph editor)
     - Vitest + RTL + MSW (tests), Playwright (E2E), Storybook

  Preciso analisar mais a fundo os problemas, tema, hype e tecnologias. Vou olhar mais detalhes do repositório, como issues recentes, contribuições e estrutura do código.


session_id: 20260530_230539_084c4b
role: tool
tool_call_id: chatcmpl-tool-882e3b6bb3cde5ac
tool_name: terminal
content:
  {"output": "a59ff3c35 feat(frontend): capture marketing-site triggerprompt into sessionStorage (#13248)\nc194ab1b7 Merge branch 'master' into dev\ncae869f7e fix(blocks): clean up file input base64 description (#13032)\n9073c0172 docs: fix Ayrshare comment typo (#13226)\n6ecb0cc1a fix(frontend/autopilot): improve AutoPilot OS push notification icon and copy (#13231)\n9c194bfa8 fix(backend/copilot-bot): point /unlink button to the new bots page (#13198)\naea4d5abd feat(platform): add Bots settings page with per-platform link management (#13222)\n7e2154c31 feat(backend/copilot): keep linked server names fresh from bot gateway events (#13221)\n8dc55d916 feat(backend/copilot-bot): post intro message when added to a server (#13220)\n5ac3fe29a feat(backend/copilot-bot): add /resume to pick and resume a past chat (#13219)\nd8d5d5f2b feat(platform): share agent chat results via public link (#13081)\n676fed209 fix(paywall): do not show for local users (#13229)\n4074fdb40 feat(backend/copilot-bot): add /new to start a fresh conversation (#13199)\nb5ab84784 fix(backend/copilot-bot): recover deleted chat sessions instead of erroring (#13197)\n8cc307208 fix(backend/copilot-bot): only answer other bots when @mentioned (#13174)\n7d8eee147 refactor(frontend/library): extract briefing tab sub-components and reorganize panel (#13213)\nbaef6f8c3 fix(copilot): strip null credential fields before validation (#13185)\na11174b7c feat(backend/copilot): require library similarity check before create_agent (#13080)\n6771f20cf fix(frontend/library): autopilot pill counts copilot follow-ups only, not graph schedules (#13212)\n4ff22cd0e fix(frontend): clean up agent briefing cost breakdown UX (#13196)", "exit_code": 0, "error": null}


session_id: 20260530_230539_084c4b
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-b9c975be711ba317", "call_id": "chatcmpl-tool-b9c975be711ba317", "response_item_id": "fc_chatcmpl-tool-b9c975be711ba317", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"cd /home/ice/AutoGPT && find . -maxdepth 3 -type d | sed 's|^\\\\./||' | sort | head -80\"}"}}]

reasoning:
  The search_files with pattern "^.*$" and target="files" didn't return results because it's probably not the right way to list files. Let me use a terminal command to get a better high-level structure.

reasoning_content:
  The search_files with pattern "^.*$" and target="files" didn't return results because it's probably not the right way to list files. Let me use a terminal command to get a better high-level structure.


session_id: 20260530_230539_084c4b
role: tool
tool_call_id: chatcmpl-tool-b9c975be711ba317
tool_name: terminal
content:
  {"output": ".\n.agents\n.claude\n.claude/skills\n.claude/skills/open-pr\n.claude/skills/orchestrate\n.claude/skills/pr-address\n.claude/skills/pr-polish\n.claude/skills/pr-review\n.claude/skills/pr-test\n.claude/skills/setup-repo\n.claude/skills/vercel-react-best-practices\n.claude/skills/worktree\n.claude/skills/write-frontend-tests\n.git\n.git/branches\n.git/hooks\n.git/info\n.git/logs\n.git/logs/refs\n.git/objects\n.git/objects/info\n.git/objects/pack\n.git/refs\n.git/refs/heads\n.git/refs/remotes\n.git/refs/tags\n.github\n.github/ISSUE_TEMPLATE\n.github/scripts\n.github/workflows\n.github/workflows/scripts\n.vscode\nassets\nautogpt_platform\nautogpt_platform/analytics\nautogpt_platform/analytics/queries\nautogpt_platform/autogpt_libs\nautogpt_platform/autogpt_libs/autogpt_libs\nautogpt_platform/backend\nautogpt_platform/backend/agents\nautogpt_platform/backend/backend\nautogpt_platform/backend/load-tests\nautogpt_platform/backend/migrations\nautogpt_platform/backend/scripts\nautogpt_platform/backend/snapshots\nautogpt_platform/backend/test\nautogpt_platform/db\nautogpt_platform/db/docker\nautogpt_platform/frontend\nautogpt_platform/frontend/.storybook\nautogpt_platform/frontend/public\nautogpt_platform/frontend/scripts\nautogpt_platform/frontend/src\nautogpt_platform/graph_templates\nautogpt_platform/installer\nclassic\nclassic/direct_benchmark\nclassic/direct_benchmark/challenges\nclassic/direct_benchmark/direct_benchmark\nclassic/forge\nclassic/forge/agbenchmark_config\nclassic/forge/forge\nclassic/forge/tests\nclassic/original_autogpt\nclassic/original_autogpt/.claude\nclassic/original_autogpt/.devcontainer\nclassic/original_autogpt/agbenchmark_config\nclassic/original_autogpt/autogpt\nclassic/original_autogpt/data\nclassic/original_autogpt/docs\nclassic/original_autogpt/hooks\nclassic/original_autogpt/plugins\nclassic/original_autogpt/scripts\nclassic/original_autogpt/tests\nclassic/reports\ndocs\ndocs/content\ndocs/content/challenges\ndocs/content/classic", "exit_code": 0, "error": null}


session_id: 20260530_230539_084c4b
role: assistant
finish_reason: stop
content:
  # Análise do repositório AutoGPT

  **O que fiz:** clonei o repositório, li a documentação principal (`README.md`) e examinei as definições de stack do backend, frontend e estrutura do monorepo.

  **Problema**
  Automação de fluxos complexos com IA ainda é pouco acessível para maioria dos usuários. AutoGPT resolve isso oferecendo uma plataforma para criar, implantar e gerenciar agentes de IA contínuos que automatizam workflows de ponta a ponta.

  **Tema**
  Construção, implantação e gerenciamento de agentes autônomos de IA, com marketplace de agentes, editor visual de workflows, execução contínua e suporte a integrações com serviços externos.

  **Razão do hype**
  - Ecossistema de agentes autônomos popular e pioneiro (um dos mais estrelados do mundo).
  - Processamento contínuo, não só chat: agentes leem contextos (ex.: Reddit, YouTube) e executam ações sem intervenção.
  - Interface low-code para montar workflows por blocos.
  - Marketplace para compartilhar templates de agentes.
  - Stack robusta e open source com backend/frontend bem definidos.

  **Tecnologias principais**

  Backend:
  - Python >=3.10,<3.14, FastAPI, Uvicorn
  - PostgreSQL + Prisma + pgvector
  - Redis, RabbitMQ
  - Supabase (auth), Pydantic, SQLAlchemy
  - Integrações: OpenAI, Anthropic, Claude Agent SDK, ElevenLabs, Groq, Ollama, yt-dlp, Reddit (praw), Twitter (tweepy), Google APIs, E2B, Firecrawl, Exa
  - Observabilidade: Sentry, Prometheus, Langfuse, PostHog, LangSmith
  - Testes: pytest + snapshot testing

  Frontend:
  - Next.js 15 (App Router), React 18, TypeScript
  - Tailwind CSS, Radix UI, shadcn/ui, Phosphor Icons
  - Zustand, React Query, Orval (OpenAPI -> TS client)
  - Workflow builder visual: @xyflow/react
  - Vitest + React Testing Library + MSW; Playwright para E2E
  - Storybook, Sentry, Launchdarkly, PostHog

  Infra/Dev:
  - Docker Compose, Poetry, pnpm, PNPM workspaces
  - Pre-commit, Ruff, Black, Isort
  - CI/CD via GitHub Actions

  Arquitetura geral: monorepo com `autogpt_platform/backend`, `autogpt_platform/frontend` e `autogpt_platform/autogpt_libs`, além da pasta `classic` contendo versões anteriores e ferramentas de benchmark.

reasoning:
  I now have enough information to provide an analysis summary of the AutoGPT repository. Let me consolidate what I found:

  1. Repository clone success
  2. README overview captured
  3. Backend tech stack captured from pyproject.toml
  4. Frontend tech stack captured from package.json
  5. Git log and directory structure evaluated

  I should now provide a concise summary in Portuguese as requested by "Analisar repositório" / "Analise e retorne: Problema, Tema, Razão hype, Tecnologias".

  Let me structure the answer:

  - Problema (Problem)
  - Tema (Theme)
  - Razão hype (Reason for hype)
  - Tecnologias (Technologies)

  I'll include the main backend and frontend stacks, monorepo structure, key architectural components, and market position.

reasoning_content:
  I now have enough information to provide an analysis summary of the AutoGPT repository. Let me consolidate what I found:

  1. Repository clone success
  2. README overview captured
  3. Backend tech stack captured from pyproject.toml
  4. Frontend tech stack captured from package.json
  5. Git log and directory structure evaluated

  I should now provide a concise summary in Portuguese as requested by "Analisar repositório" / "Analise e retorne: Problema, Tema, Razão hype, Tecnologias".

  Let me structure the answer:

  - Problema (Problem)
  - Tema (Theme)
  - Razão hype (Reason for hype)
  - Tecnologias (Technologies)

  I'll include the main backend and frontend stacks, monorepo structure, key architectural components, and market position.


session_id: 20260530_230637_ef53d3
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-826aaa0560a4baa6", "call_id": "chatcmpl-tool-826aaa0560a4baa6", "response_item_id": "fc_chatcmpl-tool-826aaa0560a4baa6", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"cd /home/ice && git clone --depth 1 https://github.com/vllm-project/vllm.git\", \"timeout\": 120}"}}]

reasoning:
  The user wants me to analyze a repository. From the context:
  - Repository: vllm-project/vllm
  - URL: https://github.com/vllm-project/vllm
  - Language: Python
  - Description: A high-throughput and memory-efficient inference and serving engine for LLMs
  - Stars: 81.446

  I need to:
  1. Clone/download the repository to the workspace
  2. Analyze it and return: Problem, Theme, Hype reason, Technologies

  Let me start by cloning the repository to /home/ice (the workspace path).

reasoning_content:
  The user wants me to analyze a repository. From the context:
  - Repository: vllm-project/vllm
  - URL: https://github.com/vllm-project/vllm
  - Language: Python
  - Description: A high-throughput and memory-efficient inference and serving engine for LLMs
  - Stars: 81.446

  I need to:
  1. Clone/download the repository to the workspace
  2. Analyze it and return: Problem, Theme, Hype reason, Technologies

  Let me start by cloning the repository to /home/ice (the workspace path).


session_id: 20260530_230637_ef53d3
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-a4b1b92fa9032a51", "call_id": "chatcmpl-tool-a4b1b92fa9032a51", "response_item_id": "fc_chatcmpl-tool-a4b1b92fa9032a51", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\": \"/home/ice/vllm/README.md\", \"limit\": 150}"}}, {"id": "chatcmpl-tool-af81555537e850d2", "call_id": "chatcmpl-tool-af81555537e850d2", "response_item_id": "fc_chatcmpl-tool-af81555537e850d2", "type": "function", "function": {"name": "search_files", "arguments": "{\"target\": \"files\", \"path\": \"/home/ice/vllm\", \"pattern\": \"setup.py\"}"}}]

reasoning:
  Repositório clonado. Agora vou analisar a estrutura e arquivos principais para extrair: Problema, Tema, Razão hype, Tecnologias.

reasoning_content:
  Repositório clonado. Agora vou analisar a estrutura e arquivos principais para extrair: Problema, Tema, Razão hype, Tecnologias.


session_id: 20260530_230637_ef53d3
role: tool
tool_call_id: chatcmpl-tool-a4b1b92fa9032a51
tool_name: read_file
content:
  {"content": "1|<!-- markdownlint-disable MD001 MD041 -->\n2|<p align=\"center\">\n3|  <picture>\n4|    <source media=\"(prefers-color-scheme: dark)\" srcset=\"https://raw.githubusercontent.com/vllm-project/vllm/main/docs/assets/logos/vllm-logo-text-dark.png\">\n5|    <img alt=\"vLLM\" src=\"https://raw.githubusercontent.com/vllm-project/vllm/main/docs/assets/logos/vllm-logo-text-light.png\" width=55%>\n6|  </picture>\n7|</p>\n8|\n9|<h3 align=\"center\">\n10|Easy, fast, and cheap LLM serving for everyone\n11|</h3>\n12|\n13|<p align=\"center\">\n14|| <a href=\"https://docs.vllm.ai\"><b>Documentation</b></a> | <a href=\"https://blog.vllm.ai/\"><b>Blog</b></a> | <a href=\"https://arxiv.org/abs/2309.06180\"><b>Paper</b></a> | <a href=\"https://x.com/vllm_project\"><b>Twitter/X</b></a> | <a href=\"https://discuss.vllm.ai\"><b>User Forum</b></a> | <a href=\"https://slack.vllm.ai\"><b>Developer Slack</b></a> |\n15|</p>\n16|\n17|🔥 We have built a vLLM website to help you get started with vLLM. Please visit [vllm.ai](https://vllm.ai) to learn more.\n18|For events, please visit [vllm.ai/events](https://vllm.ai/events) to join us.\n19|\n20|---\n21|\n22|## About\n23|\n24|vLLM is a fast and easy-to-use library for LLM inference and serving.\n25|\n26|Originally developed in the [Sky Computing Lab](https://sky.cs.berkeley.edu) at UC Berkeley, vLLM has grown into one of the most active open-source AI projects built and maintained by a diverse community of many dozens of academic institutions and companies from over 2000 contributors.\n27|\n28|vLLM is fast with:\n29|\n30|- State-of-the-art serving throughput\n31|- Efficient management of attention key and value memory with [**PagedAttention**](https://blog.vllm.ai/2023/06/20/vllm.html)\n32|- Continuous batching of incoming requests, chunked prefill, prefix caching\n33|- Fast and flexible model execution with piecewise and full CUDA/HIP graphs\n34|- Quantization: FP8, MXFP8/MXFP4, NVFP4, INT8, INT4, GPTQ/AWQ, GGUF, compressed-tensors, ModelOpt, TorchAO, and [more](https://docs.vllm.ai/en/latest/features/quantization/index.html)\n35|- Optimized attention kernels including FlashAttention, FlashInfer, TRTLLM-GEN, FlashMLA, and Triton\n36|- Optimized GEMM/MoE kernels for various precisions using CUTLASS, TRTLLM-GEN, CuTeDSL\n37|- Speculative decoding including n-gram, suffix, EAGLE, DFlash\n38|- Automatic kernel generation and graph-level transformations using torch.compile\n39|- Disaggregated prefill, decode, and encode\n40|\n41|vLLM is flexible and easy to use with:\n42|\n43|- Seamless integration with popular Hugging Face models\n44|- High-throughput serving with various decoding algorithms, including *parallel sampling*, *beam search*, and more\n45|- Tensor, pipeline, data, expert, and context parallelism for distributed inference\n46|- Streaming outputs\n47|- Generation of structured outputs using xgrammar or guidance\n48|- Tool calling and reasoning parsers\n49|- OpenAI-compatible API server, plus Anthropic Messages API and gRPC support\n50|- Efficient multi-LoRA support for dense and MoE layers\n51|- Support for NVIDIA GPUs, AMD GPUs, and x86/ARM/PowerPC CPUs. Additionally, diverse hardware plugins such as Google TPUs, Intel Gaudi, IBM Spyre, Huawei Ascend, Rebellions NPU, Apple Silicon, MetaX GPU, and more.\n52|\n53|vLLM seamlessly supports 200+ model architectures on Hugging Face, including:\n54|\n55|- Decoder-only LLMs (e.g., Llama, Qwen, Gemma)\n56|- Mixture-of-Expert LLMs (e.g., Mixtral, DeepSeek-V3, Qwen-MoE, GPT-OSS)\n57|- Hybrid attention and state-space models (e.g., Mamba, Qwen3.5)\n58|- Multi-modal models (e.g., LLaVA, Qwen-VL, Pixtral)\n59|- Embedding and retrieval models (e.g., E5-Mistral, GTE, ColBERT)\n60|- Reward and classification models (e.g., Qwen-Math)\n61|\n62|Find the full list of supported models [here](https://docs.vllm.ai/en/latest/models/supported_models.html).\n63|\n64|## Getting Started\n65|\n66|Install vLLM with [`uv`](https://docs.astral.sh/uv/) (recommended) or `pip`:\n67|\n68|```bash\n69|uv pip install vllm\n70|```\n71|\n72|Or [build from source](https://docs.vllm.ai/en/latest/getting_started/installation/gpu/index.html#build-wheel-from-source) for development.\n73|\n74|Visit our [documentation](https://docs.vllm.ai/en/latest/) to learn more.\n75|\n76|- [Installation](https://docs.vllm.ai/en/latest/getting_started/installation.html)\n77|- [Quickstart](https://docs.vllm.ai/en/latest/getting_started/quickstart.html)\n78|- [List of Supported Models](https://docs.vllm.ai/en/latest/models/supported_models.html)\n79|\n80|## Contributing\n81|\n82|We welcome and value any contributions and collaborations.\n83|Please check out [Contributing to vLLM](https://docs.vllm.ai/en/latest/contributing/index.html) for how to get involved.\n84|\n85|## Citation\n86|\n87|If you use vLLM for your research, please cite our [paper](https://arxiv.org/abs/2309.06180):\n88|\n89|```bibtex\n90|@inproceedings{kwon2023efficient,\n91|  title={Efficient Memory Management for Large Language Model Serving with PagedAttention},\n92|  author={Woosuk Kwon and Zhuohan Li and Siyuan Zhuang and Ying Sheng and Lianmin Zheng and Cody Hao Yu and Joseph E. Gonzalez and Hao Zhang and Ion Stoica},\n93|  booktitle={Proceedings of the ACM SIGOPS 29th Symposium on Operating Systems Principles},\n94|  year={2023}\n95|}\n96|```\n97|\n98|## Contact Us\n99|\n100|<!-- --8<-- [start:contact-us] -->\n101|- For technical questions and feature requests, please use GitHub [Issues](https://github.com/vllm-project/vllm/issues)\n102|- For discussing with fellow users, please use the [vLLM Forum](https://discuss.vllm.ai)\n103|- For coordinating contributions and development, please use [Slack](https://slack.vllm.ai)\n104|- For security disclosures, please use GitHub's [Security Advisories](https://github.com/vllm-project/vllm/security/advisories) feature\n105|- For collaborations and partnerships, please contact us at [collaboration@vllm.ai](mailto:collaboration@vllm.ai)\n106|<!-- --8<-- [end:contact-us] -->\n107|\n108|## Media Kit\n109|\n110|- If you wish to use vLLM's logo, please refer to [our media kit repo](https://github.com/vllm-project/media-kit)\n111|", "total_lines": 110, "file_size": 5696, "truncated": false, "is_binary": false, "is_image": false}

  [Subdirectory context discovered: vllm/AGENTS.md]
  # Agent Instructions for vLLM

  > These instructions apply to **all** AI-assisted contributions to `vllm-project/vllm`.
  > Breaching these guidelines can result in automatic banning.

  ## 1. Contribution Policy (Mandatory)

  ### Duplicate-work checks

  Before proposing a PR, run these checks:

  ```bash
  gh issue view <issue_number> --repo vllm-project/vllm --comments
  gh pr list --repo vllm-project/vllm --state open --search "<issue_number> in:body"
  gh pr list --repo vllm-project/vllm --state open --search "<short area keywords>"
  ```

  - If an open PR already addresses the same fix, do not open another.
  - If your approach is materially different, explain the difference in the issue.

  ### No low-value busywork PRs

  Do not open one-off PRs for tiny edits (single typo, isolated style change, one mutable default, etc.). Mechanical cleanups are acceptable only when bundled with substantive work.

  ### Accountability

  - Pure code-agent PRs are **not allowed**. A human submitter must understand and defend the change end-to-end.
  - The submitting human must review every changed line and run relevant tests.
  - PR descriptions for AI-assisted work **must** include:
      - Why this is not duplicating an existing PR.
      - Test commands run and results.
      - Clear statement that AI assistance was used.

  ### Fail-closed behavior

  If work is duplicate/trivial busywork, **do not proceed**. Return a short explanation of what is missing.

  ---

  ## 2. Development Workflow

  - **Never use system `python3` or bare `pip`/`pip install`.** All Python commands must go through `uv` and `.venv/bin/python`.

  ### Environment setup

  ```bash
  # Install `uv` if you don't have it already:
  curl -LsSf https://astral.sh/uv/install.sh | sh

  # Always use `uv` for Python environment management:
  uv venv --python 3.12
  source .venv/bin/activate

  # Always make sure `pre-commit` and its hooks are installed:
  uv pip install -r requirements/lint.txt
  pre-commit install
  ```

  ### Installing dependencies

  ```bash
  # If you are only making Python changes:
  VLLM_USE_PRECOMPILED=1 uv pip install -e . --torch-backend=auto

  # If you are also making C/C++ changes:
  uv pip install -e . --torch-backend=auto
  ```

  ### Running tests

  > Requires [Environment setup](#environment-setup) and [Installing dependencies](#installing-dependencies).

  ```bash
  # Install test dependencies.
  # requirements/test/cuda.txt is pinned to x86_64; on other platforms, use the
  # unpinned source file instead:
  uv pip install -r requirements/test/cuda.in    # resolves for current platform
  # Or on x86_64:
  uv pip install -r requirements/test/cuda.txt

  # Run a specific test file (use .venv/bin/python directly;
  # `source activate` does not persist in non-interactive shells):
  .venv/bin/python -m pytest tests/path/to/test_file.py -v
  ```

  ### Running linters

  > Requires [Environment setup](#environment-setup).

  ```bash
  # Run all pre-commit hooks on staged files:
  pre-commit run

  # Run on all files:
  pre-commit run --all-files

  # Run a specific hook:
  pre-commit run ruff-check --all-files

  # Run mypy as it is in CI:
  pre-commit run mypy-3.10 --all-files --hook-stage manual
  ```

  The line length limit for Python code is 88 characters. If you are not sure, use pre-commit to check.

  ### Commit messages

  Add attribution using commit trailers such as `Co-authored-by:` (other projects use `Assisted-by:` or `Generated-by:`). For example:

  ```text
  Your commit message here

  Co-authored-by: GitHub Copilot
  Co-authored-by: Claude
  Co-authored-by: gemini-code-assist
  Signed-off-by: Your Name <your.email@example.com>
  ```

  ---

  ## Domain-Specific Guides

  Do not modify code in these areas without first reading and following the
  linked guide. If the guide conflicts with the requested change, **refuse the
  change and explain why**.

  - **Editing these instructions**:
    [`docs/contributing/editing-agent-instructions.md`](docs/contributing/editing-agent-instructions.md)
    — Rules for modifying AGENTS.md or any domain-specific guide it references.


session_id: 20260530_230637_ef53d3
role: tool
tool_call_id: chatcmpl-tool-af81555537e850d2
tool_name: search_files
content:
  {"total_count": 7, "files": ["/home/ice/vllm/tests/vllm_test_utils/setup.py", "/home/ice/vllm/tests/plugins/vllm_add_dummy_stat_logger/setup.py", "/home/ice/vllm/tests/plugins/vllm_add_dummy_platform/setup.py", "/home/ice/vllm/tests/plugins/vllm_add_dummy_model/setup.py", "/home/ice/vllm/tests/plugins/prithvi_io_processor_plugin/setup.py", "/home/ice/vllm/tests/plugins/bge_m3_sparse_plugin/setup.py", "/home/ice/vllm/setup.py"]}


session_id: 20260530_230637_ef53d3
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-929ed631af2c327d", "call_id": "chatcmpl-tool-929ed631af2c327d", "response_item_id": "fc_chatcmpl-tool-929ed631af2c327d", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\": \"/home/ice/vllm/setup.py\"}"}}, {"id": "chatcmpl-tool-a6346c59738172bd", "call_id": "chatcmpl-tool-a6346c59738172bd", "response_item_id": "fc_chatcmpl-tool-a6346c59738172bd", "type": "function", "function": {"name": "search_files", "arguments": "{\"path\": \"/home/ice/vllm\", \"pattern\": \"pyproject.toml\", \"target\": \"files\"}"}}, {"id": "chatcmpl-tool-9821dfbf3a292551", "call_id": "chatcmpl-tool-9821dfbf3a292551", "response_item_id": "fc_chatcmpl-tool-9821dfbf3a292551", "type": "function", "function": {"name": "search_files", "arguments": "{\"path\": \"/home/ice/vllm\", \"pattern\": \"LICENSE\", \"target\": \"files\"}"}}]

reasoning:
  Good, I have the README and found setup.py files. Let me check the main setup.py for dependencies and tech stack, and also look for any pyproject.toml. I also want to get a summary of the directory structure to understand the project better. Let me also check the license file.

reasoning_content:
  Good, I have the README and found setup.py files. Let me check the main setup.py for dependencies and tech stack, and also look for any pyproject.toml. I also want to get a summary of the directory structure to understand the project better. Let me also check the license file.


session_id: 20260530_230637_ef53d3
role: tool
tool_call_id: chatcmpl-tool-929ed631af2c327d
tool_name: read_file
content:
  {"content": "1|# SPDX-License-Identifier: Apache-2.0\n2|# SPDX-FileCopyrightText: Copyright contributors to the vLLM project\n3|\n4|import ctypes\n5|import importlib.util\n6|import json\n7|import logging\n8|import os\n9|import re\n10|import shutil\n11|import subprocess\n12|import sys\n13|import sysconfig\n14|from pathlib import Path\n15|from shutil import which\n16|\n17|import torch\n18|from packaging.version import Version, parse\n19|from setuptools import Extension, setup\n20|from setuptools.command.build_ext import build_ext\n21|from setuptools_rust import Binding, RustExtension\n22|from setuptools_rust.build import build_rust\n23|from setuptools_scm import get_version\n24|from torch.utils.cpp_extension import CUDA_HOME, ROCM_HOME\n25|\n26|\n27|def load_module_from_path(module_name, path):\n28|    spec = importlib.util.spec_from_file_location(module_name, path)\n29|    module = importlib.util.module_from_spec(spec)\n30|    sys.modules[module_name] = module\n31|    spec.loader.exec_module(module)\n32|    return module\n33|\n34|\n35|ROOT_DIR = Path(__file__).parent\n36|logger = logging.getLogger(__name__)\n37|\n38|PRECOMPILED_RUST_FRONTEND_PATH = ROOT_DIR / \"vllm\" / \"vllm-rs\"\n39|\n40|# cannot import envs directly because it depends on vllm,\n41|#  which is not installed yet\n42|envs = load_module_from_path(\"envs\", os.path.join(ROOT_DIR, \"vllm\", \"envs.py\"))\n43|\n44|VLLM_TARGET_DEVICE = envs.VLLM_TARGET_DEVICE\n45|USE_PRECOMPILED_EXTENSIONS = envs.VLLM_USE_PRECOMPILED\n46|# VLLM_USE_PRECOMPILED implies precompiled rust frontend too.\n47|USE_PRECOMPILED_RUST_FRONTEND = (\n48|    envs.VLLM_USE_PRECOMPILED or envs.VLLM_USE_PRECOMPILED_RUST\n49|)\n50|\n51|\n52|def should_require_rust_frontend() -> bool:\n53|    value = os.getenv(\"VLLM_REQUIRE_RUST_FRONTEND\", \"\")\n54|    return value.lower() not in (\"\", \"0\", \"false\", \"no\")\n55|\n56|\n57|if sys.platform.startswith(\"darwin\") and VLLM_TARGET_DEVICE != \"cpu\":\n58|    logger.warning(\"VLLM_TARGET_DEVICE automatically set to `cpu` due to macOS\")\n59|    VLLM_TARGET_DEVICE = \"cpu\"\n60|elif not (sys.platform.startswith(\"linux\") or sys.platform.startswith(\"darwin\")):\n61|    logger.warning(\n62|        \"vLLM only supports Linux platform (including WSL) and MacOS.\"\n63|        \"Building on %s, \"\n64|        \"so vLLM may not be able to run correctly\",\n65|        sys.platform,\n66|    )\n67|    VLLM_TARGET_DEVICE = \"empty\"\n68|elif sys.platform.startswith(\"linux\") and os.getenv(\"VLLM_TARGET_DEVICE\") is None:\n69|    if torch.version.hip is not None:\n70|        VLLM_TARGET_DEVICE = \"rocm\"\n71|        logger.info(\"Auto-detected ROCm\")\n72|    elif torch.version.xpu is not None:\n73|        VLLM_TARGET_DEVICE = \"xpu\"\n74|        logger.info(\"Auto-detected XPU\")\n75|    elif torch.version.cuda is not None:\n76|        VLLM_TARGET_DEVICE = \"cuda\"\n77|        logger.info(\"Auto-detected CUDA\")\n78|    else:\n79|        VLLM_TARGET_DEVICE = \"cpu\"\n80|\n81|\n82|def is_sccache_available() -> bool:\n83|    return which(\"sccache\") is not None and not bool(\n84|        int(os.getenv(\"VLLM_DISABLE_SCCACHE\", \"0\"))\n85|    )\n86|\n87|\n88|def is_ccache_available() -> bool:\n89|    return which(\"ccache\") is not None\n90|\n91|\n92|def is_ninja_available() -> bool:\n93|    return which(\"ninja\") is not None\n94|\n95|\n96|def is_freethreaded():\n97|    return bool(sysconfig.get_config_var(\"Py_GIL_DISABLED\"))\n98|\n99|\n100|def should_bundle_tcmalloc() -> bool:\n101|    import platform\n102|\n103|    return (\n104|        VLLM_TARGET_DEVICE == \"cpu\"\n105|        and sys.platform.startswith(\"linux\")\n106|        and platform.machine() in (\"aarch64\", \"x86_64\")\n107|    )\n108|\n109|\n110|def find_tcmalloc() -> Path | None:\n111|    try:\n112|        # get all shared libs the dynamic loader knows about\n113|        output = subprocess.check_output(\n114|            [\"ldconfig\", \"-p\"],\n115|            text=True,\n116|            stderr=subprocess.DEVNULL,\n117|        )\n118|    except Exception:\n119|        return None\n120|\n121|    # search for libtcmalloc and libtcmalloc_minimal\n122|    for library_pattern in (\n123|        r\"\\blibtcmalloc_minimal\\.so\\.(\\d+)\\b\",\n124|        r\"\\blibtcmalloc\\.so\\.(\\d+)\\b\",\n125|    ):\n126|        candidates: list[tuple[int, Path]] = []\n127|        for line in output.splitlines():\n128|            match = re.search(library_pattern, line)\n129|            if match is None or \"=>\" not in line:\n130|                continue\n131|            candidate = Path(line.split(\"=>\")[1].strip())\n132|            if candidate.exists():\n133|                candidates.append((int(match.group(1)), candidate))\n134|\n135|        if candidates:\n136|            # if multiple candidates are found, pick the one with the highest\n137|            # version number\n138|            return max(candidates, key=lambda item: item[0])[1]\n139|\n140|    return None\n141|\n142|\n143|def bundle_tcmalloc(build_lib: str) -> None:\n144|    tcmalloc_library = find_tcmalloc()\n145|    if tcmalloc_library is None:\n146|        logger.warning(\n147|            \"Failed to locate tcmalloc. For best performance, \"\n148|            \"please install tcmalloc (e.g. `sudo apt-get \"\n149|            \"install -y --no-install-recommends libtcmalloc-minimal4`)\"\n150|        )\n151|        return\n152|\n153|    bundle_dir = os.path.join(build_lib, \"vllm\", \"libs\")\n154|    os.makedirs(bundle_dir, exist_ok=True)\n155|    bundle_path = os.path.join(bundle_dir, tcmalloc_library.name)\n156|    shutil.copy2(tcmalloc_library, bundle_path)\n157|    logger.info(\"Bundled tcmalloc into wheel: %s\", bundle_path)\n158|\n159|\n160|class CMakeExtension(Extension):\n161|    def __init__(self, name: str, cmake_lists_dir: str = \".\", **kwa) -> None:\n162|        super().__init__(name, sources=[], py_limited_api=not is_freethreaded(), **kwa)\n163|        self.cmake_lists_dir = os.path.abspath(cmake_lists_dir)\n164|\n165|\n166|class cmake_build_ext(build_ext):\n167|    # A dict of extension directories that have been configured.\n168|    did_config: dict[str, bool] = {}\n169|\n170|    #\n171|    # Determine number of compilation jobs and optionally nvcc compile threads.\n172|    #\n173|    def compute_num_jobs(self):\n174|        # `num_jobs` is either the value of the MAX_JOBS environment variable\n175|        # (if defined) or the number of CPUs available.\n176|        num_jobs = envs.MAX_JOBS\n177|        if num_jobs is not None:\n178|            num_jobs = int(num_jobs)\n179|            logger.info(\"Using MAX_JOBS=%d as the number of jobs.\", num_jobs)\n180|        else:\n181|            try:\n182|                # os.sched_getaffinity() isn't universally available, so fall\n183|                #  back to os.cpu_count() if we get an error here.\n184|                num_jobs = len(os.sched_getaffinity(0))\n185|            except AttributeError:\n186|                num_jobs = os.cpu_count()\n187|\n188|        nvcc_threads = None\n189|        if _is_cuda() and CUDA_HOME is not None:\n190|            try:\n191|                nvcc_version = get_nvcc_cuda_version()\n192|                if nvcc_version >= Version(\"11.2\"):\n193|                    # `nvcc_threads` is either the value of the NVCC_THREADS\n194|                    # environment variable (if defined) or 1.\n195|                    # when it is set, we reduce `num_jobs` to avoid\n196|                    # overloading the system.\n197|                    nvcc_threads = envs.NVCC_THREADS\n198|                    if nvcc_threads is not None:\n199|                        nvcc_threads = int(nvcc_threads)\n200|                        logger.info(\n201|                            \"Using NVCC_THREADS=%d as the number of nvcc threads.\",\n202|                            nvcc_threads,\n203|                        )\n204|                    else:\n205|                        nvcc_threads = 1\n206|                    num_jobs = max(1, num_jobs // nvcc_threads)\n207|            except Exception as e:\n208|                logger.warning(\"Failed to get NVCC version: %s\", e)\n209|\n210|        return num_jobs, nvcc_threads\n211|\n212|    #\n213|    # Perform cmake configuration for a single extension.\n214|    #\n215|    def configure(self, ext: CMakeExtension) -> None:\n216|        # If we've already configured using the CMakeLists.txt for\n217|        # this extension, exit early.\n218|        if ext.cmake_lists_dir in cmake_build_ext.did_config:\n219|            return\n220|\n221|        cmake_build_ext.did_config[ext.cmake_lists_dir] = True\n222|\n223|        # Select the build type.\n224|        # Note: optimization level + debug info are set by the build type\n225|        default_cfg = \"Debug\" if self.debug else \"RelWithDebInfo\"\n226|        cfg = envs.CMAKE_BUILD_TYPE or default_cfg\n227|\n228|        cmake_args = [\n229|            \"-DCMAKE_BUILD_TYPE={}\".format(cfg),\n230|            \"-DVLLM_TARGET_DEVICE={}\".format(VLLM_TARGET_DEVICE),\n231|        ]\n232|\n233|        verbose = envs.VERBOSE\n234|        if verbose:\n235|            cmake_args += [\"-DCMAKE_VERBOSE_MAKEFILE=ON\"]\n236|\n237|        if is_sccache_available():\n238|            cmake_args += [\n239|                \"-DCMAKE_C_COMPILER_LAUNCHER=sccache\",\n240|                \"-DCMAKE_CXX_COMPILER_LAUNCHER=sccache\",\n241|                \"-DCMAKE_CUDA_COMPILER_LAUNCHER=sccache\",\n242|                \"-DCMAKE_HIP_COMPILER_LAUNCHER=sccache\",\n243|            ]\n244|        elif is_ccache_available():\n245|            cmake_args += [\n246|                \"-DCMAKE_C_COMPILER_LAUNCHER=ccache\",\n247|                \"-DCMAKE_CXX_COMPILER_LAUNCHER=ccache\",\n248|                \"-DCMAKE_CUDA_COMPILER_LAUNCHER=ccache\",\n249|                \"-DCMAKE_HIP_COMPILER_LAUNCHER=ccache\",\n250|            ]\n251|\n252|        # Pass the python executable to cmake so it can find an exact\n253|        # match.\n254|        cmake_args += [\"-DVLLM_PYTHON_EXECUTABLE={}\".format(sys.executable)]\n255|\n256|        # Pass the python path to cmake so it can reuse the build dependencies\n257|        # on subsequent calls to python.\n258|        cmake_args += [\"-DVLLM_PYTHON_PATH={}\".format(\":\".join(sys.path))]\n259|\n260|        # Override the base directory for FetchContent downloads to $ROOT/.deps\n261|        # This allows sharing dependencies between profiles,\n262|        # and plays more nicely with sccache.\n263|        # To override this, set the FETCHCONTENT_BASE_DIR environment variable.\n264|        fc_base_dir = os.path.join(ROOT_DIR, \".deps\")\n265|        fc_base_dir = os.environ.get(\"FETCHCONTENT_BASE_DIR\", fc_base_dir)\n266|        cmake_args += [\"-DFETCHCONTENT_BASE_DIR={}\".format(fc_base_dir)]\n267|\n268|        #\n269|        # Setup parallelism and build tool\n270|        #\n271|        num_jobs, nvcc_threads = self.compute_num_jobs()\n272|\n273|        if nvcc_threads:\n274|            cmake_args += [\"-DNVCC_THREADS={}\".format(nvcc_threads)]\n275|\n276|        if is_ninja_available():\n277|            build_tool = [\"-G\", \"Ninja\"]\n278|            cmake_args += [\n279|                \"-DCMAKE_JOB_POOL_COMPILE:STRING=compile\",\n280|                \"-DCMAKE_JOB_POOLS:STRING=compile={}\".format(num_jobs),\n281|            ]\n282|        else:\n283|            # Default build tool to whatever cmake picks.\n284|            build_tool = []\n285|        # Make sure we use the nvcc from CUDA_HOME\n286|        if _is_cuda() and CUDA_HOME is not None:\n287|            cmake_args += [f\"-DCMAKE_CUDA_COMPILER={CUDA_HOME}/bin/nvcc\"]\n288|        elif _is_hip() and ROCM_HOME is not None:\n289|            cmake_args += [f\"-DROCM_PATH={ROCM_HOME}\"]\n290|\n291|        other_cmake_args = os.environ.get(\"CMAKE_ARGS\")\n292|        if other_cmake_args:\n293|            cmake_args += other_cmake_args.split()\n294|\n295|        subprocess.check_call(\n296|            [\"cmake\", ext.cmake_lists_dir, *build_tool, *cmake_args],\n297|            cwd=self.build_temp,\n298|        )\n299|\n300|    def build_extensions(self) -> None:\n301|        # Ensure that CMake is present and working\n302|        try:\n303|            subprocess.check_output([\"cmake\", \"--version\"])\n304|        except OSError as e:\n305|            raise RuntimeError(\"Cannot find CMake executable\") from e\n306|\n307|        # Create build directory if it does not exist.\n308|        if not os.path.exists(self.build_temp):\n309|            os.makedirs(self.build_temp)\n310|\n311|        targets = []\n312|\n313|        def target_name(s: str) -> str:\n314|            return s.removeprefix(\"vllm.\").removeprefix(\"vllm_flash_attn.\")\n315|\n316|        # Build all the extensions\n317|        for ext in self.extensions:\n318|            self.configure(ext)\n319|            targets.append(target_name(ext.name))\n320|\n321|        num_jobs, _ = self.compute_num_jobs()\n322|\n323|        build_args = [\n324|            \"--build\",\n325|            \".\",\n326|            f\"-j={num_jobs}\",\n327|            *[f\"--target={name}\" for name in targets],\n328|        ]\n329|\n330|        subprocess.check_call([\"cmake\", *build_args], cwd=self.build_temp)\n331|\n332|        # Install the libraries\n333|        for ext in self.extensions:\n334|            # Install the extension into the proper location\n335|            outdir = Path(self.get_ext_fullpath(ext.name)).parent.absolute()\n336|\n337|            # Skip if the install directory is the same as the build directory\n338|            if outdir == self.build_temp:\n339|                continue\n340|\n341|            # CMake appends the extension prefix to the install path,\n342|            # and outdir already contains that prefix, so we need to remove it.\n343|            prefix = outdir\n344|            for _ in range(ext.name.count(\".\")):\n345|                prefix = prefix.parent\n346|\n347|            # prefix here should actually be the same for all components\n348|            install_args = [\n349|                \"cmake\",\n350|                \"--install\",\n351|                \".\",\n352|                \"--prefix\",\n353|                prefix,\n354|                \"--component\",\n355|                target_name(ext.name),\n356|            ]\n357|            subprocess.check_call(install_args, cwd=self.build_temp)\n358|\n359|    def run(self):\n360|        # First, run the standard build_ext command to compile the extensions\n361|        super().run()\n362|\n363|        # bundle tcmalloc into CPU wheels for best OOB perf\n364|        if should_bundle_tcmalloc():\n365|            bundle_tcmalloc(self.build_lib)\n366|\n367|        # copy vllm/vllm_flash_attn/**/*.py from self.build_lib to current\n368|        # directory so that they can be included in the editable build\n369|        import glob\n370|\n371|        files = glob.glob(\n372|            os.path.join(self.build_lib, \"vllm\", \"vllm_flash_attn\", \"**\", \"*.py\"),\n373|            recursive=True,\n374|        )\n375|        for file in files:\n376|            dst_file = os.path.join(\n377|                \"vllm/vllm_flash_attn\", file.split(\"vllm/vllm_flash_attn/\")[-1]\n378|            )\n379|            print(f\"Copying {file} to {dst_file}\")\n380|            os.makedirs(os.path.dirname(dst_file), exist_ok=True)\n381|            self.copy_file(file, dst_file)\n382|\n383|        if _is_cuda() or _is_hip():\n384|            # copy vllm/third_party/triton_kernels/**/*.py from self.build_lib\n385|            # to current directory so that they can be included in the editable\n386|            # build\n387|            print(\n388|                f\"Copying {self.build_lib}/vllm/third_party/triton_kernels \"\n389|                \"to vllm/third_party/triton_kernels\"\n390|            )\n391|            shutil.copytree(\n392|                f\"{self.build_lib}/vllm/third_party/triton_kernels\",\n393|                \"vllm/third_party/triton_kernels\",\n394|                dirs_exist_ok=True,\n395|            )\n396|\n397|        if _is_cuda():\n398|            # copy vendored deep_gemm package from build_lib to source tree\n399|            # for editable installs\n400|            deep_gemm_build = os.path.join(\n401|                self.build_lib, \"vllm\", \"third_party\", \"deep_gemm\"\n402|            )\n403|            if os.path.exists(deep_gemm_build):\n404|                print(f\"Copying {deep_gemm_build} to vllm/third_party/deep_gemm\")\n405|                shutil.copytree(\n406|                    deep_gemm_build,\n407|                    \"vllm/third_party/deep_gemm\",\n408|                    dirs_exist_ok=True,\n409|                )\n410|\n411|\n412|class precompiled_build_ext(build_ext):\n413|    \"\"\"Disables extension building when using precompiled binaries.\"\"\"\n414|\n415|    def run(self) -> None:\n416|        return\n417|\n418|    def build_extensions(self) -> None:\n419|        print(\"Skipping build_ext: using precompiled extensions.\")\n420|        return\n421|\n422|\n423|class precompiled_build_rust(build_rust):\n424|    \"\"\"Skips local Rust builds when the precompiled wheel already ships vllm-rs.\"\"\"\n425|\n426|    def run(self) -> None:\n427|        if PRECOMPILED_RUST_FRONTEND_PATH.exists():\n428|            logger.info(\n429|                \"Skipping local Rust build: using precompiled %s\",\n430|                PRECOMPILED_RUST_FRONTEND_PATH,\n431|            )\n432|            return\n433|\n434|        logger.warning(\n435|            \"Precompiled wheel did not provide %s; falling back to local Rust build.\",\n436|            PRECOMPILED_RUST_FRONTEND_PATH,\n437|        )\n438|        super().run()\n439|\n440|\n441|class precompiled_wheel_utils:\n442|    \"\"\"Extracts libraries and other files from an existing wheel.\"\"\"\n443|\n444|    @staticmethod\n445|    def fetch_metadata_for_variant(\n446|        commit: str, variant: str | None\n447|    ) -> tuple[list[dict], str]:\n448|        \"\"\"\n449|        Fetches metadata for a specific variant of the precompiled wheel.\n450|        \"\"\"\n451|        variant_dir = f\"{variant}/\" if variant is not None else \"\"\n452|        repo_url = f\"https://wheels.vllm.ai/{commit}/{variant_dir}vllm/\"\n453|        meta_url = repo_url + \"metadata.json\"\n454|        print(f\"Trying to fetch nightly build metadata from {meta_url}\")\n455|        from urllib.request import urlopen\n456|\n457|        with urlopen(meta_url) as resp:\n458|            # urlopen raises HTTPError on unexpected status code\n459|            wheels = json.loads(resp.read().decode(\"utf-8\"))\n460|        return wheels, repo_url\n461|\n462|    @staticmethod\n463|    def is_rocm_system() -> bool:\n464|        \"\"\"Detect ROCm without relying on torch (for build environment).\"\"\"\n465|        if os.getenv(\"ROCM_PATH\"):\n466|            return True\n467|        if os.path.isdir(\"/opt/rocm\"):\n468|            return True\n469|        if which(\"rocminfo\") is not None:\n470|            return True\n471|        try:\n472|            import torch\n473|\n474|            return torch.version.hip is not None\n475|        except ImportError:\n476|            return False\n477|\n478|    @staticmethod\n479|    def detect_system_cuda_variant() -> str:\n480|        \"\"\"Auto-detect CUDA variant from torch, nvidia-smi, or env default.\"\"\"\n481|\n482|        # Map CUDA major version to hosted wheel variants on wheels.vllm.ai\n483|        supported = {12: \"cu129\", 13: \"cu130\"}\n484|\n485|        # Respect explicitly set VLLM_MAIN_CUDA_VERSION\n486|        if envs.is_set(\"VLLM_MAIN_CUDA_VERSION\"):\n487|            v = envs.VLLM_MAIN_CUDA_VERSION\n488|            print(f\"Using VLLM_MAIN_CUDA_VERSION={v}\")\n489|            return \"cu\" + v.replace(\".\", \"\")[:3]\n490|\n491|        # Try torch.version.cuda\n492|        cuda_version = None\n493|        try:\n494|            import torch\n495|\n496|            cuda_version = torch.version.cuda\n497|        except Exception:\n498|            pass\n499|\n500|        # Try nvidia-smi\n501|", "total_lines": 1199, "file_size": 45537, "truncated": true, "hint": "Use offset=501 to continue reading (showing 1-500 of 1199 lines)", "is_binary": false, "is_image": false}


session_id: 20260530_230637_ef53d3
role: tool
tool_call_id: chatcmpl-tool-a6346c59738172bd
tool_name: search_files
content:
  {"total_count": 2, "files": ["/home/ice/vllm/pyproject.toml", "/home/ice/vllm/examples/features/structured_outputs/pyproject.toml"]}


session_id: 20260530_230637_ef53d3
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-9e8fad65fe0a2ad8", "call_id": "chatcmpl-tool-9e8fad65fe0a2ad8", "response_item_id": "fc_chatcmpl-tool-9e8fad65fe0a2ad8", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\": \"/home/ice/vllm/pyproject.toml\"}"}}, {"id": "chatcmpl-tool-ab54ccc9a8b0bdb8", "call_id": "chatcmpl-tool-ab54ccc9a8b0bdb8", "response_item_id": "fc_chatcmpl-tool-ab54ccc9a8b0bdb8", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\": \"/home/ice/vllm/LICENSE\"}"}}]

reasoning:
  I have enough information from the README.md. The task asks to find the repository's Problem, Theme, Hype reason, and Technologies. Let me also check pyproject.toml for completeness.

reasoning_content:
  I have enough information from the README.md. The task asks to find the repository's Problem, Theme, Hype reason, and Technologies. Let me also check pyproject.toml for completeness.


session_id: 20260530_230637_ef53d3
role: tool
tool_call_id: chatcmpl-tool-9e8fad65fe0a2ad8
tool_name: read_file
content:
  {"content": "1|[build-system]\n2|# Should be mirrored in requirements/build/cuda.txt\n3|requires = [\n4|    \"cmake>=3.26.1\",\n5|    \"ninja\",\n6|    \"packaging>=24.2\",\n7|    \"setuptools>=77.0.3,<81.0.0\",\n8|    \"setuptools-scm>=8.0\",\n9|    \"setuptools-rust>=1.9.0\",\n10|    \"torch == 2.11.0\",\n11|    \"wheel\",\n12|    \"jinja2\",\n13|]\n14|build-backend = \"setuptools.build_meta\"\n15|\n16|[project]\n17|name = \"vllm\"\n18|authors = [{name = \"vLLM Team\"}]\n19|license = \"Apache-2.0\"\n20|license-files = [\"LICENSE\"]\n21|readme = \"README.md\"\n22|description = \"A high-throughput and memory-efficient inference and serving engine for LLMs\"\n23|classifiers = [\n24|    \"Programming Language :: Python :: 3.10\",\n25|    \"Programming Language :: Python :: 3.11\",\n26|    \"Programming Language :: Python :: 3.12\",\n27|    \"Programming Language :: Python :: 3.13\",\n28|    \"Programming Language :: Python :: 3.14\",\n29|    \"Intended Audience :: Developers\",\n30|    \"Intended Audience :: Information Technology\",\n31|    \"Intended Audience :: Science/Research\",\n32|    \"Topic :: Scientific/Engineering :: Artificial Intelligence\",\n33|    \"Topic :: Scientific/Engineering :: Information Analysis\",\n34|]\n35|requires-python = \">=3.10,<3.15\"\n36|dynamic = [ \"version\", \"dependencies\", \"optional-dependencies\"]\n37|\n38|[project.urls]\n39|Homepage=\"https://github.com/vllm-project/vllm\"\n40|Documentation=\"https://docs.vllm.ai/en/latest/\"\n41|Slack=\"https://slack.vllm.ai/\"\n42|\n43|[project.scripts]\n44|vllm = \"vllm.entrypoints.cli.main:main\"\n45|\n46|[project.entry-points.\"vllm.general_plugins\"]\n47|lora_filesystem_resolver = \"vllm.plugins.lora_resolvers.filesystem_resolver:register_filesystem_resolver\"\n48|lora_hf_hub_resolver = \"vllm.plugins.lora_resolvers.hf_hub_resolver:register_hf_hub_resolver\"\n49|\n50|[tool.setuptools_scm]\n51|# no extra settings needed, presence enables setuptools-scm\n52|\n53|[tool.setuptools.packages.find]\n54|where = [\".\"]\n55|include = [\"vllm*\"]\n56|\n57|[tool.ruff.lint.per-file-ignores]\n58|\"vllm/third_party/**\" = [\"ALL\"]\n59|\"vllm/version.py\" = [\"F401\"]\n60|\"vllm/_version.py\" = [\"ALL\"]\n61|\n62|[tool.ruff.lint]\n63|select = [\n64|    # pycodestyle\n65|    \"E\",\n66|    # Pyflakes\n67|    \"F\",\n68|    # pyupgrade\n69|    \"UP\",\n70|    # flake8-bugbear\n71|    \"B\",\n72|    # flake8-implicit-str-concat\n73|    \"ISC\",\n74|    # flake8-simplify\n75|    \"SIM\",\n76|    # isort\n77|    \"I\",\n78|    # flake8-logging-format\n79|    \"G\",\n80|]\n81|ignore = [\n82|    # star imports\n83|    \"F405\", \"F403\",\n84|    # lambda expression assignment\n85|    \"E731\",\n86|    # zip without `strict=`\n87|    \"B905\",\n88|    # Loop control variable not used within loop body\n89|    \"B007\",\n90|    # f-string format\n91|    \"UP032\",\n92|]\n93|\n94|[tool.ruff.format]\n95|docstring-code-format = true\n96|\n97|[tool.mypy]\n98|plugins = ['pydantic.mypy']\n99|ignore_missing_imports = true\n100|check_untyped_defs = true\n101|follow_imports = \"silent\"\n102|\n103|[tool.pytest.ini_options]\n104|markers = [\n105|    \"slow_test\",\n106|    \"skip_global_cleanup\",\n107|    \"core_model: enable this model test in each PR instead of only nightly\",\n108|    \"hybrid_model: models that contain mamba layers (including pure SSM and hybrid architectures)\",\n109|    \"cpu_model: enable this model test in CPU tests\",\n110|    \"cpu_test: mark test as CPU-only test\",\n111|    \"split: run this test as part of a split\",\n112|    \"distributed: run this test only in distributed GPU tests\",\n113|    \"optional: optional tests that are automatically skipped, include --optional to run them\",\n114|]\n115|\n116|[tool.ty.src]\n117|respect-ignore-files = true\n118|\n119|[tool.ty.environment]\n120|python = \"./.venv\"\n121|\n122|[tool.typos.files]\n123|# these files may be written in non english words\n124|extend-exclude = [\"tests/models/fixtures/*\", \"tests/prompts/*\", \"tests/tokenizers_/*\",\n125|    \"benchmarks/sonnet.txt\", \"tests/lora/data/*\", \"build/*\",\n126|    \"examples/pooling/token_embed/*\", \"tests/models/language/pooling/*\",\n127|    \"vllm/third_party/*\", \"vllm/entrypoints/serve/instrumentator/static/*\",\n128|    \"tests/entrypoints/speech_to_text/transcription/test_transcription_validation.py\",\n129|    \"docs/governance/process.md\", \"docs/assets/contributing/vllm_bench_serve_timeline.html\", \n130|    \"tests/v1/engine/test_fast_incdec_prefix_err.py\", \".git/*\", \"csrc/cpu/sgl-kernels/*\",\n131|    \"rust/src/chat/src/renderer/deepseek_v32/fixtures/*\",\n132|    \"rust/src/tool-parser/src/gemma4.rs\", \"rust/src/text/src/output/decoded.rs\",\n133|    \"rust/src/tokenizer/src/incremental.rs\", \"rust/src/reasoning-parser/src/tests.rs\"]\n134|ignore-hidden = false\n135|\n136|[tool.typos.default]\n137|extend-ignore-identifiers-re = [\".*[Uu][Ee][0-9][Mm][0-9].*\"]\n138|\n139|[tool.typos.default.extend-identifiers]\n140|bbc5b7ede = \"bbc5b7ede\"\n141|NOOPs = \"NOOPs\"\n142|nin_shortcut = \"nin_shortcut\"\n143|cudaDevAttrMaxSharedMemoryPerBlockOptin = \"cudaDevAttrMaxSharedMemoryPerBlockOptin\"\n144|sharedMemPerBlockOptin = \"sharedMemPerBlockOptin\"\n145|\n146|depthwise_seperable_out_channel = \"depthwise_seperable_out_channel\"\n147|pard_token = \"pard_token\"\n148|ptd_token_id = \"ptd_token_id\"\n149|ser_de = \"ser_de\"\n150|shared_memory_per_block_optin = \"shared_memory_per_block_optin\"\n151|FoPE = \"FoPE\"\n152|k_ot = \"k_ot\"\n153|view_seperator = \"view_seperator\"\n154|inverse_std_variences = \"inverse_std_variences\"\n155|\n156|[tool.typos.default.extend-words]\n157|iy = \"iy\"\n158|indx = \"indx\"\n159|# intel cpu features\n160|tme = \"tme\"\n161|dout = \"dout\"\n162|Pn = \"Pn\"\n163|arange = \"arange\"\n164|thw = \"thw\"\n165|subtile = \"subtile\"\n166|HSA = \"HSA\"\n167|setp = \"setp\"\n168|CPY = \"CPY\"\n169|thr = \"thr\"\n170|Thr = \"Thr\"\n171|PARD = \"PARD\"\n172|pard = \"pard\"\n173|AKS = \"AKS\"\n174|ba = \"ba\"\n175|fo = \"fo\"\n176|nd = \"nd\"\n177|eles = \"eles\"\n178|datas = \"datas\"\n179|ser = \"ser\"\n180|ure = \"ure\"\n181|VALU = \"VALU\"\n182|# Walsh-Hadamard Transform\n183|wht = \"wht\"\n184|WHT = \"WHT\"\n185|# Huawei Compute Architecture for Neural Networks\n186|CANN = \"CANN\"\n187|\n188|[tool.uv]\n189|no-build-isolation-package = [\"torch\"]\n190|", "total_lines": 189, "file_size": 5275, "truncated": false, "is_binary": false, "is_image": false}


session_id: 20260530_230637_ef53d3
role: tool
tool_call_id: chatcmpl-tool-ab54ccc9a8b0bdb8
tool_name: read_file
content:
  {"content": "1|                                 Apache License\n2|                           Version 2.0, January 2004\n3|                        http://www.apache.org/licenses/\n4|\n5|   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION\n6|\n7|   1. Definitions.\n8|\n9|      \"License\" shall mean the terms and conditions for use, reproduction,\n10|      and distribution as defined by Sections 1 through 9 of this document.\n11|\n12|      \"Licensor\" shall mean the copyright owner or entity authorized by\n13|      the copyright owner that is granting the License.\n14|\n15|      \"Legal Entity\" shall mean the union of the acting entity and all\n16|      other entities that control, are controlled by, or are under common\n17|      control with that entity. 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session_id: 20260530_230637_ef53d3
role: assistant
finish_reason: stop
content:
  # Análise do repositório vllm-project/vllm

  ## O que fiz
  Clonado o repositório em `/home/ice/vllm` e inspecionado arquivos principais (`README.md`, `pyproject.toml`, `setup.py`, `LICENSE`).

  ---

  ## Problema
  A necessidade de **servir e executar inferência de LLMs grandes (centenas de bilhões de parâmetros) de forma eficiente em escala**. Os desafios são:
  - Gerenciamento eficiente de memória GPU para KV cache
  - Baixa latência e alta taxa de transferência (throughput)
  - Suporte a múltiplos modelos e arquiteturas
  - Custo computacional/operacional elevado de soluções tradicionais

  ## Tema
  **Motor de inferência e serving para LLMs** — biblioteca/algoritmo para servir modelos de linguagem grandes em produção com desempenho de referência.

  ## Razão do Hype
  1. **PagedAttention**: algoritmo de gerenciamento de KV cache inspirado em paginação de memória virtual, reduzindo desperdício de memória em até 2–4×
  2. **Alta vazão**: state-of-the-art para throughput de serving
  3. **Ecosystem massivo**: 200+ arquiteturas de modelo suportadas
  4. **Stack completa**: quantização, continuous batching, chunked prefill, prefix caching, speculative decoding, Tensor/Pipeline/Data parallelism
  5. **Multi-hardware**: NVIDIA CUDA, AMD ROCm, Intel XPU, CPUs x86/ARM/PowerPC, Google TPU, Apple Silicon, entre outros
  6. **Open-source com tração**: 81k+ stars, 2000+ contribuidores, originado no UC Berkeley Sky Lab
  7. **Compatibilidade OpenAI**: servidor API drop-in replacement, Anthropic Messages API e gRPC

  ## Tecnologias
  - **Linguagem principal**: Python 3.10–3.13
  - **Framework ML**: PyTorch (torch==2.11.0 no build)
  - **GPU kernels**: CUDA, HIP (ROCm), Triton
  - **Kernels otimizados**: FlashAttention, FlashInfer, TRTLLM-GEN, FlashMLA, CUTLASS, CuTeDSL
  - **Rust**: frontend em Rust (`vllm-rs`) para performance
  - **Build system**: CMake + Ninja, cmake extensions, setuptools-rust
  - **Quantização**: FP8, MXFP8/MXFP4, NVFP4, INT8, INT4, AWQ/GPTQ, GGUF, compressed-tensors, TorchAO, ModelOpt
  - **Tooling**: setuptools-scm, uv, pre-commit, ruff, mypy, pytest
  - **Licença**: Apache 2.0

reasoning:
  I now have enough information about the vllm-project/vllm repository to produce the requested analysis. Based on what I've gathered:

  **Problema (Problem)**: A LLM serving and inference problem - serving Large Language Models (LLMs) efficiently at scale, with high-throughput, low-latency inference while managing GPU memory efficiently.

  **Tema (Theme)**: LLM Inference & Serving Engine - a high-performance model serving infrastructure.

  **Razão hype (Hype Reason)**: PagedAttention (state-of-the-art memory management), high throughput, broad hardware support (NVIDIA/AMD/Intel/TPUs/etc.), 200+ model architectures support, open-source community momentum (81k stars, 2000+ contributors), quantization support, and OpenAI-compatible API.

  **Tecnologias (Technologies)**: Python, PyTorch, CUDA/HIP kernels, FlashAttention, PagedAttention, Rust frontend (vllm-rs), CMake, CUTLASS, TRTLLM-GEN, TensorRT, Triton, vLLM-specific quantization: FP8/INT8/INT4/AWQ/GPTQ/GGUF.

  Let me produce a concise summary.

reasoning_content:
  I now have enough information about the vllm-project/vllm repository to produce the requested analysis. Based on what I've gathered:

  **Problema (Problem)**: A LLM serving and inference problem - serving Large Language Models (LLMs) efficiently at scale, with high-throughput, low-latency inference while managing GPU memory efficiently.

  **Tema (Theme)**: LLM Inference & Serving Engine - a high-performance model serving infrastructure.

  **Razão hype (Hype Reason)**: PagedAttention (state-of-the-art memory management), high throughput, broad hardware support (NVIDIA/AMD/Intel/TPUs/etc.), 200+ model architectures support, open-source community momentum (81k stars, 2000+ contributors), quantization support, and OpenAI-compatible API.

  **Tecnologias (Technologies)**: Python, PyTorch, CUDA/HIP kernels, FlashAttention, PagedAttention, Rust frontend (vllm-rs), CMake, CUTLASS, TRTLLM-GEN, TensorRT, Triton, vLLM-specific quantization: FP8/INT8/INT4/AWQ/GPTQ/GGUF.

  Let me produce a concise summary.


session_id: 20260530_230637_ad9bdd
role: assistant
finish_reason: tool_calls
content:
  Vou analisar o repositório `open-webui/open-webui` para você. Começo clonando o repositório e examinando sua estrutura e arquivos principais.

tool_calls:
  [{"id": "chatcmpl-tool-baf184e07c46993e", "call_id": "chatcmpl-tool-baf184e07c46993e", "response_item_id": "fc_chatcmpl-tool-baf184e07c46993e", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"cd /home/ice && git clone https://github.com/open-webui/open-webui.git open-webui-repo --depth=1 2>&1\", \"timeout\": 120}"}}]

reasoning:
  The user wants me to analyze the repository "open-webui/open-webui" from GitHub. Let me start by cloning or examining the repository structure to understand what it's about, then provide an analysis covering:
  - Problema (Problem)
  - Tema (Theme)
  - Razão hype (Reason for hype)
  - Tecnologias (Technologies)

  Let me first clone the repository or check if it exists locally. The workspace path is /home/ice.

  Let me start by cloning the repository and examining its structure.

reasoning_content:
  The user wants me to analyze the repository "open-webui/open-webui" from GitHub. Let me start by cloning or examining the repository structure to understand what it's about, then provide an analysis covering:
  - Problema (Problem)
  - Tema (Theme)
  - Razão hype (Reason for hype)
  - Tecnologias (Technologies)

  Let me first clone the repository or check if it exists locally. The workspace path is /home/ice.

  Let me start by cloning the repository and examining its structure.


session_id: 20260530_230637_ad9bdd
role: assistant
content: Ótimo, repositório clonado com sucesso. Agora vou explorar a estrutura e os arquivos principais.
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-819d30440c58b2e5", "call_id": "chatcmpl-tool-819d30440c58b2e5", "response_item_id": "fc_chatcmpl-tool-819d30440c58b2e5", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"cd /home/ice/open-webui-repo && ls -la && echo \\\"---\\\" && find . -maxdepth 2 -type f | head -80\", \"timeout\": 30}"}}]

reasoning:
  Good, the repo is cloned. Now let me explore its structure and read key files to understand the project.

reasoning_content:
  Good, the repo is cloned. Now let me explore its structure and read key files to understand the project.


session_id: 20260530_230637_ad9bdd
role: tool
tool_call_id: chatcmpl-tool-819d30440c58b2e5
tool_name: terminal
content:
  {"output": "total 1274\ndrwxrwxr-x 11 ice ice     59 May 30 23:06 .\ndrwx------ 33 ice ice     39 May 30 23:06 ..\n-rw-rw-r--  1 ice ice    219 May 30 23:06 .dockerignore\n-rw-rw-r--  1 ice ice    717 May 30 23:06 .env.example\n-rw-rw-r--  1 ice ice    160 May 30 23:06 .eslintignore\n-rw-rw-r--  1 ice ice    575 May 30 23:06 .eslintrc.cjs\ndrwxrwxr-x  8 ice ice     14 May 30 23:06 .git\n-rw-rw-r--  1 ice ice    768 May 30 23:06 .gitattributes\ndrwxrwxr-x  4 ice ice      7 May 30 23:06 .github\n-rw-rw-r--  1 ice ice   5436 May 30 23:06 .gitignore\n-rw-rw-r--  1 ice ice     19 May 30 23:06 .npmrc\n-rw-rw-r--  1 ice ice    186 May 30 23:06 .pre-commit-config.yaml\n-rw-rw-r--  1 ice ice   5423 May 30 23:06 .prettierignore\n-rw-rw-r--  1 ice ice    253 May 30 23:06 .prettierrc\n-rw-rw-r--  1 ice ice 806119 May 30 23:06 CHANGELOG.md\n-rw-rw-r--  1 ice ice   8263 May 30 23:06 CODE_OF_CONDUCT.md\n-rw-rw-r--  1 ice ice    802 May 30 23:06 CONTRIBUTOR_LICENSE_AGREEMENT\n-rw-rw-r--  1 ice ice   8251 May 30 23:06 Dockerfile\n-rw-rw-r--  1 ice ice   2819 May 30 23:06 LICENSE\n-rw-rw-r--  1 ice ice   2872 May 30 23:06 LICENSE_HISTORY\n-rw-rw-r--  1 ice ice    721 May 30 23:06 LICENSE_NOTICE\n-rw-rw-r--  1 ice ice    643 May 30 23:06 Makefile\n-rw-rw-r--  1 ice ice  15998 May 30 23:06 README.md\n-rw-rw-r--  1 ice ice   2971 May 30 23:06 TROUBLESHOOTING.md\ndrwxrwxr-x  4 ice ice     11 May 30 23:06 backend\n-rw-rw-r--  1 ice ice 213965 May 30 23:06 banner.png\n-rwxrwxr-x  1 ice ice    356 May 30 23:06 confirm_remove.sh\n-rw-rw-r--  1 ice ice   2073 May 30 23:06 contribution_stats.py\ndrwxrwxr-x  5 ice ice      6 May 30 23:06 cypress\n-rw-rw-r--  1 ice ice    135 May 30 23:06 cypress.config.ts\n-rw-rw-r--  1 ice ice 288037 May 30 23:06 demo.png\n-rw-rw-r--  1 ice ice   1172 May 30 23:06 docker-compose.a1111-test.yaml\n-rw-rw-r--  1 ice ice    222 May 30 23:06 docker-compose.amdgpu.yaml\n-rw-rw-r--  1 ice ice    125 May 30 23:06 docker-compose.api.yaml\n-rw-rw-r--  1 ice ice     88 May 30 23:06 docker-compose.data.yaml\n-rw-rw-r--  1 ice ice    251 May 30 23:06 docker-compose.gpu.yaml\n-rw-rw-r--  1 ice ice    904 May 30 23:06 docker-compose.otel.yaml\n-rw-rw-r--  1 ice ice    343 May 30 23:06 docker-compose.playwright.yaml\n-rw-rw-r--  1 ice ice    724 May 30 23:06 docker-compose.yaml\ndrwxrwxr-x  2 ice ice      3 May 30 23:06 docs\n-rw-rw-r--  1 ice ice    800 May 30 23:06 hatch_build.py\n-rw-rw-r--  1 ice ice    889 May 30 23:06 i18next-parser.config.ts\n-rw-rw-r--  1 ice ice 552999 May 30 23:06 package-lock.json\n-rw-rw-r--  1 ice ice   5330 May 30 23:06 package.json\n-rw-rw-r--  1 ice ice     64 May 30 23:06 postcss.config.js\n-rw-rw-r--  1 ice ice   5807 May 30 23:06 pyproject.toml\n-rwxrwxr-x  1 ice ice   7818 May 30 23:06 run-compose.sh\n-rw-rw-r--  1 ice ice    412 May 30 23:06 run-ollama-docker.sh\n-rw-rw-r--  1 ice ice    471 May 30 23:06 run.sh\ndrwxrwxr-x  2 ice ice      4 May 30 23:06 scripts\ndrwxrwxr-x  4 ice ice      8 May 30 23:06 src\ndrwxrwxr-x  8 ice ice     17 May 30 23:06 static\n-rw-rw-r--  1 ice ice   1876 May 30 23:06 svelte.config.js\n-rw-rw-r--  1 ice ice    614 May 30 23:06 tailwind.config.js\ndrwxrwxr-x  3 ice ice      3 May 30 23:06 test\n-rw-rw-r--  1 ice ice    532 May 30 23:06 tsconfig.json\n-rwxrwxr-x  1 ice ice    270 May 30 23:06 update_ollama_models.sh\n-rw-rw-r--  1 ice ice 638976 May 30 23:06 uv.lock\n-rw-rw-r--  1 ice ice    663 May 30 23:06 vite.config.ts\n---\n./postcss.config.js\n./.dockerignore\n./CODE_OF_CONDUCT.md\n./cypress/tsconfig.json\n./docs/SECURITY.md\n./tailwind.config.js\n./scripts/generate-sbom.sh\n./scripts/prepare-pyodide.js\n./.prettierignore\n./uv.lock\n./.pre-commit-config.yaml\n./LICENSE_NOTICE\n./.prettierrc\n./cypress.config.ts\n./confirm_remove.sh\n./Dockerfile\n./run-compose.sh\n./pyproject.toml\n./backend/dev.sh\n./backend/.dockerignore\n./backend/start.sh\n./backend/.gitignore\n./backend/requirements.txt\n./backend/start_windows.bat\n./backend/requirements-min.txt\n./.env.example\n./.npmrc\n./banner.png\n./LICENSE\n./.eslintignore\n./demo.png\n./CONTRIBUTOR_LICENSE_AGREEMENT\n./tsconfig.json\n./svelte.config.js\n./contribution_stats.py\n./docker-compose.otel.yaml\n./package-lock.json\n./.git/shallow\n./.git/config\n./.git/HEAD\n./.git/description\n./.git/index\n./.git/packed-refs\n./vite.config.ts\n./hatch_build.py\n./update_ollama_models.sh\n./TROUBLESHOOTING.md\n./.github/FUNDING.yml\n./.github/pull_request_template.md\n./.github/dependabot.yml\n./LICENSE_HISTORY\n./.gitattributes\n./.eslintrc.cjs\n./docker-compose.playwright.yaml\n./docker-compose.gpu.yaml\n./docker-compose.api.yaml\n./package.json\n./i18next-parser.config.ts\n./CHANGELOG.md\n./docker-compose.yaml\n./src/app.html\n./src/app.d.ts\n./src/tailwind.css\n./src/app.css\n./Makefile\n./README.md\n./docker-compose.amdgpu.yaml\n./run.sh\n./run-ollama-docker.sh\n./docker-compose.a1111-test.yaml\n./docker-compose.data.yaml\n./.gitignore\n./static/marker-icon.png\n./static/favicon.png\n./static/marker-icon-2x.png\n./static/manifest.json\n./static/marker-shadow.png\n./static/image-placeholder.png\n./static/user.png\n./static/robots.txt", "exit_code": 0, "error": null}


session_id: 20260530_230637_ad9bdd
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-b815d20058869cfe", "call_id": "chatcmpl-tool-b815d20058869cfe", "response_item_id": "fc_chatcmpl-tool-b815d20058869cfe", "type": "function", "function": {"name": "read_file", "arguments": "{\"limit\": 120, \"path\": \"/home/ice/open-webui-repo/README.md\"}"}}, {"id": "chatcmpl-tool-a53240e5a7c36c16", "call_id": "chatcmpl-tool-a53240e5a7c36c16", "response_item_id": "fc_chatcmpl-tool-a53240e5a7c36c16", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\": \"/home/ice/open-webui-repo/package.json\"}"}}, {"id": "chatcmpl-tool-8808efdbdfb61909", "call_id": "chatcmpl-tool-8808efdbdfb61909", "response_item_id": "fc_chatcmpl-tool-8808efdbdfb61909", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\": \"/home/ice/open-webui-repo/pyproject.toml\"}"}}]

reasoning:
  Good, I can see the repository structure. It's a full-stack application with:
  - Frontend: Svelte (`src/` directory, Svelte config)
  - Backend: Python (backend directory)
  - Docker support (multiple docker-compose files)

  Now let me look at key files to understand the project better.

reasoning_content:
  Good, I can see the repository structure. It's a full-stack application with:
  - Frontend: Svelte (`src/` directory, Svelte config)
  - Backend: Python (backend directory)
  - Docker support (multiple docker-compose files)

  Now let me look at key files to understand the project better.


session_id: 20260530_230637_ad9bdd
role: tool
tool_call_id: chatcmpl-tool-b815d20058869cfe
tool_name: read_file
content:
  {"content": "1|# Open WebUI 👋\n2|\n3|![GitHub stars](https://img.shields.io/github/stars/open-webui/open-webui?style=social)\n4|![GitHub forks](https://img.shields.io/github/forks/open-webui/open-webui?style=social)\n5|![GitHub watchers](https://img.shields.io/github/watchers/open-webui/open-webui?style=social)\n6|![GitHub repo size](https://img.shields.io/github/repo-size/open-webui/open-webui)\n7|![GitHub language count](https://img.shields.io/github/languages/count/open-webui/open-webui)\n8|![GitHub top language](https://img.shields.io/github/languages/top/open-webui/open-webui)\n9|![GitHub last commit](https://img.shields.io/github/last-commit/open-webui/open-webui?color=red)\n10|[![Discord](https://img.shields.io/badge/Discord-Open_WebUI-blue?logo=discord&logoColor=white)](https://discord.gg/5rJgQTnV4s)\n11|[![](https://img.shields.io/static/v1?label=Sponsor&message=%E2%9D%A4&logo=GitHub&color=%23fe8e86)](https://github.com/sponsors/tjbck)\n12|\n13|![Open WebUI Banner](./banner.png)\n14|\n15|**Open WebUI is an [extensible](https://docs.openwebui.com/features/extensibility/plugin), feature-rich, and user-friendly self-hosted AI platform designed to operate entirely offline.** It supports various LLM runners like **Ollama** and **OpenAI-compatible APIs**, with **built-in inference engine** for RAG, making it a **powerful AI deployment solution**.\n16|\n17|Passionate about open-source AI? [Join our team →](https://careers.openwebui.com/)\n18|\n19|![Open WebUI Demo](./demo.png)\n20|\n21|> [!TIP]  \n22|> **Looking for an [Enterprise Plan](https://docs.openwebui.com/enterprise)?** – **[Speak with Our Sales Team Today!](https://docs.openwebui.com/enterprise)**\n23|>\n24|> Get **enhanced capabilities**, including **custom theming and branding**, **Service Level Agreement (SLA) support**, **Long-Term Support (LTS) versions**, and **more!**\n25|\n26|For more information, be sure to check out our [Open WebUI Documentation](https://docs.openwebui.com/).\n27|\n28|## Key Features of Open WebUI ⭐\n29|\n30|- 🚀 **Effortless Setup**: Install seamlessly using Docker or Kubernetes (kubectl, kustomize or helm) for a hassle-free experience with support for both `:ollama` and `:cuda` tagged images.\n31|\n32|- 🤝 **Ollama/OpenAI API Integration**: Effortlessly integrate OpenAI-compatible APIs for versatile conversations alongside Ollama models. Customize the OpenAI API URL to link with **LMStudio, GroqCloud, Mistral, OpenRouter, and more**.\n33|\n34|- 🛡️ **Granular Permissions and User Groups**: By allowing administrators to create detailed user roles and permissions, we ensure a secure user environment. This granularity not only enhances security but also allows for customized user experiences, fostering a sense of ownership and responsibility amongst users.\n35|\n36|- 📱 **Responsive Design**: Enjoy a seamless experience across Desktop PC, Laptop, and Mobile devices.\n37|\n38|- 📱 **Progressive Web App (PWA) for Mobile**: Enjoy a native app-like experience on your mobile device with our PWA, providing offline access on localhost and a seamless user interface.\n39|\n40|- ✒️🔢 **Full Markdown and LaTeX Support**: Elevate your LLM experience with comprehensive Markdown and LaTeX capabilities for enriched interaction.\n41|\n42|- 🎤📹 **Hands-Free Voice/Video Call**: Experience seamless communication with integrated hands-free voice and video call features using multiple Speech-to-Text providers (Local Whisper, OpenAI, Deepgram, Azure) and Text-to-Speech engines (Azure, ElevenLabs, OpenAI, Transformers, WebAPI), allowing for dynamic and interactive chat environments.\n43|\n44|- 🛠️ **Model Builder**: Easily create Ollama models via the Web UI. Create and add custom characters/agents, customize chat elements, and import models effortlessly through [Open WebUI Community](https://openwebui.com/) integration.\n45|\n46|- 🐍 **Native Python Function Calling Tool**: Enhance your LLMs with built-in code editor support in the tools workspace. Bring Your Own Function (BYOF) by simply adding your pure Python functions, enabling seamless integration with LLMs.\n47|\n48|- 💾 **Persistent Artifact Storage**: Built-in key-value storage API for artifacts, enabling features like journals, trackers, leaderboards, and collaborative tools with both personal and shared data scopes across sessions.\n49|\n50|- 📚 **Local RAG Integration**: Dive into the future of chat interactions with groundbreaking Retrieval Augmented Generation (RAG) support using your choice of 9 vector databases and multiple content extraction engines (Tika, Docling, Document Intelligence, Mistral OCR, PaddleOCR-vl, External loaders). Load documents directly into chat or add files to your document library, effortlessly accessing them using the `#` command before a query.\n51|\n52|- 🔍 **Web Search for RAG**: Perform web searches using 15+ providers including `SearXNG`, `Google PSE`, `Brave Search`, `Kagi`, `Mojeek`, `Tavily`, `Perplexity`, `serpstack`, `serper`, `Serply`, `DuckDuckGo`, `SearchApi`, `SerpApi`, `Bing`, `Jina`, `Exa`, `Sougou`, `Azure AI Search`, and `Ollama Cloud`, injecting results directly into your chat experience.\n53|\n54|- 🌐 **Web Browsing Capability**: Seamlessly integrate websites into your chat experience using the `#` command followed by a URL. This feature allows you to incorporate web content directly into your conversations, enhancing the richness and depth of your interactions.\n55|\n56|- 🎨 **Image Generation & Editing Integration**: Create and edit images using multiple engines including OpenAI's DALL-E, Gemini, ComfyUI (local), and AUTOMATIC1111 (local), with support for both generation and prompt-based editing workflows.\n57|\n58|- ⚙️ **Many Models Conversations**: Effortlessly engage with various models simultaneously, harnessing their unique strengths for optimal responses. Enhance your experience by leveraging a diverse set of models in parallel.\n59|\n60|- 🔐 **Role-Based Access Control (RBAC)**: Ensure secure access with restricted permissions; only authorized individuals can access your Ollama, and exclusive model creation/pulling rights are reserved for administrators.\n61|\n62|- 🗄️ **Flexible Database & Storage Options**: Choose from SQLite (with optional encryption), PostgreSQL, or configure cloud storage backends (S3, Google Cloud Storage, Azure Blob Storage) for scalable deployments.\n63|\n64|- 🔍 **Advanced Vector Database Support**: Select from 9 vector database options including ChromaDB, PGVector, Qdrant, Milvus, Elasticsearch, OpenSearch, Pinecone, S3Vector, and Oracle 23ai for optimal RAG performance.\n65|\n66|- 🔐 **Enterprise Authentication**: Full support for LDAP/Active Directory integration, SCIM 2.0 automated provisioning, and SSO via trusted headers alongside OAuth providers. Enterprise-grade user and group provisioning through SCIM 2.0 protocol, enabling seamless integration with identity providers like Okta, Azure AD, and Google Workspace for automated user lifecycle management.\n67|\n68|- ☁️ **Cloud-Native Integration**: Native support for Google Drive and OneDrive/SharePoint file picking, enabling seamless document import from enterprise cloud storage.\n69|\n70|- 📊 **Production Observability**: Built-in OpenTelemetry support for traces, metrics, and logs, enabling comprehensive monitoring with your existing observability stack.\n71|\n72|- ⚖️ **Horizontal Scalability**: Redis-backed session management and WebSocket support for multi-worker and multi-node deployments behind load balancers.\n73|\n74|- 🌐🌍 **Multilingual Support**: Experience Open WebUI in your preferred language with our internationalization (i18n) support. Join us in expanding our supported languages! We're actively seeking contributors!\n75|\n76|- 🧩 **Pipelines, Open WebUI Plugin Support**: Seamlessly integrate custom logic and Python libraries into Open WebUI using [Pipelines Plugin Framework](https://github.com/open-webui/pipelines). Launch your Pipelines instance, set the OpenAI URL to the Pipelines URL, and explore endless possibilities. [Examples](https://github.com/open-webui/pipelines/tree/main/examples) include **Function Calling**, User **Rate Limiting** to control access, **Usage Monitoring** with tools like Langfuse, **Live Translation with LibreTranslate** for multilingual support, **Toxic Message Filtering** and much more.\n77|\n78|- 🌟 **Continuous Updates**: We are committed to improving Open WebUI with regular updates, fixes, and new features.\n79|\n80|Want to learn more about Open WebUI's features? Check out our [Open WebUI documentation](https://docs.openwebui.com/features) for a comprehensive overview!\n81|\n82|---\n83|\n84|We are incredibly grateful for the generous support of our sponsors. Their contributions help us to maintain and improve our project, ensuring we can continue to deliver quality work to our community. Thank you!\n85|\n86|## How to Install 🚀\n87|\n88|### Installation via Python pip 🐍\n89|\n90|Open WebUI can be installed using pip, the Python package installer. Before proceeding, ensure you're using **Python 3.11** to avoid compatibility issues.\n91|\n92|1. **Install Open WebUI**:\n93|   Open your terminal and run the following command to install Open WebUI:\n94|\n95|   ```bash\n96|   pip install open-webui\n97|   ```\n98|\n99|2. **Running Open WebUI**:\n100|   After installation, you can start Open WebUI by executing:\n101|\n102|   ```bash\n103|   open-webui serve\n104|   ```\n105|\n106|This will start the Open WebUI server, which you can access at [http://localhost:8080](http://localhost:8080)\n107|\n108|### Quick Start with Docker 🐳\n109|\n110|> [!NOTE]  \n111|> Please note that for certain Docker environments, additional configurations might be needed. If you encounter any connection issues, our detailed guide on [Open WebUI Documentation](https://docs.openwebui.com/) is ready to assist you.\n112|\n113|> [!WARNING]\n114|> When using Docker to install Open WebUI, make sure to include the `-v open-webui:/app/backend/data` in your Docker command. This step is crucial as it ensures your database is properly mounted and prevents any loss of data.\n115|\n116|> [!TIP]  \n117|> If you wish to utilize Open WebUI with Ollama included or CUDA acceleration, we recommend utilizing our official images tagged with either `:cuda` or `:ollama`. To enable CUDA, you must install the [Nvidia CUDA container toolkit](https://docs.nvidia.com/dgx/nvidia-container-runtime-upgrade/) on your Linux/WSL system.\n118|\n119|### Installation with Default Configuration\n120|\n121|", "total_lines": 237, "file_size": 15998, "truncated": true, "hint": "Use offset=121 to continue reading (showing 1-120 of 237 lines)", "is_binary": false, "is_image": false}


session_id: 20260530_230637_ad9bdd
role: tool
tool_call_id: chatcmpl-tool-a53240e5a7c36c16
tool_name: read_file
content:
  {"content": "1|{\n2|\t\"name\": \"open-webui\",\n3|\t\"version\": \"0.9.5\",\n4|\t\"private\": true,\n5|\t\"scripts\": {\n6|\t\t\"dev\": \"npm run pyodide:fetch && vite dev --host\",\n7|\t\t\"dev:5050\": \"npm run pyodide:fetch && vite dev --port 5050\",\n8|\t\t\"build\": \"npm run pyodide:fetch && vite build\",\n9|\t\t\"build:watch\": \"npm run pyodide:fetch && vite build --watch\",\n10|\t\t\"preview\": \"vite preview\",\n11|\t\t\"check\": \"svelte-kit sync && svelte-check --tsconfig ./tsconfig.json\",\n12|\t\t\"check:watch\": \"svelte-kit sync && svelte-check --tsconfig ./tsconfig.json --watch\",\n13|\t\t\"lint\": \"npm run lint:frontend ; npm run lint:types ; npm run lint:backend\",\n14|\t\t\"lint:frontend\": \"eslint . --fix\",\n15|\t\t\"lint:types\": \"npm run check\",\n16|\t\t\"lint:backend\": \"pylint backend/\",\n17|\t\t\"format\": \"prettier --plugin-search-dir --write \\\"**/*.{js,ts,svelte,css,md,html,json}\\\"\",\n18|\t\t\"format:backend\": \"ruff format . --exclude .venv --exclude venv\",\n19|\t\t\"i18n:parse\": \"i18next --config i18next-parser.config.ts && prettier --write \\\"src/lib/i18n/**/*.{js,json}\\\"\",\n20|\t\t\"cy:open\": \"cypress open\",\n21|\t\t\"test:frontend\": \"vitest --passWithNoTests\",\n22|\t\t\"pyodide:fetch\": \"node scripts/prepare-pyodide.js\"\n23|\t},\n24|\t\"devDependencies\": {\n25|\t\t\"@sveltejs/adapter-auto\": \"3.2.2\",\n26|\t\t\"@sveltejs/adapter-static\": \"^3.0.2\",\n27|\t\t\"@sveltejs/kit\": \"^2.5.27\",\n28|\t\t\"@sveltejs/vite-plugin-svelte\": \"^4.0.0\",\n29|\t\t\"@tailwindcss/container-queries\": \"^0.1.1\",\n30|\t\t\"@tailwindcss/postcss\": \"^4.0.0\",\n31|\t\t\"@tailwindcss/typography\": \"^0.5.13\",\n32|\t\t\"@typescript-eslint/eslint-plugin\": \"^8.31.1\",\n33|\t\t\"@typescript-eslint/parser\": \"^8.31.1\",\n34|\t\t\"cypress\": \"^13.15.0\",\n35|\t\t\"eslint\": \"^8.56.0\",\n36|\t\t\"eslint-config-prettier\": \"^9.1.0\",\n37|\t\t\"eslint-plugin-cypress\": \"^3.4.0\",\n38|\t\t\"eslint-plugin-svelte\": \"^2.45.1\",\n39|\t\t\"i18next-parser\": \"^9.0.1\",\n40|\t\t\"postcss\": \"^8.4.31\",\n41|\t\t\"prettier\": \"^3.3.3\",\n42|\t\t\"prettier-plugin-svelte\": \"^3.2.6\",\n43|\t\t\"sass-embedded\": \"^1.81.0\",\n44|\t\t\"svelte\": \"^5.53.10\",\n45|\t\t\"svelte-check\": \"^4.0.0\",\n46|\t\t\"svelte-confetti\": \"^2.3.2\",\n47|\t\t\"tailwindcss\": \"^4.0.0\",\n48|\t\t\"tslib\": \"^2.4.1\",\n49|\t\t\"typescript\": \"^5.5.4\",\n50|\t\t\"vite\": \"^5.4.21\",\n51|\t\t\"vitest\": \"^1.6.1\"\n52|\t},\n53|\t\"type\": \"module\",\n54|\t\"dependencies\": {\n55|\t\t\"@azure/msal-browser\": \"^4.5.0\",\n56|\t\t\"@codemirror/lang-javascript\": \"^6.2.2\",\n57|\t\t\"@codemirror/lang-python\": \"^6.1.6\",\n58|\t\t\"@codemirror/language-data\": \"^6.5.1\",\n59|\t\t\"@codemirror/theme-one-dark\": \"^6.1.2\",\n60|\t\t\"@floating-ui/dom\": \"^1.7.2\",\n61|\t\t\"@huggingface/transformers\": \"^3.0.0\",\n62|\t\t\"@joplin/turndown-plugin-gfm\": \"^1.0.62\",\n63|\t\t\"@mediapipe/tasks-vision\": \"^0.10.17\",\n64|\t\t\"@pyscript/core\": \"^0.4.32\",\n65|\t\t\"@sveltejs/adapter-node\": \"^2.0.0\",\n66|\t\t\"@sveltejs/svelte-virtual-list\": \"^3.0.1\",\n67|\t\t\"@tiptap/core\": \"^3.0.7\",\n68|\t\t\"@tiptap/extension-bubble-menu\": \"^3.0.7\",\n69|\t\t\"@tiptap/extension-code\": \"^3.0.7\",\n70|\t\t\"@tiptap/extension-code-block-lowlight\": \"^3.0.7\",\n71|\t\t\"@tiptap/extension-drag-handle\": \"^3.4.5\",\n72|\t\t\"@tiptap/extension-file-handler\": \"^3.0.7\",\n73|\t\t\"@tiptap/extension-floating-menu\": \"^3.0.7\",\n74|\t\t\"@tiptap/extension-highlight\": \"^3.3.0\",\n75|\t\t\"@tiptap/extension-image\": \"^3.0.7\",\n76|\t\t\"@tiptap/extension-link\": \"^3.0.7\",\n77|\t\t\"@tiptap/extension-list\": \"^3.0.7\",\n78|\t\t\"@tiptap/extension-mention\": \"^3.0.9\",\n79|\t\t\"@tiptap/extension-table\": \"^3.0.7\",\n80|\t\t\"@tiptap/extension-typography\": \"^3.0.7\",\n81|\t\t\"@tiptap/extension-youtube\": \"^3.0.7\",\n82|\t\t\"@tiptap/extensions\": \"^3.0.7\",\n83|\t\t\"@tiptap/pm\": \"^3.0.7\",\n84|\t\t\"@tiptap/starter-kit\": \"^3.0.7\",\n85|\t\t\"@tiptap/suggestion\": \"^3.4.2\",\n86|\t\t\"@xterm/addon-fit\": \"^0.11.0\",\n87|\t\t\"@xterm/addon-web-links\": \"^0.12.0\",\n88|\t\t\"@xterm/xterm\": \"^6.0.0\",\n89|\t\t\"@xyflow/svelte\": \"^0.1.19\",\n90|\t\t\"alpinejs\": \"^3.15.0\",\n91|\t\t\"async\": \"^3.2.5\",\n92|\t\t\"bits-ui\": \"^2.0.0\",\n93|\t\t\"chart.js\": \"^4.5.0\",\n94|\t\t\"codemirror\": \"^6.0.1\",\n95|\t\t\"codemirror-lang-elixir\": \"^4.0.0\",\n96|\t\t\"codemirror-lang-hcl\": \"^0.1.0\",\n97|\t\t\"crc-32\": \"^1.2.2\",\n98|\t\t\"dayjs\": \"^1.11.10\",\n99|\t\t\"dompurify\": \"^3.2.6\",\n100|\t\t\"eventsource-parser\": \"^1.1.2\",\n101|\t\t\"fast-deep-equal\": \"^3.1.3\",\n102|\t\t\"file-saver\": \"^2.0.5\",\n103|\t\t\"focus-trap\": \"^7.6.4\",\n104|\t\t\"fuse.js\": \"^7.0.0\",\n105|\t\t\"heic2any\": \"^0.0.4\",\n106|\t\t\"highlight.js\": \"^11.9.0\",\n107|\t\t\"html-entities\": \"^2.5.3\",\n108|\t\t\"html2canvas-pro\": \"^1.5.11\",\n109|\t\t\"i18next\": \"^23.10.0\",\n110|\t\t\"i18next-browser-languagedetector\": \"^7.2.0\",\n111|\t\t\"i18next-resources-to-backend\": \"^1.2.0\",\n112|\t\t\"idb\": \"^7.1.1\",\n113|\t\t\"js-sha256\": \"^0.10.1\",\n114|\t\t\"jspdf\": \"^4.0.0\",\n115|\t\t\"jszip\": \"^3.10.1\",\n116|\t\t\"katex\": \"^0.16.22\",\n117|\t\t\"kokoro-js\": \"^1.1.1\",\n118|\t\t\"leaflet\": \"^1.9.4\",\n119|\t\t\"lowlight\": \"^3.3.0\",\n120|\t\t\"mammoth\": \"^1.11.0\",\n121|\t\t\"marked\": \"^9.1.0\",\n122|\t\t\"mermaid\": \"^11.10.1\",\n123|\t\t\"paneforge\": \"^0.0.6\",\n124|\t\t\"panzoom\": \"^9.4.3\",\n125|\t\t\"pdfjs-dist\": \"^5.4.149\",\n126|\t\t\"prosemirror-collab\": \"^1.3.1\",\n127|\t\t\"prosemirror-commands\": \"^1.6.0\",\n128|\t\t\"prosemirror-example-setup\": \"^1.2.3\",\n129|\t\t\"prosemirror-history\": \"^1.4.1\",\n130|\t\t\"prosemirror-keymap\": \"^1.2.2\",\n131|\t\t\"prosemirror-markdown\": \"^1.13.1\",\n132|\t\t\"prosemirror-model\": \"^1.23.0\",\n133|\t\t\"prosemirror-schema-basic\": \"^1.2.3\",\n134|\t\t\"prosemirror-schema-list\": \"^1.5.1\",\n135|\t\t\"prosemirror-state\": \"^1.4.3\",\n136|\t\t\"prosemirror-tables\": \"^1.7.1\",\n137|\t\t\"prosemirror-view\": \"^1.34.3\",\n138|\t\t\"pyodide\": \"^0.28.2\",\n139|\t\t\"shiki\": \"^4.0.1\",\n140|\t\t\"socket.io-client\": \"^4.2.0\",\n141|\t\t\"sortablejs\": \"^1.15.6\",\n142|\t\t\"sql.js\": \"^1.14.1\",\n143|\t\t\"svelte-sonner\": \"^0.3.19\",\n144|\t\t\"tippy.js\": \"^6.3.7\",\n145|\t\t\"turndown\": \"^7.2.0\",\n146|\t\t\"turndown-plugin-gfm\": \"^1.0.2\",\n147|\t\t\"undici\": \"^7.3.0\",\n148|\t\t\"uuid\": \"^9.0.1\",\n149|\t\t\"vega\": \"^6.2.0\",\n150|\t\t\"vega-lite\": \"^6.4.1\",\n151|\t\t\"vite-plugin-static-copy\": \"^2.2.0\",\n152|\t\t\"xlsx\": \"^0.18.5\",\n153|\t\t\"y-prosemirror\": \"^1.3.7\",\n154|\t\t\"y-protocols\": \"^1.0.7\",\n155|\t\t\"yaml\": \"^2.7.1\",\n156|\t\t\"yjs\": \"^13.6.27\"\n157|\t},\n158|\t\"engines\": {\n159|\t\t\"node\": \">=18.13.0 <=22.x.x\",\n160|\t\t\"npm\": \">=6.0.0\"\n161|\t}\n162|}\n163|", "total_lines": 162, "file_size": 5330, "truncated": false, "is_binary": false, "is_image": false}


session_id: 20260530_230637_ad9bdd
role: tool
tool_call_id: chatcmpl-tool-8808efdbdfb61909
tool_name: read_file
content:
  {"content": "1|[project]\n2|name = \"open-webui\"\n3|description = \"Open WebUI\"\n4|authors = [\n5|    { name = \"Timothy Jaeryang Baek\", email = \"tim@openwebui.com\" }\n6|]\n7|license = { file = \"LICENSE\" }\n8|dependencies = [\n9|    \"fastapi==0.135.1\",\n10|    \"uvicorn[standard]==0.41.0\",\n11|    \"pydantic==2.12.5\",\n12|    \"python-multipart==0.0.22\",\n13|    \"itsdangerous==2.2.0\",\n14|\n15|    \"python-socketio==5.16.1\",\n16|    \"python-jose==3.5.0\",\n17|    \"cryptography==46.0.5\",\n18|    \"bcrypt==5.0.0\",\n19|    \"argon2-cffi==25.1.0\",\n20|    \"PyJWT[crypto]==2.11.0\",\n21|    \"authlib==1.6.10\",\n22|\n23|    \"requests==2.33.1\",\n24|    \"aiohttp==3.13.5\", # do not update to 3.13.3 - broken\n25|    \"async-timeout==5.0.1\",\n26|    \"aiocache==0.12.3\",\n27|    \"aiofiles==25.1.0\",\n28|    \"starlette-compress==1.7.0\",\n29|    \"Brotli==1.2.0\",\n30|    \"brotlicffi==1.2.0.1\",\n31|    \"httpx[socks,http2,zstd,cli,brotli]==0.28.1\",\n32|    \"starsessions[redis]==2.2.1\",\n33|    \"python-mimeparse==2.0.0\",\n34|\n35|    \"sqlalchemy[asyncio]==2.0.48\",\n36|    \"aiosqlite==0.21.0\",\n37|    \"psycopg[binary]==3.2.9\",\n38|    \"alembic==1.18.4\",\n39|    \"peewee==3.19.0\",\n40|    \"peewee-migrate==1.14.3\",\n41|\n42|    \"pycrdt==0.12.47\",\n43|    \"redis==7.4.0\",\n44|\n45|    \"pytz==2026.1.post1\",\n46|    \"APScheduler==3.11.2\",\n47|    \"RestrictedPython==8.1\",\n48|\n49|    \"loguru==0.7.3\",\n50|    \"asgiref==3.11.1\",\n51|\n52|    \"tiktoken==0.12.0\",\n53|    \"mcp==1.26.0\",\n54|\n55|    \"openai==2.29.0\",\n56|    \"anthropic==0.86.0\",\n57|    \"google-genai==1.66.0\",\n58|\n59|    \"langchain==1.2.10\",\n60|    \"langchain-community==0.4.1\",\n61|    \"langchain-classic==1.0.1\",\n62|    \"langchain-text-splitters==1.1.1\",\n63|\n64|    \"fake-useragent==2.2.0\",\n65|    \"chromadb==1.5.2\",\n66|    \"opensearch-py==3.1.0\",\n67|    \"PyMySQL==1.1.2\",\n68|    \"boto3==1.42.62\",\n69|    \n70|    \"transformers==5.5.4\",\n71|    \"sentence-transformers==5.4.0\",\n72|    \"accelerate==1.13.0\",\n73|    \"pyarrow==20.0.0\", # fix: pin pyarrow version to 20 for rpi compatibility #15897\n74|    \"einops==0.8.2\",\n75|\n76|    \"ftfy==6.3.1\",\n77|    \"chardet==5.2.0\",\n78|    \"pypdf==6.7.5\",\n79|    \"fpdf2==2.8.7\",\n80|    \"pymdown-extensions==10.21\",\n81|    \"docx2txt==0.9\",\n82|    \"python-pptx==1.0.2\",\n83|    \"msoffcrypto-tool==6.0.0\",\n84|    \"nltk==3.9.3\",\n85|    \"Markdown==3.10.2\",\n86|    \"beautifulsoup4==4.14.3\",\n87|    \"pypandoc==1.16.2\",\n88|    \"pandas==3.0.1\",\n89|    \"openpyxl==3.1.5\",\n90|    \"pyxlsb==1.0.10\",\n91|    \"xlrd==2.0.2\",\n92|    \"validators==0.35.0\",\n93|    \"psutil==7.2.2\",\n94|    \"sentencepiece==0.2.1\",\n95|    \"soundfile==0.13.1\",\n96|    \"azure-ai-documentintelligence==1.0.2\",\n97|\n98|    \"pillow==12.1.1\",\n99|    \"opencv-python-headless==4.13.0.92\",\n100|    \"rapidocr-onnxruntime==1.4.4\",\n101|    \"rank-bm25==0.2.2\",\n102|\n103|    \"onnxruntime==1.24.3\",\n104|    \"faster-whisper==1.2.1\",\n105|\n106|    \"black==26.3.1\",\n107|    \"youtube-transcript-api==1.2.4\",\n108|    \"pytube==15.0.0\",\n109|\n110|    \"pydub==0.25.1\",\n111|    \"ddgs==9.11.3\",\n112|\n113|    \"google-api-python-client==2.193.0\",\n114|    \"google-auth-httplib2==0.3.0\",\n115|    \"google-auth-oauthlib==1.3.0\",\n116|\n117|    \"googleapis-common-protos==1.72.0\",\n118|    \"google-cloud-storage==3.9.0\",\n119|\n120|    \"azure-identity==1.25.2\",\n121|    \"azure-storage-blob==12.28.0\",\n122|\n123|    \"ldap3==2.9.1\",\n124|]\n125|readme = \"README.md\"\n126|requires-python = \">= 3.11, < 3.13.0a1\"\n127|dynamic = [\"version\"]\n128|classifiers = [\n129|    \"Development Status :: 4 - Beta\",\n130|    \"License :: Other/Proprietary License\",\n131|    \"Programming Language :: Python :: 3\",\n132|    \"Programming Language :: Python :: 3.11\",\n133|    \"Programming Language :: Python :: 3.12\",\n134|    \"Topic :: Communications :: Chat\",\n135|    \"Topic :: Multimedia\",\n136|]\n137|\n138|[project.optional-dependencies]\n139|postgres = [\n140|    \"psycopg2-binary==2.9.11\",\n141|    \"pgvector==0.4.2\",\n142|]\n143|mariadb = [\n144|    \"mariadb==1.1.14\",\n145|]\n146|unstructured = [\n147|    \"unstructured==0.18.31\",\n148|]\n149|\n150|all = [\n151|    \"pymongo==4.16.0\",\n152|    \"psycopg2-binary==2.9.11\",\n153|    \"pgvector==0.4.2\",\n154|    \"moto[s3]>=5.0.26\",\n155|    \"gcp-storage-emulator>=2024.8.3\",\n156|    \"docker~=7.1.0\",\n157|    \"pytest~=8.3.2\",\n158|    \"pytest-docker~=3.2.5\",\n159|    \"playwright==1.58.0\", # Caution: version must match docker-compose.playwright.yaml - Update the docker-compose.yaml if necessary\n160|    \"elasticsearch==9.3.0\",\n161|\n162|    \"qdrant-client==1.17.0\",\n163|    \n164|    \"weaviate-client==4.20.3\",\n165|    \"pymilvus==2.6.9\",\n166|    \"pinecone==6.0.2\",\n167|    \"oracledb==3.4.2\",\n168|    \"colbert-ai==0.2.22\",\n169|\n170|    \"azure-search-documents==11.6.0\",\n171|    \"unstructured==0.18.31\",\n172|]\n173|\n174|[project.scripts]\n175|open-webui = \"open_webui:app\"\n176|\n177|[build-system]\n178|requires = [\"hatchling\"]\n179|build-backend = \"hatchling.build\"\n180|\n181|[tool.rye]\n182|managed = true\n183|dev-dependencies = []\n184|\n185|[tool.hatch.metadata]\n186|allow-direct-references = true\n187|\n188|[tool.hatch.version]\n189|path = \"package.json\"\n190|pattern = '\"version\":\\s*\"(?P<version>[^\"]+)\"'\n191|\n192|[tool.hatch.build.hooks.custom]  # keep this for reading hooks from `hatch_build.py`\n193|\n194|[tool.hatch.build.targets.wheel]\n195|sources = [\"backend\"]\n196|exclude = [\n197|    \".dockerignore\",\n198|    \".gitignore\",\n199|    \".webui_secret_key\",\n200|    \"dev.sh\",\n201|    \"requirements.txt\",\n202|    \"start.sh\",\n203|    \"start_windows.bat\",\n204|    \"webui.db\",\n205|    \"chroma.sqlite3\",\n206|]\n207|force-include = { \"CHANGELOG.md\" = \"open_webui/CHANGELOG.md\", build = \"open_webui/frontend\" }\n208|\n209|[tool.codespell]\n210|# Ref: https://github.com/codespell-project/codespell#using-a-config-file\n211|skip = '.git*,*.svg,package-lock.json,i18n,*.lock,*.css,*-bundle.js,locales,example-doc.txt,emoji-shortcodes.json'\n212|check-hidden = true\n213|# ignore-regex = ''\n214|ignore-words-list = 'ans'\n215|\n216|[dependency-groups]\n217|dev = [\n218|    \"pytest-asyncio>=1.0.0\",\n219|    \"ruff>=0.15.5\",\n220|]\n221|\n222|[tool.black]\n223|line-length = 120\n224|skip-string-normalization = true\n225|\n226|[tool.ruff]\n227|line-length = 120\n228|\n229|[tool.ruff.format]\n230|quote-style = \"single\"\n231|docstring-code-format = false\n232|\n233|[tool.ruff.lint]\n234|select = [\n235|  \"E\",    # pycodestyle errors\n236|  \"F\",    # pyflakes\n237|  \"W\",    # pycodestyle warnings\n238|  \"I\",    # isort\n239|  \"UP\",   # pyupgrade\n240|  \"C90\",  # mccabe\n241|  \"Q\",    # flake8-quotes\n242|  \"ICN\",  # flake8-import-conventions\n243|]\n244|\n245|# Plugin configs:\n246|flake8-import-conventions.banned-from = [ \"ast\", \"datetime\" ]\n247|flake8-import-conventions.aliases = { datetime = \"dt\" }\n248|flake8-quotes.inline-quotes = \"single\"\n249|mccabe.max-complexity = 10\n250|pydocstyle.convention = \"google\"\n251|", "total_lines": 250, "file_size": 5807, "truncated": false, "is_binary": false, "is_image": false}


session_id: 20260530_230637_ad9bdd
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-b3683f8ff1f8789f", "call_id": "chatcmpl-tool-b3683f8ff1f8789f", "response_item_id": "fc_chatcmpl-tool-b3683f8ff1f8789f", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"cd /home/ice/open-webui-repo && find backend -maxdepth 3 -type d | head -40 && echo \\\"---\\\" && find src -maxdepth 3 -type d | head -40\", \"timeout\": 30}"}}]

reasoning:
  I have enough information to provide a comprehensive analysis. Let me also quickly check the backend structure to understand the architecture better.

reasoning_content:
  I have enough information to provide a comprehensive analysis. Let me also quickly check the backend structure to understand the architecture better.


session_id: 20260530_230637_ad9bdd
role: tool
tool_call_id: chatcmpl-tool-b3683f8ff1f8789f
tool_name: terminal
content:
  {"output": "backend\nbackend/data\nbackend/open_webui\nbackend/open_webui/socket\nbackend/open_webui/data\nbackend/open_webui/routers\nbackend/open_webui/test\nbackend/open_webui/test/apps\nbackend/open_webui/test/util\nbackend/open_webui/internal\nbackend/open_webui/internal/migrations\nbackend/open_webui/storage\nbackend/open_webui/models\nbackend/open_webui/utils\nbackend/open_webui/utils/telemetry\nbackend/open_webui/utils/images\nbackend/open_webui/utils/mcp\nbackend/open_webui/utils/access_control\nbackend/open_webui/static\nbackend/open_webui/static/fonts\nbackend/open_webui/static/assets\nbackend/open_webui/static/swagger-ui\nbackend/open_webui/migrations\nbackend/open_webui/migrations/versions\nbackend/open_webui/retrieval\nbackend/open_webui/retrieval/models\nbackend/open_webui/retrieval/web\nbackend/open_webui/retrieval/loaders\nbackend/open_webui/retrieval/vector\nbackend/open_webui/tools\n---\nsrc\nsrc/routes\nsrc/routes/auth\nsrc/routes/s\nsrc/routes/s/[id]\nsrc/routes/(app)\nsrc/routes/(app)/automations\nsrc/routes/(app)/admin\nsrc/routes/(app)/home\nsrc/routes/(app)/c\nsrc/routes/(app)/workspace\nsrc/routes/(app)/notes\nsrc/routes/(app)/channels\nsrc/routes/(app)/playground\nsrc/routes/(app)/calendar\nsrc/routes/watch\nsrc/routes/error\nsrc/lib\nsrc/lib/components\nsrc/lib/components/chat\nsrc/lib/components/layout\nsrc/lib/components/calendar\nsrc/lib/components/admin\nsrc/lib/components/icons\nsrc/lib/components/workspace\nsrc/lib/components/common\nsrc/lib/components/playground\nsrc/lib/components/channel\nsrc/lib/components/automations\nsrc/lib/components/app\nsrc/lib/components/notes\nsrc/lib/workers\nsrc/lib/utils\nsrc/lib/utils/characters\nsrc/lib/utils/marked\nsrc/lib/utils/transitions\nsrc/lib/types\nsrc/lib/i18n\nsrc/lib/i18n/locales\nsrc/lib/constants", "exit_code": 0, "error": null}


session_id: 20260530_230637_ad9bdd
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-9399ae4a0e78fe9a", "call_id": "chatcmpl-tool-9399ae4a0e78fe9a", "response_item_id": "fc_chatcmpl-tool-9399ae4a0e78fe9a", "type": "function", "function": {"name": "read_file", "arguments": "{\"limit\": 120, \"offset\": 121, \"path\": \"/home/ice/open-webui-repo/README.md\"}"}}, {"id": "chatcmpl-tool-b179bec8292e8275", "call_id": "chatcmpl-tool-b179bec8292e8275", "response_item_id": "fc_chatcmpl-tool-b179bec8292e8275", "type": "function", "function": {"name": "read_file", "arguments": "{\"limit\": 200, \"path\": \"/home/ice/open-webui-repo/CHANGELOG.md\"}"}}]

reasoning:
  Good — I have a picture now: FastAPI backend (`backend/`) + SvelteKit frontend (`src/`). Next I’m going to inspect the problem statement/top issues area by looking at the README further down (issues, troubleshooting), CHANGELOG for problem themes, and GitHub metadata like open issues/funding. I already saw part of README; now I’ll read the rest and extract concrete problem themes, not just feature marketing. I'll also check issue templates and .github for workflow hints.

reasoning_content:
  Good — I have a picture now: FastAPI backend (`backend/`) + SvelteKit frontend (`src/`). Next I’m going to inspect the problem statement/top issues area by looking at the README further down (issues, troubleshooting), CHANGELOG for problem themes, and GitHub metadata like open issues/funding. I already saw part of README; now I’ll read the rest and extract concrete problem themes, not just feature marketing. I'll also check issue templates and .github for workflow hints.


session_id: 20260530_230637_ad9bdd
role: tool
tool_call_id: chatcmpl-tool-9399ae4a0e78fe9a
tool_name: read_file
content:
  {"content": "121|- **If Ollama is on your computer**, use this command:\n122|\n123|  ```bash\n124|  docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main\n125|  ```\n126|\n127|- **If Ollama is on a Different Server**, use this command:\n128|\n129|  To connect to Ollama on another server, change the `OLLAMA_BASE_URL` to the server's URL:\n130|\n131|  ```bash\n132|  docker run -d -p 3000:8080 -e OLLAMA_BASE_URL=https://example.com -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main\n133|  ```\n134|\n135|- **To run Open WebUI with Nvidia GPU support**, use this command:\n136|\n137|  ```bash\n138|  docker run -d -p 3000:8080 --gpus all --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:cuda\n139|  ```\n140|\n141|### Installation for OpenAI API Usage Only\n142|\n143|- **If you're only using OpenAI API**, use this command:\n144|\n145|  ```bash\n146|  docker run -d -p 3000:8080 -e OPENAI_API_KEY=your_secret_key -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main\n147|  ```\n148|\n149|### Installing Open WebUI with Bundled Ollama Support\n150|\n151|This installation method uses a single container image that bundles Open WebUI with Ollama, allowing for a streamlined setup via a single command. Choose the appropriate command based on your hardware setup:\n152|\n153|- **With GPU Support**:\n154|  Utilize GPU resources by running the following command:\n155|\n156|  ```bash\n157|  docker run -d -p 3000:8080 --gpus=all -v ollama:/root/.ollama -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:ollama\n158|  ```\n159|\n160|- **For CPU Only**:\n161|  If you're not using a GPU, use this command instead:\n162|\n163|  ```bash\n164|  docker run -d -p 3000:8080 -v ollama:/root/.ollama -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:ollama\n165|  ```\n166|\n167|Both commands facilitate a built-in, hassle-free installation of both Open WebUI and Ollama, ensuring that you can get everything up and running swiftly.\n168|\n169|After installation, you can access Open WebUI at [http://localhost:3000](http://localhost:3000). Enjoy! 😄\n170|\n171|### Other Installation Methods\n172|\n173|We offer various installation alternatives, including non-Docker native installation methods, Docker Compose, Kustomize, and Helm. Visit our [Open WebUI Documentation](https://docs.openwebui.com/getting-started/) or join our [Discord community](https://discord.gg/5rJgQTnV4s) for comprehensive guidance.\n174|\n175|### Troubleshooting\n176|\n177|Encountering connection issues? Our [Open WebUI Documentation](https://docs.openwebui.com/troubleshooting/) has got you covered. For further assistance and to join our vibrant community, visit the [Open WebUI Discord](https://discord.gg/5rJgQTnV4s).\n178|\n179|#### Open WebUI: Server Connection Error\n180|\n181|If you're experiencing connection issues, it’s often due to the WebUI docker container not being able to reach the Ollama server at 127.0.0.1:11434 (host.docker.internal:11434) inside the container . Use the `--network=host` flag in your docker command to resolve this. Note that the port changes from 3000 to 8080, resulting in the link: `http://localhost:8080`.\n182|\n183|**Example Docker Command**:\n184|\n185|```bash\n186|docker run -d --network=host -v open-webui:/app/backend/data -e OLLAMA_BASE_URL=http://127.0.0.1:11434 --name open-webui --restart always ghcr.io/open-webui/open-webui:main\n187|```\n188|\n189|### Keeping Your Docker Installation Up-to-Date\n190|\n191|Check our Updating Guide available in our [Open WebUI Documentation](https://docs.openwebui.com/getting-started/updating).\n192|\n193|### Using the Dev Branch 🌙\n194|\n195|> [!WARNING]\n196|> The `:dev` branch contains the latest unstable features and changes. Use it at your own risk as it may have bugs or incomplete features.\n197|\n198|If you want to try out the latest bleeding-edge features and are okay with occasional instability, you can use the `:dev` tag like this:\n199|\n200|```bash\n201|docker run -d -p 3000:8080 -v open-webui:/app/backend/data --name open-webui --add-host=host.docker.internal:host-gateway --restart always ghcr.io/open-webui/open-webui:dev\n202|```\n203|\n204|### Offline Mode\n205|\n206|If you are running Open WebUI in an offline environment, you can set the `HF_HUB_OFFLINE` environment variable to `1` to prevent attempts to download models from the internet.\n207|\n208|```bash\n209|export HF_HUB_OFFLINE=1\n210|```\n211|\n212|## What's Next? 🌟\n213|\n214|Discover upcoming features on our roadmap in the [Open WebUI Documentation](https://docs.openwebui.com/roadmap/).\n215|\n216|## License 📜\n217|\n218|This project contains code under multiple licenses. The current codebase includes components licensed under the Open WebUI License with an additional requirement to preserve the \"Open WebUI\" branding, as well as prior contributions under their respective original licenses. For a detailed record of license changes and the applicable terms for each section of the code, please refer to [LICENSE_HISTORY](./LICENSE_HISTORY). For complete and updated licensing details, please see the [LICENSE](./LICENSE) and [LICENSE_HISTORY](./LICENSE_HISTORY) files.\n219|\n220|## Support 💬\n221|\n222|If you have any questions, suggestions, or need assistance, please open an issue or join our\n223|[Open WebUI Discord community](https://discord.gg/5rJgQTnV4s) to connect with us! 🤝\n224|\n225|## Star History\n226|\n227|<a href=\"https://star-history.com/#open-webui/open-webui&Date\">\n228|  <picture>\n229|    <source media=\"(prefers-color-scheme: dark)\" srcset=\"https://api.star-history.com/svg?repos=open-webui/open-webui&type=Date&theme=dark\" />\n230|    <source media=\"(prefers-color-scheme: light)\" srcset=\"https://api.star-history.com/svg?repos=open-webui/open-webui&type=Date\" />\n231|    <img alt=\"Star History Chart\" src=\"https://api.star-history.com/svg?repos=open-webui/open-webui&type=Date\" />\n232|  </picture>\n233|</a>\n234|\n235|---\n236|\n237|Created by [Timothy Jaeryang Baek](https://github.com/tjbck) - Let's make Open WebUI even more amazing together! 💪\n238|", "total_lines": 237, "file_size": 15998, "truncated": false, "is_binary": false, "is_image": false}


session_id: 20260530_230637_ad9bdd
role: tool
tool_call_id: chatcmpl-tool-b179bec8292e8275
tool_name: read_file
content:
  {"content": "1|# Changelog\n2|\n3|All notable changes to this project will be documented in this file.\n4|\n5|The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),\n6|and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).\n7|\n8|## [0.9.5] - 2026-05-09\n9|\n10|### Added\n11|\n12|- 🛡️ **Redirect-based SSRF protection.** All outbound HTTP requests now block 3xx redirects by default via a new `AIOHTTP_CLIENT_ALLOW_REDIRECTS` environment variable, preventing redirect-based SSRF where a public URL silently redirects to internal addresses (RFC 1918, loopback, cloud-metadata endpoints). Affected call sites include web fetch, image loading, OAuth discovery, tool server execution, and code interpreter login. [#24491](https://github.com/open-webui/open-webui/pull/24491)\n13|- 🛡️ **Iframe content security policy.** Administrators can now configure a Content-Security-Policy for all srcdoc iframes (Artifacts, tool embeds, file previews, citation modals) via the `IFRAME_CSP` environment variable, restricting what LLM-generated or user-uploaded HTML can load and execute inside previews. [Commit](https://github.com/open-webui/open-webui/commit/3bba1c227059a44c7eeefa97b8c69a63bf4f3454)\n14|- 🎛️ **Granular markdown rendering controls.** Users can now independently disable Markdown rendering for user messages and assistant responses from Interface settings, preventing unintended formatting when pasting text that contains Markdown-sensitive characters. [Commit](https://github.com/open-webui/open-webui/commit/4a1064cefd6f48a8b3b02cd31f77838c8802b635)\n15|- 🔧 **Terminal proxy response headers.** Administrators can now inject custom response headers into terminal proxy responses via the `TERMINAL_PROXY_HEADERS` environment variable (JSON object), enabling deployment-specific security headers like sandbox policies for proxied content. [Commit](https://github.com/open-webui/open-webui/commit/8d3133fe2835122bffaa4f2ce584730bc9c78981)\n16|- 🔌 **Channel streaming and tool support.** Mentioning a model in a Channel now streams responses in real time and supports the full chat completion pipeline, including native and default function calling, built-in tools (web search, image generation), user tools, MCP tools, filters, and RAG knowledge injection — the same capabilities available in standard chats.\n17|\n18|### Fixed\n19|\n20|- 📝 **Notes create and open reliability.** Creating new notes and opening existing notes no longer fails with a TypeError caused by `is_pinned` being passed to the SQLAlchemy model on create, and passed twice to `NoteResponse` on read. [#24484](https://github.com/open-webui/open-webui/issues/24484), [#24486](https://github.com/open-webui/open-webui/pull/24486)\n21|- 🔐 **Skill public sharing permission enforcement.** Creating or updating skills now filters access grants through the `sharing.public_skills` permission, preventing non-admin users from making skills publicly accessible without the required permission. [#24494](https://github.com/open-webui/open-webui/pull/24494)\n22|- 🔐 **Calendar public sharing permission enforcement.** Creating or updating calendars now filters access grants through a new `sharing.public_calendars` permission, preventing users from making calendars publicly readable or writable without explicit admin-granted sharing permission. [#24493](https://github.com/open-webui/open-webui/pull/24493)\n23|- 🔐 **Feedback user attribution spoofing.** Submitting evaluation feedback can no longer forge the `user_id` field through mass-assignment, preventing authenticated users from attributing ratings to other users and corrupting Elo leaderboard rankings and admin feedback exports. [#24508](https://github.com/open-webui/open-webui/pull/24508)\n24|- 🛡️ **Image URL redirect-based SSRF.** Chat messages containing image URLs no longer follow 3xx redirects to internal addresses during base64 conversion, closing the most reachable redirect-based SSRF variant that required no special permissions or feature flags. [#24524](https://github.com/open-webui/open-webui/pull/24524)\n25|- 🛡️ **Collection write access on file processing.** The `process_file` and `process_files_batch` retrieval endpoints now enforce collection write-access checks before embedding content, preventing authenticated users from injecting file content into another user's knowledge-base collection. [#24524](https://github.com/open-webui/open-webui/pull/24524)\n26|- 🔐 **Tool source code update authorization.** Updating a tool's Python source code now requires `workspace.tools` or `workspace.tools_import` permission, preventing users with only a write-access grant from overwriting executable tool code while still allowing metadata edits. [#24513](https://github.com/open-webui/open-webui/pull/24513)\n27|- 🔐 **Channel message ownership enforcement.** Updating or deleting messages in group and DM channels now requires message ownership, preventing channel members from tampering with or silently removing other members' messages. [#24506](https://github.com/open-webui/open-webui/pull/24506)\n28|- 🔐 **Channel pin write permission.** Pinning and unpinning messages on standard channels now requires write permission instead of read permission, preventing read-only users from modifying pinned content. [#24521](https://github.com/open-webui/open-webui/pull/24521)\n29|- 🛡️ **Image generation URL validation.** Generated image URLs are now validated through `validate_url()` before fetching, aligning the defense-in-depth posture with sibling image-loading paths. [#24518](https://github.com/open-webui/open-webui/pull/24518)\n30|- 🔐 **Model params exposure for read-only users.** The per-model API endpoint now strips the `params` dict (including system prompts) from responses to callers without write access, preventing read-only users from viewing admin-curated model configuration. [#24525](https://github.com/open-webui/open-webui/pull/24525)\n31|- 🛡️ **URL parser SSRF bypass.** URL validation now rejects backslash, tab, CR, and LF characters that cause urllib and requests/aiohttp to disagree on the target host, closing a parser-confusion SSRF bypass. [#24534](https://github.com/open-webui/open-webui/pull/24534)\n32|- 🛡️ **Profile image MIME-type allowlist.** Serving profile images from data URIs now enforces a strict MIME-type allowlist (PNG, JPEG, GIF, WEBP by default, configurable via `PROFILE_IMAGE_ALLOWED_MIME_TYPES`) and sets `X-Content-Type-Options: nosniff`, preventing stored-XSS through SVG or other executable content types. [Commit](https://github.com/open-webui/open-webui/commit/15e696691cad98692c329de62ed8a5bdb3a26d4e)\n33|- 🔐 **File ownership in folder and knowledge attachments.** Attaching files to folders or knowledge bases now verifies per-file read access, and folder file lists in chat middleware are filtered to entries the caller can read, preventing unauthorized file content from being injected into RAG context. [Commit](https://github.com/open-webui/open-webui/commit/2dbf7b6764a7922458d3b0139687ad6dcd7596d9)\n34|- 🔐 **Shared chat access for owners and admins.** Chat owners can now view and clone their own shared chats without requiring an explicit access grant, and administrators can manage shared chat access controls on any chat. [Commit](https://github.com/open-webui/open-webui/commit/3a21b334cce30226750c5c537345dc51bb8bef17), [Commit](https://github.com/open-webui/open-webui/commit/315566064aedeff071854b023d09e5f1ea0eb950)\n35|- 🧵 **Legacy chat history self-healing.** Loading legacy conversations now automatically detects broken parent-link graphs in migrated message records, merges missing messages from the embedded JSON history, and backfills them to the normalized table so future loads use the fast path without data loss. [Commit](https://github.com/open-webui/open-webui/commit/1388f4568b8f508c26542673dd01f1fa049e798a)\n36|- 🎛️ **Filter selector reactivity.** Model filter checkboxes now derive state reactively from the current filter list and selected IDs instead of capturing a one-time snapshot at mount, so checkboxes update correctly when model contexts or filter configurations change at runtime. [Commit](https://github.com/open-webui/open-webui/commit/d1ef5382377f590f97a6dbaee88f369e6d7c5f6f)\n37|- 🌐 **Portuguese (Brazil) translation updates.** Translations for newly added UI items were added along with a consistency pass across existing entries. [#24503](https://github.com/open-webui/open-webui/pull/24503)\n38|\n39|### Changed\n40|\n41|- 🧹 **Removed unauthenticated retrieval status endpoint.** The unauthenticated `GET /api/v1/retrieval/` status endpoint has been removed as dead code — retrieval configuration is already available through authenticated admin endpoints. [#24497](https://github.com/open-webui/open-webui/pull/24497)\n42|- 📋 **PR template issue requirement.** Pull requests now require a linked Issue or Discussion reference, ensuring better traceability for all contributions. PRs without a linked issue or discussion may be closed without review.\n43|\n44|## [0.9.4] - 2026-05-09\n45|\n46|### Fixed\n47|\n48|- 📜 **Chat scroll position on load.** Opening a chat conversation now reliably scrolls to the bottom of the message history, fixing a regression caused by `content-visibility: auto` where estimated element sizes prevented the initial scroll from reaching the true bottom.\n49|\n50|## [0.9.3] - 2026-05-09\n51|\n52|### Added\n53|\n54|- 🔇 **Voice Mode mute control.** Voice Mode now includes a dedicated mute toggle with an \"M\" shortcut and auto-unmute after assistant playback, so you can prevent accidental interruptions from background noise without leaving the call overlay. [Commit](https://github.com/open-webui/open-webui/commit/072d2000f35a9f7b96342fa9bb28f925a92e7b4c), [#23832](https://github.com/open-webui/open-webui/issues/23832)\n55|- 🚀 **Faster prompt list loading.** Prompt and prompt-tag pages now load much faster for non-admin users, even with large prompt libraries, because accessible prompts are filtered efficiently in a single database query. [#24288](https://github.com/open-webui/open-webui/pull/24288), [#24258](https://github.com/open-webui/open-webui/discussions/24258)\n56|- ⚡ **Faster chat history loading.** Chat history maps now load from normalized message records when available, reducing overhead for large conversations while preserving fallback behavior for legacy chats. [Commit](https://github.com/open-webui/open-webui/commit/485d689cfd1ef8b9e7f77cd7b535b8b8747dff1f), [#23159](https://github.com/open-webui/open-webui/pull/23159)\n57|- 🗑️ **Delete from conversation menu.** You can now delete the current conversation directly from the chat menu with a confirmation step, so cleanup is faster without searching through the full chat list. [Commit](https://github.com/open-webui/open-webui/commit/ef6d4f2d6c4b79c7e12e864a4fcb6a57ee84e5d4), [#24329](https://github.com/open-webui/open-webui/issues/24329)\n58|- ⬆️ **Scroll to Top shortcut.** Long conversations now include a Scroll to Top action in the chat menu when you are away from the top, making it much faster to jump back to the beginning of a chat. [Commit](https://github.com/open-webui/open-webui/commit/cdfcbc4af6e9aec835b88dc1806a2a46711e6947), [#24133](https://github.com/open-webui/open-webui/issues/24133)\n59|- 📅 **Calendar creation flow.** Users can now create calendars from a dedicated modal and a quick-add action in the calendar sidebar, making calendar setup faster from the calendar workspace. [Commit](https://github.com/open-webui/open-webui/commit/34146ab60f5dc1a2f8bdda8e61ce02797233a25d), [Commit](https://github.com/open-webui/open-webui/commit/1baf73bdd56f4e5ded12a4bd3c168f4d2a70b840)\n60|- 🧭 **Unified model unload controls.** Administrators can now unload running models from the model selector across supported providers, with loaded-state indicators shown for Ollama and llama.cpp models. [Commit](https://github.com/open-webui/open-webui/commit/4fe2de78643c2213652190d2820f4e8d9f4f89cc)\n61|- ⚡ **Health check responsiveness.** Health and readiness probes now avoid blocking database calls and skip sync session commit handling on probe paths, improving responsiveness and reducing false unready transitions during database pressure. [#24380](https://github.com/open-webui/open-webui/pull/24380), [#24384](https://github.com/open-webui/open-webui/pull/24384)\n62|- 🎛️ **Playground controls panel.** The Playground now includes a dedicated Controls toggle so you can adjust parameters like temperature and related settings per chat run without changing model-level defaults. [Commit](https://github.com/open-webui/open-webui/commit/c6763521c00f042a28829e33fb6f1b7355054046), [#24103](https://github.com/open-webui/open-webui/issues/24103)\n63|- 🎙️ **STT file extension controls.** Administrators can now configure which audio file extensions are accepted for speech-to-text uploads, helping enforce safer and more predictable upload policies. [Commit](https://github.com/open-webui/open-webui/commit/4754ece4a2de5bba85a1d53af2dc8d24fdfb58be)\n64|- 📷 **Remembered call camera selection.** Voice call overlay now remembers your last selected camera and restores it automatically when available, so you do not need to reselect it every time you start voice mode. [Commit](https://github.com/open-webui/open-webui/commit/5c3edc2539ac4d92c4cc2d37079549995203238a), [#24416](https://github.com/open-webui/open-webui/issues/24416)\n65|- 👥 **User group prompt variable.** System and template prompts now support the \"{{USER_GROUPS}}\" variable, which expands to the user’s group memberships so prompts can adapt to role- or access-based context automatically. [Commit](https://github.com/open-webui/open-webui/commit/c1202a23277abb8e7080271a929dcc9d29b67e66), [#24462](https://github.com/open-webui/open-webui/issues/24462)\n66|- 🔐 **Public chat sharing permission control.** Administrators can now control whether users are allowed to create publicly shareable chats through a dedicated permission setting. [Commit](https://github.com/open-webui/open-webui/commit/ef6d4f2d6c4b79c7e12e864a4fcb6a57ee84e5d4)\n67|- 🔐 **Profile image forwarding control.** Administrators can now disable external profile image URL forwarding with the \"ENABLE_PROFILE_IMAGE_URL_FORWARDING\" setting to prevent browser metadata leaks to third-party servers. [#24420](https://github.com/open-webui/open-webui/pull/24420)\n68|- 🏷️ **Dynamic header template variables.** Administrators can now use chat, message, and user template variables in custom connection and tool server headers so each request can carry per-conversation context automatically. [Commit](https://github.com/open-webui/open-webui/commit/9907c0a25ae830d134af70022238715f834d20c6), [#24164](https://github.com/open-webui/open-webui/pull/24164)\n69|- 🛂 **MCP OAuth server URL setting.** Static OAuth tool server setups can now define a separate OAuth server URL, making discovery and client registration work when authentication endpoints are hosted separately from the tool server URL. [Commit](https://github.com/open-webui/open-webui/commit/9907c0a25ae830d134af70022238715f834d20c6), [#24164](https://github.com/open-webui/open-webui/pull/24164), [#24216](https://github.com/open-webui/open-webui/issues/24216)\n70|- ⚡ **Faster memory query performance.** Per-user memory lookups and deletions now run much faster at scale because the memory user filter is indexed for existing and new installations. [Commit](https://github.com/open-webui/open-webui/commit/38a382ef888685650135d61dcc8ec0e29eb65573), [#23836](https://github.com/open-webui/open-webui/pull/23836)\n71|- 🚀 **Smarter function dependency installs.** Function dependencies are now skipped when they were already preinstalled and unchanged, reducing first-load delays and repeated package installation churn after startup. [Commit](https://github.com/open-webui/open-webui/commit/ae43562b869b24699408e5ab107261a0a8bdb4bc), [#24166](https://github.com/open-webui/open-webui/pull/24166)\n72|- 🔎 **Brave LLM Context web search.** Administrators can now choose Brave LLM Context as a web search provider to retrieve richer grounded passages with a configurable context token budget. [Commit](https://github.com/open-webui/open-webui/commit/6700f7bb72d14a3f8dbb72dfa064cae3b3dc29ac), [#24120](https://github.com/open-webui/open-webui/issues/24120)\n73|- 🗂️ **Open Terminal date sorting.** Open Terminal now includes sort controls for name and date, with directory-first ordering and modified-time visibility to make file browsing faster. [Commit](https://github.com/open-webui/open-webui/commit/6bdc2ffa79d72daf78981209c9c5292c697cbfe5), [#24425](https://github.com/open-webui/open-webui/issues/24425)\n74|- 🎤 **Voice mode prompt toggle.** Administrators can now explicitly enable or disable the Voice Mode custom prompt behavior from Interface settings, giving finer control over how voice replies are guided. [Commit](https://github.com/open-webui/open-webui/commit/17893038869e3a763a8b34457f723b9666804e27)\n75|- 🧮 **LaTeX copy shortcut.** You can now click rendered LaTeX expressions to copy the raw formula to your clipboard, making it easier to reuse equations outside chat. [Commit](https://github.com/open-webui/open-webui/commit/064fdecb675c176a04b024c16ce179f4dda45236), [#24244](https://github.com/open-webui/open-webui/pull/24244)\n76|- ✨ **Smoother rich text editing.** The message composer now defers formatting toolbar refresh work to the next animation frame, reducing typing jank while formatting controls stay accurate. [Commit](https://github.com/open-webui/open-webui/commit/794b97025d4c56f91d49c9d1ec4775d2ea07b53a), [#24013](https://github.com/open-webui/open-webui/pull/24013)\n77|- 🖼️ **Arena model profile images.** Arena models can now reliably display configured profile images instead of falling back to the default icon. [Commit](https://github.com/open-webui/open-webui/commit/1dee67b64d0b34e70bac949682b216c0aaec8152), [#24412](https://github.com/open-webui/open-webui/issues/24412)\n78|- 🔄 **Replaceable tool embed updates.** Pipes and Tools can now overwrite previously emitted rich-UI embeds in-place by passing a `replace` flag on the `embeds` event, enabling live dashboards and progress panels that update without stacking duplicate entries.\n79|- ✏️ **Assistant response editing and continuation.** You can now edit and restructure assistant output items — including reasoning blocks, tool calls, and text content — from a dedicated editor view, and continue generating from the edited state so the model receives full prior context.\n80|- 🔄 **General improvements.** Various improvements were implemented across the application to enhance performance, stability, and security.\n81|- 🌐 **Translation updates.** Translations for Chinese, Catalan, Filipino, and Korean were enhanced and expanded.\n82|\n83|### Fixed\n84|\n85|- 🧵 **Background code execution reliability.** Code execution no longer hangs indefinitely when you switch conversations or browser tabs during a run, and disconnected or inactive sessions now fail with a clear timeout error instead of endless processing. [Commit](https://github.com/open-webui/open-webui/commit/552bbcecfae5ae273ab98e2ce3e540d0771aa964), [#24089](https://github.com/open-webui/open-webui/issues/24089)\n86|- 🎙️ **Voice recording MIME fallback support.** Voice recording now tries a broader set of browser-supported audio formats and resets halted audio playback cleanly, improving microphone capture reliability in browsers where recording previously failed to start. [Commit](https://github.com/open-webui/open-webui/commit/8ffc3d746f20007e9eb4e3ae4f152f383bc371e1), [#24162](https://github.com/open-webui/open-webui/issues/24162)\n87|- 🧠 **Direct-connection task generation reliability.** Title, tags, follow-up, emoji, query, and related task-generation endpoints now work correctly when chats use direct-connection models instead of failing with model-not-found errors. [Commit](https://github.com/open-webui/open-webui/commit/1b4cd705d0b9a51a5e3a7851ec012fb3141eb0a9), [Commit](https://github.com/open-webui/open-webui/commit/005df577fec16733a64edbec8a1b46f42f4e9a43), [#24092](https://github.com/open-webui/open-webui/issues/24092)\n88|- 🔧 **Parameterized URL tool readiness.** New chats now wait for model defaults to finish applying before auto-submit, preventing early requests that can miss configured external tools. [Commit](https://github.com/open-webui/open-webui/commit/212bb68a66435dc1803a6d67cb4ea584d3455fb7), [#24176](https://github.com/open-webui/open-webui/issues/24176)\n89|- 🚦 **MCP cleanup response reliability.** Successful native MCP tool calls no longer get replaced by a 500 \"No response returned\" error during cleanup, so valid chat responses are now returned consistently. [#24105](https://github.com/open-webui/open-webui/pull/24105)\n90|- 🧵 **Active task state recovery.** Chat input no longer stays blocked by unrelated background tasks after a response is already complete, and interrupted assistant replies are now marked done more reliably. [Commit](https://github.com/open-webui/open-webui/commit/04bd0425ead28185bcd124e77892e31209a6e15b), [#23264](https://github.com/open-webui/open-webui/pull/23264)\n91|- 📌 **Per-user note pinning behavior.** Pinned notes are now tracked per user instead of with a shared note-level flag, so one person’s pin changes no longer affect everyone else. [Commit](https://github.com/open-webui/open-webui/commit/33e588cf09b294f0abe08b9566efa8545a7dbf92)\n92|- 🧱 **Custom header value coercion.** Custom header values are now converted to text before requests are sent, preventing request failures when non-text values are configured. [Commit](https://github.com/open-webui/open-webui/commit/9907c0a25ae830d134af70022238715f834d20c6), [#24164](https://github.com/open-webui/open-webui/pull/24164)\n93|- 🔗 **HTTP share link copy fallback.** Copy Link now works reliably on HTTP deployments by using a selection-based fallback when secure clipboard APIs are unavailable. [Commit](https://github.com/open-webui/open-webui/commit/f70b0da1563ffa0a8daecbe71cbc30fd8cf834c4), [#24135](https://github.com/open-webui/open-webui/issues/24135)\n94|- 🧵 **Regeneration loading lock recovery.** Chats no longer get stuck in a permanent loading state after failed regenerations because invalid message-tree references are repaired before rendering. [Commit](https://github.com/open-webui/open-webui/commit/ee3b82926b37843f2771c6a8d432781a557ea96a), [#24424](https://github.com/open-webui/open-webui/issues/24424)\n95|- 📸 **Complete chat image capture.** Downloaded chat snapshots now include all messages more reliably through visibility overrides and layout timing improvements during capture. [Commit](https://github.com/open-webui/open-webui/commit/34146ab60f5dc1a2f8bdda8e61ce02797233a25d), [Commit](https://github.com/open-webui/open-webui/commit/1baf73bdd56f4e5ded12a4bd3c168f4d2a70b840), [#24088](https://github.com/open-webui/open-webui/issues/24088)\n96|- 🗓️ **Calendar deletion lock handling.** Calendar deletion now avoids SQLite write-lock contention by revoking calendar access grants in a separate transaction after calendar and event removal. [Commit](https://github.com/open-webui/open-webui/commit/1d892ce2c513c4d933c902de5e5d76c317a06dd2)\n97|- 🧩 **Filter and internal tool coexistence.** Internal tools now remain available when filters add provider-native tools, so filter-added tools no longer replace the built-in tool set during request processing. [Commit](https://github.com/open-webui/open-webui/commit/02f9fe78907c2ecf6f1d93646cbfa2173409bbe8), [#24237](https://github.com/open-webui/open-webui/issues/24237)\n98|- 🛠️ **OpenAPI tool spec compatibility.** OpenAPI tool integrations now handle null or non-operation path entries more safely and parse path-level parameters consistently, preventing crashes and improving tool execution reliability across imperfect OpenAPI specs. [Commit](https://github.com/open-webui/open-webui/commit/2ba6b423aa0c9c800bd96cb638c6ade867cac0f6), [Commit](https://github.com/open-webui/open-webui/commit/5b80932e5951786bb348b91589e8d87753f18905), [#24376](https://github.com/open-webui/open-webui/pull/24376)\n99|- 🧰 **OpenAPI tool schema parsing.** OpenAPI tool imports now ignore non-method path item fields and correctly resolve nested composition schemas, preventing invalid tool parsing for compatible specs. [Commit](https://github.com/open-webui/open-webui/commit/85c7373f68ac3e39a9cd37e63b6926b13fb8b8cc), [#23254](https://github.com/open-webui/open-webui/pull/23254)\n100|- 🌍 **Web search proxy compatibility.** DuckDuckGo search now respects configured proxy environments more reliably, and trust-env behavior defaults to enabled so proxied web loading does not fail unexpectedly. [Commit](https://github.com/open-webui/open-webui/commit/bb0e6cb1085aa3c3da66a5f5ea1cecff7e9b5297), [#23810](https://github.com/open-webui/open-webui/pull/23810)\n101|- 🧾 **Final markdown render flush.** Streaming markdown now forces an immediate final parse when generation completes, preventing stale or partially rendered final output. [Commit](https://github.com/open-webui/open-webui/commit/29f6c72e879d67f23021938e24a21914cc9fb120), [#24088](https://github.com/open-webui/open-webui/issues/24088)\n102|- 🛡️ **Webhook avatar URL validation.** Channel webhook profile image URLs are now validated before saving, preventing invalid or unsafe avatar URLs from being accepted. [#24370](https://github.com/open-webui/open-webui/pull/24370)\n103|- 📝 **System prompt editor scroll stability.** Editing large system prompts no longer jumps the page back to the top, so you can continue editing long model prompts without losing your place. [Commit](https://github.com/open-webui/open-webui/commit/c978a788c8315e37357c93c1b605a2831fc77485), [#23999](https://github.com/open-webui/open-webui/issues/23999)\n104|- 🔎 **Knowledge content search matching.** Knowledge file search now matches both file titles and file content, so relevant files are easier to find even when the keyword is not in the filename. [Commit](https://github.com/open-webui/open-webui/commit/11e076817ae5db34621ce03136353248f7377d97), [#24297](https://github.com/open-webui/open-webui/pull/24297)\n105|- ⚡ **Faster prompt tag loading.** Prompt tag filters now load much faster for non-admin users by fetching only accessible tags directly, avoiding per-prompt permission checks and unnecessary prompt data loading. [#24287](https://github.com/open-webui/open-webui/pull/24287), [#24258](https://github.com/open-webui/open-webui/discussions/24258)\n106|- 🧾 **Citation overflow badge readability.** Citation overflow badges now keep multi-digit counts readable in a single compact bubble, preventing wrapped or cramped display when many sources are attached. [Commit](https://github.com/open-webui/open-webui/commit/23ff9943a9fc8c314100fa074157853fbece1a55), [#24391](https://github.com/open-webui/open-webui/pull/24391)\n107|- 🌐 **Yandex result parsing guard.** Yandex web search no longer fails when some XML fields are missing in individual results, so valid search responses continue to return usable sources instead of dropping to no results. [Commit](https://github.com/open-webui/open-webui/commit/9386fc83a3eff3e55cc157ac8c15c337e3d822c1), [#24243](https://github.com/open-webui/open-webui/issues/24243)\n108|- 🎧 **Safer voice transcription uploads.** Empty or failed voice conversions are now rejected with a clear error instead of continuing as malformed audio, reducing failed transcription attempts from corrupted or near-empty recordings. [Commit](https://github.com/open-webui/open-webui/commit/072d2000f35a9f7b96342fa9bb28f925a92e7b4c)\n109|- 🎚️ **Safer chunked STT processing.** Chunked transcription now limits worker concurrency when no external STT engine is configured, reducing failed transcription behavior caused by overly parallel local processing. [Commit](https://github.com/open-webui/open-webui/commit/55e7c7854bba5182803239c903a0ac2d14426a4c)\n110|- 📈 **Imported chat analytics coverage.** Imported ChatGPT conversations now carry proper model and timestamp metadata and reliably write imported messages into analytics-backed storage, so imported chats are reflected correctly in Admin Analytics totals and model usage views. [Commit](https://github.com/open-webui/open-webui/commit/4d766a3edfa116abcefe7168f1d1284683b860b2), [#24263](https://github.com/open-webui/open-webui/issues/24263)\n111|- 📎 **Knowledge collection persistence.** Knowledge collections selected with the chat input selector now remain attached after reloads and chat switches, so attached context no longer disappears between sessions. [Commit](https://github.com/open-webui/open-webui/commit/7c398a625a8d51f79d80217f6d329fc30c72b782), [#24142](https://github.com/open-webui/open-webui/issues/24142)\n112|- 🧹 **Embedding model name trimming.** Embedding model names entered in Documents settings now automatically trim surrounding whitespace, preventing silent embedding failures caused by accidental trailing spaces. [Commit](https://github.com/open-webui/open-webui/commit/6082e1adaebc8aa3e7f55265c8dc2dbe130c0446), [#24090](https://github.com/open-webui/open-webui/issues/24090)\n113|- 🔊 **PCM TTS playback compatibility.** Text-to-speech audio returned as PCM is now converted to MP3 before delivery, so speech playback works correctly with providers that return raw PCM audio. [Commit](https://github.com/open-webui/open-webui/commit/ff791b4814fc1453df2235ea78016d7015aa6806), [#24143](https://github.com/open-webui/open-webui/issues/24143)\n114|- 🪟 **Windows PostgreSQL startup compatibility.** Windows pip installs using PostgreSQL now start reliably with psycopg async by using a compatible event loop policy instead of the default Proactor loop. [Commit](https://github.com/open-webui/open-webui/commit/7eaecbad5a0913ed04ca3bc10c930bb051dd2bd9), [#24152](https://github.com/open-webui/open-webui/issues/24152)\n115|- ⏱️ **MCP OAuth timeout control.** OAuth token exchanges for MCP tool server connections now respect the configurable client timeout setting, reducing callback failures with slower providers. [Commit](https://github.com/open-webui/open-webui/commit/cde72dab71671645e119564ca9747ce25dd590ad), [#24138](https://github.com/open-webui/open-webui/issues/24138)\n116|- 📄 **PDF text search restoration.** PDF previews now include a proper text layer so browser text selection and find-in-page search work again instead of rendering only image-like pages. [Commit](https://github.com/open-webui/open-webui/commit/bc4d6eef33dcb92719b07483cdb1d63ebf250721), [#24149](https://github.com/open-webui/open-webui/issues/24149)\n117|- 🔑 **Android password autofill support.** Password inputs now expose the expected field name metadata, improving password manager autofill reliability on Android login pages. [Commit](https://github.com/open-webui/open-webui/commit/60ea4214aa42f1ad22142f1a43535007a2293d16), [#24137](https://github.com/open-webui/open-webui/issues/24137)\n118|- 🎤 **Non-blocking STT processing.** Speech-to-text transcription no longer blocks the server event loop during both live transcription and uploaded audio file processing, so other users can continue using chats and live connections under concurrent load. [#24338](https://github.com/open-webui/open-webui/pull/24338), [#24379](https://github.com/open-webui/open-webui/pull/24379), [#24169](https://github.com/open-webui/open-webui/issues/24169)\n119|- 🌐 **SearXNG language parameter handling.** Web searches now send clean multi-language values without trailing separators, so SearXNG requests no longer fail when multiple languages are selected. [Commit](https://github.com/open-webui/open-webui/commit/6dff85b9d205cfc4bc2845dac40909b8d859910c), [#24198](https://github.com/open-webui/open-webui/issues/24198)\n120|- 📂 **File modal open-link behavior.** Clicking a file name in the file details modal now opens the correct file content in a new tab for uploaded file items instead of failing to open. [#24125](https://github.com/open-webui/open-webui/pull/24125)\n121|- 📎 **Chat attachment display recovery.** Files attached by chat tools now appear reliably in assistant responses, including non-image file attachments that were previously hidden. [Commit](https://github.com/open-webui/open-webui/commit/7eeff2fdf945024585a01b72071a61971afc844d), [#24332](https://github.com/open-webui/open-webui/pull/24332)\n122|- 🧱 **Channel embed rendering guard.** Channel message embeds now appear only for model-generated messages and are suppressed in reply previews, preventing unintended embed expansion in regular user posts. [Commit](https://github.com/open-webui/open-webui/commit/e1dce9914745de9b4d2c67b1deddde3472ce4dfa)\n123|- 🛡️ **Safer image URL handling.** Untrusted external image URLs are now blocked in profile and rich-text image rendering paths, preventing unintended client-side requests to attacker-controlled domains. [#24420](https://github.com/open-webui/open-webui/pull/24420)\n124|- 🛡️ **Sanitized spreadsheet HTML previews.** Spreadsheet previews now sanitize generated HTML before rendering, reducing the risk of unsafe content being executed when opening office files in chat and file modals. [#24468](https://github.com/open-webui/open-webui/pull/24468)\n125|- 🧰 **Multi-worker tool update consistency.** Updated tool code now refreshes correctly across workers without requiring a full service restart, so chats no longer run stale tool versions after edits. [Commit](https://github.com/open-webui/open-webui/commit/3309f5d9f11f521c0ee97b64c59a83e3cf390bde), [#24400](https://github.com/open-webui/open-webui/issues/24400), [#24433](https://github.com/open-webui/open-webui/pull/24433)\n126|- 🧩 **Default model metadata env parsing.** The \"DEFAULT_MODEL_METADATA\" environment setting is now parsed and applied correctly, including when persistent config is disabled, so configured model capability defaults are no longer ignored at startup. [Commit](https://github.com/open-webui/open-webui/commit/0103d7e82cccbd5c4b1c8daabcb3e5160fa74a97), [#24319](https://github.com/open-webui/open-webui/issues/24319)\n127|- 🔄 **Config import and Redis consistency.** Imported settings now remain effective after import because configuration values are immediately synchronized to Redis, preventing stale cached values from overriding imported permissions and settings. [Commit](https://github.com/open-webui/open-webui/commit/55a572cd398c9b4e6118728f8f129941437aa225), [Commit](https://github.com/open-webui/open-webui/commit/1c1c8b18e5cc90ca3c6961a4c193a4363febbc83), [#24346](https://github.com/open-webui/open-webui/issues/24346)\n128|- 🔔 **LDAP signup webhook parity.** New accounts created through LDAP now trigger the same signup webhook notifications as password and OAuth signups, so downstream provisioning and audit automations receive consistent events. [Commit](https://github.com/open-webui/open-webui/commit/fd3368c0bff168417e3c49ffd73491c344702339), [#24377](https://github.com/open-webui/open-webui/issues/24377)\n129|- 🦆 **DDGS auto-backend compatibility.** Web search now handles DDGS automatic backend selection correctly and safely falls back on empty or rate-limited responses, preventing search failures in newer DDGS versions. [Commit](https://github.com/open-webui/open-webui/commit/9adc0c442a57eaa88a5f30c2b2cb393623154e20), [#24188](https://github.com/open-webui/open-webui/issues/24188)\n130|- 🤖 **Automation update tool reliability.** Updating existing automations in chat now works correctly instead of failing with a missing method error. [Commit](https://github.com/open-webui/open-webui/commit/f39f4a86aedc2769d8268670a020b1f3c16776dd), [#24405](https://github.com/open-webui/open-webui/issues/24405#issuecomment-4408011166)\n131|- 📅 **Calendar event permission checks.** Calendar event update and delete actions now handle ownership and access checks more reliably, returning clean access-denied results when appropriate. [Commit](https://github.com/open-webui/open-webui/commit/2977910ffd9d2369dfa504aa6ab12745b3dbd19a)\n132|- 🛡️ **Safer cached file delivery.** Cached files that are not recognized as image, audio, or video now download as attachments instead of rendering inline, reducing the risk of unsafe browser content handling. [Commit](https://github.com/open-webui/open-webui/commit/4754ece4a2de5bba85a1d53af2dc8d24fdfb58be)\n133|- 📊 **Streaming token analytics accuracy.** Admin Analytics now records and aggregates token usage correctly for streaming chats across Responses API and OpenAI-compatible providers, including fallback handling for provider usage formats that use prompt and completion token keys. [Commit](https://github.com/open-webui/open-webui/commit/989d5fd4e2ce285edf4475a1e13f0981a78d3821), [Commit](https://github.com/open-webui/open-webui/commit/a32d26e61d24d9f63650faed5cb8909ed90af661), [#24217](https://github.com/open-webui/open-webui/issues/24217), [#24294](https://github.com/open-webui/open-webui/issues/24294), [#24241](https://github.com/open-webui/open-webui/issues/24241)\n134|- 🔗 **Admin shared chat links.** Admin users can now open and clone shared chat links reliably without 401 errors because shared links are now resolved by share ID first, with safe fallback behavior for direct chat ID access. [Commit](https://github.com/open-webui/open-webui/commit/cde21b9f6dc11575a668484f42440824ec5a4fae), [#24311](https://github.com/open-webui/open-webui/issues/24311), [#24096](https://github.com/open-webui/open-webui/issues/24096)\n135|- 💾 **Chat settings persistence.** System prompts and other chat-level settings now persist correctly after creating a new chat and reloading, preventing prompt loss in affected conversations. [Commit](https://github.com/open-webui/open-webui/commit/86df8bf27e1b84abbe2eeedcc8650df59c7d23d6), [#24193](https://github.com/open-webui/open-webui/issues/24193), [#24270](https://github.com/open-webui/open-webui/issues/24270)\n136|- 💾 **Chat control autosave persistence.** Changes to chat controls like system prompt, parameters, and attached files are now autosaved on existing chats, so edits are no longer lost when you refresh or navigate away before sending a message. [Commit](https://github.com/open-webui/open-webui/commit/a938c8ae2e45a00d2f06151fdaeaee94e54a8095), [#23897](https://github.com/open-webui/open-webui/pull/23897)\n137|- ☁️ **OneDrive option visibility.** OneDrive personal and business upload options now appear only when their respective client IDs are configured, preventing unavailable options from showing in attachment menus. [Commit](https://github.com/open-webui/open-webui/commit/b72019db393a658ca0ceecdcc59b70f6cc5dcd40), [#24411](https://github.com/open-webui/open-webui/issues/24411)\n138|- 🧠 **Reasoning content leakage prevention.** Tool-call round-trip messages no longer wrap reasoning text in `<think>` tags inside the content field, preventing raw markup from leaking into chat output for models whose templates don't strip think tags (e.g. Gemma 4). [#23844](https://github.com/open-webui/open-webui/issues/23844)\n139|- 🖥️ **Terminal sidebar auto-open guard.** The terminal sidebar no longer auto-opens on chat load when OpenTerminal is disabled, because stale terminal IDs saved on models or in localStorage are now validated against available terminal servers before use.\n140|- 🔁 **Single-confirmation connection deletion.** Deleting OpenAI, Ollama, tool server, and terminal server connections now shows exactly one confirmation dialog instead of two, because redundant outer confirmation wrappers were removed from all connection components.\n141|- 🧵 **Reliable background task cleanup.** The chat task lifecycle now deregisters completed tasks before checking for remaining siblings, eliminating the off-by-one timing issue that could leave the stop button stuck or dismiss the sidebar activity spinner too early.\n142|\n143|### Changed\n144|\n145|- ⚠️ **Database Migrations**: This release includes database schema changes; we strongly recommend backing up your database and all associated data before upgrading in production environments. If you are running a multi-worker, multi-server, or load-balanced deployment, all instances must be updated simultaneously, rolling updates are not supported and will cause application failures due to schema incompatibility.\n146|- 🚪 **Signout request method.** The signout endpoint now requires POST instead of GET, so custom clients and integrations must update logout calls accordingly. [#24420](https://github.com/open-webui/open-webui/pull/24420)\n147|\n148|## [0.9.2] - 2026-04-24\n149|\n150|### Added\n151|\n152|- 🧠 **PaddleOCR-vl document extraction.** Administrators can now use PaddleOCR-vl as a content extraction engine for document processing, with configurable API URL and token settings in document retrieval configuration. [#23945](https://github.com/open-webui/open-webui/pull/23945)\n153|- 🔥 **Firecrawl v2 API.** Firecrawl web loading now uses the v2 API directly with proper retry logic, exponential backoff on rate limits, and configurable timeout handling, improving reliability for both cloud and self-hosted Firecrawl setups. [#23934](https://github.com/open-webui/open-webui/pull/23934)\n154|- ⏰ **Calendar event reminder customization.** Calendar events now support a configurable `reminder_minutes` parameter, allowing models to set custom reminder durations instead of the default 10-minute notification.\n155|- 🔑 **Custom API key header.** Administrators can now configure a custom header name for API key authentication via the `CUSTOM_API_KEY_HEADER` environment variable, enabling compatibility with reverse proxies that use the `Authorization` header for their own authentication.\n156|- 🔌 **OAuth session disconnection.** Users can now disconnect OAuth sessions for specific providers (e.g., MCP connections) through a new API endpoint, enabling cleaner re-authentication workflows.\n157|- 📚 **Source overflow indicator.** The Sources button now shows a +N badge when more than three sources are available, so hidden sources are clearly indicated in chat responses. [#23918](https://github.com/open-webui/open-webui/pull/23918)\n158|- ⚡ **Model list performance.** Model list API responses now strip base64 profile image data from paginated results, and model tags are fetched via a dedicated efficient query instead of loading all models. This significantly reduces payload sizes and improves workspace Models page responsiveness.\n159|- ⚡ **Model avatar cache reuse.** Default model profile images now redirect to a shared static path instead of reading files from disk per-request, reducing repeated I/O and improving loading efficiency when multiple models use the fallback icon. [#24015](https://github.com/open-webui/open-webui/pull/24015)\n160|- 🚀 **Faster splash image loading.** Splash screen images are now prioritized earlier during page load with preload links, improving first-load LCP behavior and reducing delayed image discovery. [#24011](https://github.com/open-webui/open-webui/pull/24011)\n161|- 🧵 **Streaming markdown performance stability.** Streaming responses now stay more memory-efficient by preventing repeated cleanup callback registration during markdown updates. [#24048](https://github.com/open-webui/open-webui/pull/24048)\n162|- 📊 **Telemetry gauge reliability.** OpenTelemetry user gauge callbacks now use synchronous database queries directly, eliminating cross-thread async bridging issues that could cause silent failures in metric collection.\n163|- 🔄 **General improvements.** Various improvements were implemented across the application to enhance performance, stability, and security.\n164|- 🌐 **Translation updates.** Translations for Finnish, Korean, Portuguese (Brazil), and Dutch were enhanced and expanded.\n165|\n166|### Fixed\n167|\n168|- 🔧 **MCP task cancellation stability.** Interrupted MCP tool calls no longer cause CPU spikes or runaway cleanup behavior. MCP client disconnection now runs in the same asyncio task as connection, respecting cancel scope constraints, and chat-active events are properly shielded during cancellation.\n169|- 🧠 **Persistent chat skill injection.** Skills mentioned in persisted chats now inject into the system prompt reliably. Skill ID extraction from `<$skillId|label>` message tags is now handled server-side, and tags are stripped before messages reach the model.\n170|- 🗄️ **Async database driver migration.** The async database backend now uses psycopg (v3) instead of asyncpg, eliminating brittle SSL parameter translation and supporting native libpq connection strings including `sslmode`, `options`, and `target_session_attrs` without any stripping or conversion.\n171|- 🐳 **Docker ARM64 reliability.** Docker images built for arm64 via QEMU cross-compilation no longer produce 0-byte corrupted Python dependencies. `UV_LINK_MODE=copy` is now set in the Dockerfile to force reliable file installation.\n172|- 🛠️ **Throttle request handling.** Request handling no longer fails when user activity status updates are throttled with a non-zero interval. [#23979](https://github.com/open-webui/open-webui/pull/23979)\n173|- ✍️ **Rich text extension conflicts.** Rich text editing no longer triggers duplicate extension conflicts for lists and code blocks, improving editor stability. [#24009](https://github.com/open-webui/open-webui/pull/24009)\n174|- 🔇 **Fetch URL null content guard.** The `fetch_url` built-in tool now safely handles `None` content returned by web loaders instead of crashing with a `TypeError`.\n175|- 🌐 **OAuth discovery fallback.** OAuth protected resource discovery now falls back to well-known RFC 9728 URIs when the `WWW-Authenticate` header doesn't contain a `resource_metadata` link, improving compatibility with more MCP server implementations.\n176|- 🔐 **Session token resolution.** Session user endpoints now gracefully handle missing `Authorization` headers by falling back to cookie and request state tokens, preventing errors when used behind forward-auth proxies.\n177|- 🚫 **Direct API error responses.** Chat completion requests without a WebSocket channel (direct API calls) now return proper HTTP error responses instead of silently returning null on failure.\n178|- 📡 **Cancelled response stream cleanup.** Cancelled chat generation now explicitly closes the upstream response body iterator, preventing orphaned async generators from spinning in anyio internals.\n179|- 🔒 **Model profile image path safety.** Model profile image endpoints now validate and sanitize static asset redirect paths, preventing path traversal through encoded dots or malicious URL patterns.\n180|- 📊 **RAG template validation UI.** The Documents settings page now displays a warning when RAG templates contain multiple `[context]` or `{{CONTEXT}}` placeholders, helping administrators avoid accidental redundant context injection.\n181|- 🧩 **Automation model detection.** The `create_automation` tool now correctly detects the current model ID even when `model_id` is not yet set in metadata, falling back to the model dict.\n182|- 🔄 **MCP resource content handling.** MCP tool results with the `resource` content type are now correctly detected and their `resource.text` payload is extracted, instead of being silently ignored.\n183|- 🔄 **Ollama and OpenAI metadata forwarding.** Ollama and OpenAI proxy routes now forward request metadata to downstream handlers, ensuring consistent context propagation.\n184|- 🧹 **Browser-native message virtualization.** The custom JavaScript-based message culling system (spacers, height caching, scroll listeners) was replaced with CSS `content-visibility: auto`, letting the browser natively skip rendering of off-screen messages without destroying component trees. This eliminates scroll jump artifacts and mount/destroy thrashing while preserving memory efficiency in long conversations.\n185|- 📻 **Redis notification compatibility.** Redis pub/sub now handles missing or incompatible `client_name` support more gracefully, preventing connection errors with certain Redis configurations.\n186|\n187|### Changed\n188|\n189|- ⚙️ **psycopg v3 async driver.** The async database driver has been migrated from `asyncpg` to `psycopg` (v3). This is a transparent change for most deployments, but custom connection strings with `asyncpg`-specific parameters may need adjustment.\n190|- 🔑 **Brotli dependency update.** Brotli has been updated to address CVE-2025-6176.\n191|- 🖥️ **Windows startup script.** The Windows startup batch script has been updated for improved compatibility.\n192|\n193|## [0.9.1] - 2026-04-21\n194|\n195|### Fixed\n196|\n197|- 🐛 **Missing `aiosqlite` dependency.** Fixed a startup crash (`ModuleNotFoundError: No module named 'aiosqlite'`) when installing Open WebUI via `pip` or `uv` by adding the missing `aiosqlite` package to `pyproject.toml`. The dependency was listed in `requirements.txt` but not in the published package metadata, so it was not installed automatically. [#23916](https://github.com/open-webui/open-webui/issues/23916)\n198|- 🐛 **Missing `asyncpg` dependency.** Added the missing `asyncpg` package to `pyproject.toml` to prevent the same startup crash for PostgreSQL users. Like `aiosqlite`, it was present in `requirements.txt` but absent from the published package dependencies.\n199|\n200|## [0.9.0] - 2026-04-20\n201|", "total_lines": 4586, "file_size": 806119, "truncated": true, "hint": "Use offset=201 to continue reading (showing 1-200 of 4586 lines)", "is_binary": false, "is_image": false}


session_id: 20260530_230637_ad9bdd
role: assistant
finish_reason: stop
content:
  Com base na análise do repositório clonado, segue o resumo estruturado:

  **1. Problema que resolve**
  - Falta de uma interface web amigável, self-hosted e offline para interagir com LLMs.
  - Dificuldade de integrar múltiplos provedores (Ollama, OpenAI, Anthropic, Groq, etc.) em um único lugar.
  - Ausência de RAG nativo em ferramentas abertas com suporte a múltiplos bancos vetoriais e formatos de arquivo.
  - Falta de workspace colaborativo com RBAC, canais, voz/vídeo e ferramentas plugáveis em uma única stack.

  **2. Tema**
  Plataforma open source de IA — “User-friendly self-hosted AI platform” — com foco em privacidade, operação offline e poliglota de modelos.

  **3. Razão hype**
  - Integração plug-and-play com Ollama e APIs OpenAI-compatíveis (GroqCloud, Mistral, OpenRouter, LMStudio etc.).
  - RAG nativo: 9 bancos vetoriais (ChromaDB, Qdrant, Milvus, OpenSearch, Pinecone, PGVector, S3Vector, Oracle 23ai, Elasticsearch) + múltiplos engines de extração (Tika, Docling, Azure, Mistral OCR, PaddleOCR-vl).
  - Ecosystem completo: voz/vídeo, web search (15+ providers), image generation, channels/DMs, calendars, notes, automations, MCP tools.
  - Deploy simples (Docker/Kubernetes, pip) e offline-first com PWA.

  **4. Tecnologias**
  - Backend: Python (FastAPI + Fastify), Uvicorn, SQLAlchemy, Alembic, LangChain, Redis, WebSockets (python-socketio), RAG (Chroma/unstructured/ sentence-transformers/ faster-whisper), multi-DB (SQLite/PostgreSQL/MariaDB).
  - Frontend: Svelte 5 + TypeScript, Vite, TailwindCSS 4, ProseMirror/Tiptap, yjs (collab), CodeMirror, KaTeX/Mermaid, PDF.js, Chart.js, xterm, socket.io-client.
  - Infra/IA: PyODIDE (client-side Python), HuggingFace Transformers (web), OCR (OpenCV, RapidOCR), STT/TTS (faster-whisper, Kokoro, ElevenLabs/Azure/OpenAI), ONNX Runtime.
  - Deploy/observability: Docker, Compose, Helm/Kustomize, OpenTelemetry.

reasoning:
  Good, I have a clear picture of the project now. Let me summarize what I found:

  1. **Projeto/Package**: open-webui, versão 0.9.5 (private, Single-Package Repository)
  2. **Frontend**: Svelte 5 + TypeScript + Vite
  3. **Backend**: Python (FastAPI + Fastify) - repo monorepo-like structure com backend em /backend/open_webui e frontend em /src
  4. **Key dependencies**: Python 3.11+, Svelte 5, TailwindCSS 4, etc.

  **Problema que resolve**: Interface web amigável para interagir com LLMs locais (Ollama) ou APIs OpenAI-compatíveis, com RAG nativo, ferramentas, canais, voz/vídeo, etc.

  **Tema/Hype**: Plataforma self-hosted de IA, compatível com Ollama, OpenAI, Anthropic, Google, com RAG avançado, knowledge bases, ferramentas, workspace colaborativo, PWA, etc.

  **Tecnologias**: Frontend - Svelte, TypeScript, Vite, Tailwind, ProseMirror, Tiptap, yjs, etc. Backend - FastAPI, Fastify, Uvicorn, SQLAlchemy, Alembic, LangChain, ChromaDB, etc. Infra: Docker, Docker Compose, Kubernetes.

  **Stars**: 139.294 NÃO bate com a info da task (139.294 = ~139k, que é próximo do valor real do Open WebUI).

  Estou fazendo uma análise detalhada do CHANGELOG.md, onde identifiquei no lançamento 0.9.5 vários campos essenciais que preciso examinar mais de perto: Problema, Tema, Razão hype e Tecnologias. Isso vai me ajudar a entender melhor a estrutura e as características do projeto.

  Agora, com base na análise do repositório clonado, compilei uma visão abrangente dos itens analisados:

  - Problema: Criação de uma interface web amigável para interação com LLMs locais e APIs compatíveis com OpenAI, incluindo suporte a Ollama, RAG nativo e ferramentas de colaboração.
  - Tema: Plataforma self-hosted de IA.
  - Razão hype: Suporte extenso a múltiplos provedores LLM, recursos avançados de RAG, interface moderna,部署 flexível e funcionalidades exclusivas como canais, voz/vídeo e PWA.
  - Tecnologias: Stack diversificado envolvendo Svelte 5, TypeScript, Vite, FastAPI, Fastify, SQLAlchemy, LangChain, ChromaDB, Docker e Kubernetes, além de bibliotecas especializadas para edição de texto e processamento de documentos.

  Estou pronto para estruturar essa informação de forma mais coesa e detalhada no formato solicitado.

reasoning_content:
  Good, I have a clear picture of the project now. Let me summarize what I found:

  1. **Projeto/Package**: open-webui, versão 0.9.5 (private, Single-Package Repository)
  2. **Frontend**: Svelte 5 + TypeScript + Vite
  3. **Backend**: Python (FastAPI + Fastify) - repo monorepo-like structure com backend em /backend/open_webui e frontend em /src
  4. **Key dependencies**: Python 3.11+, Svelte 5, TailwindCSS 4, etc.

  **Problema que resolve**: Interface web amigável para interagir com LLMs locais (Ollama) ou APIs OpenAI-compatíveis, com RAG nativo, ferramentas, canais, voz/vídeo, etc.

  **Tema/Hype**: Plataforma self-hosted de IA, compatível com Ollama, OpenAI, Anthropic, Google, com RAG avançado, knowledge bases, ferramentas, workspace colaborativo, PWA, etc.

  **Tecnologias**: Frontend - Svelte, TypeScript, Vite, Tailwind, ProseMirror, Tiptap, yjs, etc. Backend - FastAPI, Fastify, Uvicorn, SQLAlchemy, Alembic, LangChain, ChromaDB, etc. Infra: Docker, Docker Compose, Kubernetes.

  **Stars**: 139.294 NÃO bate com a info da task (139.294 = ~139k, que é próximo do valor real do Open WebUI).

  Estou fazendo uma análise detalhada do CHANGELOG.md, onde identifiquei no lançamento 0.9.5 vários campos essenciais que preciso examinar mais de perto: Problema, Tema, Razão hype e Tecnologias. Isso vai me ajudar a entender melhor a estrutura e as características do projeto.

  Agora, com base na análise do repositório clonado, compilei uma visão abrangente dos itens analisados:

  - Problema: Criação de uma interface web amigável para interação com LLMs locais e APIs compatíveis com OpenAI, incluindo suporte a Ollama, RAG nativo e ferramentas de colaboração.
  - Tema: Plataforma self-hosted de IA.
  - Razão hype: Suporte extenso a múltiplos provedores LLM, recursos avançados de RAG, interface moderna,部署 flexível e funcionalidades exclusivas como canais, voz/vídeo e PWA.
  - Tecnologias: Stack diversificado envolvendo Svelte 5, TypeScript, Vite, FastAPI, Fastify, SQLAlchemy, LangChain, ChromaDB, Docker e Kubernetes, além de bibliotecas especializadas para edição de texto e processamento de documentos.

  Estou pronto para estruturar essa informação de forma mais coesa e detalhada no formato solicitado.


session_id: 20260530_230637_2fe223
role: assistant
content: Vou clonar o repositório e analisar.
finish_reason: tool_calls
reasoning: Vou clonar o repositório e analisar.
reasoning_content: Vou clonar o repositório e analisar.
tool_calls:
  [{"id": "chatcmpl-tool-8ec993ea44bbdc2f", "call_id": "chatcmpl-tool-8ec993ea44bbdc2f", "response_item_id": "fc_chatcmpl-tool-8ec993ea44bbdc2f", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"git clone https://github.com/infiniflow/ragflow.git /home/ice/ragflow\", \"timeout\": 120}"}}]


session_id: 20260530_230637_2fe223
role: tool
tool_call_id: chatcmpl-tool-8ec993ea44bbdc2f
tool_name: terminal
content:
  {"output": "Cloning into '/home/ice/ragflow'...", "exit_code": 0, "error": null}

  [Subdirectory context discovered: ragflow/AGENTS.md]
  # RAGFlow Project Instructions for GitHub Copilot

  This file provides context, build instructions, and coding standards for the RAGFlow project.
  It is structured to follow GitHub Copilot's [customization guidelines](https://docs.github.com/en/copilot/concepts/prompting/response-customization).

  ## 1. Project Overview
  RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It is a full-stack application with a Python backend and a React/TypeScript frontend.

  - **Backend**: Python 3.10+ (Flask/Quart)
  - **Frontend**: TypeScript, React, UmiJS
  - **Architecture**: Microservices based on Docker.
    - `api/`: Backend API server.
    - `rag/`: Core RAG logic (indexing, retrieval).
    - `deepdoc/`: Document parsing and OCR.
    - `web/`: Frontend application.

  ## 2. Directory Structure
  - `api/`: Backend API server (Flask/Quart).
    - `apps/`: API Blueprints (Knowledge Base, Chat, etc.).
    - `db/`: Database models and services.
  - `rag/`: Core RAG logic.
    - `llm/`: LLM, Embedding, and Rerank model abstractions.
  - `deepdoc/`: Document parsing and OCR modules.
  - `agent/`: Agentic reasoning components.
  - `web/`: Frontend application (React + UmiJS).
  - `docker/`: Docker deployment configurations.
  - `sdk/`: Python SDK.
  - `test/`: Backend tests.

  ## 3. Build Instructions

  ### Backend (Python)
  The project uses **uv** for dependency management.

  1. **Setup Environment**:
     ```bash
     uv sync --python 3.13 --all-extras
     uv run python3 download_deps.py
     ```

  2. **Run Server**:
     - **Pre-requisite**: Start dependent services (MySQL, ES/Infinity, Redis, MinIO).
       ```bash
       docker compose -f docker/docker-compose-base.yml up -d
       ```
     - **Launch**:
       ```bash
       source .venv/bin/activate
       export PYTHONPATH=$(pwd)
       bash docker/launch_backend_service.sh
       ```

  ### Frontend (TypeScript/React)
  Located in `web/`.

  1. **Install Dependencies**:
     ```bash
     cd web
     npm install
     ```

  2. **Run Dev Server**:
     ```bash
     npm run dev
     ```
     Runs on port 8000 by default.

  ### Docker Deployment
  To run the full stack using Docker:
  ```bash
  cd docker
  docker compose -f docker-compose.yml up -d
  ```

  ## 4. Testing Instructions

  ### Backend Tests
  - **Run All Tests**:
    ```bash
    uv run pytest
    ```
  - **Run Specific Test**:
    ```bash
    uv run pytest test/test_api.py
    ```

  ### Frontend Tests
  - **Run Tests**:
    ```bash
    cd web
    npm run test
    ```

  ## 5. Coding Standards & Guidelines
  - **Python Formatting**: Use `ruff` for linting and formatting.
    ```bash
    ruff check
    ruff format
    ```
  - **Frontend Linting**:
    ```bash
    cd web
    npm run lint
    ```
  - **Pre-commit**: Ensure pre-commit hooks are installed.
    ```bash
    pre-commit install
    pre-commit run --all-files
    ```


session_id: 20260530_230637_2fe223
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-805951aad7708e46", "call_id": "chatcmpl-tool-805951aad7708e46", "response_item_id": "fc_chatcmpl-tool-805951aad7708e46", "type": "function", "function": {"name": "read_file", "arguments": "{\"limit\": 200, \"path\": \"/home/ice/ragflow/README.md\"}"}}, {"id": "chatcmpl-tool-a06988e1e3d46d17", "call_id": "chatcmpl-tool-a06988e1e3d46d17", "response_item_id": "fc_chatcmpl-tool-a06988e1e3d46d17", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\": \"/home/ice/ragflow/pyproject.toml\"}"}}]

reasoning:
  Good, the repository is cloned. Let me explore the structure and gather information about the project. I'll look at the README and pyproject.toml to understand the project better.

reasoning_content:
  Good, the repository is cloned. Let me explore the structure and gather information about the project. I'll look at the README and pyproject.toml to understand the project better.


session_id: 20260530_230637_2fe223
role: tool
tool_call_id: chatcmpl-tool-805951aad7708e46
tool_name: read_file
content:
  {"content": "1|<div align=\"center\">\n2|<a href=\"https://cloud.ragflow.io/\">\n3|<img src=\"web/src/assets/logo-with-text.svg\" width=\"520\" alt=\"ragflow logo\">\n4|</a>\n5|</div>\n6|\n7|<p align=\"center\">\n8|  <a href=\"./README.md\"><img alt=\"README in English\" src=\"https://img.shields.io/badge/English-DBEDFA\"></a>\n9|  <a href=\"./README_zh.md\"><img alt=\"简体中文版自述文件\" src=\"https://img.shields.io/badge/简体中文-DFE0E5\"></a>\n10|  <a href=\"./README_tzh.md\"><img alt=\"繁體版中文自述文件\" src=\"https://img.shields.io/badge/繁體中文-DFE0E5\"></a>\n11|  <a href=\"./README_ja.md\"><img alt=\"日本語のREADME\" src=\"https://img.shields.io/badge/日本語-DFE0E5\"></a>\n12|  <a href=\"./README_ko.md\"><img alt=\"한국어\" src=\"https://img.shields.io/badge/한국어-DFE0E5\"></a>\n13|  <a href=\"./README_fr.md\"><img alt=\"README en Français\" src=\"https://img.shields.io/badge/Français-DFE0E5\"></a>\n14|  <a href=\"./README_id.md\"><img alt=\"Bahasa Indonesia\" src=\"https://img.shields.io/badge/Bahasa Indonesia-DFE0E5\"></a>\n15|  <a href=\"./README_pt_br.md\"><img alt=\"Português(Brasil)\" src=\"https://img.shields.io/badge/Português(Brasil)-DFE0E5\"></a>\n16|  <a href=\"./README_ar.md\"><img alt=\"README in Arabic\" src=\"https://img.shields.io/badge/Arabic-DFE0E5\"></a>\n17|  <a href=\"./README_tr.md\"><img alt=\"Türkçe README\" src=\"https://img.shields.io/badge/Türkçe-DFE0E5\"></a>\n18|</p>\n19|\n20|<p align=\"center\">\n21|    <a href=\"https://x.com/intent/follow?screen_name=infiniflowai\" target=\"_blank\">\n22|        <img src=\"https://img.shields.io/twitter/follow/infiniflow?logo=X&color=%20%23f5f5f5\" alt=\"follow on X(Twitter)\">\n23|    </a>\n24|    <a href=\"https://cloud.ragflow.io\" target=\"_blank\">\n25|        <img alt=\"Static Badge\" src=\"https://img.shields.io/badge/Get-Started-4e6b99\">\n26|    </a>\n27|    <a href=\"https://hub.docker.com/r/infiniflow/ragflow\" target=\"_blank\">\n28|        <img src=\"https://img.shields.io/docker/pulls/infiniflow/ragflow?label=Docker%20Pulls&color=0db7ed&logo=docker&logoColor=white&style=flat-square\" alt=\"docker pull infiniflow/ragflow:v0.25.6\">\n29|    </a>\n30|    <a href=\"https://github.com/infiniflow/ragflow/releases/latest\">\n31|        <img src=\"https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=Latest%20Release\" alt=\"Latest Release\">\n32|    </a>\n33|    <a href=\"https://github.com/infiniflow/ragflow/blob/main/LICENSE\">\n34|        <img height=\"21\" src=\"https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4\" alt=\"license\">\n35|    </a>\n36|    <a href=\"https://deepwiki.com/infiniflow/ragflow\">\n37|        <img alt=\"Ask DeepWiki\" src=\"https://deepwiki.com/badge.svg\">\n38|    </a>\n39|</p>\n40|\n41|<h4 align=\"center\">\n42|  <a href=\"https://cloud.ragflow.io\">Cloud</a> |\n43|  <a href=\"https://ragflow.io/docs/dev/\">Document</a> |\n44|  <a href=\"https://github.com/infiniflow/ragflow/issues/12241\">Roadmap</a> |\n45|  <a href=\"https://discord.gg/NjYzJD3GM3\">Discord</a>\n46|</h4>\n47|\n48|<div align=\"center\" style=\"margin-top:20px;margin-bottom:20px;\">\n49|<img src=\"https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/ragflow-octoverse.png\" width=\"1200\"/>\n50|</div>\n51|\n52|<div align=\"center\">\n53|<a href=\"https://trendshift.io/repositories/9064\" target=\"_blank\"><img src=\"https://trendshift.io/api/badge/repositories/9064\" alt=\"infiniflow%2Fragflow | Trendshift\" style=\"width: 250px; height: 55px;\" width=\"250\" height=\"55\"/></a>\n54|</div>\n55|\n56|<details open>\n57|<summary><b>📕 Table of Contents</b></summary>\n58|\n59|- 💡 [What is RAGFlow?](#-what-is-ragflow)\n60|- 🎮 [Get Started](#-get-started)\n61|- 📌 [Latest Updates](#-latest-updates)\n62|- 🌟 [Key Features](#-key-features)\n63|- 🔎 [System Architecture](#-system-architecture)\n64|- 🎬 [Self-Hosting](#-self-hosting)\n65|- 🔧 [Configurations](#-configurations)\n66|- 🔧 [Build a Docker image](#-build-a-docker-image)\n67|- 🔨 [Launch service from source for development](#-launch-service-from-source-for-development)\n68|- 📚 [Documentation](#-documentation)\n69|- 📜 [Roadmap](#-roadmap)\n70|- 🏄 [Community](#-community)\n71|- 🙌 [Contributing](#-contributing)\n72|\n73|</details>\n74|\n75|## 💡 What is RAGFlow?\n76|\n77|[RAGFlow](https://ragflow.io/) is a leading open-source Retrieval-Augmented Generation ([RAG](https://ragflow.io/basics/what-is-rag)) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs. It offers a streamlined RAG workflow adaptable to enterprises of any scale. Powered by a converged [context engine](https://ragflow.io/basics/what-is-agent-context-engine) and pre-built agent templates, RAGFlow enables developers to transform complex data into high-fidelity, production-ready AI systems with exceptional efficiency and precision.\n78|\n79|## 🎮 Get Started\n80|\n81|Try our cloud service at [https://cloud.ragflow.io](https://cloud.ragflow.io).\n82|\n83|<div align=\"center\" style=\"margin-top:20px;margin-bottom:20px;\">\n84|<img src=\"https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/chunking.gif\" width=\"1200\"/>\n85|<img src=\"https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/agentic-dark.gif\" width=\"1200\"/>\n86|</div>\n87|\n88|## 🔥 Latest Updates\n89|\n90|- 2026-04-24 Supports DeepSeek v4.\n91|- 2026-03-24 [RAGFlow Skill on OpenClaw](https://clawhub.ai/yingfeng/ragflow-skill) — Provides an official skill for accessing RAGFlow datasets via OpenClaw.\n92|- 2025-12-26 Supports 'Memory' for AI agent.\n93|- 2025-11-19 Supports Gemini 3 Pro.\n94|- 2025-11-12 Supports data synchronization from Confluence, S3, Notion, Discord, Google Drive.\n95|- 2025-10-23 Supports MinerU & Docling as document parsing methods.\n96|- 2025-10-15 Supports orchestrable ingestion pipeline.\n97|- 2025-08-08 Supports OpenAI's latest GPT-5 series models.\n98|- 2025-08-01 Supports agentic workflow and MCP.\n99|- 2025-05-23 Adds a Python/JavaScript code executor component to Agent.\n100|- 2025-05-05 Supports cross-language query.\n101|- 2025-03-19 Supports using a multi-modal model to make sense of images within PDF or DOCX files.\n102|\n103|## 🎉 Stay Tuned\n104|\n105|⭐️ Star our repository to stay up-to-date with exciting new features and improvements! Get instant notifications for new\n106|releases! 🌟\n107|\n108|<div align=\"center\" style=\"margin-top:20px;margin-bottom:20px;\">\n109|<img src=\"https://github.com/user-attachments/assets/18c9707e-b8aa-4caf-a154-037089c105ba\" width=\"1200\"/>\n110|</div>\n111|\n112|## 🌟 Key Features\n113|\n114|### 🍭 **\"Quality in, quality out\"**\n115|\n116|- [Deep document understanding](./deepdoc/README.md)-based knowledge extraction from unstructured data with complicated\n117|  formats.\n118|- Finds \"needle in a data haystack\" of literally unlimited tokens.\n119|\n120|### 🍱 **Template-based chunking**\n121|\n122|- Intelligent and explainable.\n123|- Plenty of template options to choose from.\n124|\n125|### 🌱 **Grounded citations with reduced hallucinations**\n126|\n127|- Visualization of text chunking to allow human intervention.\n128|- Quick view of the key references and traceable citations to support grounded answers.\n129|\n130|### 🍔 **Compatibility with heterogeneous data sources**\n131|\n132|- Supports Word, slides, excel, txt, images, scanned copies, structured data, web pages, and more.\n133|\n134|### 🛀 **Automated and effortless RAG workflow**\n135|\n136|- Streamlined RAG orchestration catered to both personal and large businesses.\n137|- Configurable LLMs as well as embedding models.\n138|- Multiple recall paired with fused re-ranking.\n139|- Intuitive APIs for seamless integration with business.\n140|\n141|## 🔎 System Architecture\n142|\n143|<div align=\"center\" style=\"margin-top:20px;margin-bottom:20px;\">\n144|<img src=\"https://github.com/user-attachments/assets/31b0dd6f-ca4f-445a-9457-70cb44a381b2\" width=\"1000\"/>\n145|</div>\n146|\n147|## 🎬 Self-Hosting\n148|\n149|### 📝 Prerequisites\n150|\n151|- CPU >= 4 cores\n152|- RAM >= 16 GB\n153|- Disk >= 50 GB\n154|- Docker >= 24.0.0 & Docker Compose >= v2.26.1\n155|- Python >= 3.13\n156|- [gVisor](https://gvisor.dev/docs/user_guide/install/): Required only if you intend to use the code executor (sandbox) feature of RAGFlow.\n157|\n158|> [!TIP]\n159|> If you have not installed Docker on your local machine (Windows, Mac, or Linux), see [Install Docker Engine](https://docs.docker.com/engine/install/).\n160|\n161|### 🚀 Start up the server\n162|\n163|1. Ensure `vm.max_map_count` >= 262144:\n164|\n165|   > To check the value of `vm.max_map_count`:\n166|   >\n167|   > ```bash\n168|   > $ sysctl vm.max_map_count\n169|   > ```\n170|   >\n171|   > Reset `vm.max_map_count` to a value at least 262144 if it is not.\n172|   >\n173|   > ```bash\n174|   > # In this case, we set it to 262144:\n175|   > $ sudo sysctl -w vm.max_map_count=262144\n176|   > ```\n177|   >\n178|   > This change will be reset after a system reboot. To ensure your change remains permanent, add or update the\n179|   > `vm.max_map_count` value in **/etc/sysctl.conf** accordingly:\n180|   >\n181|   > ```bash\n182|   > vm.max_map_count=262144\n183|   > ```\n184|   >\n185|2. Clone the repo:\n186|\n187|   ```bash\n188|   $ git clone https://github.com/infiniflow/ragflow.git\n189|   ```\n190|3. Start up the server using the pre-built Docker images:\n191|\n192|> [!CAUTION]\n193|> All Docker images are built for x86 platforms. We don't currently offer Docker images for ARM64.\n194|> If you are on an ARM64 platform, follow [this guide](https://ragflow.io/docs/dev/build_docker_image) to build a Docker image compatible with your system.\n195|\n196|> The command below downloads the `v0.25.6` edition of the RAGFlow Docker image. See the following table for descriptions of different RAGFlow editions. To download a RAGFlow edition different from `v0.25.6`, update the `RAGFLOW_IMAGE` variable accordingly in **docker/.env** before using `docker compose` to start the server.\n197|\n198|```bash\n199|   $ cd ragflow/docker\n200|\n201|", "total_lines": 415, "file_size": 16962, "truncated": true, "hint": "Use offset=201 to continue reading (showing 1-200 of 415 lines)", "is_binary": false, "is_image": false}


session_id: 20260530_230637_2fe223
role: tool
tool_call_id: chatcmpl-tool-a06988e1e3d46d17
tool_name: read_file
content:
  {"content": "1|[project]\n2|name = \"ragflow\"\n3|version = \"0.25.6\"\n4|description = \"[RAGFlow](https://ragflow.io/) is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from various complex formatted data.\"\n5|authors = [{ name = \"Zhichang Yu\", email = \"yuzhichang@gmail.com\" }]\n6|license-files = [\"LICENSE\"]\n7|readme = \"README.md\"\n8|requires-python = \">=3.13,<3.15\"\n9|dependencies = [\n10|    # discord-py==2.3.2 unconditionally imports audioop in discord/player.py at module-\n11|    # load time. audioop was removed from the CPython stdlib in Python 3.13 (PEP 594),\n12|    # so any import of the discord package raises ImportError on Python 3.13 — even in\n13|    # tests that never use voice features. audioop-lts provides the module as a backport.\n14|    \"audioop-lts>=0.2.1\",\n15|    \"aiosmtplib>=5.0.0\",\n16|    \"akshare>=1.15.78,<2.0.0\",\n17|    \"anthropic==0.76.0\",\n18|    \"arxiv==2.1.3\",\n19|    \"atlassian-python-api==4.0.7\",\n20|    \"azure-identity>=1.25.3\",\n21|    \"azure-storage-file-datalake==12.16.0\",\n22|    \"beartype>=0.20.0,<1.0.0\",\n23|    \"bio==1.7.1\",\n24|    \"browser-use>=0.11.1,<0.12.0\",\n25|    \"boto3>=1.28.0\",\n26|    \"boxsdk>=10.1.0\",\n27|    \"captcha>=0.7.1\",\n28|    \"chardet>=5.2.0,<6.0.0\",\n29|    \"cn2an==0.5.22\",\n30|    \"cohere==5.6.2\",\n31|    \"crawl4ai>=0.8.0\",\n32|    \"dashscope==1.25.11\",\n33|    \"deepl==1.18.0\",\n34|    \"debugpy>=1.8.13\",\n35|    \"demjson3==3.0.6\",\n36|    \"discord-py==2.3.2\",\n37|    \"dropbox==12.0.2\",\n38|    \"duckduckgo-search>=7.2.0,<8.0.0\",\n39|    \"editdistance==0.8.1\",\n40|    \"elasticsearch-dsl==8.12.0\",\n41|    \"exceptiongroup>=1.3.0,<2.0.0\",\n42|    \"feedparser>=6.0.11,<7.0.0\",\n43|    \"extract-msg>=0.39.0\",\n44|    \"ffmpeg-python>=0.2.0\",\n45|    \"flasgger>=0.9.7.1,<0.10.0\",\n46|    \"flask-cors==6.0.2\",\n47|    \"flask-login==0.6.3\",\n48|    \"flask-mail>=0.10.0\",\n49|    \"flask-session==0.8.0\",\n50|    \"google-api-python-client>=2.190.0,<3.0.0\",\n51|    \"google-auth-oauthlib>=1.2.0,<2.0.0\",\n52|    \"google-cloud-storage>=2.19.0,<3.0.0\",\n53|    \"google-genai>=1.41.0,<2.0.0\",\n54|    \"google-search-results==2.4.2\",\n55|    \"graspologic @ git+https://gitee.com/infiniflow/graspologic.git@38e680cab72bc9fb68a7992c3bcc2d53b24e42fd\",\n56|    \"groq>=0.30.0,<1.0.0\",\n57|    \"grpcio-status==1.67.1\",\n58|    \"html-text==0.6.2\",\n59|    \"infinity-sdk==0.7.0\",\n60|    \"infinity-emb>=0.0.66,<0.0.67\",\n61|    \"jira==3.10.5\",\n62|    \"json-repair==0.35.0\",\n63|    \"langfuse>=4.0.1\",\n64|    \"mammoth>=1.11.0\",\n65|    \"markdown==3.6\",\n66|    \"markdown-to-json==2.1.1\",\n67|    \"markdownify>=1.2.0\",\n68|    \"mcp>=1.19.0\",\n69|    \"mini-racer>=0.12.4,<0.13.0\",\n70|    \"minio==7.2.4\",\n71|    \"mistralai==0.4.2\",\n72|    \"mysql-connector-python>=9.0.0,<10.0.0\",\n73|    \"moodlepy>=0.23.0\",\n74|    \"mypy-boto3-s3==1.40.26\",\n75|    \"Office365-REST-Python-Client==2.6.2\",\n76|    \"ollama>=0.5.0\",\n77|    \"onnxruntime==1.23.2; sys_platform == 'darwin' or platform_machine != 'x86_64'\",\n78|    \"onnxruntime-gpu==1.23.2; sys_platform != 'darwin' and platform_machine == 'x86_64'\",\n79|    \"opencv-python==4.10.0.84\",\n80|    \"opencv-python-headless==4.10.0.84\",\n81|    \"opendal>=0.45.0,<0.46.0\",\n82|    \"opensearch-py==2.7.1\",\n83|    \"ormsgpack>=1.6.0\",\n84|    \"pdfplumber==0.10.4\",\n85|    \"pluginlib>=0.10.0\",\n86|    \"psycopg2-binary>=2.9.11,<3.0.0\",\n87|    \"pyclipper>=1.4.0,<2.0.0\",\n88|    # \"pywencai>=0.13.1,<1.0.0\",  # Temporarily disabled: conflicts with agentrun-sdk (pydash>=8), needed for agent/tools/wencai.py\n89|    \"pycryptodomex==3.20.0\",\n90|    \"pyobvector==0.2.22\",\n91|    \"pyodbc>=5.2.0,<6.0.0\",\n92|    \"pypandoc>=1.16\",\n93|    \"pypdf>=6.10.2\",\n94|    \"python-calamine>=0.4.0\",\n95|    \"python-docx>=1.1.2,<2.0.0\",\n96|    \"paramiko>=3.5.1\",\n97|    \"python-pptx>=1.0.2,<2.0.0\",\n98|    # \"pywencai>=0.13.1,<1.0.0\",  # Temporarily disabled: conflicts with agentrun-sdk (pydash>=8), needed for agent/tools/wencai.py\n99|    \"qianfan==0.4.6\",\n100|    \"quart-auth==0.11.0\",\n101|    \"quart-cors==0.8.0\",\n102|    \"ranx==0.3.20\",\n103|    \"readability-lxml>=0.8.4,<1.0.0\",\n104|    \"replicate==0.31.0\",\n105|    \"reportlab>=4.4.1\",\n106|    \"roman-numbers==1.0.2\",\n107|    \"ruamel-base==1.0.0\",\n108|    \"ruamel-yaml>=0.18.6,<0.19.0\",\n109|    \"scholarly==1.7.11\",\n110|    \"selenium-wire==5.1.0\",\n111|    \"spacy==3.8.14\",\n112|    \"en-core-web-sm @ https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.8.0/en_core_web_sm-3.8.0-py3-none-any.whl\",\n113|    \"slack-sdk==3.37.0\",\n114|    \"socksio==1.0.0\",\n115|    \"agentrun-sdk>=0.0.16,<1.0.0\",\n116|    \"nest-asyncio>=1.6.0,<2.0.0\",  # Needed for agent/component/message.py\n117|    \"sqlglotrs==0.9.0\",\n118|    \"tavily-python==0.5.1\",\n119|    \"tencentcloud-sdk-python==3.0.1478\",\n120|    \"tika==2.6.0\",\n121|    \"valkey==6.0.2\",\n122|    \"volcengine==1.0.194\",\n123|    \"voyageai==0.2.3\",\n124|    \"webdav4>=0.10.0,<0.11.0\",\n125|    \"webdriver-manager==4.0.1\",\n126|    \"wikipedia==1.4.0\",\n127|    \"word2number==1.1\",\n128|    \"xgboost==1.6.0\",\n129|    \"setuptools>=78.1.1,<81.0.0\",\n130|    \"xpinyin==0.7.6\",\n131|    \"yfinance==0.2.65\",\n132|    \"zhipuai==2.0.1\",\n133|    \"peewee>=3.17.1,<4.0.0\",\n134|    #    following modules aren't necessary\n135|    #    \"nltk==3.9.1\",\n136|    #    \"numpy>=1.26.0,<2.0.0\",\n137|    #    \"openai>=1.45.0\",\n138|    #    \"openpyxl>=3.1.0,<4.0.0\",\n139|    #    \"pandas>=2.2.0,<3.0.0\",\n140|    #    \"pillow>=12.2.0,<13.0.0\",\n141|    #    \"protobuf==5.27.2\",\n142|    #    \"pymysql>=1.1.1,<2.0.0\",\n143|    #    \"python-dotenv==1.0.1\",\n144|    #    \"python-dateutil==2.8.2\",\n145|    #    \"Quart==0.20.0\",\n146|    #    \"requests>=2.32.3,<3.0.0\",\n147|    #    \"scikit-learn==1.5.0\",\n148|    #    \"selenium==4.22.0\",\n149|    #    \"shapely==2.0.5\",\n150|    #    \"six==1.16.0\",\n151|    #    \"tabulate==0.9.0\",\n152|    #    \"tiktoken==0.7.0\",\n153|    #    \"umap_learn==0.5.6\",\n154|    #    \"werkzeug==3.0.6\",\n155|    #    \"xxhash>=3.5.0,<4.0.0\",\n156|    #    \"trio>=0.17.0,<0.29.0\",\n157|    #    \"click>=8.1.8\",\n158|    \"litellm~=1.82.0,!=1.82.7,!=1.82.8\",\n159|    #    \"pip>=25.2\",\n160|    #    \"imageio-ffmpeg>=0.6.0\",\n161|    #    \"cryptography==46.0.3\",\n162|    #    \"jinja2>=3.1.0\",\n163|    \"pyairtable>=3.3.0\",\n164|    \"pygithub>=2.8.1\",\n165|    \"asana>=5.2.2\",\n166|    \"python-gitlab>=7.0.0\",\n167|    \"alibabacloud-dingtalk>=2.0.0\",\n168|    \"quart-schema==0.23.0\",\n169|]\n170|\n171|[dependency-groups]\n172|test = [\n173|    \"hypothesis>=6.132.0\",\n174|    \"openpyxl>=3.1.5\",\n175|    \"pillow>=12.2.0,<13.0.0\",\n176|    \"pytest>=8.3.5\",\n177|    \"pytest-asyncio>=1.3.0\",\n178|    \"pytest-xdist>=3.8.0\",\n179|    \"pytest-cov>=7.0.0\",\n180|    \"python-docx>=1.1.2\",\n181|    \"python-pptx>=1.0.2\",\n182|    \"reportlab>=4.4.1\",\n183|    \"requests>=2.32.2\",\n184|    \"requests-toolbelt>=1.0.0\",\n185|    \"pycryptodomex==3.20.0\",\n186|    \"pytest-playwright>=0.7.2\",\n187|    \"codecov>=2.1.13\",\n188|]\n189|\n190|[tool.uv]\n191|constraint-dependencies = [\n192|    # CVE-2026-30922: Denial of Service via unbounded recursion in ASN.1 decoding (CVSS 7.5 HIGH)\n193|    # pyasn1 < 0.6.3 is vulnerable; pulled in transitively via google-auth / rsa / pyasn1-modules\n194|    \"pyasn1>=0.6.3\",\n195|    # Python 3.13 added pathlib.PurePath.parser as a public class attribute holding\n196|    # the posixpath/ntpath module. trio<0.26 introspects all Path class attributes to\n197|    # generate async forwards and raises TypeError on any non-callable attribute it\n198|    # encounters (fixed in trio 0.26 by skipping non-callables). Pulled in transitively\n199|    # via selenium-wire -> trio-websocket -> trio.\n200|    \"trio>=0.26.0\",\n201|]\n202|override-dependencies = [\n203|    # moodlepy<=0.24.1 pins attrs<23.0.0, but trio>=0.26.0 requires attrs>=23.2.0.\n204|    # attrs 23.x is backward-compatible; moodlepy works fine at runtime with it.\n205|    \"attrs>=23.2.0\",\n206|]\n207|# trio 0.26+ (Python 3.13 compatible) is not yet on the Aliyun mirror.\n208|# Mark PyPI as explicit so it is used only for packages listed in [tool.uv.sources].\n209|[[tool.uv.index]]\n210|name = \"pypi\"\n211|url = \"https://pypi.org/simple\"\n212|explicit = true\n213|\n214|[[tool.uv.index]]\n215|url = \"https://mirrors.aliyun.com/pypi/simple\"\n216|\n217|[tool.uv.sources]\n218|trio = [{ index = \"pypi\" }]\n219|\n220|[tool.setuptools]\n221|packages = [\n222|    'agent',\n223|    'api',\n224|    'deepdoc',\n225|    'graphrag',\n226|    'intergrations.chatgpt-on-wechat.plugins',\n227|    'mcp.server',\n228|    'rag',\n229|    'sdk.python.ragflow_sdk',\n230|]\n231|\n232|[tool.ruff]\n233|line-length = 200\n234|exclude = [\".venv\", \"rag/svr/discord_svr.py\"]\n235|\n236|[tool.ruff.lint]\n237|extend-select = [\"ASYNC\", \"ASYNC1\"]\n238|ignore = [\"E402\"]\n239|\n240|[tool.pytest.ini_options]\n241|pythonpath = [\n242|    \".\"\n243|]\n244|\n245|testpaths = [\"test\"]\n246|python_files = [\"test_*.py\"]\n247|python_classes = [\"Test*\"]\n248|python_functions = [\"test_*\"]\n249|\n250|markers = [\n251|    \"p0: critical priority test cases\",\n252|    \"p1: high priority test cases\",\n253|    \"p2: medium priority test cases\",\n254|    \"p3: low priority test cases\",\n255|    \"smoke: smoke test cases\",\n256|    \"auth: authentication UI tests\",\n257|    \"asyncio: mark test as async\",\n258|]\n259|\n260|# Test collection and runtime configuration\n261|asyncio_mode = \"auto\"\n262|asyncio_default_fixture_loop_scope = \"function\"\n263|filterwarnings = [\n264|    \"error\",  # Treat warnings as errors\n265|    \"ignore::DeprecationWarning\",  # Ignore specific warnings\n266|    \"ignore:pkg_resources is deprecated:UserWarning\",\n267|]\n268|\n269|# Command line options\n270|addopts = [\n271|    \"-v\",  # Verbose output\n272|    \"--strict-markers\",  # Enforce marker definitions\n273|    \"--tb=short\",  # Simplified traceback\n274|    \"--disable-warnings\",  # Disable warnings\n275|    \"--color=yes\",  # Colored output\n276|    \"-p\",\n277|    \"no:anyio\",  # anyio's pytest plugin conflicts with pytest-asyncio on Py3.13\n278|]\n279|\n280|\n281|# Coverage configuration\n282|[tool.coverage.run]\n283|# Source paths - adjust according to your project structure\n284|source = [\n285|    # \"../../api/db/services\",\n286|    # Add more directories if needed:\n287|    \"../../common\",\n288|    # \"../../utils\",\n289|]\n290|\n291|# Files/directories to exclude\n292|omit = [\n293|    \"*/tests/*\",\n294|    \"*/test_*\",\n295|    \"*/__pycache__/*\",\n296|    \"*/.pytest_cache/*\",\n297|    \"*/venv/*\",\n298|    \"*/.venv/*\",\n299|    \"*/env/*\",\n300|    \"*/site-packages/*\",\n301|    \"*/dist/*\",\n302|    \"*/build/*\",\n303|    \"*/migrations/*\",\n304|    \"setup.py\"\n305|]\n306|\n307|[tool.coverage.report]\n308|# Report configuration\n309|precision = 2\n310|show_missing = true\n311|skip_covered = false\n312|fail_under = 0  # Minimum coverage requirement (0-100)\n313|\n314|# Lines to exclude (optional)\n315|exclude_lines = [\n316|#    \"pragma: no cover\",\n317|#    \"def __repr__\",\n318|#    \"raise AssertionError\",\n319|#    \"raise NotImplementedError\",\n320|#    \"if __name__ == .__main__.:\",\n321|#    \"if TYPE_CHECKING:\",\n322|    \"pass\"\n323|]\n324|\n325|[tool.coverage.html]\n326|# HTML report configuration\n327|directory = \"htmlcov\"\n328|title = \"Test Coverage Report\"\n329|# extra_css = \"custom.css\"  # Optional custom CSS\n330|", "total_lines": 329, "file_size": 10023, "truncated": false, "is_binary": false, "is_image": false}


session_id: 20260530_230637_2fe223
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-94ecbc838270b734", "call_id": "chatcmpl-tool-94ecbc838270b734", "response_item_id": "fc_chatcmpl-tool-94ecbc838270b734", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"find /home/ice/ragflow -maxdepth 2 -type d | sort\"}"}}, {"id": "chatcmpl-tool-81edf1ab73fbf4c9", "call_id": "chatcmpl-tool-81edf1ab73fbf4c9", "response_item_id": "fc_chatcmpl-tool-81edf1ab73fbf4c9", "type": "function", "function": {"name": "search_files", "arguments": "{\"limit\": 20, \"output_mode\": \"files_only\", \"path\": \"/home/ice/ragflow\", \"pattern\": \"*.py\"}"}}]

reasoning:
  Good, I've cloned the repo and read key files. Let me explore the directory structure and some key source files to understand the architecture better.

reasoning_content:
  Good, I've cloned the repo and read key files. Let me explore the directory structure and some key source files to understand the architecture better.


session_id: 20260530_230637_2fe223
role: tool
tool_call_id: chatcmpl-tool-94ecbc838270b734
tool_name: terminal
content:
  {"output": "/home/ice/ragflow\n/home/ice/ragflow/.agents\n/home/ice/ragflow/.agents/rules\n/home/ice/ragflow/.agents/skills\n/home/ice/ragflow/.git\n/home/ice/ragflow/.git/branches\n/home/ice/ragflow/.git/hooks\n/home/ice/ragflow/.git/info\n/home/ice/ragflow/.git/logs\n/home/ice/ragflow/.git/objects\n/home/ice/ragflow/.git/refs\n/home/ice/ragflow/.github\n/home/ice/ragflow/.github/ISSUE_TEMPLATE\n/home/ice/ragflow/.github/workflows\n/home/ice/ragflow/admin\n/home/ice/ragflow/admin/client\n/home/ice/ragflow/admin/server\n/home/ice/ragflow/agent\n/home/ice/ragflow/agent/component\n/home/ice/ragflow/agent/plugin\n/home/ice/ragflow/agent/sandbox\n/home/ice/ragflow/agent/templates\n/home/ice/ragflow/agent/test\n/home/ice/ragflow/agent/tools\n/home/ice/ragflow/api\n/home/ice/ragflow/api/apps\n/home/ice/ragflow/api/common\n/home/ice/ragflow/api/db\n/home/ice/ragflow/api/utils\n/home/ice/ragflow/bin\n/home/ice/ragflow/cmd\n/home/ice/ragflow/common\n/home/ice/ragflow/common/data_source\n/home/ice/ragflow/common/doc_store\n/home/ice/ragflow/conf\n/home/ice/ragflow/conf/models\n/home/ice/ragflow/deepdoc\n/home/ice/ragflow/deepdoc/parser\n/home/ice/ragflow/deepdoc/vision\n/home/ice/ragflow/docker\n/home/ice/ragflow/docker/nginx\n/home/ice/ragflow/docker/oceanbase\n/home/ice/ragflow/docs\n/home/ice/ragflow/docs/administrator\n/home/ice/ragflow/docs/basics\n/home/ice/ragflow/docs/develop\n/home/ice/ragflow/docs/guides\n/home/ice/ragflow/docs/references\n/home/ice/ragflow/example\n/home/ice/ragflow/example/chat_demo\n/home/ice/ragflow/example/http\n/home/ice/ragflow/example/sdk\n/home/ice/ragflow/helm\n/home/ice/ragflow/helm/templates\n/home/ice/ragflow/internal\n/home/ice/ragflow/internal/admin\n/home/ice/ragflow/internal/binding\n/home/ice/ragflow/internal/cache\n/home/ice/ragflow/internal/cli\n/home/ice/ragflow/internal/common\n/home/ice/ragflow/internal/cpp\n/home/ice/ragflow/internal/dao\n/home/ice/ragflow/internal/engine\n/home/ice/ragflow/internal/entity\n/home/ice/ragflow/internal/handler\n/home/ice/ragflow/internal/ingestion\n/home/ice/ragflow/internal/proto\n/home/ice/ragflow/internal/router\n/home/ice/ragflow/internal/server\n/home/ice/ragflow/internal/service\n/home/ice/ragflow/internal/storage\n/home/ice/ragflow/internal/tokenizer\n/home/ice/ragflow/internal/utility\n/home/ice/ragflow/mcp\n/home/ice/ragflow/mcp/client\n/home/ice/ragflow/mcp/server\n/home/ice/ragflow/memory\n/home/ice/ragflow/memory/services\n/home/ice/ragflow/memory/utils\n/home/ice/ragflow/rag\n/home/ice/ragflow/rag/advanced_rag\n/home/ice/ragflow/rag/app\n/home/ice/ragflow/rag/flow\n/home/ice/ragflow/rag/graphrag\n/home/ice/ragflow/rag/llm\n/home/ice/ragflow/rag/nlp\n/home/ice/ragflow/rag/prompts\n/home/ice/ragflow/rag/res\n/home/ice/ragflow/rag/svr\n/home/ice/ragflow/rag/utils\n/home/ice/ragflow/sdk\n/home/ice/ragflow/sdk/python\n/home/ice/ragflow/test\n/home/ice/ragflow/test/benchmark\n/home/ice/ragflow/test/playwright\n/home/ice/ragflow/test/testcases\n/home/ice/ragflow/test/unit_test\n/home/ice/ragflow/tools\n/home/ice/ragflow/tools/chatgpt-on-wechat\n/home/ice/ragflow/tools/es-to-oceanbase-migration\n/home/ice/ragflow/tools/firecrawl\n/home/ice/ragflow/tools/scripts\n/home/ice/ragflow/web\n/home/ice/ragflow/web/.agents\n/home/ice/ragflow/web/.husky\n/home/ice/ragflow/web/.storybook\n/home/ice/ragflow/web/public\n/home/ice/ragflow/web/src", "exit_code": 0, "error": null}


session_id: 20260530_230637_2fe223
role: tool
tool_call_id: chatcmpl-tool-81edf1ab73fbf4c9
tool_name: search_files
content:
  {"total_count": 8, "files": ["/home/ice/ragflow/docs/develop/build_docker_image.mdx", "/home/ice/ragflow/pyproject.toml", "/home/ice/ragflow/api/apps/__init__.py", "/home/ice/ragflow/agent/sandbox/sandbox_spec.md", "/home/ice/ragflow/agent/sandbox/tests/pytest.ini", "/home/ice/ragflow/.rooignore", "/home/ice/ragflow/check_comment_ascii.py", "/home/ice/ragflow/tools/es-to-oceanbase-migration/pyproject.toml"]}


session_id: 20260530_230637_2fe223
role: assistant
finish_reason: tool_calls
reasoning: Let me search for more Python files by adjusting the search strategy.
reasoning_content: Let me search for more Python files by adjusting the search strategy.
tool_calls:
  [{"id": "chatcmpl-tool-9460b786a217cde0", "call_id": "chatcmpl-tool-9460b786a217cde0", "response_item_id": "fc_chatcmpl-tool-9460b786a217cde0", "type": "function", "function": {"name": "search_files", "arguments": "{\"limit\": 30, \"output_mode\": \"files_only\", \"path\": \"/home/ice/ragflow/rag\", \"pattern\": \"*.py\"}"}}, {"id": "chatcmpl-tool-9f098fdaa1ff4bb2", "call_id": "chatcmpl-tool-9f098fdaa1ff4bb2", "response_item_id": "fc_chatcmpl-tool-9f098fdaa1ff4bb2", "type": "function", "function": {"name": "search_files", "arguments": "{\"limit\": 30, \"output_mode\": \"files_only\", \"path\": \"/home/ice/ragflow/api\", \"pattern\": \"*.py\"}"}}, {"id": "chatcmpl-tool-a923243acd29a9f8", "call_id": "chatcmpl-tool-a923243acd29a9f8", "response_item_id": "fc_chatcmpl-tool-a923243acd29a9f8", "type": "function", "function": {"name": "search_files", "arguments": "{\"limit\": 30, \"output_mode\": \"files_only\", \"path\": \"/home/ice/ragflow/deepdoc\", \"pattern\": \"*.py\"}"}}]


session_id: 20260530_230637_2fe223
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-9d1a52437c4c114d", "call_id": "chatcmpl-tool-9d1a52437c4c114d", "response_item_id": "fc_chatcmpl-tool-9d1a52437c4c114d", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"ls -la /home/ice/ragflow/ && ls /home/ice/ragflow/rag/ && ls /home/ice/ragflow/agent/ && ls /home/ice/ragflow/api/\"}"}}]

reasoning:
  It seems the search_files didn't find many Python files because the repository might have a mixed structure. The `rag` and `deepdoc` directories have no Python files at the top level or maybe I need to search deeper. Wait, the pyproject.toml shows packages like 'rag', 'api', 'deepdoc', 'agent', etc. Let me explore deeper.

  Actually, looking at the file listing from find, `rag/`, `deepdoc/`, `agent/` etc have subdirectories like `rag/llm/`, `agent/component/`, but search_files `*.py` returned 0, 1, 0. This is odd. Maybe the files don't exist yet because there's a different structure? Or maybe I need to check if the clone was partial?

  Let me check actual files.

reasoning_content:
  It seems the search_files didn't find many Python files because the repository might have a mixed structure. The `rag` and `deepdoc` directories have no Python files at the top level or maybe I need to search deeper. Wait, the pyproject.toml shows packages like 'rag', 'api', 'deepdoc', 'agent', etc. Let me explore deeper.

  Actually, looking at the file listing from find, `rag/`, `deepdoc/`, `agent/` etc have subdirectories like `rag/llm/`, `agent/component/`, but search_files `*.py` returned 0, 1, 0. This is odd. Maybe the files don't exist yet because there's a different structure? Or maybe I need to check if the clone was partial?

  Let me check actual files.


session_id: 20260530_230637_2fe223
role: tool
tool_call_id: chatcmpl-tool-9d1a52437c4c114d
tool_name: terminal
content:
  {"output": "total 1050\ndrwxrwxr-x 25 ice ice      60 May 30 23:06 .\ndrwx------ 33 ice ice      39 May 30 23:06 ..\ndrwxrwxr-x  4 ice ice       4 May 30 23:06 .agents\ndrwxrwxr-x  8 ice ice      13 May 30 23:06 .git\n-rw-rw-r--  1 ice ice      61 May 30 23:06 .gitattributes\ndrwxrwxr-x  4 ice ice       6 May 30 23:06 .github\n-rw-rw-r--  1 ice ice    4022 May 30 23:06 .gitignore\n-rw-rw-r--  1 ice ice     470 May 30 23:06 .pre-commit-config.yaml\n-rw-rw-r--  1 ice ice    1336 May 30 23:06 .rooignore\n-rw-rw-r--  1 ice ice     145 May 30 23:06 .trivyignore\n-rw-rw-r--  1 ice ice    2763 May 30 23:06 AGENTS.md\n-rw-rw-r--  1 ice ice    3952 May 30 23:06 CLAUDE.md\n-rw-rw-r--  1 ice ice    9066 May 30 23:06 Dockerfile\n-rw-rw-r--  1 ice ice     514 May 30 23:06 Dockerfile.deps\n-rw-rw-r--  1 ice ice    1908 May 30 23:06 Dockerfile.scratch.oc9\n-rw-rw-r--  1 ice ice     985 May 30 23:06 Dockerfile_tei\n-rw-rw-r--  1 ice ice   11357 May 30 23:06 LICENSE\n-rw-rw-r--  1 ice ice   16962 May 30 23:06 README.md\n-rw-rw-r--  1 ice ice   20437 May 30 23:06 README_ar.md\n-rw-rw-r--  1 ice ice   18559 May 30 23:06 README_fr.md\n-rw-rw-r--  1 ice ice   16001 May 30 23:06 README_id.md\n-rw-rw-r--  1 ice ice   19380 May 30 23:06 README_ja.md\n-rw-rw-r--  1 ice ice   17920 May 30 23:06 README_ko.md\n-rw-rw-r--  1 ice ice   18303 May 30 23:06 README_pt_br.md\n-rw-rw-r--  1 ice ice   18428 May 30 23:06 README_tr.md\n-rw-rw-r--  1 ice ice   17569 May 30 23:06 README_tzh.md\n-rw-rw-r--  1 ice ice   17542 May 30 23:06 README_zh.md\n-rw-rw-r--  1 ice ice    1934 May 30 23:06 SECURITY.md\ndrwxrwxr-x  4 ice ice       5 May 30 23:06 admin\ndrwxrwxr-x  8 ice ice      12 May 30 23:06 agent\ndrwxrwxr-x  6 ice ice      11 May 30 23:06 api\ndrwxrwxr-x  2 ice ice       3 May 30 23:06 bin\n-rwxrwxr-x  1 ice ice    6597 May 30 23:06 build.sh\n-rw-rw-r--  1 ice ice    1301 May 30 23:06 check_comment_ascii.py\ndrwxrwxr-x  2 ice ice       6 May 30 23:06 cmd\n-rw-rw-r--  1 ice ice      51 May 30 23:06 codecov.yml\ndrwxrwxr-x  4 ice ice      32 May 30 23:06 common\ndrwxrwxr-x  3 ice ice      16 May 30 23:06 conf\ndrwxrwxr-x  4 ice ice       8 May 30 23:06 deepdoc\ndrwxrwxr-x  4 ice ice      17 May 30 23:06 docker\ndrwxrwxr-x  7 ice ice      11 May 30 23:06 docs\n-rw-rw-r--  1 ice ice    3906 May 30 23:06 download_deps.py\ndrwxrwxr-x  5 ice ice       5 May 30 23:06 example\n-rw-rw-r--  1 ice ice    6045 May 30 23:06 go.mod\n-rw-rw-r--  1 ice ice   35655 May 30 23:06 go.sum\ndrwxrwxr-x  3 ice ice       7 May 30 23:06 helm\ndrwxrwxr-x 20 ice ice      21 May 30 23:06 internal\ndrwxrwxr-x  4 ice ice       4 May 30 23:06 mcp\ndrwxrwxr-x  4 ice ice       5 May 30 23:06 memory\n-rw-rw-r--  1 ice ice   10023 May 30 23:06 pyproject.toml\ndrwxrwxr-x 12 ice ice      16 May 30 23:06 rag\n-rwxrwxr-x  1 ice ice     774 May 30 23:06 run_go_tests.sh\n-rwxrwxr-x  1 ice ice    9797 May 30 23:06 run_tests.py\ndrwxrwxr-x  3 ice ice       3 May 30 23:06 sdk\n-rw-rw-r--  1 ice ice    1822 May 30 23:06 show_env.sh\ndrwxrwxr-x  6 ice ice       8 May 30 23:06 test\n-rw-rw-r--  1 ice ice     243 May 30 23:06 test.py\ndrwxrwxr-x  6 ice ice       6 May 30 23:06 tools\n-rw-rw-r--  1 ice ice 1223581 May 30 23:06 uv.lock\ndrwxrwxr-x  7 ice ice      30 May 30 23:06 web\n__init__.py\nadvanced_rag\napp\nbenchmark.py\nflow\ngraphrag\nllm\nnlp\nprompts\nraptor.py\nres\nsettings.py\nsvr\nutils\n__init__.py\ncanvas.py\ncomponent\ndsl_migration.py\nplugin\nsandbox\nsettings.py\ntemplates\ntest\ntools\n__init__.py\napps\ncommon\nconstants.py\ndb\nragflow_server.py\nsettings.py\nutils\nvalidation.py", "exit_code": 0, "error": null}


session_id: 20260530_230637_2fe223
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-9dbbbc0f584e4208", "call_id": "chatcmpl-tool-9dbbbc0f584e4208", "response_item_id": "fc_chatcmpl-tool-9dbbbc0f584e4208", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"ls /home/ice/ragflow/rag/llm/ && echo \\\"---\\\" && ls /home/ice/ragflow/rag/flow/ && echo \\\"---\\\" && ls /home/ice/ragflow/rag/nlp/ | head -30\"}"}}, {"id": "chatcmpl-tool-aced5f246a1a3316", "call_id": "chatcmpl-tool-aced5f246a1a3316", "response_item_id": "fc_chatcmpl-tool-aced5f246a1a3316", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"ls /home/ice/ragflow/internal/ && echo \\\"---\\\" && ls /home/ice/ragflow/deepdoc/parser/ && echo \\\"---\\\" && ls /home/ice/ragflow/rag/graphrag/\"}"}}]

reasoning:
  Now I have a comprehensive view. Let me dig a bit deeper into the core components to understand the architecture better.

reasoning_content:
  Now I have a comprehensive view. Let me dig a bit deeper into the core components to understand the architecture better.


session_id: 20260530_230637_2fe223
role: tool
tool_call_id: chatcmpl-tool-9dbbbc0f584e4208
tool_name: terminal
content:
  {"output": "__init__.py\nchat_model.py\ncv_model.py\nembedding_model.py\nocr_model.py\nrerank_model.py\nsequence2txt_model.py\ntool_decorator.py\ntts_model.py\n---\n__init__.py\nbase.py\nchunker\nextractor\nfile.py\nparser\npipeline.py\ntests\ntokenizer\n---\n__init__.py\nquery.py\nrag_tokenizer.py\nsearch.py\nsurname.py\nsynonym.py\nterm_weight.py", "exit_code": 0, "error": null}


session_id: 20260530_230637_2fe223
role: tool
tool_call_id: chatcmpl-tool-aced5f246a1a3316
tool_name: terminal
content:
  {"output": "admin\nbinding\ncache\ncli\ncommon\ncpp\ndao\ndevelopment.md\nengine\nentity\nhandler\ningestion\nproto\nrouter\nserver\nservice\nstorage\ntokenizer\nutility\n---\n__init__.py\ndocling_parser.py\ndocx_parser.py\nepub_parser.py\nexcel_parser.py\nfigure_parser.py\nhtml_parser.py\njson_parser.py\nmarkdown_parser.py\nmineru_parser.py\nopendataloader_parser.py\npaddleocr_parser.py\npdf_parser.py\nppt_parser.py\nresume\ntcadp_parser.py\ntxt_parser.py\nutils.py\n---\n__init__.py\nentity_resolution.py\nentity_resolution_prompt.py\ngeneral\nlight\nner\nphase_markers.py\nquery_analyze_prompt.py\nsearch.py\nutils.py", "exit_code": 0, "error": null}


session_id: 20260530_230637_2fe223
role: assistant
finish_reason: stop
content:
  ## Análise do Repositório RAGFlow

  Clonado em `/home/ice/ragflow`. Aqui está o resumo:

  ---

  ### Problema
  O RAGFlow resolve um problema fundamental e persistente em IA generativa: **perguntas a LLMs com base em documentos reais frequentemente geram alucinações, respostas sem fundamento e baixa precisão**, porque o LLM não "entende" profundamente documentos complexos e não consegue rastrear respostas a trechos específicos. Sistemas tradicionais de RAG fazem chunking ingênuo, perdem contexto e não oferecem citações verificáveis.

  ---

  ### Tema
  **Motor RAG (Retrieval-Augmented Generation) + Agent** de código aberto para uso empresarial. Foco em:
  - Compreensão profunda de documentos (deep document understanding)
  - Workflow RAG completo e automatizado
  - Agentes com raciocínio (agentic reasoning) e memória
  - Multi-modalidade (texto, imagem, PDF escaneado, planilhas, etc.)

  ---

  ### Razão do Hype
  1. **Qualidade de chunks**: Chunking inteligente e explicável, com visualização — o usuário pode validar o que o RAG "vê"
  2. **Rastreabilidade**: Citações grounded, reduz alucinações — diferencial forte frente a concorrentes genéricos
  3. **Multi-fonte**: Suporta desde PDFs escaneados (OCR) até Confluence, S3, Notion, Google Drive, Discord
  4. **Agentes prontos**: Templates de agentes, MCP (Model Context Protocol), code executor (sandbox), browser-use
  5. **Multi-LLM**: Suporta praticamente todos os provedores (OpenAI, Anthropic, Gemini, DeepSeek, Groq, Ollama, modelos chineses, etc.) via LiteLLM
  6. **Hybrid search + reranking**: Vetores + busca lexical + reranker para máxima recuperação
  7. **GraphRAG / Entity Resolution**: Recursos avançados de grafo de conhecimento
  8. **Self-hosted + cloud**: Pode rodar com Docker Compose completo ou usar o cloud em cloud.ragflow.io
  9. **81K+ estrelas**: Adoção massiva, comunidade ativa, roadmap público
  10. **Full-stack aberto**: Web app React/UmiJS + SDK Python/JS + backend Python completo

  ---

  ### Tecnologias

  #### Backend
  | Camada | Tech |
  |---|---|
  | Linguagem | Python 3.13+ |
  | Web Framework | Flask / Quart (async) |
  | Vector DB | Infinity, OpenSearch |
  | Relacional | MySQL, PostgreSQL, OceanBase |
  | Cache/Fila | Valkey (Redis fork), MinIO |
  | ORM | Peewee (legado), sqlglotrs |
  | Agent/MCP | `mcp` library, LiteLLM (~1.82), browser-use |
  | Agent Tools | crawl4ai, Chrome via selenium/mini-racer, Tavily, DDG, Wikipedia |
  | LLM/Embedding/Rerank | Wrappers próprios + LiteLLM + Voyage AI + Cohere + infinity-emb |
  | Document Parsing | MinerU, Docling, PaddleOCR, pdfplumber, pypdf, python-docx, python-pptx, pypandoc, Tlika, OpenDataLoader |
  | Visão/OCR | OpenCV (`opencv-python`), OCR próprio em `deepdoc/vision/` |
  | NLP | spaCy (en-core-web-sm), graphrag, graspologic, xgboost |
  | Graph/Knowledge | GraphRAG, entity resolution |
  | Storage multi-cloud | OpenDAL, MinIO, S3, Azure Blob, GCS, WebDAV, Dropbox, Box |

  #### Frontend
  | Tech | Uso |
  |---|---|
  | TypeScript / React | Interface principal |
  | UmiJS | Framework/framework de app |
  | react-player, etc. | Visualização e multimídia |

  #### DevOps / Infra
  - Docker Compose (orchestração de ~10+ serviços)
  - gVisor (sandbox para code executor)
  - Go (serviços internos auxiliares — tem `go.mod`)
  - Helm charts para Kubernetes
  - `uv` para gerenciamento de dependências Python
  - Ruff para linting/formatting
  - Pre-commit hooks
  - pytest + pytest-playwright (testes E2E)

  ---

  ### Observações adicionais
  - O repo tem **camada Go** (`cmd/`, `internal/` com proto, engine, cpp) além do Python, sugerindo componentes de alto desempenho para ingestão/engine
  - Suporte a **cross-language query** (consulta em diferente idioma do documento)
  - Integrações extensas: Jira, Slack, Discord, Confluence, Google Workspace, Salesforce (pyairtable), GitHub, GitLab, Asana, Moodle, etc.
  - **Versão atual**: 0.25.6 (em desenvolvimento rápido — atualizações mensais listadas no README)

reasoning:
  Now I have enough information to compile a comprehensive analysis. Let me synthesize what I've found:

  1. **Repository**: infiniflow/ragflow
  2. **Language**: Python (full-stack: Python backend + React/TypeScript frontend)
  3. **Version**: 0.25.6
  4. **Stars**: 81,564 (given in context)

  **Structure and Technologies:**

  Backend (Python 3.13+):
  - API server: Flask/Quart (api/)
  - Core RAG: rag/ (advanced_rag, flow, graphrag, llm, nlp, prompts, svr, utils)
  - Agent: agent/ (component, plugin, sandbox, templates, tools)
  - Document parsing: deepdoc/ (parser, vision)
  - Internal services: internal/ (admin, binding, cache, dao, engine, ingestion, proto, server, service, storage, tokenizer)
  - MCP server: mcp/
  - Memory: memory/

  Key dependencies (from pyproject.toml):
  - Flask/Quart for web server
  - Multi-modal LLM support: OpenAI, Anthropic, Google, Mistral, Groq, Ollama, Azure, Baidu (qianfan), Alibaba (dashscope), Tencent, Moonshot (zhipuai), Cohere, Voyage AI, Replicate
  - Embedding: infinity-sdk, infinity-emb, Voyage AI, etc.
  - Reranking: Jina reranker, Cohere rerank, etc.
  - Document parsing: MinerU, Docling, PaddleOCR, pdfplumber, pypdf, python-docx, python-pptx, mammoth, opendal


  - Vector stores: Infinity, OpenSearch, PostgreSQL/pgvector (pyobvector)
  - Databases: MySQL, PostgreSQL (psycopg2)
  - Storage: MinIO, S3 (boto3), Azure Blob, GCS, WebDAV
  - Agent tools: browser-use, crawl4ai, duckduckgo-search, tavily, wikipedia, scholarly
  - MCP: Model Context Protocol integration (mcp>=1.19.0)
  - LiteLLM for unified LLM interface (~1.82.0)
  - NLP: spaCy, graphrag, graspologic
  - Graph processing: xgboost, ranx (ranking evaluation)
  - Agent capabilities: code executor sandbox, browser automation, MCP integration

  The platform offers comprehensive RAG functionality with deep document understanding through multiple parsing options, intelligent chunking with human visualization, agentic workflows with memory, multi-modal support, and broad integration with major LLM providers and calling conventions.

reasoning_content:
  Now I have enough information to compile a comprehensive analysis. Let me synthesize what I've found:

  1. **Repository**: infiniflow/ragflow
  2. **Language**: Python (full-stack: Python backend + React/TypeScript frontend)
  3. **Version**: 0.25.6
  4. **Stars**: 81,564 (given in context)

  **Structure and Technologies:**

  Backend (Python 3.13+):
  - API server: Flask/Quart (api/)
  - Core RAG: rag/ (advanced_rag, flow, graphrag, llm, nlp, prompts, svr, utils)
  - Agent: agent/ (component, plugin, sandbox, templates, tools)
  - Document parsing: deepdoc/ (parser, vision)
  - Internal services: internal/ (admin, binding, cache, dao, engine, ingestion, proto, server, service, storage, tokenizer)
  - MCP server: mcp/
  - Memory: memory/

  Key dependencies (from pyproject.toml):
  - Flask/Quart for web server
  - Multi-modal LLM support: OpenAI, Anthropic, Google, Mistral, Groq, Ollama, Azure, Baidu (qianfan), Alibaba (dashscope), Tencent, Moonshot (zhipuai), Cohere, Voyage AI, Replicate
  - Embedding: infinity-sdk, infinity-emb, Voyage AI, etc.
  - Reranking: Jina reranker, Cohere rerank, etc.
  - Document parsing: MinerU, Docling, PaddleOCR, pdfplumber, pypdf, python-docx, python-pptx, mammoth, opendal


  - Vector stores: Infinity, OpenSearch, PostgreSQL/pgvector (pyobvector)
  - Databases: MySQL, PostgreSQL (psycopg2)
  - Storage: MinIO, S3 (boto3), Azure Blob, GCS, WebDAV
  - Agent tools: browser-use, crawl4ai, duckduckgo-search, tavily, wikipedia, scholarly
  - MCP: Model Context Protocol integration (mcp>=1.19.0)
  - LiteLLM for unified LLM interface (~1.82.0)
  - NLP: spaCy, graphrag, graspologic
  - Graph processing: xgboost, ranx (ranking evaluation)
  - Agent capabilities: code executor sandbox, browser automation, MCP integration

  The platform offers comprehensive RAG functionality with deep document understanding through multiple parsing options, intelligent chunking with human visualization, agentic workflows with memory, multi-modal support, and broad integration with major LLM providers and calling conventions.


session_id: 20260530_230735_8b01b4
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-8f2659d7a5bbd82b", "call_id": "chatcmpl-tool-8f2659d7a5bbd82b", "response_item_id": "fc_chatcmpl-tool-8f2659d7a5bbd82b", "type": "function", "function": {"name": "terminal", "arguments": "{\"background\": true, \"command\": \"cd /home/ice && git clone --depth=1 https://github.com/langflow-ai/langflow.git\", \"notify_on_complete\": true}"}}]

reasoning:
  The user wants me to analyze the repository `langflow-ai/langflow`. I need to:
  1. Clone the repository
  2. Analyze it
  3. Return: Problema (Problem), Tema (Theme), Razão hype (Hype reason), Tecnologias (Technologies)

  Let me start by cloning the repository.

reasoning_content:
  The user wants me to analyze the repository `langflow-ai/langflow`. I need to:
  1. Clone the repository
  2. Analyze it
  3. Return: Problema (Problem), Tema (Theme), Razão hype (Hype reason), Tecnologias (Technologies)

  Let me start by cloning the repository.


session_id: 20260530_230735_8b01b4
role: tool
tool_call_id: chatcmpl-tool-8f2659d7a5bbd82b
tool_name: terminal
content:
  {"output": "Background process started", "session_id": "proc_02065b774888", "pid": 8555, "exit_code": 0, "error": null, "notify_on_complete": true}


session_id: 20260530_230735_8b01b4
role: assistant
finish_reason: tool_calls
reasoning: O clone está em andamento. Vou esperar ele terminar e depois explorar o repositório.
reasoning_content: O clone está em andamento. Vou esperar ele terminar e depois explorar o repositório.
tool_calls:
  [{"id": "chatcmpl-tool-a9247bee939273d9", "call_id": "chatcmpl-tool-a9247bee939273d9", "response_item_id": "fc_chatcmpl-tool-a9247bee939273d9", "type": "function", "function": {"name": "process", "arguments": "{\"action\": \"wait\", \"session_id\": \"proc_02065b774888\", \"timeout\": 120}"}}]


session_id: 20260530_230735_8b01b4
role: tool
tool_call_id: chatcmpl-tool-a9247bee939273d9
tool_name: process
content:
  {"status": "exited", "exit_code": 0, "output": "Cloning into 'langflow'...\n", "timeout_note": "Requested wait of 120s was clamped to configured limit of 60s"}


session_id: 20260530_230735_8b01b4
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-ae818aa7bdd68061", "call_id": "chatcmpl-tool-ae818aa7bdd68061", "response_item_id": "fc_chatcmpl-tool-ae818aa7bdd68061", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"cd /home/ice/langflow && ls -la\"}"}}, {"id": "chatcmpl-tool-ab81524ae581263a", "call_id": "chatcmpl-tool-ab81524ae581263a", "response_item_id": "fc_chatcmpl-tool-ab81524ae581263a", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\": \"/home/ice/langflow/README.md\", \"limit\": 120}"}}]

reasoning:
  The clone completed. Now let's inspect the repository contents, especially focusing on key metadata and descriptions.

reasoning_content:
  The clone completed. Now let's inspect the repository contents, especially focusing on key metadata and descriptions.


session_id: 20260530_230735_8b01b4
role: tool
tool_call_id: chatcmpl-tool-ae818aa7bdd68061
tool_name: terminal
content:
  {"output": "total 1695\ndrwxrwxr-x 15 ice ice      45 May 30 23:07 .\ndrwx------ 36 ice ice      42 May 30 23:07 ..\ndrwxrwxr-x  3 ice ice       3 May 30 23:07 .agents\n-rw-rw-r--  1 ice ice    6046 May 30 23:07 .coderabbit.yaml\n-rw-rw-r--  1 ice ice       3 May 30 23:07 .composio.lock\ndrwxrwxr-x  2 ice ice       3 May 30 23:07 .cursor\ndrwxrwxr-x  2 ice ice       5 May 30 23:07 .devcontainer\n-rw-rw-r--  1 ice ice     219 May 30 23:07 .dockerignore\n-rw-rw-r--  1 ice ice    5403 May 30 23:07 .env.example\n-rw-rw-r--  1 ice ice    2079 May 30 23:07 .eslintrc.json\ndrwxrwxr-x  8 ice ice      14 May 30 23:07 .git\n-rw-rw-r--  1 ice ice     673 May 30 23:07 .gitattributes\ndrwxrwxr-x  5 ice ice      10 May 30 23:07 .github\n-rw-rw-r--  1 ice ice    4214 May 30 23:07 .gitignore\n-rw-rw-r--  1 ice ice    3258 May 30 23:07 .pre-commit-config.yaml\n-rw-rw-r--  1 ice ice  303095 May 30 23:07 .secrets.baseline\ndrwxrwxr-x  2 ice ice       4 May 30 23:07 .vscode\n-rw-rw-r--  1 ice ice     209 May 30 23:07 .whitesource\n-rw-rw-r--  1 ice ice   21243 May 30 23:07 AGENTS-example.md\n-rw-rw-r--  1 ice ice    6828 May 30 23:07 AGENTS.md\n-rw-rw-r--  1 ice ice     289 May 30 23:07 CLAUDE.md\n-rw-rw-r--  1 ice ice    5220 May 30 23:07 CODE_OF_CONDUCT.md\n-rw-rw-r--  1 ice ice    1405 May 30 23:07 CONTRIBUTING.md\n-rw-rw-r--  1 ice ice   30552 May 30 23:07 DESIGN.md\n-rw-rw-r--  1 ice ice   14075 May 30 23:07 DEVELOPMENT.md\n-rw-rw-r--  1 ice ice    1065 May 30 23:07 LICENSE\n-rw-rw-r--  1 ice ice   48966 May 30 23:07 Makefile\n-rw-rw-r--  1 ice ice   12375 May 30 23:07 Makefile.frontend\n-rw-rw-r--  1 ice ice    4729 May 30 23:07 README.md\n-rw-rw-r--  1 ice ice    4782 May 30 23:07 RELEASE.md\n-rw-rw-r--  1 ice ice    1051 May 30 23:07 SECURITY.md\n-rw-rw-r--  1 ice ice   13288 May 30 23:07 ci-skip-analysis.md\n-rw-rw-r--  1 ice ice    4154 May 30 23:07 codecov.yml\ndrwxrwxr-x  2 ice ice       8 May 30 23:07 deploy\ndrwxrwxr-x  3 ice ice      17 May 30 23:07 docker\ndrwxrwxr-x  2 ice ice       7 May 30 23:07 docker_example\ndrwxrwxr-x 12 ice ice      26 May 30 23:07 docs\n-rw-rw-r--  1 ice ice     889 May 30 23:07 package-lock.json\n-rw-rw-r--  1 ice ice      60 May 30 23:07 package.json\n-rw-rw-r--  1 ice ice   16026 May 30 23:07 pyproject.toml\n-rw-rw-r--  1 ice ice     682 May 30 23:07 render.yaml\ndrwxrwxr-x  9 ice ice      22 May 30 23:07 scripts\ndrwxrwxr-x  6 ice ice       6 May 30 23:07 src\ndrwxrwxr-x  2 ice ice       3 May 30 23:07 test-results\n-rw-rw-r--  1 ice ice 2846118 May 30 23:07 uv.lock", "exit_code": 0, "error": null}

  [Subdirectory context discovered: langflow/AGENTS.md]
  # AGENTS.md

  Guidance for AI coding agents working in this repository.

  > **Before you write code, read [docs/agents/PHILOSOPHY.md](./docs/agents/PHILOSOPHY.md).** Most off-narrative work comes from skipping it.

  ## What Langflow is

  Langflow is a **visual flow builder first**. Users drag components onto a canvas, wire them together, and either run the resulting flow in the Playground, deploy it as an API, or expose it as an MCP server. Saved flows are persistent JSON artifacts running in production — backwards compatibility for components is non-negotiable.

  The repo is three Python packages and one frontend:

  - **`lfx`** (`src/lfx/`): the executor core. Component base classes, the graph engine, and built-in components live here. Should not depend on `langflow` or `langflow-base` — see [docs/agents/ARCHITECTURE.md](./docs/agents/ARCHITECTURE.md) for the ~14 known violations to fix-not-extend.
  - **`langflow-base`** (`src/backend/base/langflow/`): the platform. FastAPI routes, auth, persistence, alembic, services. May import `lfx`.
  - **`langflow`**: the integration distribution that ships everything together.
  - **`frontend`** (`src/frontend/`): React 19 + TypeScript + Vite + Zustand + `@xyflow/react`. Talks to the backend over HTTP/WebSocket only.

  Dependencies flow one way: `frontend → langflow → langflow-base → lfx`. See [docs/agents/ARCHITECTURE.md](./docs/agents/ARCHITECTURE.md).

  ## Non-negotiable tenets

  These are extracted from [PHILOSOPHY.md](./docs/agents/PHILOSOPHY.md). The full file has the rest; these are the ones every change must respect.

  1. **Flows are user artifacts.** Component class names, `name` attributes, input/output names, and input types are frozen once shipped. Mark old components `legacy=True` instead of editing.
  2. **Every backend feature must land on the canvas.** If it can't be a component or a property of one, it's an SDK feature and belongs in `lfx`, not `langflow-base`.
  3. **Components are the unit of work.** Don't add a route, store, or service unless a component or UI page consumes it.
  4. **Visible data flow beats clever magic.** Pass data through inputs and outputs. No hidden globals or side-channel state.
  5. **Composition over capability.** One job per component. Split before you add a tenth input.
  6. **It is not a fix without evidence.** Adding error handling, retries, type widening, or skipping a flaky test does not constitute a fix.

  ## Documentation map

  Read the file that matches your task before you write code.

  | Topic | File | When to read |
  |---|---|---|
  | Project story, design tenets | [docs/agents/PHILOSOPHY.md](./docs/agents/PHILOSOPHY.md) | Before any non-trivial change |
  | Package boundaries, where code goes, API versioning | [docs/agents/ARCHITECTURE.md](./docs/agents/ARCHITECTURE.md) | Before adding a file or endpoint |
  | Component dev: scope, breaking changes, conventions, icons | [docs/agents/COMPONENTS.md](./docs/agents/COMPONENTS.md) | Before adding or editing a component |
  | User-facing contracts: flow JSON, REST API, MCP, env vars | [docs/agents/CONTRACTS.md](./docs/agents/CONTRACTS.md) | Before changing anything user-visible |
  | Test patterns, fixtures, mocking policy | [docs/agents/TESTING.md](./docs/agents/TESTING.md) | Before writing or changing tests |
  | Don't/do rules, "fixes that aren't," before-claiming-done checklist | [docs/agents/ANTI-PATTERNS.md](./docs/agents/ANTI-PATTERNS.md) | Before claiming work is done |

  ## Prerequisites

  - **Python:** 3.10–3.13
  - **uv:** ≥0.4 (always use `uv run` for Python commands)
  - **Node.js:** ≥20.19.0 (v22.12 LTS recommended)
  - **npm:** v10.9+
  - **make:** for build coordination

  ## Common commands

  ### Development setup

  ```bash
  make init              # Install all dependencies + pre-commit hooks
  make run_cli           # Build and run Langflow (http://localhost:7860)
  make run_clic          # Clean build and run (use when frontend issues occur)
  ```

  ### Development mode (hot reload)

  ```bash
  make backend           # FastAPI on port 7860 (terminal 1)
  make frontend          # Vite dev server on port 3000 (terminal 2)
  ```

  For component development with dynamic loading:

  ```bash
  LFX_DEV=1 make backend                    # Load all components dynamically
  LFX_DEV=mistral,openai make backend       # Load only specific modules
  ```

  ### Code quality

  ```bash
  make format_backend    # Format Python (ruff) — run FIRST before lint
  make format_frontend   # Format TypeScript (biome)
  make format            # Both
  make lint              # mypy type checking
  ```

  ### Testing

  ```bash
  make unit_tests                            # Backend unit tests (pytest, parallel)
  make unit_tests async=false                # Sequential
  uv run pytest path/to/test.py              # Single test file
  uv run pytest path/to/test.py::test_name   # Single test

  make test_frontend                         # Jest unit tests
  make tests_frontend                        # Playwright e2e tests

  # lfx tests specifically — run uv sync inside src/lfx (not src/lfx/src/lfx)
  cd src/lfx && uv sync && uv run pytest

  # Sub-package tests (langflow-base, lfx) — sync that package's dev group first,
  # otherwise dev-only deps like fakeredis stay uninstalled.
  uv sync --group dev --package langflow-base
  ```

  See [docs/agents/TESTING.md](./docs/agents/TESTING.md) for fixtures, base classes, and the graph testing pattern.

  ### Database migrations

  ```bash
  make alembic-revision message="Description"  # Create migration
  make alembic-upgrade                          # Apply migrations
  make alembic-downgrade                        # Rollback one version
  ```

  Never edit a past migration. Run `test_database.py` sequentially after any DB change.

  ### Version management

  ```bash
  make patch v=1.5.0  # Update version across all packages
  ```

  ## Pre-commit workflow

  Pre-commit hooks run ruff and biome automatically on `git commit`, so manual formatting isn't required. To avoid an extra commit cycle:

  1. Run `make format_backend` once before staging — fixes most ruff issues up front.
  2. Run `uv run git commit` (the `uv run` ensures pre-commit finds the right Python).
  3. If you touched backend code, run `make unit_tests` locally for faster feedback than CI.

  ## Pull request guidelines

  - Follow [semantic commit conventions](https://www.conventionalcommits.org/).
  - Reference issues fixed (`Fixes #1234`).
  - Target the active `release-X.Y.Z` branch, not `main`. See [CONTRIBUTING.md](./CONTRIBUTING.md).
  - Don't push or open PRs without explicit user direction.
  - No "Generated with Claude Code" / `Co-Authored-By: Claude` trailers.
  - No test-plan checklists or Jira links in PR descriptions.

  ## Documentation

  Documentation uses Docusaurus and lives in `docs/`:

  ```bash
  cd docs
  yarn install
  yarn start        # Dev server on port 3000 (3001 if 3000 is in use)
  ```


session_id: 20260530_230735_8b01b4
role: tool
tool_call_id: chatcmpl-tool-ab81524ae581263a
tool_name: read_file
content:
  {"content": "1|<!-- markdownlint-disable MD030 -->\n2|\n3|<picture>\n4|  <source media=\"(prefers-color-scheme: dark)\" srcset=\"./docs/static/img/langflow-logo-color-blue-bg.svg\">\n5|  <img src=\"./docs/static/img/langflow-logo-color-black-solid.svg\" alt=\"Langflow logo\">\n6|</picture>\n7|\n8|[![Release Notes](https://img.shields.io/github/release/langflow-ai/langflow?style=flat-square)](https://github.com/langflow-ai/langflow/releases)\n9|[![PyPI - License](https://img.shields.io/badge/license-MIT-orange)](https://opensource.org/licenses/MIT)\n10|[![PyPI - Downloads](https://img.shields.io/pypi/dm/langflow?style=flat-square)](https://pypistats.org/packages/langflow)\n11|[![Twitter](https://img.shields.io/twitter/url/https/twitter.com/langflow-ai.svg?style=social&label=Follow%20%40Langflow)](https://twitter.com/langflow_ai)\n12|[![YouTube Channel](https://img.shields.io/youtube/channel/subscribers/UCn2bInQrjdDYKEEmbpwblLQ?label=Subscribe)](https://www.youtube.com/@Langflow)\n13|[![Discord Server](https://img.shields.io/discord/1116803230643527710?logo=discord&style=social&label=Join)](https://discord.gg/EqksyE2EX9)\n14|[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langflow-ai/langflow)\n15|\n16|[Langflow](https://langflow.org) is a powerful platform for building and deploying AI-powered agents and workflows. It provides developers with both a visual authoring experience and built-in API and MCP servers that turn every workflow into a tool that can be integrated into applications built on any framework or stack. Langflow comes with batteries included and supports all major LLMs, vector databases and a growing library of AI tools.\n17|\n18|## ✨ Highlight features\n19|\n20|- **Visual builder interface** to quickly get started and iterate.\n21|- **Source code access** lets you customize any component using Python.\n22|- **Interactive playground** to immediately test and refine your flows with step-by-step control.\n23|- **Multi-agent orchestration** with conversation management and retrieval.\n24|- **Deploy as an API** or export as JSON for Python apps.\n25|- **Deploy as an MCP server** and turn your flows into tools for MCP clients.\n26|- **Observability** with LangSmith, LangFuse and other integrations.\n27|- **Enterprise-ready** security and scalability.\n28|\n29|## 🖥️  Langflow Desktop\n30|\n31|Langflow Desktop is the easiest way to get started with Langflow. All dependencies are included, so you don't need to manage Python environments or install packages manually.\n32|Available for Windows and macOS.\n33|\n34|[📥 Download Langflow Desktop](https://www.langflow.org/desktop)\n35|\n36|## ⚡️ Quickstart\n37|\n38|### Install locally (recommended)\n39|\n40|Requires Python 3.10–3.13 and [uv](https://docs.astral.sh/uv/getting-started/installation/) (recommended package manager).\n41|\n42|#### Install\n43|\n44|From a fresh directory, run:\n45|```shell\n46|uv pip install langflow -U\n47|```\n48|\n49|The latest Langflow package is installed.\n50|For more information, see [Install and run the Langflow OSS Python package](https://docs.langflow.org/get-started-installation#install-and-run-the-langflow-oss-python-package).\n51|\n52|#### Run\n53|\n54|To start Langflow, run:\n55|```shell\n56|uv run langflow run\n57|```\n58|\n59|Langflow starts at http://127.0.0.1:7860.\n60|\n61|That's it! You're ready to build with Langflow! 🎉\n62|\n63|## 📦 Other install options\n64|\n65|### Run from source\n66|If you've cloned this repository and want to contribute, run this command from the repository root:\n67|```shell\n68|make run_cli\n69|```\n70|For more information, see [DEVELOPMENT.md](./DEVELOPMENT.md).\n71|\n72|### Docker\n73|Start a Langflow container with default settings:\n74|```shell\n75|docker run -p 7860:7860 langflowai/langflow:latest\n76|```\n77|Langflow is available at http://localhost:7860/.\n78|For configuration options, see the [Docker deployment guide](https://docs.langflow.org/deployment-docker).\n79|\n80|## 🛡️ Security\n81|\n82|For security information, see our [Security Policy](./SECURITY.md).\n83|\n84|## 🚀 Deployment\n85|\n86|Langflow is completely open source and you can deploy it to all major deployment clouds. To learn how to deploy Langflow, see our [Langflow deployment guides](https://docs.langflow.org/deployment-overview).\n87|\n88|## ⭐ Stay up-to-date\n89|\n90|Star Langflow on GitHub to be instantly notified of new releases.\n91|\n92|![Star Langflow](https://github.com/user-attachments/assets/03168b17-a11d-4b2a-b0f7-c1cce69e5a2c)\n93|\n94|## 👋 Contribute\n95|\n96|We welcome contributions from developers of all levels. If you'd like to contribute, please check our [contributing guidelines](./CONTRIBUTING.md) and help make Langflow more accessible.\n97|\n98|---\n99|\n100|[![Star History Chart](https://api.star-history.com/svg?repos=langflow-ai/langflow&type=Timeline)](https://star-history.com/#langflow-ai/langflow&Date)\n101|\n102|## ❤️ Contributors\n103|\n104|[![langflow contributors](https://contrib.rocks/image?repo=langflow-ai/langflow)](https://github.com/langflow-ai/langflow/graphs/contributors)\n105|", "total_lines": 104, "file_size": 4729, "truncated": false, "is_binary": false, "is_image": false}


session_id: 20260530_230735_8b01b4
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-844298be8068142f", "call_id": "chatcmpl-tool-844298be8068142f", "response_item_id": "fc_chatcmpl-tool-844298be8068142f", "type": "function", "function": {"name": "read_file", "arguments": "{\"limit\": 200, \"path\": \"/home/ice/langflow/pyproject.toml\"}"}}, {"id": "chatcmpl-tool-9e52936e41d723dc", "call_id": "chatcmpl-tool-9e52936e41d723dc", "response_item_id": "fc_chatcmpl-tool-9e52936e41d723dc", "type": "function", "function": {"name": "read_file", "arguments": "{\"limit\": 80, \"path\": \"/home/ice/langflow/src/frontend/package.json\"}"}}]

reasoning:
  I have cloned the repo, but only read the top-level README. I need more than that for the requested analysis: problem, theme, hype reason, technologies. But from that and the AGENTS.md, I already know a lot.

  I should get a bit more specific:
  - search for tech stack hints in pyproject.toml (dependencies)
  - inspect frontend/package.json for frontend tech stack
  - peek docs/agents/PHILOSOPHY.md or docs maybe not needed but could enrich "theme"/hype

  Then I can return a concise summary in Portuguese, since the request appears in Portuguese ("Analisar repositório"). Actually the request is in Portuguese. The user asked: "Analise e retorne: Problema, Tema, Razão hype, Tecnologias". So they want an analysis in Portuguese. I'll produce that concise output.

  I'll inspect pyproject.toml for Python deps and look at frontend directory if exists. The repo is monorepo/mixed: src/ is Python. Let's read pyproject.toml.

reasoning_content:
  I have cloned the repo, but only read the top-level README. I need more than that for the requested analysis: problem, theme, hype reason, technologies. But from that and the AGENTS.md, I already know a lot.

  I should get a bit more specific:
  - search for tech stack hints in pyproject.toml (dependencies)
  - inspect frontend/package.json for frontend tech stack
  - peek docs/agents/PHILOSOPHY.md or docs maybe not needed but could enrich "theme"/hype

  Then I can return a concise summary in Portuguese, since the request appears in Portuguese ("Analisar repositório"). Actually the request is in Portuguese. The user asked: "Analise e retorne: Problema, Tema, Razão hype, Tecnologias". So they want an analysis in Portuguese. I'll produce that concise output.

  I'll inspect pyproject.toml for Python deps and look at frontend directory if exists. The repo is monorepo/mixed: src/ is Python. Let's read pyproject.toml.


session_id: 20260530_230735_8b01b4
role: tool
tool_call_id: chatcmpl-tool-844298be8068142f
tool_name: read_file
content:
  {"content": "1|[project]\n2|name = \"langflow\"\n3|version = \"1.9.4\"\n4|description = \"A Python package with a built-in web application\"\n5|requires-python = \">=3.10,<3.15\"\n6|license = \"MIT\"\n7|keywords = [\"nlp\", \"langchain\", \"openai\", \"gpt\", \"gui\"]\n8|readme = \"README.md\"\n9|maintainers = [\n10|    { name = \"Carlos Coelho\", email = \"carlos@langflow.org\" },\n11|    { name = \"Cristhian Zanforlin\", email = \"cristhian.lousa@gmail.com\" },\n12|    { name = \"Gabriel Almeida\", email = \"gabriel@langflow.org\" },\n13|    { name = \"Lucas Eduoli\", email = \"lucaseduoli@gmail.com\" },\n14|    { name = \"Otávio Anovazzi\", email = \"otavio2204@gmail.com\" },\n15|    { name = \"Rodrigo Nader\", email = \"rodrigo@langflow.org\" },\n16|    { name = \"Italo dos Anjos\", email = \"italojohnnydosanjos@gmail.com\" },\n17|]\n18|# Define your main dependencies here\n19|dependencies = [\n20|    \"langflow-base[complete]>=0.9.4\",\n21|]\n22|\n23|\n24|[dependency-groups]\n25|dev = [\n26|    \"pytest-instafail>=0.5.0\",\n27|    \"ipykernel>=6.29.0\",\n28|    \"ruff~=0.13.1\",\n29|    \"httpx>=0.28.1\",\n30|    \"pytest>=9.0.3\",\n31|    \"requests>=2.33.0\",\n32|    \"pytest-cov>=5.0.0\",\n33|    \"pytest-mock>=3.14.0\",\n34|    \"pytest-xdist>=3.6.0\",\n35|    \"pytest-sugar>=1.0.0\",\n36|    \"respx>=0.21.1\",\n37|    \"pytest-asyncio>=0.23.0\",\n38|    \"pytest-profiling>=1.7.0\",\n39|    \"pre-commit>=3.7.0\",\n40|    \"vulture>=2.11\",\n41|    \"dictdiffer>=0.9.0\",\n42|    \"pytest-split>=0.9.0\",\n43|    \"pytest-flakefinder>=1.1.0\",\n44|    \"packaging>=24.1,<25.0\",\n45|    \"asgi-lifespan>=2.1.0\",\n46|    \"pytest-github-actions-annotate-failures>=0.2.0\",\n47|    \"blockbuster>=1.5.20,<1.6\",\n48|    \"types-aiofiles>=24.1.0.20240626\",\n49|    \"codeflash>=0.8.4\",\n50|    \"hypothesis>=6.123.17\",\n51|    \"locust~=2.43.4\",\n52|    \"pytest-rerunfailures>=15.0\",\n53|    \"scrapegraph-py>=1.10.2\",\n54|    'elevenlabs==1.58.1; python_version == \"3.12\"',\n55|    'elevenlabs>=1.52.0; python_version != \"3.12\"',\n56|    \"faker>=37.0.0\",\n57|    \"pytest-timeout>=2.3.1\",\n58|    \"pyyaml>=6.0.2\",\n59|    \"pyleak>=0.1.14\",\n60|    \"mcp-server-fetch>=2025.1.17\",\n61|    \"onnxruntime>=1.20,<1.24; python_version<'3.14'\", # >=1.24 does not support Python 3.10; <1.24 allows 1.23.x for agent-lifecycle-toolkit\n62|    \"onnxruntime>=1.26; python_version>='3.14'\",\n63|]\n64|\n65|[[tool.uv.index]]\n66|name = \"pytorch-cpu\"\n67|url = \"https://download.pytorch.org/whl/cpu\"\n68|explicit = true\n69|\n70|[tool.uv.sources]\n71|langflow-base = { workspace = true }\n72|langflow = { workspace = true }\n73|lfx = { workspace = true }\n74|langflow-sdk = { workspace = true }\n75|torch = { index = \"pytorch-cpu\" }\n76|torchvision = { index = \"pytorch-cpu\" }\n77|\n78|[tool.uv.workspace]\n79|members = [\n80|    \"src/backend/base\",\n81|    \".\",\n82|    \"src/lfx\",\n83|    \"src/sdk\",\n84|]\n85|\n86|[tool.hatch.build.targets.wheel]\n87|packages = [\"src/backend/langflow\"]\n88|\n89|[project.urls]\n90|Repository = \"https://github.com/langflow-ai/langflow\"\n91|Documentation = \"https://docs.langflow.org\"\n92|\n93|[project.optional-dependencies]\n94|docling = [\n95|    \"langchain-docling>=1.1.0\",\n96|    \"tesserocr>=2.8.0\",\n97|    \"rapidocr-onnxruntime>=1.4.4\",\n98|    \"ocrmac>=1.0.0; sys_platform == 'darwin'\",\n99|    # CPU-only PyTorch required for docling features\n100|    # Loose version ranges intentionally used to avoid conflicts with transitive dependencies (e.g., altk)\n101|    # Updated to 2.6.0+ to address CVE: RCE vulnerability in torch.load() with weights_only=True\n102|    \"torch>=2.6.0\",\n103|    \"torchvision>=0.21.0\",  # torchvision 0.21+ is compatible with PyTorch 2.6+\n104|]\n105|\n106|audio = [\n107|    \"webrtcvad>=2.0.10\",\n108|]\n109|\n110|\n111|couchbase = [\n112|    \"couchbase>=4.2.1\"\n113|]\n114|cassio = [\n115|    \"cassio>=0.1.7\"\n116|]\n117|local = [\n118|    \"sentence-transformers>=2.3.1\",\n119|    \"ctransformers>=0.2.10\"\n120|]\n121|clickhouse-connect = [\n122|    \"clickhouse-connect==0.7.19\"\n123|]\n124|\n125|nv-ingest = [\n126|    \"nv-ingest-api>=26.1.0,<27.0.0 ; python_version >= '3.12'\",\n127|    \"nv-ingest-client>=26.1.0,<27.0.0 ; python_version >= '3.12'\",\n128|]\n129|\n130|postgresql = [\n131|    \"sqlalchemy[postgresql_psycopg2binary]>=2.0.38,<3.0.0\",\n132|    \"sqlalchemy[postgresql_psycopg]>=2.0.38,<3.0.0\",\n133|]\n134|\n135|[tool.uv]\n136|override-dependencies = [\n137|    # temporary force a newer python-pptx\n138|    \"python-pptx>=1.0.2\",\n139|    # z3-solver 4.15.7 dropped Linux wheels, pin until codeflash is removed\n140|    \"z3-solver<4.15.7\",\n141|    # Security: Force upgraded versions to prevent transitive deps from pulling older vulnerable versions\n142|    \"orjson>=3.11.6\",\n143|    \"gunicorn>=25.3.0\",\n144|    \"pypdf>=6.10.0\",  # Force pypdf 6.10+ to prevent vulnerable 6.6.x versions\n145|    \"nltk>=3.9.4\",\n146|    \"Markdown>=3.8.0\",\n147|    \"dynaconf>=3.2.13\",\n148|    \"pillow>=12.1.1\",  # Force Pillow 12.1.1+ to prevent CVE-vulnerable versions\n149|    \"playwright>=1.59.0\",  # Latest available on PyPI; ensures updated Chromium with CVE fixes\n150|    # Transitive dependency CVE fixes\n151|    \"lxml>=6.1.0,<7.0.0\",  # CVE-2026-41066\n152|    \"mako>=1.3.12,<2.0.0\",  # CVE-2026-44307\n153|    \"urllib3>=2.7.0,<3.0.0\",  # CVE-2026-44431, CVE-2026-44432\n154|    \"python-liquid>=2.2.0,<3.0.0\",  # CVE-2026-45017\n155|]\n156|\n157|[project.scripts]\n158|langflow = \"langflow.langflow_launcher:main\"\n159|\n160|[tool.codespell]\n161|skip = '.git,*.pdf,*.svg,*.pdf,*.yaml,*.ipynb,poetry.lock,*.min.js,*.css,package-lock.json,*.trig.,**/node_modules/**,./stuff/*,*.csv'\n162|# Ignore latin etc\n163|ignore-regex = '.*(Stati Uniti|Tense=Pres).*'\n164|\n165|\n166|[tool.pytest.ini_options]\n167|timeout = 150\n168|timeout_method = \"signal\"\n169|minversion = \"6.0\"\n170|testpaths = [\"src/backend/tests\", \"src/lfx/tests\"]\n171|console_output_style = \"progress\"\n172|filterwarnings = [\n173|    \"ignore::DeprecationWarning\",\n174|    \"ignore::ResourceWarning\",\n175|    \"ignore:Skipped unsupported reflection:sqlalchemy.exc.SAWarning\",\n176|    \"ignore:.*SQL-parsed foreign key constraint:sqlalchemy.exc.SAWarning\",\n177|    \"ignore:autogenerate skipping metadata-specified expression-based index:UserWarning\",\n178|]\n179|log_cli = true\n180|log_cli_format = \"%(asctime)s [%(levelname)8s] %(message)s (%(filename)s:%(lineno)s)\"\n181|log_cli_date_format = \"%Y-%m-%d %H:%M:%S\"\n182|markers = [\n183|    \"async_test\",\n184|    \"api_key_required\",\n185|    \"no_blockbuster\",\n186|    \"benchmark\",\n187|    \"unit: Unit tests\",\n188|    \"integration: Integration tests\",\n189|    \"slow: Slow-running tests\",\n190|    \"security: Security regression tests (IDOR, auth, access control)\"\n191|]\n192|asyncio_mode = \"auto\"\n193|asyncio_default_fixture_loop_scope = \"function\"\n194|addopts = \"-p no:benchmark\"\n195|\n196|[tool.coverage.run]\n197|command_line = \"\"\"\n198|    -m pytest --ignore=tests/integration\n199|    --cov --cov-report=term --cov-report=html\n200|    --instafail -ra -n auto -m \"not api_key_required\"\n201|", "total_lines": 462, "file_size": 16026, "truncated": true, "hint": "Use offset=201 to continue reading (showing 1-200 of 462 lines)", "is_binary": false, "is_image": false}


session_id: 20260530_230735_8b01b4
role: tool
tool_call_id: chatcmpl-tool-9e52936e41d723dc
tool_name: read_file
content:
  {"content": "1|{\n2|  \"name\": \"langflow\",\n3|  \"version\": \"1.9.3\",\n4|  \"private\": true,\n5|  \"engines\": {\n6|    \"node\": \">=20.19.0\"\n7|  },\n8|  \"overrides\": {\n9|    \"tar\": \"^7.5.7\",\n10|    \"tar-fs\": \"^2.1.4\",\n11|    \"glob\": \"^11.1.0\",\n12|    \"test-exclude\": \"^7.0.0\",\n13|    \"picomatch\": \"^4.0.4\",\n14|    \"ip-address\": \"^10.1.1\",\n15|    \"jest-util\": {\n16|      \"picomatch\": \"^4.0.4\"\n17|    },\n18|    \"jest-message-util\": {\n19|      \"picomatch\": \"^4.0.4\"\n20|    },\n21|    \"playwright\": \"^1.59.1\",\n22|    \"brace-expansion\": \"^5.0.5\",\n23|    \"handlebars\": \"^4.7.9\",\n24|    \"minimatch\": \"^10.2.5\"\n25|  },\n26|  \"dependencies\": {\n27|    \"@chakra-ui/number-input\": \"^2.1.2\",\n28|    \"@chakra-ui/system\": \"^2.6.2\",\n29|    \"@emotion/react\": \"^11.14.0\",\n30|    \"@emotion/styled\": \"^11.14.1\",\n31|    \"@headlessui/react\": \"^2.2.9\",\n32|    \"@hookform/resolvers\": \"^3.6.0\",\n33|    \"@radix-ui/react-accordion\": \"^1.2.12\",\n34|    \"@radix-ui/react-checkbox\": \"^1.3.3\",\n35|    \"@radix-ui/react-context-menu\": \"^2.2.16\",\n36|    \"@radix-ui/react-dialog\": \"^1.1.15\",\n37|    \"@radix-ui/react-dropdown-menu\": \"^2.1.16\",\n38|    \"@radix-ui/react-form\": \"^0.1.8\",\n39|    \"@radix-ui/react-icons\": \"^1.3.0\",\n40|    \"@radix-ui/react-label\": \"^2.1.8\",\n41|    \"@radix-ui/react-popover\": \"^1.1.15\",\n42|    \"@radix-ui/react-radio-group\": \"^1.3.8\",\n43|    \"@radix-ui/react-select\": \"^2.2.6\",\n44|    \"@radix-ui/react-separator\": \"^1.1.8\",\n45|    \"@radix-ui/react-slider\": \"^1.3.6\",\n46|    \"@radix-ui/react-slot\": \"^1.2.4\",\n47|    \"@radix-ui/react-switch\": \"^1.2.6\",\n48|    \"@radix-ui/react-tabs\": \"^1.1.13\",\n49|    \"@radix-ui/react-tooltip\": \"^1.2.8\",\n50|    \"@tabler/icons-react\": \"^3.6.0\",\n51|    \"@tailwindcss/forms\": \"^0.5.7\",\n52|    \"@tailwindcss/line-clamp\": \"^0.4.4\",\n53|    \"@tanstack/react-query\": \"^5.49.2\",\n54|    \"@types/axios\": \"^0.14.0\",\n55|    \"@types/mustache\": \"^4.2.6\",\n56|    \"@xyflow/react\": \"^12.3.6\",\n57|    \"ace-builds\": \"^1.41.0\",\n58|    \"ag-grid-community\": \"^32.3.9\",\n59|    \"ag-grid-react\": \"^32.3.9\",\n60|    \"ansi-to-html\": \"^0.7.2\",\n61|    \"axios\": \"^1.15.0\",\n62|    \"base64-js\": \"^1.5.1\",\n63|    \"class-variance-authority\": \"^0.7.0\",\n64|    \"clsx\": \"^2.1.1\",\n65|    \"cmdk\": \"^1.1.1\",\n66|    \"dompurify\": \"^3.2.4\",\n67|    \"dotenv\": \"^16.4.5\",\n68|    \"elkjs\": \"^0.9.3\",\n69|    \"emoji-regex\": \"^10.3.0\",\n70|    \"esbuild\": \"^0.25.0\",\n71|    \"fetch-intercept\": \"^2.4.0\",\n72|    \"file-saver\": \"^2.0.5\",\n73|    \"framer-motion\": \"^11.2.10\",\n74|    \"fuse.js\": \"^7.0.0\",\n75|    \"i18next\": \"^25.8.18\",\n76|    \"lodash\": \"^4.17.21\",\n77|    \"lucide-react\": \"^0.575.0\",\n78|    \"moment\": \"^2.30.1\",\n79|    \"moment-timezone\": \"^0.5.48\",\n80|    \"mustache\": \"^4.2.0\",\n81|", "total_lines": 196, "file_size": 6159, "truncated": true, "hint": "Use offset=81 to continue reading (showing 1-80 of 196 lines)", "is_binary": false, "is_image": false}


session_id: 20260530_230735_8b01b4
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-b6d355c25b24315f", "call_id": "chatcmpl-tool-b6d355c25b24315f", "response_item_id": "fc_chatcmpl-tool-b6d355c25b24315f", "type": "function", "function": {"name": "read_file", "arguments": "{\"limit\": 200, \"offset\": 201, \"path\": \"/home/ice/langflow/pyproject.toml\"}"}}, {"id": "chatcmpl-tool-944eb4fc7223dfa4", "call_id": "chatcmpl-tool-944eb4fc7223dfa4", "response_item_id": "fc_chatcmpl-tool-944eb4fc7223dfa4", "type": "function", "function": {"name": "search_files", "arguments": "{\"limit\": 30, \"path\": \"/home/ice/langflow\", \"pattern\": \"TODO|FIXME|HACK|XXX\"}"}}]

reasoning:
  Procurando mais detalhes sobre arquitetura, propósito principal e possíveis problemas do repositório para montar a análise.

reasoning_content:
  Procurando mais detalhes sobre arquitetura, propósito principal e possíveis problemas do repositório para montar a análise.


session_id: 20260530_230735_8b01b4
role: tool
tool_call_id: chatcmpl-tool-b6d355c25b24315f
tool_name: read_file
content:
  {"content": "201|\"\"\"\n202|source = [\"src/backend/base/langflow/\"]\n203|omit = [\"*/alembic/*\", \"tests/*\", \"*/__init__.py\"]\n204|\n205|\n206|[tool.coverage.report]\n207|sort = \"Stmts\"\n208|skip_empty = true\n209|show_missing = false\n210|ignore_errors = true\n211|\n212|\n213|[tool.coverage.html]\n214|directory = \"coverage\"\n215|\n216|\n217|[tool.ruff]\n218|target-version = \"py310\"\n219|exclude = [\n220|    \"src/backend/base/langflow/alembic/*\",\n221|    \"src/frontend/tests/assets/*\",\n222|    \"src/lfx/src/lfx/_assets/component_index.json\",\n223|    \"docs/**/API-Reference/python-examples/**\",\n224|]\n225|line-length = 120\n226|\n227|[tool.ruff.lint]\n228|flake8-annotations.mypy-init-return = true\n229|flake8-bugbear.extend-immutable-calls = [\n230|    \"fastapi.Depends\",\n231|    \"fastapi.File\",\n232|    \"fastapi.Query\",\n233|    \"typer.Option\",\n234|]\n235|flake8-type-checking.runtime-evaluated-base-classes = [\n236|    \"pydantic.BaseModel\",\n237|    \"typing.TypedDict\",  # Needed by fastapi\n238|    \"typing_extensions.TypedDict\",  # Needed by fastapi\n239|]\n240|pydocstyle.convention = \"google\"\n241|select = [\"ALL\"]\n242|ignore = [\n243|    \"C90\", # McCabe complexity\n244|    \"CPY\", # Missing copyright\n245|    \"COM812\", # Messes with the formatter\n246|    \"ERA\", # Eradicate commented-out code\n247|    \"FIX002\", # Line contains TODO\n248|    \"ISC001\", # Messes with the formatter\n249|    \"PERF203\", # Rarely useful\n250|    \"PLR09\", # Too many something (arg, statements, etc)\n251|    \"RUF012\", # Pydantic models are currently not well detected. See https://github.com/astral-sh/ruff/issues/13630\n252|    \"TD002\", # Missing author in TODO\n253|    \"TD003\", # Missing issue link in TODO\n254|    \"TRY301\", # A bit too harsh (Abstract `raise` to an inner function)\n255|    \"PLC0415\", # Inline imports\n256|    \"D10\", # Missing docstrings\n257|    \"PLW1641\", # Object does not implement `__hash__` method (mutable objects shouldn't be hashable)\n258|    # Rules that are TODOs\n259|    \"ANN\"\n260|]\n261|\n262|# Preview rules that are not yet activated\n263|external = [\"RUF027\"]\n264|\n265|[tool.ruff.lint.per-file-ignores]\n266|\"scripts/*\" = [\"D1\", \"INP\", \"T201\"]\n267|\"scripts/gp/tests/*\" = [\n268|    \"D1\",      # Missing docstrings\n269|    \"PLR2004\", # Magic value comparisons\n270|    \"S101\",    # Use of assert (required for pytest)\n271|    \"TRY003\",  # Long exception messages\n272|    \"EM101\",   # String literals in exceptions\n273|]\n274|\"scripts/ci/test_*.py\" = [\n275|    \"D1\",      # Missing docstrings\n276|    \"PLR2004\", # Magic value comparisons\n277|    \"S101\",    # Use of assert (required for pytest)\n278|    \"TRY003\",  # Long exception messages\n279|    \"EM101\",   # String literals in exceptions\n280|]\n281|\"src/backend/base/langflow/alembic/versions/*\" = [\"INP001\", \"D415\", \"PGH003\"]\n282|\"src/backend/base/langflow/custom/__init__.py\" = [\n283|    \"I001\",  # Import order affects initialization - must import custom module first\n284|]\n285|\"src/backend/base/langflow/api/v1/*\" = [\n286|    \"TCH\",  # FastAPI needs to evaluate types at runtime\n287|]\n288|\"src/backend/base/langflow/api/v2/*\" = [\n289|    \"TCH\",  # FastAPI needs to evaluate types at runtime\n290|]\n291|\"src/backend/base/langflow/__main__.py\" = [\n292|    \"B008\",  # Typer CLI requires function calls in defaults\n293|]\n294|\"src/backend/base/langflow/services/cache/*\" = [\n295|    \"S301\",  # Pickle usage is intentional for caching\n296|]\n297|\"src/backend/base/langflow/services/tracing/*\" = [\n298|    \"SLF001\",  # Third-party library private member access (langwatch, opik)\n299|]\n300|\"src/lfx/src/lfx/base/curl/parse.py\" = [\n301|    \"S105\",  # False positive: 'token' variable name, not a password\n302|]\n303|\"src/lfx/src/lfx/services/auth/service.py\" = [\n304|    \"ARG002\",  # No-op impl: unused args required by interface\n305|    \"EM101\",  # NotImplementedError messages as literals\n306|    \"TC003\",  # Type-only imports used in signatures\n307|]\n308|\"src/lfx/src/lfx/base/mcp/util.py\" = [\n309|    \"SLF001\",  # MCP library private member access\n310|]\n311|\"src/lfx/src/lfx/cli/common.py\" = [\n312|    \"S104\",  # Intentional binding to all interfaces for server\n313|    \"S105\",  # False positive: GITHUB_TOKEN_ENV is an env var name\n314|]\n315|\"src/lfx/src/lfx/components/__init__.py\" = [\n316|    \"SLF001\",  # Accessing _dynamic_imports from modules\n317|]\n318|\"src/lfx/src/lfx/components/data/save_file.py\" = [\n319|    \"SLF001\",  # Google API client private member access\n320|]\n321|\"src/lfx/src/lfx/components/datastax/astradb_vectorstore.py\" = [\n322|    \"S110\",  # Try-except-pass for optional metadata\n323|]\n324|\"src/lfx/src/lfx/components/google/google_generative_ai_embeddings.py\" = [\n325|    \"SLF001\",  # Google AI library private member access\n326|]\n327|\"src/lfx/src/lfx/components/knowledge_bases/retrieval.py\" = [\n328|    \"SLF001\",  # Chroma client private member access\n329|]\n330|\"src/lfx/src/lfx/components/mongodb/mongodb_atlas.py\" = [\n331|    \"SLF001\",  # MongoDB collection private member access\n332|]\n333|\"src/lfx/src/lfx/components/tools/{python_code_structured_tool.py,searxng.py}\" = [\n334|    \"S102\",  # Use of exec/eval for dynamic code execution\n335|    \"SLF001\",  # Component internal member access\n336|]\n337|\"src/lfx/src/lfx/components/vectorstores/astradb.py\" = [\n338|    \"S110\",  # Try-except-pass for optional metadata\n339|]\n340|\"src/lfx/src/lfx/custom/{code_parser/code_parser.py,validate.py}\" = [\n341|    \"S102\",  # Use of exec for code validation\n342|]\n343|\"src/lfx/src/lfx/custom/custom_component/component.py\" = [\n344|    \"SLF001\",  # Component internal state management\n345|]\n346|\"src/lfx/src/lfx/custom/directory_reader/directory_reader.py\" = [\n347|    \"SLF001\",  # Component introspection\n348|]\n349|\"src/lfx/src/lfx/custom/utils.py\" = [\n350|    \"SLF001\",  # Component code analysis\n351|]\n352|\"src/lfx/src/lfx/graph/graph/ascii.py\" = [\n353|    \"SLF001\",  # Grandalf library private member access\n354|]\n355|\"src/lfx/src/lfx/inputs/input_mixin.py\" = [\n356|    \"S105\",  # False positive: PASSWORD is a type constant\n357|]\n358|\"src/lfx/src/lfx/__main__.py\" = [\n359|    \"B008\",   # Typer CLI requires function calls in argument defaults\n360|    \"FBT001\", # Bool flags are the standard typer pattern\n361|    \"FBT003\", # Boolean positional values in typer.Option() calls\n362|]\n363|\"src/lfx/src/lfx/cli/_setup_commands.py\" = [\n364|    \"B008\",   # Typer CLI requires function calls in argument defaults\n365|    \"FBT001\", # Bool flags are the standard typer pattern\n366|    \"FBT003\", # Boolean positional values in typer.Option() calls\n367|]\n368|\"src/lfx/src/lfx/cli/_authoring_commands.py\" = [\n369|    \"B008\",   # Typer CLI requires function calls in argument defaults\n370|    \"FBT001\", # Bool flags are the standard typer pattern\n371|    \"FBT003\", # Boolean positional values in typer.Option() calls\n372|]\n373|\"src/lfx/src/lfx/cli/_running_commands.py\" = [\n374|    \"B008\",   # Typer CLI requires function calls in argument defaults\n375|    \"FBT001\", # Bool flags are the standard typer pattern\n376|    \"FBT003\", # Boolean positional values in typer.Option() calls\n377|]\n378|\"src/lfx/src/lfx/cli/_remote_commands.py\" = [\n379|    \"B008\",   # Typer CLI requires function calls in argument defaults\n380|    \"FBT001\", # Bool flags are the standard typer pattern\n381|    \"FBT003\", # Boolean positional values in typer.Option() calls\n382|]\n383|\"src/backend/base/langflow/api/utils/*\" = [\n384|    \"TCH\",  # Imports are used at runtime (FastAPI deps, SQLAlchemy queries, model constructors)\n385|]\n386|\"src/sdk/src/langflow_sdk/_http.py\" = [\n387|    \"TCH\",  # httpx is used at runtime (response object methods)\n388|]\n389|\"src/sdk/src/langflow_sdk/environments.py\" = [\n390|    \"TRY003\", # Contextual error messages are necessary here\n391|    \"EM102\",  # f-string messages assigned before raise where possible\n392|]\n393|\"src/sdk/tests/*\" = [\n394|    \"S101\",   # assert is the standard pytest assertion style\n395|    \"INP001\", # Not a package namespace issue in tests\n396|    \"TC003\",  # pytest fixture type hints are evaluated at runtime\n397|]\n398|\"src/lfx/src/lfx/schema/table.py\" = [\n399|    \"S105\",  # False positive: PASSWORD is a formatter type\n400|]\n401|", "total_lines": 462, "file_size": 16026, "truncated": true, "hint": "Use offset=401 to continue reading (showing 201-400 of 462 lines)", "is_binary": false, "is_image": false}


session_id: 20260530_230735_8b01b4
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-bdd08ccc8026f725", "call_id": "chatcmpl-tool-bdd08ccc8026f725", "response_item_id": "fc_chatcmpl-tool-bdd08ccc8026f725", "type": "function", "function": {"name": "read_file", "arguments": "{\"limit\": 120, \"path\": \"/home/ice/langflow/DESIGN.md\"}"}}, {"id": "chatcmpl-tool-9070cc7026f3d501", "call_id": "chatcmpl-tool-9070cc7026f3d501", "response_item_id": "fc_chatcmpl-tool-9070cc7026f3d501", "type": "function", "function": {"name": "search_files", "arguments": "{\"limit\": 40, \"path\": \"/home/ice/langflow/src\", \"pattern\": \"fastapi|sqlalchemy|langchain\"}"}}]

reasoning:
  Vou analisar o repositório do Langflow com base no que já examinei e talvez dar uma olhada mais detalhada no stack e em alguns arquivos-chave.

  Até agora eu sei:
  - Repositório: langflow-ai/langflow no GitHub
  - Descrição: Langflow is a powerful platform for building and deploying AI-powered agents and workflows.
  - Linguagem: Python
  - Stars: ~148.923
  - Tem frontend em src/frontend/ e backend em src/

  Preciso responder: Problema, Tema, Razão hype, Tecnologias.

  Problema:
  - Organizador visual de workflows/agentes de IA
  - O problema é dificuldade/barreira para criar aplicações com IA sem necessidade de programação pesada
  - Problema: "Construir e orquestrar fluxos de agentes de IA é complexo, exige código knowledge de vários serviços/APIs"
  - Também problema de deploy e acesso às ferramentas/LLM facilmente.

  Tema:
  - Low-code/no-code visual builder para AI agents e workflows.
  - Orquestração multi-agente.
  - Deploy como API/MCP.
  - Integração com vector DBs, LLMs, ferramentas.

  Razão hype:
  - Facilidade de uso (visual drag-and-drop)
  - Multi-agente
  - MCP server export
  - Open-source, módulos de LangChain/LLM/Vector DB
  - Integração com LangSmith/LangFuse
  - Desktop app
  - 148k estrelas
  - Ecosistema LLM em alta
  - "Batteries included"

  Tecnologias:
  - Python 3.10-3.13
  - FastAPI backend
  - SQLAlchemy + Alembic
  - LangChain
  - React 19 + TypeScript + Vite + Zustana + @xyflow/react (frontend)
  - uv (Python package manager)
  - Pydantic
  - Playwright (tests)
  - Redis/Memcached opcional
  - Vector DBs: Chroma, Pinecone, AstraDB, MongoDB Atlas, Clickhouse, Couchbase
  - Observabilidade: LangSmith, LangFuse

  Vou checar alguns arquivos para complementar.

reasoning_content:
  Vou analisar o repositório do Langflow com base no que já examinei e talvez dar uma olhada mais detalhada no stack e em alguns arquivos-chave.

  Até agora eu sei:
  - Repositório: langflow-ai/langflow no GitHub
  - Descrição: Langflow is a powerful platform for building and deploying AI-powered agents and workflows.
  - Linguagem: Python
  - Stars: ~148.923
  - Tem frontend em src/frontend/ e backend em src/

  Preciso responder: Problema, Tema, Razão hype, Tecnologias.

  Problema:
  - Organizador visual de workflows/agentes de IA
  - O problema é dificuldade/barreira para criar aplicações com IA sem necessidade de programação pesada
  - Problema: "Construir e orquestrar fluxos de agentes de IA é complexo, exige código knowledge de vários serviços/APIs"
  - Também problema de deploy e acesso às ferramentas/LLM facilmente.

  Tema:
  - Low-code/no-code visual builder para AI agents e workflows.
  - Orquestração multi-agente.
  - Deploy como API/MCP.
  - Integração com vector DBs, LLMs, ferramentas.

  Razão hype:
  - Facilidade de uso (visual drag-and-drop)
  - Multi-agente
  - MCP server export
  - Open-source, módulos de LangChain/LLM/Vector DB
  - Integração com LangSmith/LangFuse
  - Desktop app
  - 148k estrelas
  - Ecosistema LLM em alta
  - "Batteries included"

  Tecnologias:
  - Python 3.10-3.13
  - FastAPI backend
  - SQLAlchemy + Alembic
  - LangChain
  - React 19 + TypeScript + Vite + Zustana + @xyflow/react (frontend)
  - uv (Python package manager)
  - Pydantic
  - Playwright (tests)
  - Redis/Memcached opcional
  - Vector DBs: Chroma, Pinecone, AstraDB, MongoDB Atlas, Clickhouse, Couchbase
  - Observabilidade: LangSmith, LangFuse

  Vou checar alguns arquivos para complementar.


session_id: 20260530_230735_8b01b4
role: tool
tool_call_id: chatcmpl-tool-bdd08ccc8026f725
tool_name: read_file
content:
  {"content": "1|---\n2|version: alpha\n3|name: Langflow\n4|description: Visual AI workflow builder for composing LLM-powered applications\n5|colors:\n6|  # Core UI palette\n7|  primary: \"#000000\"\n8|  primary-foreground: \"#FFFFFF\"\n9|  primary-hover: \"#27272A\"\n10|  background: \"#FFFFFF\"\n11|  foreground: \"#000000\"\n12|  muted: \"#F4F4F5\"\n13|  muted-foreground: \"#71717A\"\n14|  border: \"#E4E4E7\"\n15|  input: \"#E4E4E7\"\n16|  ring: \"#000000\"\n17|  card: \"#FFFFFF\"\n18|  card-foreground: \"#000000\"\n19|  popover: \"#FFFFFF\"\n20|  popover-foreground: \"#000000\"\n21|  secondary: \"#FFFFFF\"\n22|  secondary-foreground: \"#27272A\"\n23|  secondary-hover: \"#E4E4E7\"\n24|  accent: \"#F4F4F5\"\n25|  accent-foreground: \"#000000\"\n26|  placeholder: \"#A1A1AA\"\n27|  placeholder-foreground: \"#A1A1AA\"\n28|  tooltip: \"#000000\"\n29|  tooltip-foreground: \"#FFFFFF\"\n30|\n31|  # Semantic status\n32|  destructive: \"#DC2626\"\n33|  destructive-foreground: \"#FFFFFF\"\n34|  error: \"#991B1B\"\n35|  error-background: \"#FEF2F2\"\n36|  error-foreground: \"#991B1B\"\n37|  success-background: \"#F0FDF4\"\n38|  success-foreground: \"#14532D\"\n39|  info-background: \"#F0F4FD\"\n40|  info-foreground: \"#141653\"\n41|  warning: \"#FCE68A\"\n42|  warning-foreground: \"#18181B\"\n43|  warning-text: \"#FFFFFF\"\n44|\n45|  # Status indicators\n46|  status-red: \"#EF4444\"\n47|  status-green: \"#4ADE80\"\n48|  status-yellow: \"#EAB308\"\n49|  status-blue: \"#2563EB\"\n50|  status-gray: \"#6B7280\"\n51|\n52|  # Accent families (background / foreground pairs)\n53|  accent-emerald: \"#D1F9E4\"\n54|  accent-emerald-foreground: \"#047857\"\n55|  accent-emerald-hover: \"#A7F3D0\"\n56|  accent-indigo: \"#E0E7FF\"\n57|  accent-indigo-foreground: \"#4F46E5\"\n58|  accent-pink: \"#FCE8F3\"\n59|  accent-pink-foreground: \"#BE185D\"\n60|  accent-amber: \"#FCE68A\"\n61|  accent-amber-foreground: \"#B45309\"\n62|\n63|  # Standalone accent references (not bg/fg pairs -- used for text, icons, links)\n64|  accent-blue: \"#3B82F6\"\n65|  accent-blue-muted: \"#D5E4FF\"\n66|  accent-blue-muted-foreground: \"#51A2FF\"\n67|  accent-purple-foreground: \"#9333EA\"\n68|  accent-purple-muted: \"#EDD5FF\"\n69|  accent-purple-muted-foreground: \"#C27AFF\"\n70|  accent-red-foreground: \"#DC2626\"\n71|\n72|  # Indigo scale\n73|  high-indigo: \"#4338CA\"\n74|  medium-indigo: \"#6366F1\"\n75|  low-indigo: \"#E0E7FF\"\n76|\n77|  # Canvas and node system\n78|  canvas: \"#F4F4F5\"\n79|  canvas-dot: \"#A1A1AA\"\n80|  node-selected: \"#4F46E5\"\n81|  node-ring: \"#E4E4E7\"\n82|  connection: \"#555555\"\n83|  hover: \"#F2F4F5\"\n84|  selected: \"#2196F3\"\n85|\n86|  # Code blocks\n87|  code-background: \"#18181B\"\n88|  code-foreground: \"#E4E4E7\"\n89|\n90|  # Utility\n91|  hard-zinc: \"#51515A\"\n92|  smooth-red: \"#FDE1E1\"\n93|\n94|  # Note colors (sticky notes on canvas)\n95|  note-amber: \"#FCE68A\"\n96|  note-neutral: \"#E4E4E7\"\n97|  note-rose: \"#FECDD3\"\n98|  note-blue: \"#BFDBFE\"\n99|  note-lime: \"#D9F99D\"\n100|\n101|  # Beta feature badge\n102|  beta-background: \"#DBEAFE\"\n103|  beta-foreground: \"#2563EB\"\n104|\n105|  # Data type colors (node port type indicators -- light mode)\n106|  # In light mode: base = saturated, foreground = light tint\n107|  datatype-pink: \"#DB2777\"\n108|  datatype-pink-foreground: \"#FBE6F2\"\n109|  datatype-rose: \"#E11D48\"\n110|  datatype-rose-foreground: \"#FFE4E6\"\n111|  datatype-yellow: \"#CA8A04\"\n112|  datatype-yellow-foreground: \"#FEF9C3\"\n113|  datatype-blue: \"#2563EB\"\n114|  datatype-blue-foreground: \"#DBEAFE\"\n115|  datatype-gray: \"#4B5563\"\n116|  datatype-gray-foreground: \"#F3F4F6\"\n117|  datatype-lime: \"#65A30D\"\n118|  datatype-lime-foreground: \"#ECFCCB\"\n119|  datatype-red: \"#DC2626\"\n120|  datatype-red-foreground: \"#FEE2E2\"\n121|", "total_lines": 752, "file_size": 30552, "truncated": true, "hint": "Use offset=121 to continue reading (showing 1-120 of 752 lines)", "is_binary": false, "is_image": false}


session_id: 20260530_230735_8b01b4
role: assistant
finish_reason: stop
content:
  Análise concluída do repositório `langflow-ai/langflow` (`/home/ice/langflow`).

  ## Resultado

  - **Problema:** Construir fluxos de IA de forma visual e reutilizável, sem exigir programação pesada; os fluxos salvos precisam ser artefatos persistentes e backward-compatible.
  - **Tema:** Plataforma low-code/no-code para orquestração de agentes e workflows LLM com deploy como API ou MCP server.
  - **Razão do hype:** Visual builder + multi-agent orchestration + deploy como API/MCP + biblioteca crescente de componentes e integrações com LangSmith/LangFuse/vectorstores.
  - **Tecnologias principais:**
    - **Backend:** Python 3.10–3.13, FastAPI, SQLAlchemy/Alembic
    - **Frontend:** React 19, TypeScript, Vite, Zustand, `@xyflow/react`
    - **Core de execução:** pacotes `lfx` + `langflow-base`
    - **Tooling/dev:** `uv`, `make`, `ruff`, `pytest`, `pre-commit`

reasoning:
  Hmm, I need to switch back to Portuguese now.

  Maybe I can use /start_he_en/ to switch back to English if I'm already in the assistant mode. But first, let me do the analysis summary in Portuguese.

reasoning_content:
  Hmm, I need to switch back to Portuguese now.

  Maybe I can use /start_he_en/ to switch back to English if I'm already in the assistant mode. But first, let me do the analysis summary in Portuguese.


session_id: 20260530_230735_c58bbc
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-a67389301f8f76a1", "call_id": "chatcmpl-tool-a67389301f8f76a1", "response_item_id": "fc_chatcmpl-tool-a67389301f8f76a1", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"cd /home/ice && git clone https://github.com/langgenius/dify.git 2>&1 | tail -5\", \"timeout\": 120}"}}]

reasoning:
  The user wants me to analyze the repository `langgenius/dify` and return: Problem, Theme, Hype reason, Technologies.

  I need to clone the repository first, then explore it to gather information. Let me start by cloning the repo.

reasoning_content:
  The user wants me to analyze the repository `langgenius/dify` and return: Problem, Theme, Hype reason, Technologies.

  I need to clone the repository first, then explore it to gather information. Let me start by cloning the repo.


session_id: 20260530_230735_c58bbc
role: tool
tool_call_id: chatcmpl-tool-a67389301f8f76a1
tool_name: terminal
content:
  {"output": "Cloning into 'dify'...\nUpdating files:  98% (11970/12133)\rUpdating files:  99% (12012/12133)\rUpdating files: 100% (12133/12133)\rUpdating files: 100% (12133/12133), done.", "exit_code": 0, "error": null}


session_id: 20260530_230735_c58bbc
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-8ffdd8cac8b880db", "call_id": "chatcmpl-tool-8ffdd8cac8b880db", "response_item_id": "fc_chatcmpl-tool-8ffdd8cac8b880db", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\": \"cd /home/ice/dify && ls -la\"}"}}]

reasoning:
  Good, the repository is cloned. Now let me analyze it. I'll start by looking at key files like README, package.json, and the directory structure.

reasoning_content:
  Good, the repository is cloned. Now let me analyze it. I'll start by looking at key files like README, package.json, and the directory structure.


session_id: 20260530_230735_c58bbc
role: tool
tool_call_id: chatcmpl-tool-8ffdd8cac8b880db
tool_name: terminal
content:
  {"output": "total 518\ndrwxrwxr-x 22 ice ice     44 May 30 23:07 .\ndrwx------ 36 ice ice     42 May 30 23:07 ..\ndrwxrwxr-x  3 ice ice      3 May 30 23:07 .agents\ndrwxrwxr-x  3 ice ice      4 May 30 23:07 .claude\n-rw-rw-r--  1 ice ice      0 May 30 23:07 .codex\n-rw-rw-r--  1 ice ice    104 May 30 23:07 .coveragerc\ndrwxrwxr-x  2 ice ice      9 May 30 23:07 .devcontainer\n-rw-rw-r--  1 ice ice    170 May 30 23:07 .dockerignore\n-rw-rw-r--  1 ice ice    758 May 30 23:07 .editorconfig\ndrwxrwxr-x  2 ice ice      3 May 30 23:07 .gemini\ndrwxrwxr-x  8 ice ice     13 May 30 23:07 .git\n-rw-rw-r--  1 ice ice    487 May 30 23:07 .gitattributes\ndrwxrwxr-x  8 ice ice     13 May 30 23:07 .github\n-rw-rw-r--  1 ice ice   4327 May 30 23:07 .gitignore\n-rw-rw-r--  1 ice ice      3 May 30 23:07 .nvmrc\ndrwxrwxr-x  2 ice ice      3 May 30 23:07 .vite-hooks\ndrwxrwxr-x  2 ice ice      5 May 30 23:07 .vscode\n-rw-rw-r--  1 ice ice   2002 May 30 23:07 AGENTS.md\n-rw-rw-r--  1 ice ice     56 May 30 23:07 AUTHORS\nlrwxrwxrwx  1 ice ice      9 May 30 23:07 CLAUDE.md -> AGENTS.md\n-rw-rw-r--  1 ice ice   5154 May 30 23:07 CONTRIBUTING.md\n-rw-rw-r--  1 ice ice   1801 May 30 23:07 LICENSE\n-rw-rw-r--  1 ice ice   8680 May 30 23:07 Makefile\n-rw-rw-r--  1 ice ice  14398 May 30 23:07 README.md\ndrwxrwxr-x 31 ice ice     51 May 30 23:07 api\ndrwxrwxr-x  6 ice ice     13 May 30 23:07 cli\n-rw-rw-r--  1 ice ice    508 May 30 23:07 codecov.yml\n-rw-rw-r--  1 ice ice     20 May 30 23:07 depot.json\ndrwxrwxr-x  2 ice ice     13 May 30 23:07 dev\ndrwxrwxr-x  6 ice ice     14 May 30 23:07 dify-agent\ndrwxrwxr-x 13 ice ice     24 May 30 23:07 docker\ndrwxrwxr-x 20 ice ice     21 May 30 23:07 docs\ndrwxrwxr-x  6 ice ice     14 May 30 23:07 e2e\n-rw-rw-r--  1 ice ice 139999 May 30 23:07 eslint-suppressions.json\n-rw-rw-r--  1 ice ice   1762 May 30 23:07 eslint.config.mjs\ndrwxrwxr-x  2 ice ice      5 May 30 23:07 images\n-rw-rw-r--  1 ice ice    975 May 30 23:07 package.json\ndrwxrwxr-x  8 ice ice      8 May 30 23:07 packages\n-rw-rw-r--  1 ice ice 641739 May 30 23:07 pnpm-lock.yaml\n-rw-rw-r--  1 ice ice   6353 May 30 23:07 pnpm-workspace.yaml\ndrwxrwxr-x  3 ice ice      3 May 30 23:07 scripts\ndrwxrwxr-x  4 ice ice      5 May 30 23:07 sdks\n-rw-rw-r--  1 ice ice    203 May 30 23:07 vite.config.ts\ndrwxrwxr-x 29 ice ice     51 May 30 23:07 web", "exit_code": 0, "error": null}

  [Subdirectory context discovered: dify/AGENTS.md]
  # AGENTS.md

  ## Project Overview

  Dify is an open-source platform for developing LLM applications with an intuitive interface combining agentic AI workflows, RAG pipelines, agent capabilities, and model management.

  The codebase is split into:

  - **Backend API** (`/api`): Python Flask application organized with Domain-Driven Design
  - **Frontend Web** (`/web`): Next.js application using TypeScript and React
  - **Docker deployment** (`/docker`): Containerized deployment configurations
  - **Dify Agent Backend** (`/dify-agent`): Backend services for managing and executing agent

  ## Backend Workflow

  - Read `api/AGENTS.md` for details
  - Run backend CLI commands through `uv run --project api <command>`.
  - Integration tests are CI-only and are not expected to run in the local environment.

  ## Frontend Workflow

  - Read `web/AGENTS.md` for details

  ## Testing & Quality Practices

  - Follow TDD: red → green → refactor.
  - Use `pytest` for backend tests with Arrange-Act-Assert structure.
  - Enforce strong typing; avoid `Any` and prefer explicit type annotations.
  - Write self-documenting code; only add comments that explain intent.

  ## Language Style

  - **Python**: Keep type hints on functions and attributes, and implement relevant special methods (e.g., `__repr__`, `__str__`). Prefer `TypedDict` over `dict` or `Mapping` for type safety and better code documentation.
  - **TypeScript**: Use the strict config, rely on ESLint (`pnpm lint:fix` preferred) plus `pnpm type-check`, and avoid `any` types.

  ## General Practices

  - Prefer editing existing files; add new documentation only when requested.
  - Inject dependencies through constructors and preserve clean architecture boundaries.
  - Handle errors with domain-specific exceptions at the correct layer.

  ## Project Conventions

  - Backend architecture adheres to DDD and Clean Architecture principles.
  - Async work runs through Celery with Redis as the broker.
  - Frontend user-facing strings must use `web/i18n/en-US/`; avoid hardcoded text.


session_id: 20260530_230735_c58bbc
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-83e9e6a18b1ca04a", "call_id": "chatcmpl-tool-83e9e6a18b1ca04a", "response_item_id": "fc_chatcmpl-tool-83e9e6a18b1ca04a", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\": \"/home/ice/dify/README.md\"}"}}]

reasoning:
  I have cloned the repository and can see it's a large project. Let me read key files to analyze it: README.md, package.json (or relevant configs), and some core files to understand the tech stack.

reasoning_content:
  I have cloned the repository and can see it's a large project. Let me read key files to analyze it: README.md, package.json (or relevant configs), and some core files to understand the tech stack.


session_id: 20260530_230735_c58bbc
role: tool
tool_call_id: chatcmpl-tool-83e9e6a18b1ca04a
tool_name: read_file
content:
  {"content": "1|![cover-v5-optimized](./images/GitHub_README_if.png)\n2|\n3|<p align=\"center\">\n4|  <a href=\"https://cloud.dify.ai\">Dify Cloud</a> ·\n5|  <a href=\"https://docs.dify.ai/getting-started/install-self-hosted\">Self-hosting</a> ·\n6|  <a href=\"https://docs.dify.ai\">Documentation</a> ·\n7|  <a href=\"https://dify.ai/pricing\">Dify edition overview</a>\n8|</p>\n9|\n10|<p align=\"center\">\n11|    <a href=\"https://dify.ai\" target=\"_blank\">\n12|        <img alt=\"Static Badge\" src=\"https://img.shields.io/badge/Product-F04438\"></a>\n13|    <a href=\"https://dify.ai/pricing\" target=\"_blank\">\n14|        <img alt=\"Static Badge\" src=\"https://img.shields.io/badge/free-pricing?logo=free&color=%20%23155EEF&label=pricing&labelColor=%20%23528bff\"></a>\n15|    <a href=\"https://discord.gg/FngNHpbcY7\" target=\"_blank\">\n16|        <img src=\"https://img.shields.io/discord/1082486657678311454?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb\"\n17|            alt=\"chat on Discord\"></a>\n18|    <a href=\"https://reddit.com/r/difyai\" target=\"_blank\">  \n19|        <img src=\"https://img.shields.io/reddit/subreddit-subscribers/difyai?style=plastic&logo=reddit&label=r%2Fdifyai&labelColor=white\"\n20|            alt=\"join Reddit\"></a>\n21|    <a href=\"https://twitter.com/intent/follow?screen_name=dify_ai\" target=\"_blank\">\n22|        <img src=\"https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5\"\n23|            alt=\"follow on X(Twitter)\"></a>\n24|    <a href=\"https://www.linkedin.com/company/langgenius/\" target=\"_blank\">\n25|        <img src=\"https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff\"\n26|            alt=\"follow on LinkedIn\"></a>\n27|    <a href=\"https://hub.docker.com/u/langgenius\" target=\"_blank\">\n28|        <img alt=\"Docker Pulls\" src=\"https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009\"></a>\n29|    <a href=\"https://github.com/langgenius/dify/graphs/commit-activity\" target=\"_blank\">\n30|        <img alt=\"Commits last month\" src=\"https://img.shields.io/github/commit-activity/m/langgenius/dify?labelColor=%20%2332b583&color=%20%2312b76a\"></a>\n31|    <a href=\"https://github.com/langgenius/dify/\" target=\"_blank\">\n32|        <img alt=\"Issues closed\" src=\"https://img.shields.io/github/issues-search?query=repo%3Alanggenius%2Fdify%20is%3Aclosed&label=issues%20closed&labelColor=%20%237d89b0&color=%20%235d6b98\"></a>\n33|    <a href=\"https://github.com/langgenius/dify/discussions/\" target=\"_blank\">\n34|        <img alt=\"Discussion posts\" src=\"https://img.shields.io/github/discussions/langgenius/dify?labelColor=%20%239b8afb&color=%20%237a5af8\"></a>\n35|    <a href=\"https://insights.linuxfoundation.org/project/langgenius-dify\" target=\"_blank\">\n36|        <img alt=\"LFX Health Score\" src=\"https://insights.linuxfoundation.org/api/badge/health-score?project=langgenius-dify\"></a>\n37|    <a href=\"https://insights.linuxfoundation.org/project/langgenius-dify\" target=\"_blank\">\n38|        <img alt=\"LFX Contributors\" src=\"https://insights.linuxfoundation.org/api/badge/contributors?project=langgenius-dify\"></a>\n39|    <a href=\"https://insights.linuxfoundation.org/project/langgenius-dify\" target=\"_blank\">\n40|        <img alt=\"LFX Active Contributors\" src=\"https://insights.linuxfoundation.org/api/badge/active-contributors?project=langgenius-dify\"></a>\n41|</p>\n42|\n43|<p align=\"center\">\n44|  <a href=\"./README.md\"><img alt=\"README in English\" src=\"https://img.shields.io/badge/English-d9d9d9\"></a>\n45|  <a href=\"./docs/zh-TW/README.md\"><img alt=\"繁體中文文件\" src=\"https://img.shields.io/badge/繁體中文-d9d9d9\"></a>\n46|  <a href=\"./docs/zh-CN/README.md\"><img alt=\"简体中文文件\" src=\"https://img.shields.io/badge/简体中文-d9d9d9\"></a>\n47|  <a href=\"./docs/ja-JP/README.md\"><img alt=\"日本語のREADME\" src=\"https://img.shields.io/badge/日本語-d9d9d9\"></a>\n48|  <a href=\"./docs/es-ES/README.md\"><img alt=\"README en Español\" src=\"https://img.shields.io/badge/Español-d9d9d9\"></a>\n49|  <a href=\"./docs/fr-FR/README.md\"><img alt=\"README en Français\" src=\"https://img.shields.io/badge/Français-d9d9d9\"></a>\n50|  <a href=\"./docs/tlh/README.md\"><img alt=\"README tlhIngan Hol\" src=\"https://img.shields.io/badge/Klingon-d9d9d9\"></a>\n51|  <a href=\"./docs/ko-KR/README.md\"><img alt=\"README in Korean\" src=\"https://img.shields.io/badge/한국어-d9d9d9\"></a>\n52|  <a href=\"./docs/ar-SA/README.md\"><img alt=\"README بالعربية\" src=\"https://img.shields.io/badge/العربية-d9d9d9\"></a>\n53|  <a href=\"./docs/tr-TR/README.md\"><img alt=\"Türkçe README\" src=\"https://img.shields.io/badge/Türkçe-d9d9d9\"></a>\n54|  <a href=\"./docs/vi-VN/README.md\"><img alt=\"README Tiếng Việt\" src=\"https://img.shields.io/badge/Ti%E1%BA%BFng%20Vi%E1%BB%87t-d9d9d9\"></a>\n55|  <a href=\"./docs/de-DE/README.md\"><img alt=\"README in Deutsch\" src=\"https://img.shields.io/badge/German-d9d9d9\"></a>\n56|  <a href=\"./docs/it-IT/README.md\"><img alt=\"README in Italiano\" src=\"https://img.shields.io/badge/Italiano-d9d9d9\"></a>\n57|  <a href=\"./docs/pt-BR/README.md\"><img alt=\"README em Português do Brasil\" src=\"https://img.shields.io/badge/Portugu%C3%AAs%20do%20Brasil-d9d9d9\"></a>\n58|  <a href=\"./docs/sl-SI/README.md\"><img alt=\"README Slovenščina\" src=\"https://img.shields.io/badge/Sloven%C5%A1%C4%8Dina-d9d9d9\"></a>\n59|  <a href=\"./docs/bn-BD/README.md\"><img alt=\"README in বাংলা\" src=\"https://img.shields.io/badge/বাংলা-d9d9d9\"></a>\n60|  <a href=\"./docs/hi-IN/README.md\"><img alt=\"README in हिन्दी\" src=\"https://img.shields.io/badge/Hindi-d9d9d9\"></a>\n61|</p>\n62|\n63|Dify is an open-source LLM app development platform. Its intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features (including [Opik](https://www.comet.com/docs/opik/integrations/dify), [Langfuse](https://docs.langfuse.com), and [Arize Phoenix](https://docs.arize.com/phoenix)) and more, letting you quickly go from prototype to production. Here's a list of the core features:\n64|\n65|## Quick start\n66|\n67|> Before installing Dify, make sure your machine meets the following minimum system requirements:\n68|>\n69|> - CPU >= 2 Core\n70|> - RAM >= 4 GiB\n71|\n72|<br/>\n73|\n74|The easiest way to start the Dify server is through [Docker Compose](docker/docker-compose.yaml). Before running Dify with the following commands, make sure that [Docker](https://docs.docker.com/get-docker/) and [Docker Compose](https://docs.docker.com/compose/install/) are installed on your machine:\n75|\n76|```bash\n77|cd dify\n78|cd docker\n79|cp .env.example .env\n80|docker compose up -d\n81|```\n82|\n83|After running, you can access the Dify dashboard in your browser at [http://localhost/install](http://localhost/install) and start the initialization process.\n84|\n85|#### Seeking help\n86|\n87|Please refer to our [FAQ](https://docs.dify.ai/getting-started/install-self-hosted/faqs) if you encounter problems setting up Dify. Reach out to [the community and us](#community--contact) if you are still having issues.\n88|\n89|> If you'd like to contribute to Dify or do additional development, refer to our [guide to deploying from source code](https://docs.dify.ai/getting-started/install-self-hosted/local-source-code)\n90|\n91|## Key features\n92|\n93|**1. Workflow**:\n94|Build and test powerful AI workflows on a visual canvas, leveraging all the following features and beyond.\n95|\n96|**2. Comprehensive model support**:\n97|Seamless integration with hundreds of proprietary / open-source LLMs from dozens of inference providers and self-hosted solutions, covering GPT, Mistral, Llama3, and any OpenAI API-compatible models. A full list of supported model providers can be found [here](https://docs.dify.ai/getting-started/readme/model-providers).\n98|\n99|![providers-v5](https://github.com/langgenius/dify/assets/13230914/5a17bdbe-097a-4100-8363-40255b70f6e3)\n100|\n101|**3. Prompt IDE**:\n102|Intuitive interface for crafting prompts, comparing model performance, and adding additional features such as text-to-speech to a chat-based app.\n103|\n104|**4. RAG Pipeline**:\n105|Extensive RAG capabilities that cover everything from document ingestion to retrieval, with out-of-box support for text extraction from PDFs, PPTs, and other common document formats.\n106|\n107|**5. Agent capabilities**:\n108|You can define agents based on LLM Function Calling or ReAct, and add pre-built or custom tools for the agent. Dify provides 50+ built-in tools for AI agents, such as Google Search, DALL·E, Stable Diffusion and WolframAlpha.\n109|\n110|**6. LLMOps**:\n111|Monitor and analyze application logs and performance over time. You could continuously improve prompts, datasets, and models based on production data and annotations.\n112|\n113|**7. Backend-as-a-Service**:\n114|All of Dify's offerings come with corresponding APIs, so you could effortlessly integrate Dify into your own business logic.\n115|\n116|## Using Dify\n117|\n118|- **Cloud <br/>**\n119|  We host a [Dify Cloud](https://dify.ai) service for anyone to try with zero setup. It provides all the capabilities of the self-deployed version, and includes 200 free GPT-4 calls in the sandbox plan.\n120|\n121|- **Self-hosting Dify Community Edition<br/>**\n122|  Quickly get Dify running in your environment with this [starter guide](#quick-start).\n123|  Use our [documentation](https://docs.dify.ai) for further references and more in-depth instructions.\n124|\n125|- **Dify for enterprise / organizations<br/>**\n126|  We provide additional enterprise-centric features. [Send us an email](mailto:business@dify.ai?subject=%5BGitHub%5DBusiness%20License%20Inquiry) to discuss your enterprise needs. <br/>\n127|\n128|  > For startups and small businesses using AWS, check out [Dify Premium on AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6) and deploy it to your own AWS VPC with one click. It's an affordable AMI offering with the option to create apps with custom logo and branding.\n129|\n130|## Staying ahead\n131|\n132|Star Dify on GitHub and be instantly notified of new releases.\n133|\n134|![star-us](https://github.com/langgenius/dify/assets/13230914/b823edc1-6388-4e25-ad45-2f6b187adbb4)\n135|\n136|## Advanced Setup\n137|\n138|### Custom configurations\n139|\n140|If you need to customize the configuration, edit `docker/.env`. The essential startup defaults live in [`docker/.env.example`](docker/.env.example), and optional advanced variables are split under `docker/envs/` by theme. After making any changes, re-run `docker compose up -d` from the `docker` directory. You can find the full list of available environment variables [here](https://docs.dify.ai/getting-started/install-self-hosted/environments).\n141|\n142|### Metrics Monitoring with Grafana\n143|\n144|Import the dashboard to Grafana, using Dify's PostgreSQL database as data source, to monitor metrics in granularity of apps, tenants, messages, and more.\n145|\n146|- [Grafana Dashboard by @bowenliang123](https://github.com/bowenliang123/dify-grafana-dashboard)\n147|\n148|### Deployment with Kubernetes\n149|\n150|If you'd like to configure a highly available setup, there are community-contributed [Helm Charts](https://helm.sh/) and YAML files which allow Dify to be deployed on Kubernetes.\n151|\n152|- [Helm Chart by @LeoQuote](https://github.com/douban/charts/tree/master/charts/dify)\n153|- [Helm Chart by @BorisPolonsky](https://github.com/BorisPolonsky/dify-helm)\n154|- [Helm Chart by @magicsong](https://github.com/magicsong/ai-charts)\n155|- [YAML file by @Winson-030](https://github.com/Winson-030/dify-kubernetes)\n156|- [YAML file by @wyy-holding](https://github.com/wyy-holding/dify-k8s)\n157|- [🚀 NEW! YAML files (Supports Dify v1.6.0) by @Zhoneym](https://github.com/Zhoneym/DifyAI-Kubernetes)\n158|\n159|#### Using Terraform for Deployment\n160|\n161|Deploy Dify to Cloud Platform with a single click using [terraform](https://www.terraform.io/)\n162|\n163|##### Azure Global\n164|\n165|- [Azure Terraform by @nikawang](https://github.com/nikawang/dify-azure-terraform)\n166|\n167|##### Google Cloud\n168|\n169|- [Google Cloud Terraform by @sotazum](https://github.com/DeNA/dify-google-cloud-terraform)\n170|\n171|#### Using AWS CDK for Deployment\n172|\n173|Deploy Dify to AWS with [CDK](https://aws.amazon.com/cdk/)\n174|\n175|##### AWS\n176|\n177|- [AWS CDK by @KevinZhao (EKS based)](https://github.com/aws-samples/solution-for-deploying-dify-on-aws)\n178|- [AWS CDK by @tmokmss (ECS based)](https://github.com/aws-samples/dify-self-hosted-on-aws)\n179|\n180|#### Using Alibaba Cloud Computing Nest\n181|\n182|Quickly deploy Dify to Alibaba cloud with [Alibaba Cloud Computing Nest](https://computenest.console.aliyun.com/service/instance/create/default?type=user&ServiceName=Dify%E7%A4%BE%E5%8C%BA%E7%89%88)\n183|\n184|#### Using Alibaba Cloud Data Management\n185|\n186|One-Click deploy Dify to Alibaba Cloud with [Alibaba Cloud Data Management](https://www.alibabacloud.com/help/en/dms/dify-in-invitational-preview/)\n187|\n188|#### Deploy to AKS with Azure Devops Pipeline\n189|\n190|One-Click deploy Dify to AKS with [Azure Devops Pipeline Helm Chart by @LeoZhang](https://github.com/Ruiruiz30/Dify-helm-chart-AKS)\n191|\n192|## Contributing\n193|\n194|For those who'd like to contribute code, see our [Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).\n195|At the same time, please consider supporting Dify by sharing it on social media and at events and conferences.\n196|\n197|> We are looking for contributors to help translate Dify into languages other than Mandarin or English. If you are interested in helping, please see the [i18n README](https://github.com/langgenius/dify/blob/main/web/i18n-config/README.md) for more information, and leave us a comment in the `global-users` channel of our [Discord Community Server](https://discord.gg/8Tpq4AcN9c).\n198|\n199|## Community & contact\n200|\n201|- [GitHub Discussion](https://github.com/langgenius/dify/discussions). Best for: sharing feedback and asking questions.\n202|- [GitHub Issues](https://github.com/langgenius/dify/issues). Best for: bugs you encounter using Dify.AI, and feature proposals. See our [Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).\n203|- [Discord](https://discord.gg/FngNHpbcY7). Best for: sharing your applications and hanging out with the community.\n204|- [X(Twitter)](https://twitter.com/dify_ai). Best for: sharing your applications and hanging out with the community.\n205|\n206|**Contributors**\n207|\n208|<a href=\"https://github.com/langgenius/dify/graphs/contributors\">\n209|  <img src=\"https://contrib.rocks/image?repo=langgenius/dify\" />\n210|</a>\n211|\n212|## Star history\n213|\n214|[![Star History Chart](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)\n215|\n216|## Security disclosure\n217|\n218|To protect your privacy, please avoid posting security issues on GitHub. Instead, report issues to security@dify.ai, and our team will respond with detailed answer.\n219|\n220|## License\n221|\n222|This repository is licensed under the [Dify Open Source License](LICENSE), based on Apache 2.0 with additional conditions.\n223|", "total_lines": 222, "file_size": 14398, "truncated": false, "is_binary": false, "is_image": false}


session_id: 20260530_230735_c58bbc
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-a39daabe53f92476", "call_id": "chatcmpl-tool-a39daabe53f92476", "response_item_id": "fc_chatcmpl-tool-a39daabe53f92476", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\": \"/home/ice/dify/package.json\"}"}}, {"id": "chatcmpl-tool-b64373e04c5f7711", "call_id": "chatcmpl-tool-b64373e04c5f7711", "response_item_id": "fc_chatcmpl-tool-b64373e04c5f7711", "type": "function", "function": {"name": "read_file", "arguments": "{\"path\": \"/home/ice/dify/pyproject.toml\"}"}}]

reasoning:
  Let me gather more details about the structure, tech stack, and specific features to provide a comprehensive analysis. I'll read package.json for frontend tech and api structure for backend.

reasoning_content:
  Let me gather more details about the structure, tech stack, and specific features to provide a comprehensive analysis. I'll read package.json for frontend tech and api structure for backend.


session_id: 20260530_230735_c58bbc
role: tool
tool_call_id: chatcmpl-tool-a39daabe53f92476
tool_name: read_file
content:
  {"content": "1|{\n2|  \"name\": \"dify\",\n3|  \"type\": \"module\",\n4|  \"private\": true,\n5|  \"packageManager\": \"pnpm@11.2.2\",\n6|  \"devEngines\": {\n7|    \"runtime\": {\n8|      \"name\": \"node\",\n9|      \"version\": \"^22.22.1\",\n10|      \"onFail\": \"download\"\n11|    }\n12|  },\n13|  \"engines\": {\n14|    \"node\": \"^22.22.1\"\n15|  },\n16|  \"scripts\": {\n17|    \"dev\": \"concurrently -k -n vinext,proxy \\\"vp run dify-web#dev:vinext\\\" \\\"vp run dify-web#dev:proxy\\\"\",\n18|    \"prepare\": \"vp config\",\n19|    \"type-check\": \"vp run -r type-check\",\n20|    \"lint\": \"eslint --cache --concurrency=auto\",\n21|    \"lint:ci\": \"eslint --cache --cache-strategy content --concurrency 2\",\n22|    \"lint:fix\": \"vp run lint --fix\",\n23|    \"lint:quiet\": \"vp run lint --quiet\"\n24|  },\n25|  \"devDependencies\": {\n26|    \"@antfu/eslint-config\": \"catalog:\",\n27|    \"concurrently\": \"catalog:\",\n28|    \"eslint\": \"catalog:\",\n29|    \"eslint-markdown\": \"catalog:\",\n30|    \"eslint-plugin-markdown-preferences\": \"catalog:\",\n31|    \"eslint-plugin-no-barrel-files\": \"catalog:\",\n32|    \"vite\": \"catalog:\",\n33|    \"vite-plus\": \"catalog:\"\n34|  }\n35|}\n36|", "total_lines": 35, "file_size": 975, "truncated": false, "is_binary": false, "is_image": false}


session_id: 20260530_230735_c58bbc
role: tool
tool_call_id: chatcmpl-tool-b64373e04c5f7711
tool_name: read_file
content:
  {"content": "", "total_lines": 0, "file_size": 0, "truncated": false, "is_binary": false, "is_image": false, "error": "File not found: /home/ice/dify/pyproject.toml"}


session_id: 20260530_230735_c58bbc
role: assistant
finish_reason: tool_calls
tool_calls:
  [{"id": "chatcmpl-tool-a8a73242699947e2", "call_id": "chatcmpl-tool-a8a73242699947e2", "response_item_id": "fc_chatcmpl-tool-a8a73242699947e2", "type": "function", "function": {"name": "search_files", "arguments": "{\"path\": \"/home/ice/dify/api\", \"pattern\": \"pyproject.toml\", \"target\": \"files\"}"}}]

reasoning:
  O pyproject.toml não está na raiz. O backend deve estar na pasta /api. Vou procurar arquivos de configuração do Python lá.

reasoning_content:
  O pyproject.toml não está na raiz. O backend deve estar na pasta /api. Vou procurar arquivos de configuração do Python lá.


session_id: 20260530_230735_c58bbc
role: tool
tool_call_id: chatcmpl-tool-a8a73242699947e2
tool_name: search_files
content:
  {"total_count": 39, "files": ["/home/ice/dify/api/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-weaviate/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-vikingdb/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-vastbase/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-upstash/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-tidb-vector/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-tidb-on-qdrant/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-tencent/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-tablestore/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-relyt/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-qdrant/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-pgvector/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-pgvecto-rs/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-oracle/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-opensearch/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-opengauss/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-oceanbase/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-myscale/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-milvus/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-matrixone/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-lindorm/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-iris/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-huawei-cloud/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-hologres/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-elasticsearch/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-couchbase/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-clickzetta/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-chroma/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-baidu/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-analyticdb/pyproject.toml", "/home/ice/dify/api/providers/vdb/vdb-alibabacloud-mysql/pyproject.toml", "/home/ice/dify/api/providers/trace/trace-weave/pyproject.toml", "/home/ice/dify/api/providers/trace/trace-tencent/pyproject.toml", "/home/ice/dify/api/providers/trace/trace-opik/pyproject.toml", "/home/ice/dify/api/providers/trace/trace-mlflow/pyproject.toml", "/home/ice/dify/api/providers/trace/trace-langsmith/pyproject.toml", "/home/ice/dify/api/providers/trace/trace-langfuse/pyproject.toml", "/home/ice/dify/api/providers/trace/trace-arize-phoenix/pyproject.toml", "/home/ice/dify/api/providers/trace/trace-aliyun/pyproject.toml"]}

  [Subdirectory context discovered: dify/api/AGENTS.md]
  # API Agent Guide

  ## Notes for Agent (must-check)

  Before changing any backend code under `api/`, you MUST read the surrounding docstrings and comments. These notes contain required context (invariants, edge cases, trade-offs) and are treated as part of the spec.

  Look for:

  - The module (file) docstring at the top of a source code file
  - Docstrings on classes and functions/methods
  - Paragraph/block comments for non-obvious logic

  ### What to write where

  - Keep notes scoped: module notes cover module-wide context, class notes cover class-wide context, function/method notes cover behavioural contracts, and paragraph/block comments cover local “why”. Avoid duplicating the same content across scopes unless repetition prevents misuse.
  - **Module (file) docstring**: purpose, boundaries, key invariants, and “gotchas” that a new reader must know before editing.
    - Include cross-links to the key collaborators (modules/services) when discovery is otherwise hard.
    - Prefer stable facts (invariants, contracts) over ephemeral “today we…” notes.
  - **Class docstring**: responsibility, lifecycle, invariants, and how it should be used (or not used).
    - If the class is intentionally stateful, note what state exists and what methods mutate it.
    - If concurrency/async assumptions matter, state them explicitly.
  - **Function/method docstring**: behavioural contract.
    - Document arguments, return shape, side effects (DB writes, external I/O, task dispatch), and raised domain exceptions.
    - Add examples only when they prevent misuse.
  - **Paragraph/block comments**: explain *why* (trade-offs, historical constraints, surprising edge cases), not what the code already states.
    - Keep comments adjacent to the logic they justify; delete or rewrite comments that no longer match reality.

  ### Rules (must follow)

  In this section, “notes” means module/class/function docstrings plus any relevant paragraph/block comments.

  - **Before working**
    - Read the notes in the area you’ll touch; treat them as part of the spec.
    - If a docstring or comment conflicts with the current code, treat the **code as the single source of truth** and update the docstring or comment to match reality.
    - If important intent/invariants/edge cases are missing, add them in the closest docstring or comment (module for overall scope, function for behaviour).
  - **During working**
    - Keep the notes in sync as you discover constraints, make decisions, or change approach.
    - If you move/rename responsibilities across modules/classes, update the affected docstrings and comments so readers can still find the “why” and the invariants.
    - Record non-obvious edge cases, trade-offs, and the test/verification plan in the nearest docstring or comment that will stay correct.
    - Keep the notes **coherent**: integrate new findings into the relevant docstrings and comments; avoid append-only “recent fix” / changelog-style additions.
  - **When finishing**
    - Update the notes to reflect what changed, why, and any new edge cases/tests.
    - Remove or rewrite any comments that could be mistaken as current guidance but no longer apply.
    - Keep docstrings and comments concise and accurate; they are meant to prevent repeated rediscovery.

  ## Coding Style

  This is the default standard for backend code in this repo. Follow it for new code and use it as the checklist when reviewing changes.

  ### Linting & Formatting

  - Use Ruff for formatting and linting (follow `.ruff.toml`).
  - Keep each line under 120 characters (including spaces).

  ### Naming Conventions

  - Use `snake_case` for variables and functions.
  - Use `PascalCase` for classes.
  - Use `UPPER_CASE` for constants.

  ### Typing & Class Layout

  - Code should usually include type annotations that match the repo’s current Python version (avoid untyped public APIs and “mystery” values).
  - Prefer modern typing forms (e.g. `list[str]`, `dict[str, int]`) and avoid `Any` unless there’s a strong reason.
  - For dictionary-like data with known keys and value types, prefer `TypedDict` over `dict[...]` or `Mapping[...]`.
  - For optional keys in typed payloads, use `NotRequired[...]` (or `total=False` when most fields are optional).
  - Keep `dict[...]` / `Mapping[...]` for truly dynamic key spaces where the key set is unknown.

  ```python
  from datetime import datetime
  from typing import NotRequired, TypedDict


  class UserProfile(TypedDict):
      user_id: str
      email: str
      created_at: datetime
      nickname: NotRequired[str]
  ```

  - For classes, declare all member variables explicitly with types at the top of the class body (before `__init__`), even when the class is not a dataclass or Pydantic model, so the class shape is obvious at a glance:

  ```python
  from datetime import datetime


  class Example:
      user_id: str
      created_at: datetime

      def __init__(self, user_id: str, created_at: datetime) -> None:
          self.user_id = user_id
          self.created_at = created_at
  ```

  ### General Rules

  - Use Pydantic v2 conventions.
  - Use `uv` for Python package management in this repo (usually with `--project api`).
  - Prefer simple functions over small “utility classes” for lightweight helpers.
  - Avoid implementing dunder methods unless it’s clearly needed and matches existing patterns.
  - Never start long-running services as part of agent work (`uv run app.py`, `flask run`, etc.); running tests is allowed.
  - Keep files below ~800 lines; split when necessary.
  - Keep code readable and explicit—avoid clever hacks.

  ### Architecture & Boundaries

  - Mirror the layered architecture: controller → service → core/domain.
  - Reuse existing helpers in `core/`, `services/`, and `libs/` before creating new abstractions.
  - Optimise for observability: deterministic control flow, clear logging, actionable errors.

  ### Logging & Errors

  - Never use `print`; use a module-level logger:
    - `logger = logging.getLogger(__name__)`
  - Include tenant/app/workflow identifiers in log context when relevant.
  - Raise domain-specific exceptions (`services/errors`, `core/errors`) and translate them into HTTP responses in controllers.
  - Log retryable events at `warning`, terminal failures at `error`.

  ### SQLAlchemy Patterns

  - Models inherit from `models.base.TypeBase`; do not create ad-hoc metadata or engines.
  - Open sessions with context managers:

  ```python
  from sqlalchemy.orm import Session

  with Session(db.engine, expire_on_commit=False) as session:
      stmt = select(Workflow).where(
          Workflow.id == workflow_id,
          Workflow.tenant_id == tenant_id,
      )
      workflow = session.execute(stmt).scalar_one_or_none()
  ```

  - Prefer SQLAlchemy expressions; avoid raw SQL unless necessary.
  - Always scope queries by `tenant_id` and protect write paths with safeguards (`FOR UPDATE`, row counts, etc.).
  - Introduce repository abstractions only for very large tables (e.g., workflow executions) or when alternative storage strategies are required.

  ### Storage & External I/O

  - Access storage via `extensions.ext_storage.storage`.
  - Use `core.helper.ssrf_proxy` for outbound HTTP fetches.
  - Background tasks that touch storage must be idempotent, and should log relevant object identifiers.

  ### Pydantic Usage

  - Define DTOs with Pydantic v2 models and forbid extras by default.
  - Use `@field_validator` / `@model_validator` for domain rules.

  Example:

  ```python
  from pydantic import BaseModel, ConfigDict, HttpUrl, field_validator


  class TriggerConfig(BaseModel):
      endpoint: HttpUrl
      secret: str

      model_config = ConfigDict(extra="forbid")

      @field_validator("secret")
      def ensure_secret_prefix(cls, value: str) -> str:
          if not value.startswith("dify_"):
              raise ValueError("secret must start with dify_")
          return value
  ```

  ### Generics & Protocols

  - Use `typing.Protocol` to define behavioural contracts (e.g., cache interfaces).
  - Apply generics (`TypeVar`, `Generic`) for reusable utilities like caches or providers.
  - Validate dynamic inputs at runtime when generics cannot enforce safet

  [...truncated AGENTS.md: 9,668 chars total]


