{ "data": { "edges": [ { "animated": false, "className": "", "data": { "sourceHandle": { "dataType": "ChatInput", "id": "ChatInput-SzjnT", "name": "message", "output_types": [ "Message" ] }, "targetHandle": { "fieldName": "input_value", "id": "LanguageModelComponent-kBOja", "inputTypes": [ "Message" ], "type": "str" } }, "id": "reactflow__edge-ChatInput-SzjnT{œdataTypeœ:œChatInputœ,œidœ:œChatInput-SzjnTœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-LanguageModelComponent-kBOja{œfieldNameœ:œinput_valueœ,œidœ:œLanguageModelComponent-kBOjaœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", "selected": false, "source": "ChatInput-SzjnT", "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-SzjnTœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", "target": "LanguageModelComponent-kBOja", "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œLanguageModelComponent-kBOjaœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" }, { "animated": false, "className": "", "data": { "sourceHandle": { "dataType": "LanguageModelComponent", "id": "LanguageModelComponent-kBOja", "name": "text_output", "output_types": [ "Message" ] }, "targetHandle": { "fieldName": "input_value", "id": "ChatOutput-8ZWWB", "inputTypes": [ "Data", "DataFrame", "Message" ], "type": "str" } }, "id": "reactflow__edge-LanguageModelComponent-kBOja{œdataTypeœ:œLanguageModelComponentœ,œidœ:œLanguageModelComponent-kBOjaœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-8ZWWB{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-8ZWWBœ,œinputTypesœ:[œDataœ,œDataFrameœ,œMessageœ],œtypeœ:œstrœ}", "selected": false, "source": "LanguageModelComponent-kBOja", "sourceHandle": "{œdataTypeœ: œLanguageModelComponentœ, œidœ: œLanguageModelComponent-kBOjaœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", "target": "ChatOutput-8ZWWB", "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-8ZWWBœ, œinputTypesœ: [œDataœ, œDataFrameœ, œMessageœ], œtypeœ: œstrœ}" }, { "animated": false, "data": { "sourceHandle": { "dataType": "Prompt", "id": "Prompt-tOH5D", "name": "prompt", "output_types": [ "Message" ] }, "targetHandle": { "fieldName": "system_message", "id": "LanguageModelComponent-kBOja", "inputTypes": [ "Message" ], "type": "str" } }, "id": "xy-edge__Prompt-tOH5D{œdataTypeœ:œPromptœ,œidœ:œPrompt-tOH5Dœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-LanguageModelComponent-kBOja{œfieldNameœ:œsystem_messageœ,œidœ:œLanguageModelComponent-kBOjaœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", "selected": false, "source": "Prompt-tOH5D", "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-tOH5Dœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", "target": "LanguageModelComponent-kBOja", "targetHandle": "{œfieldNameœ: œsystem_messageœ, œidœ: œLanguageModelComponent-kBOjaœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" } ], "nodes": [ { "data": { "description": "Get chat inputs from the Playground.", "display_name": "Chat Input", "id": "ChatInput-SzjnT", "node": { "base_classes": [ "Message" ], "beta": false, "conditional_paths": [], "custom_fields": {}, "description": "Get chat inputs from the Playground.", "display_name": "Chat Input", "documentation": "", "edited": false, "field_order": [ "input_value", "store_message", "sender", "sender_name", "session_id", "files" ], "frozen": false, "icon": "MessagesSquare", "legacy": false, "lf_version": "1.4.2", "metadata": {}, "output_types": [], "outputs": [ { "allows_loop": false, "cache": true, "display_name": "Chat Message", "group_outputs": false, "method": "message_response", "name": "message", "selected": "Message", "tool_mode": true, "types": [ "Message" ], "value": "__UNDEFINED__" } ], "pinned": false, "template": { "_type": "Component", "code": { "advanced": true, "dynamic": true, "fileTypes": [], "file_path": "", "info": "", "list": false, "load_from_db": false, "multiline": true, "name": "code", "password": false, "placeholder": "", "required": true, "show": true, "title_case": false, "type": "code", "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.inputs.inputs import BoolInput\nfrom langflow.io import (\n DropdownInput,\n FileInput,\n MessageTextInput,\n MultilineInput,\n Output,\n)\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import (\n MESSAGE_SENDER_AI,\n MESSAGE_SENDER_NAME_USER,\n MESSAGE_SENDER_USER,\n)\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n documentation: str = \"https://docs.langflow.org/components-io#chat-input\"\n icon = \"MessagesSquare\"\n name = \"ChatInput\"\n minimized = True\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Input Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n input_types=[],\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_USER,\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_USER,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n temp_file=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Chat Message\", name=\"message\", method=\"message_response\"),\n ]\n\n async def message_response(self) -> Message:\n # Ensure files is a list and filter out empty/None values\n files = self.files if self.files else []\n if files and not isinstance(files, list):\n files = [files]\n files = [f for f in files if f is not None and f != \"\"]\n\n message = await Message.create(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=files,\n )\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = await self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n" }, "files": { "advanced": true, "display_name": "Files", "dynamic": false, "fileTypes": [ "csv", "json", "pdf", "txt", "md", "mdx", "yaml", "yml", "xml", "html", "htm", "docx", "py", "sh", "sql", "js", "ts", "tsx", "jpg", "jpeg", "png", "bmp", "image" ], "file_path": "", "info": "Files to be sent with the message.", "list": true, "name": "files", "placeholder": "", "required": false, "show": true, "temp_file": true, "title_case": false, "trace_as_metadata": true, "type": "file", "value": "" }, "input_value": { "advanced": false, "display_name": "Input Text", "dynamic": false, "info": "Message to be passed as input.", "input_types": [], "list": false, "load_from_db": false, "multiline": true, "name": "input_value", "placeholder": "", "required": false, "show": true, "title_case": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "Hello" }, "sender": { "advanced": true, "display_name": "Sender Type", "dynamic": false, "info": "Type of sender.", "name": "sender", "options": [ "Machine", "User" ], "placeholder": "", "required": false, "show": true, "title_case": false, "trace_as_metadata": true, "type": "str", "value": "User" }, "sender_name": { "advanced": true, "display_name": "Sender Name", "dynamic": false, "info": "Name of the sender.", "input_types": [ "Message" ], "list": false, "load_from_db": false, "name": "sender_name", "placeholder": "", "required": false, "show": true, "title_case": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "User" }, "session_id": { "advanced": true, "display_name": "Session ID", "dynamic": false, "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", "input_types": [ "Message" ], "list": false, "load_from_db": false, "name": "session_id", "placeholder": "", "required": false, "show": true, "title_case": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "" }, "should_store_message": { "_input_type": "BoolInput", "advanced": true, "display_name": "Store Messages", "dynamic": false, "info": "Store the message in the history.", "list": false, "name": "should_store_message", "placeholder": "", "required": false, "show": true, "title_case": false, "trace_as_metadata": true, "type": "bool", "value": true } } }, "selected_output": "message", "type": "ChatInput" }, "dragging": false, "height": 234, "id": "ChatInput-SzjnT", "measured": { "height": 234, "width": 320 }, "position": { "x": 689.5720422421635, "y": 765.155834131403 }, "positionAbsolute": { "x": 689.5720422421635, "y": 765.155834131403 }, "selected": false, "type": "genericNode", "width": 320 }, { "data": { "description": "Create a prompt template with dynamic variables.", "display_name": "Prompt", "id": "Prompt-tOH5D", "node": { "base_classes": [ "Message" ], "beta": false, "conditional_paths": [], "custom_fields": { "template": [] }, "description": "Create a prompt template with dynamic variables.", "display_name": "Prompt", "documentation": "", "edited": false, "field_order": [ "template" ], "frozen": false, "icon": "braces", "legacy": false, "lf_version": "1.4.2", "metadata": { "code_hash": "3bf0b511e227", "module": "langflow.components.prompts.prompt.PromptComponent" }, "output_types": [], "outputs": [ { "allows_loop": false, "cache": true, "display_name": "Prompt", "group_outputs": false, "method": "build_prompt", "name": "prompt", "selected": "Message", "tool_mode": true, "types": [ "Message" ], "value": "__UNDEFINED__" } ], "pinned": false, "template": { "_type": "Component", "code": { "advanced": true, "dynamic": true, "fileTypes": [], "file_path": "", "info": "", "list": false, "load_from_db": false, "multiline": true, "name": "code", "password": false, "placeholder": "", "required": true, "show": true, "title_case": false, "type": "code", "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom.custom_component.component import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"braces\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def update_frontend_node(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().update_frontend_node(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "template": { "_input_type": "PromptInput", "advanced": false, "display_name": "Template", "dynamic": false, "info": "", "list": false, "load_from_db": false, "name": "template", "placeholder": "", "required": false, "show": true, "title_case": false, "tool_mode": false, "trace_as_input": true, "type": "prompt", "value": "Answer the user as if you were a GenAI expert, enthusiastic about helping them get started building something fresh." }, "tool_placeholder": { "_input_type": "MessageTextInput", "advanced": true, "display_name": "Tool Placeholder", "dynamic": false, "info": "A placeholder input for tool mode.", "input_types": [ "Message" ], "list": false, "load_from_db": false, "name": "tool_placeholder", "placeholder": "", "required": false, "show": true, "title_case": false, "tool_mode": true, "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "" } }, "tool_mode": false }, "selected_output": "prompt", "type": "Prompt" }, "dragging": false, "height": 260, "id": "Prompt-tOH5D", "measured": { "height": 260, "width": 320 }, "position": { "x": 688.9222183027662, "y": 1044.5004597498394 }, "positionAbsolute": { "x": 690.2015147036818, "y": 1018.5443911764344 }, "selected": false, "type": "genericNode", "width": 320 }, { "data": { "id": "undefined-qkI8p", "node": { "description": "This template demonstrates a standard chat flow with additional instructions provided by a prompt. Prompts provide instructions and inputs for a Large Language Model (LLM) beyond the standard user-provided chat input. In this example, the prompt describes the LLM's role and persona.\n\n## Quick Start\n1. Add your **OpenAI API Key** to the **Language Model** component, or select a different provider and model.\n2. Open the **Playground** to start the chat and run the flow.\n\n## Next steps\nChange the prompt template, model, or model settings, such as **Temperature**, and then see how the responses change with these different inputs.\n💡 Some component settings are hidden by default; to view all settings click **Controls** in each component's header menu.\n💡 You can use curly braces to create variables in your template, such as `{variable}`. These can be populated from other components, with Langflow global variables, or at runtime.", "display_name": "Read Me", "documentation": "", "template": { "backgroundColor": "neutral" } } }, "dragging": false, "height": 403, "id": "undefined-qkI8p", "measured": { "height": 403, "width": 324 }, "position": { "x": 309.22132329147314, "y": 803.5424763412283 }, "positionAbsolute": { "x": 66.38770028934243, "y": 749.744424427066 }, "resizing": false, "selected": false, "style": { "height": 250, "width": 324 }, "type": "noteNode", "width": 324 }, { "data": { "id": "note-CLC7a", "node": { "description": "### Configure your Model Provider", "display_name": "", "documentation": "", "template": { "backgroundColor": "transparent" } }, "type": "note" }, "dragging": false, "height": 324, "id": "note-CLC7a", "measured": { "height": 324, "width": 324 }, "position": { "x": 1080.9467591245357, "y": 744.1979207661088 }, "positionAbsolute": { "x": 1075.829573520873, "y": 657.2057655038416 }, "resizing": false, "selected": false, "style": { "height": 324, "width": 324 }, "type": "noteNode", "width": 324 }, { "data": { "id": "ChatOutput-8ZWWB", "node": { "base_classes": [ "Message" ], "beta": false, "conditional_paths": [], "custom_fields": {}, "description": "Display a chat message in the Playground.", "display_name": "Chat Output", "documentation": "", "edited": false, "field_order": [ "input_value", "should_store_message", "sender", "sender_name", "session_id", "data_template", "background_color", "chat_icon", "text_color" ], "frozen": false, "icon": "MessagesSquare", "legacy": false, "lf_version": "1.4.2", "metadata": {}, "output_types": [], "outputs": [ { "allows_loop": false, "cache": true, "display_name": "Output Message", "group_outputs": false, "method": "message_response", "name": "message", "selected": "Message", "tool_mode": true, "types": [ "Message" ], "value": "__UNDEFINED__" } ], "pinned": false, "template": { "_type": "Component", "code": { "advanced": true, "dynamic": true, "fileTypes": [], "file_path": "", "info": "", "list": false, "load_from_db": false, "multiline": true, "name": "code", "password": false, "placeholder": "", "required": true, "show": true, "title_case": false, "type": "code", "value": "from collections.abc import Generator\nfrom typing import Any\n\nimport orjson\nfrom fastapi.encoders import jsonable_encoder\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.helpers.data import safe_convert\nfrom langflow.inputs.inputs import BoolInput, DropdownInput, HandleInput, MessageTextInput\nfrom langflow.schema.data import Data\nfrom langflow.schema.dataframe import DataFrame\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.template.field.base import Output\nfrom langflow.utils.constants import (\n MESSAGE_SENDER_AI,\n MESSAGE_SENDER_NAME_AI,\n MESSAGE_SENDER_USER,\n)\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n documentation: str = \"https://docs.langflow.org/components-io#chat-output\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n minimized = True\n\n inputs = [\n HandleInput(\n name=\"input_value\",\n display_name=\"Inputs\",\n info=\"Message to be passed as output.\",\n input_types=[\"Data\", \"DataFrame\", \"Message\"],\n required=True,\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(\n display_name=\"Output Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, id_: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if id_:\n source_dict[\"id\"] = id_\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n # Handle case where source is a ChatOpenAI object\n if hasattr(source, \"model_name\"):\n source_dict[\"source\"] = source.model_name\n elif hasattr(source, \"model\"):\n source_dict[\"source\"] = str(source.model)\n else:\n source_dict[\"source\"] = str(source)\n return Source(**source_dict)\n\n async def message_response(self) -> Message:\n # First convert the input to string if needed\n text = self.convert_to_string()\n\n # Get source properties\n source, icon, display_name, source_id = self.get_properties_from_source_component()\n\n # Create or use existing Message object\n if isinstance(self.input_value, Message):\n message = self.input_value\n # Update message properties\n message.text = text\n else:\n message = Message(text=text)\n\n # Set message properties\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(source_id, display_name, source)\n\n # Store message if needed\n if self.session_id and self.should_store_message:\n stored_message = await self.send_message(message)\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n\n def _serialize_data(self, data: Data) -> str:\n \"\"\"Serialize Data object to JSON string.\"\"\"\n # Convert data.data to JSON-serializable format\n serializable_data = jsonable_encoder(data.data)\n # Serialize with orjson, enabling pretty printing with indentation\n json_bytes = orjson.dumps(serializable_data, option=orjson.OPT_INDENT_2)\n # Convert bytes to string and wrap in Markdown code blocks\n return \"```json\\n\" + json_bytes.decode(\"utf-8\") + \"\\n```\"\n\n def _validate_input(self) -> None:\n \"\"\"Validate the input data and raise ValueError if invalid.\"\"\"\n if self.input_value is None:\n msg = \"Input data cannot be None\"\n raise ValueError(msg)\n if isinstance(self.input_value, list) and not all(\n isinstance(item, Message | Data | DataFrame | str) for item in self.input_value\n ):\n invalid_types = [\n type(item).__name__\n for item in self.input_value\n if not isinstance(item, Message | Data | DataFrame | str)\n ]\n msg = f\"Expected Data or DataFrame or Message or str, got {invalid_types}\"\n raise TypeError(msg)\n if not isinstance(\n self.input_value,\n Message | Data | DataFrame | str | list | Generator | type(None),\n ):\n type_name = type(self.input_value).__name__\n msg = f\"Expected Data or DataFrame or Message or str, Generator or None, got {type_name}\"\n raise TypeError(msg)\n\n def convert_to_string(self) -> str | Generator[Any, None, None]:\n \"\"\"Convert input data to string with proper error handling.\"\"\"\n self._validate_input()\n if isinstance(self.input_value, list):\n clean_data: bool = getattr(self, \"clean_data\", False)\n return \"\\n\".join([safe_convert(item, clean_data=clean_data) for item in self.input_value])\n if isinstance(self.input_value, Generator):\n return self.input_value\n return safe_convert(self.input_value)\n" }, "data_template": { "_input_type": "MessageTextInput", "advanced": true, "display_name": "Data Template", "dynamic": false, "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", "input_types": [ "Message" ], "list": false, "load_from_db": false, "name": "data_template", "placeholder": "", "required": false, "show": true, "title_case": false, "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "{text}" }, "input_value": { "_input_type": "MessageInput", "advanced": false, "display_name": "Inputs", "dynamic": false, "info": "Message to be passed as output.", "input_types": [ "Data", "DataFrame", "Message" ], "list": false, "load_from_db": false, "name": "input_value", "placeholder": "", "required": true, "show": true, "title_case": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "" }, "sender": { "_input_type": "DropdownInput", "advanced": true, "combobox": false, "display_name": "Sender Type", "dynamic": false, "info": "Type of sender.", "name": "sender", "options": [ "Machine", "User" ], "placeholder": "", "required": false, "show": true, "title_case": false, "tool_mode": false, "trace_as_metadata": true, "type": "str", "value": "Machine" }, "sender_name": { "_input_type": "MessageTextInput", "advanced": true, "display_name": "Sender Name", "dynamic": false, "info": "Name of the sender.", "input_types": [ "Message" ], "list": false, "load_from_db": false, "name": "sender_name", "placeholder": "", "required": false, "show": true, "title_case": false, "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "AI" }, "session_id": { "_input_type": "MessageTextInput", "advanced": true, "display_name": "Session ID", "dynamic": false, "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", "input_types": [ "Message" ], "list": false, "load_from_db": false, "name": "session_id", "placeholder": "", "required": false, "show": true, "title_case": false, "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "" }, "should_store_message": { "_input_type": "BoolInput", "advanced": true, "display_name": "Store Messages", "dynamic": false, "info": "Store the message in the history.", "list": false, "name": "should_store_message", "placeholder": "", "required": false, "show": true, "title_case": false, "trace_as_metadata": true, "type": "bool", "value": true } }, "tool_mode": false }, "type": "ChatOutput" }, "dragging": false, "height": 234, "id": "ChatOutput-8ZWWB", "measured": { "height": 234, "width": 320 }, "position": { "x": 1460.070372772908, "y": 872.7273956769025 }, "positionAbsolute": { "x": 1444.936881624563, "y": 872.7273956769025 }, "selected": false, "type": "genericNode", "width": 320 }, { "data": { "id": "LanguageModelComponent-kBOja", "node": { "base_classes": [ "LanguageModel", "Message" ], "beta": false, "conditional_paths": [], "custom_fields": {}, "description": "Runs a language model given a specified provider. ", "display_name": "Language Model", "documentation": "", "edited": false, "field_order": [ "provider", "model_name", "api_key", "input_value", "system_message", "stream", "temperature" ], "frozen": false, "icon": "brain-circuit", "legacy": false, "metadata": { "keywords": [ "model", "llm", "language model", "large language model" ] }, "minimized": false, "output_types": [], "outputs": [ { "allows_loop": false, "cache": true, "display_name": "Model Response", "group_outputs": false, "hidden": null, "method": "text_response", "name": "text_output", "options": null, "required_inputs": null, "selected": "Message", "tool_mode": true, "types": [ "Message" ], "value": "__UNDEFINED__" }, { "allows_loop": false, "cache": true, "display_name": "Language Model", "group_outputs": false, "hidden": null, "method": "build_model", "name": "model_output", "options": null, "required_inputs": null, "selected": "LanguageModel", "tool_mode": true, "types": [ "LanguageModel" ], "value": "__UNDEFINED__" } ], "pinned": false, "priority": 0, "template": { "_type": "Component", "api_key": { "_input_type": "SecretStrInput", "advanced": false, "display_name": "OpenAI API Key", "dynamic": false, "info": "Model Provider API key", "input_types": [], "load_from_db": true, "name": "api_key", "password": true, "placeholder": "", "real_time_refresh": true, "required": false, "show": true, "title_case": false, "type": "str", "value": "OPENAI_API_KEY" }, "code": { "advanced": true, "dynamic": true, "fileTypes": [], "file_path": "", "info": "", "list": false, "load_from_db": false, "multiline": true, "name": "code", "password": false, "placeholder": "", "required": true, "show": true, "title_case": false, "type": "code", "value": "from typing import Any\n\nfrom langchain_anthropic import ChatAnthropic\nfrom langchain_google_genai import ChatGoogleGenerativeAI\nfrom langchain_openai import ChatOpenAI\n\nfrom langflow.base.models.anthropic_constants import ANTHROPIC_MODELS\nfrom langflow.base.models.google_generative_ai_constants import GOOGLE_GENERATIVE_AI_MODELS\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_CHAT_MODEL_NAMES, OPENAI_REASONING_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MultilineInput, SecretStrInput, SliderInput\nfrom langflow.schema.dotdict import dotdict\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider.\"\n documentation: str = \"https://docs.langflow.org/components-models\"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n DropdownInput(\n name=\"provider\",\n display_name=\"Model Provider\",\n options=[\"OpenAI\", \"Anthropic\", \"Google\"],\n value=\"OpenAI\",\n info=\"Select the model provider\",\n real_time_refresh=True,\n options_metadata=[{\"icon\": \"OpenAI\"}, {\"icon\": \"Anthropic\"}, {\"icon\": \"GoogleGenerativeAI\"}],\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n options=OPENAI_CHAT_MODEL_NAMES + OPENAI_REASONING_MODEL_NAMES,\n value=OPENAI_CHAT_MODEL_NAMES[0],\n info=\"Select the model to use\",\n real_time_refresh=True,\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=False,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n provider = self.provider\n model_name = self.model_name\n temperature = self.temperature\n stream = self.stream\n\n if provider == \"OpenAI\":\n if not self.api_key:\n msg = \"OpenAI API key is required when using OpenAI provider\"\n raise ValueError(msg)\n\n if model_name in OPENAI_REASONING_MODEL_NAMES:\n # reasoning models do not support temperature (yet)\n temperature = None\n\n return ChatOpenAI(\n model_name=model_name,\n temperature=temperature,\n streaming=stream,\n openai_api_key=self.api_key,\n )\n if provider == \"Anthropic\":\n if not self.api_key:\n msg = \"Anthropic API key is required when using Anthropic provider\"\n raise ValueError(msg)\n return ChatAnthropic(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n anthropic_api_key=self.api_key,\n )\n if provider == \"Google\":\n if not self.api_key:\n msg = \"Google API key is required when using Google provider\"\n raise ValueError(msg)\n return ChatGoogleGenerativeAI(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n google_api_key=self.api_key,\n )\n msg = f\"Unknown provider: {provider}\"\n raise ValueError(msg)\n\n def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None) -> dotdict:\n if field_name == \"provider\":\n if field_value == \"OpenAI\":\n build_config[\"model_name\"][\"options\"] = OPENAI_CHAT_MODEL_NAMES + OPENAI_REASONING_MODEL_NAMES\n build_config[\"model_name\"][\"value\"] = OPENAI_CHAT_MODEL_NAMES[0]\n build_config[\"api_key\"][\"display_name\"] = \"OpenAI API Key\"\n elif field_value == \"Anthropic\":\n build_config[\"model_name\"][\"options\"] = ANTHROPIC_MODELS\n build_config[\"model_name\"][\"value\"] = ANTHROPIC_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Anthropic API Key\"\n elif field_value == \"Google\":\n build_config[\"model_name\"][\"options\"] = GOOGLE_GENERATIVE_AI_MODELS\n build_config[\"model_name\"][\"value\"] = GOOGLE_GENERATIVE_AI_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Google API Key\"\n elif field_name == \"model_name\" and field_value.startswith(\"o1\") and self.provider == \"OpenAI\":\n # Hide system_message for o1 models - currently unsupported\n if \"system_message\" in build_config:\n build_config[\"system_message\"][\"show\"] = False\n elif field_name == \"model_name\" and not field_value.startswith(\"o1\") and \"system_message\" in build_config:\n build_config[\"system_message\"][\"show\"] = True\n return build_config\n" }, "input_value": { "_input_type": "MessageInput", "advanced": false, "display_name": "Input", "dynamic": false, "info": "The input text to send to the model", "input_types": [ "Message" ], "list": false, "list_add_label": "Add More", "load_from_db": false, "name": "input_value", "placeholder": "", "required": false, "show": true, "title_case": false, "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "" }, "model_name": { "_input_type": "DropdownInput", "advanced": false, "combobox": false, "dialog_inputs": {}, "display_name": "Model Name", "dynamic": false, "info": "Select the model to use", "name": "model_name", "options": [ "gpt-4o-mini", "gpt-4o", "gpt-4.1", "gpt-4.1-mini", "gpt-4.1-nano", "gpt-4.5-preview", "gpt-4-turbo", "gpt-4-turbo-preview", "gpt-4", "gpt-3.5-turbo" ], "options_metadata": [], "placeholder": "", "required": false, "show": true, "title_case": false, "toggle": false, "tool_mode": false, "trace_as_metadata": true, "type": "str", "value": "gpt-4.1" }, "provider": { "_input_type": "DropdownInput", "advanced": false, "combobox": false, "dialog_inputs": {}, "display_name": "Model Provider", "dynamic": false, "info": "Select the model provider", "name": "provider", "options": [ "OpenAI", "Anthropic", "Google" ], "options_metadata": [ { "icon": "OpenAI" }, { "icon": "Anthropic" }, { "icon": "GoogleGenerativeAI" } ], "placeholder": "", "real_time_refresh": true, "required": false, "show": true, "title_case": false, "toggle": false, "tool_mode": false, "trace_as_metadata": true, "type": "str", "value": "OpenAI" }, "stream": { "_input_type": "BoolInput", "advanced": true, "display_name": "Stream", "dynamic": false, "info": "Whether to stream the response", "list": false, "list_add_label": "Add More", "name": "stream", "placeholder": "", "required": false, "show": true, "title_case": false, "tool_mode": false, "trace_as_metadata": true, "type": "bool", "value": false }, "system_message": { "_input_type": "MultilineInput", "advanced": false, "copy_field": false, "display_name": "System Message", "dynamic": false, "info": "A system message that helps set the behavior of the assistant", "input_types": [ "Message" ], "list": false, "list_add_label": "Add More", "load_from_db": false, "multiline": true, "name": "system_message", "placeholder": "", "required": false, "show": true, "title_case": false, "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "type": "str", "value": "" }, "temperature": { "_input_type": "SliderInput", "advanced": true, "display_name": "Temperature", "dynamic": false, "info": "Controls randomness in responses", "max_label": "", "max_label_icon": "", "min_label": "", "min_label_icon": "", "name": "temperature", "placeholder": "", "range_spec": { "max": 1, "min": 0, "step": 0.01, "step_type": "float" }, "required": false, "show": true, "slider_buttons": false, "slider_buttons_options": [], "slider_input": false, "title_case": false, "tool_mode": false, "type": "slider", "value": 0.1 } }, "tool_mode": false }, "selected_output": "text_output", "showNode": true, "type": "LanguageModelComponent" }, "dragging": false, "id": "LanguageModelComponent-kBOja", "measured": { "height": 534, "width": 320 }, "position": { "x": 1085.7542386472996, "y": 795.0399905192078 }, "selected": true, "type": "genericNode" } ], "viewport": { "x": -171.73930599141136, "y": -281.4054320344371, "zoom": 0.7267911009473667 } }, "description": "Perform basic prompting with an OpenAI model.", "endpoint_name": null, "id": "0dbee653-41ae-4e51-af2e-55757fb24be3", "is_component": false, "last_tested_version": "1.5.0", "name": "Basic Prompting", "tags": [ "chatbots" ] }