{ "id": "019b0830-219e-4b74-b4e1-0b662e28de5f", "data": { "nodes": [ { "id": "CustomComponent-rvzAl", "type": "genericNode", "position": { "x": -569.8552060027972, "y": 166.49085050046935 }, "data": { "node": { "template": { "_type": "Component", "api_id": { "load_from_db": false, "required": true, "placeholder": "", "show": true, "name": "api_id", "value": "", "display_name": "API ID", "advanced": false, "input_types": [ "Message" ], "dynamic": false, "info": "Your SheetDB API ID (e.g., 58f61be4dda40).", "title_case": false, "password": true, "type": "str", "_input_type": "SecretStrInput" }, "cast_numbers": { "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "cast_numbers", "value": "", "display_name": "Cast Numbers", "advanced": false, "dynamic": false, "info": "Comma-separated column names to cast as numbers.", "title_case": false, "type": "str", "_input_type": "StrInput" }, "code": { "type": "code", "required": true, "placeholder": "", "list": false, "show": true, "multiline": true, "value": "import requests\r\nfrom typing import Dict, Any, List, Optional\r\nfrom pydantic import BaseModel, Field\r\nfrom langchain.tools import StructuredTool\r\nfrom langflow.base.langchain_utilities.model import LCToolComponent\r\nfrom langflow.field_typing import Data, Tool\r\nfrom langflow.inputs import SecretStrInput, StrInput, IntInput, DropdownInput\r\n\r\n\r\nclass SheetDBReadToolComponent(LCToolComponent):\r\n display_name = \"Sheet DB io\"\r\n description = \"Reads data from a Google Sheet using SheetDB API.\"\r\n documentation = \"https://sheetdb.io/documentation\"\r\n icon = \"table\"\r\n name = \"SheetDBReader\"\r\n\r\n inputs = [\r\n SecretStrInput(\r\n name=\"api_id\",\r\n display_name=\"API ID\",\r\n info=\"Your SheetDB API ID (e.g., 58f61be4dda40).\",\r\n required=True,\r\n ),\r\n StrInput(\r\n name=\"sheet\",\r\n display_name=\"Sheet Name\",\r\n required=False,\r\n ),\r\n IntInput(\r\n name=\"limit\",\r\n display_name=\"Limit\",\r\n required=False,\r\n ),\r\n IntInput(\r\n name=\"offset\",\r\n display_name=\"Offset\",\r\n required=False,\r\n ),\r\n StrInput(\r\n name=\"sort_by\",\r\n display_name=\"Sort By\",\r\n required=False,\r\n ),\r\n DropdownInput(\r\n name=\"sort_order\",\r\n display_name=\"Sort Order\",\r\n options=[\"asc\", \"desc\", \"random\"],\r\n required=False,\r\n ),\r\n StrInput(\r\n name=\"cast_numbers\",\r\n display_name=\"Cast Numbers\",\r\n info=\"Comma-separated column names to cast as numbers.\",\r\n required=False,\r\n ),\r\n ]\r\n\r\n class SheetDBReadSchema(BaseModel):\r\n sheet: Optional[str] = Field(None)\r\n limit: Optional[int] = Field(None)\r\n offset: Optional[int] = Field(None)\r\n sort_by: Optional[str] = Field(None)\r\n sort_order: Optional[str] = Field(None)\r\n cast_numbers: Optional[str] = Field(None)\r\n\r\n def _read_sheetdb(\r\n self,\r\n sheet: Optional[str] = None,\r\n limit: Optional[int] = None,\r\n offset: Optional[int] = None,\r\n sort_by: Optional[str] = None,\r\n sort_order: Optional[str] = None,\r\n cast_numbers: Optional[str] = None,\r\n ) -> List[Data]:\r\n url = f\"https://sheetdb.io/api/v1/{self.api_id}\"\r\n params = {}\r\n\r\n if sheet:\r\n params[\"sheet\"] = sheet\r\n if limit:\r\n params[\"limit\"] = str(limit)\r\n if offset:\r\n params[\"offset\"] = str(offset)\r\n if sort_by:\r\n params[\"sort_by\"] = sort_by\r\n if sort_order:\r\n params[\"sort_order\"] = sort_order\r\n if cast_numbers:\r\n params[\"cast_numbers\"] = cast_numbers\r\n\r\n try:\r\n response = requests.get(url, params=params)\r\n response.raise_for_status()\r\n result = response.json()\r\n\r\n # Corrige erro: SheetDB pode retornar lista, mas Langflow espera dict\r\n if isinstance(result, list):\r\n return [Data(data={\"items\": result})]\r\n else:\r\n return [Data(data=result)]\r\n\r\n except Exception as e:\r\n return [Data(data={\"error\": str(e)})]\r\n\r\n def build_tool(self) -> Tool:\r\n return StructuredTool.from_function(\r\n name=\"read_sheetdb_data\",\r\n description=\"Fetches data from a SheetDB spreadsheet with optional sorting and filtering.\",\r\n func=self._read_sheetdb,\r\n args_schema=self.SheetDBReadSchema,\r\n )\r\n\r\n def run_model(self) -> List[Data]:\r\n return self._read_sheetdb(\r\n sheet=self.sheet,\r\n limit=self.limit,\r\n offset=self.offset,\r\n sort_by=self.sort_by,\r\n sort_order=self.sort_order,\r\n cast_numbers=self.cast_numbers,\r\n )\r\n", "fileTypes": [], "file_path": "", "password": false, "name": "code", "advanced": true, "dynamic": true, "info": "", "load_from_db": false, "title_case": false }, "limit": { "trace_as_metadata": true, "list": false, "required": false, "placeholder": "", "show": true, "name": "limit", "value": 3, "display_name": "Limit", "advanced": false, "dynamic": false, "info": "", "title_case": false, "type": "int", "_input_type": "IntInput", "load_from_db": false }, "offset": { "trace_as_metadata": true, "list": false, "required": false, "placeholder": "", "show": true, "name": "offset", "value": "", "display_name": "Offset", "advanced": false, "dynamic": false, "info": "", "title_case": false, "type": "int", "_input_type": "IntInput" }, "sheet": { "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "sheet", "value": "", "display_name": "Sheet Name", "advanced": false, "dynamic": false, "info": "", "title_case": false, "type": "str", "_input_type": "StrInput" }, "sort_by": { "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "sort_by", "value": "", "display_name": "Sort By", "advanced": false, "dynamic": false, "info": "", "title_case": false, "type": "str", "_input_type": "StrInput" }, "sort_order": { "tool_mode": false, "trace_as_metadata": true, "options": [ "asc", "desc", "random" ], "combobox": false, "required": false, "placeholder": "", "show": true, "name": "sort_order", "value": "", "display_name": "Sort Order", "advanced": false, "dynamic": false, "info": "", "title_case": false, "type": "str", "_input_type": "DropdownInput" } }, "description": "Reads data from a Google Sheet using SheetDB API.", "icon": "table", "base_classes": [ "Data", "Tool" ], "display_name": "Reads all data - SheetDB", "documentation": "https://sheetdb.io/documentation", "custom_fields": {}, "output_types": [], "pinned": false, "conditional_paths": [], "frozen": false, "outputs": [ { "types": [ "Data" ], "selected": "Data", "name": "api_run_model", "display_name": "Data", "method": "run_model", "value": "__UNDEFINED__", "cache": true, "required_inputs": [ "api_id" ] }, { "types": [ "Tool" ], "selected": "Tool", "name": "api_build_tool", "display_name": "Tool", "method": "build_tool", "value": "__UNDEFINED__", "cache": true, "required_inputs": [ "api_id" ] } ], "field_order": [ "api_id", "sheet", "limit", "offset", "sort_by", "sort_order", "cast_numbers" ], "beta": false, "legacy": false, "edited": true, "metadata": {}, "tool_mode": false, "lf_version": "1.1.1" }, "type": "CustomComponent", "id": "CustomComponent-rvzAl" }, "selected": false, "width": 320, "height": 815, "positionAbsolute": { "x": -569.8552060027972, "y": 166.49085050046935 }, "dragging": false }, { "id": "Agent-XtQp3", "type": "genericNode", "position": { "x": 823.4221991899246, "y": 80.89232362913731 }, "data": { "node": { "template": { "_type": "Component", "memory": { "trace_as_metadata": true, "list": false, "required": false, "placeholder": "", "show": true, "name": "memory", "value": "", "display_name": "External Memory", "advanced": true, "input_types": [ "BaseChatMessageHistory" ], "dynamic": false, "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.", "title_case": false, "type": "other", "_input_type": "HandleInput" }, "output_parser": { "trace_as_metadata": true, "list": false, "required": false, "placeholder": "", "show": true, "name": "output_parser", "value": "", "display_name": "Output Parser", "advanced": true, "input_types": [ "OutputParser" ], "dynamic": false, "info": "The parser to use to parse the output of the model", "title_case": false, "type": "other", "_input_type": "HandleInput" }, "tools": { "trace_as_metadata": true, "list": true, "required": false, "placeholder": "", "show": true, "name": "tools", "value": "", "display_name": "Tools", "advanced": false, "input_types": [ "Tool", "BaseTool", "StructuredTool" ], "dynamic": false, "info": "These are the tools that the agent can use to help with tasks.", "title_case": false, "type": "other", "_input_type": "HandleInput" }, "add_current_date_tool": { "trace_as_metadata": true, "list": false, "required": false, "placeholder": "", "show": true, "name": "add_current_date_tool", "value": true, "display_name": "Add tool Current Date", "advanced": true, "dynamic": false, "info": "If true, will add a tool to the agent that returns the current date.", "title_case": false, "type": "bool", "_input_type": "BoolInput" }, "agent_description": { "tool_mode": false, "trace_as_input": true, "multiline": true, "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "agent_description", "value": "A helpful assistant with access to the following tools:", "display_name": "Agent Description", "advanced": true, "input_types": [ "Message" ], "dynamic": false, "info": "The description of the agent. This is only used when in Tool Mode. Defaults to 'A helpful assistant with access to the following tools:' and tools are added dynamically.", "title_case": false, "type": "str", "_input_type": "MultilineInput" }, "agent_llm": { "tool_mode": false, "trace_as_metadata": true, "options": [ "Amazon Bedrock", "Anthropic", "Azure OpenAI", "Groq", "NVIDIA", "OpenAI", "Custom" ], "combobox": false, "required": false, "placeholder": "", "show": true, "name": "agent_llm", "value": "OpenAI", "display_name": "Model Provider", "advanced": false, "input_types": [], "dynamic": false, "info": "The provider of the language model that the agent will use to generate responses.", "real_time_refresh": true, "title_case": false, "type": "str", "_input_type": "DropdownInput" }, "api_key": { "load_from_db": true, "required": false, "placeholder": "", "show": true, "name": "api_key", "value": "", "display_name": "OpenAI API Key", "advanced": false, "input_types": [ "Message" ], "dynamic": false, "info": "The OpenAI API Key to use for the OpenAI model.", "title_case": false, "password": true, "type": "str", "_input_type": "SecretStrInput" }, "code": { "type": "code", "required": true, "placeholder": "", "list": false, "show": true, "multiline": true, "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import ALL_PROVIDER_FIELDS, MODEL_PROVIDERS_DICT\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import ToolCallingAgentComponent\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Add tool Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return self._build_llm_model(component_class, inputs, prefix), display_name\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call the component class's update_build_config method\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call each component class's update_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n return build_config\n", "fileTypes": [], "file_path": "", "password": false, "name": "code", "advanced": true, "dynamic": true, "info": "", "load_from_db": false, "title_case": false }, "handle_parsing_errors": { "trace_as_metadata": true, "list": false, "required": false, "placeholder": "", "show": true, "name": "handle_parsing_errors", "value": true, "display_name": "Handle Parse Errors", "advanced": true, "dynamic": false, "info": "Should the Agent fix errors when reading user input for better processing?", "title_case": false, "type": "bool", "_input_type": "BoolInput" }, "input_value": { "tool_mode": true, "trace_as_input": true, "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "input_value", "value": "", "display_name": "Input", "advanced": false, "input_types": [ "Message" ], "dynamic": false, "info": "The input provided by the user for the agent to process.", "title_case": false, "type": "str", "_input_type": "MessageTextInput" }, "json_mode": { "trace_as_metadata": true, "list": false, "required": false, "placeholder": "", "show": true, "name": "json_mode", "value": false, "display_name": "JSON Mode", "advanced": true, "dynamic": false, "info": "If True, it will output JSON regardless of passing a schema.", "title_case": false, "type": "bool", "_input_type": "BoolInput" }, "max_iterations": { "trace_as_metadata": true, "list": false, "required": false, "placeholder": "", "show": true, "name": "max_iterations", "value": 15, "display_name": "Max Iterations", "advanced": true, "dynamic": false, "info": "The maximum number of attempts the agent can make to complete its task before it stops.", "title_case": false, "type": "int", "_input_type": "IntInput" }, "max_tokens": { "trace_as_metadata": true, "range_spec": { "step_type": "float", "min": 0, "max": 128000, "step": 0.1 }, "list": false, "required": false, "placeholder": "", "show": true, "name": "max_tokens", "value": "", "display_name": "Max Tokens", "advanced": true, "dynamic": false, "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", "title_case": false, "type": "int", "_input_type": "IntInput" }, "model_kwargs": { "trace_as_input": true, "list": false, "required": false, "placeholder": "", "show": true, "name": "model_kwargs", "value": {}, "display_name": "Model Kwargs", "advanced": true, "dynamic": false, "info": "Additional keyword arguments to pass to the model.", "title_case": false, "type": "dict", "_input_type": "DictInput" }, "model_name": { "tool_mode": false, "trace_as_metadata": true, "options": [ "gpt-4o-mini", "gpt-4o", "gpt-4-turbo", "gpt-4-turbo-preview", "gpt-4", "gpt-3.5-turbo", "gpt-3.5-turbo-0125" ], "combobox": false, "required": false, "placeholder": "", "show": true, "name": "model_name", "value": "gpt-4o-mini", "display_name": "Model Name", "advanced": false, "dynamic": false, "info": "", "title_case": false, "type": "str", "_input_type": "DropdownInput" }, "n_messages": { "trace_as_metadata": true, "list": false, "required": false, "placeholder": "", "show": true, "name": "n_messages", "value": 100, "display_name": "Number of Messages", "advanced": true, "dynamic": false, "info": "Number of messages to retrieve.", "title_case": false, "type": "int", "_input_type": "IntInput" }, "openai_api_base": { "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "openai_api_base", "value": "", "display_name": "OpenAI API Base", "advanced": true, "dynamic": false, "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", "title_case": false, "type": "str", "_input_type": "StrInput" }, "order": { "tool_mode": false, "trace_as_metadata": true, "options": [ "Ascending", "Descending" ], "combobox": false, "required": false, "placeholder": "", "show": true, "name": "order", "value": "Ascending", "display_name": "Order", "advanced": true, "dynamic": false, "info": "Order of the messages.", "title_case": false, "type": "str", "_input_type": "DropdownInput" }, "output_schema": { "trace_as_input": true, "list": true, "required": false, "placeholder": "", "show": true, "name": "output_schema", "value": {}, "display_name": "Schema", "advanced": true, "dynamic": false, "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", "title_case": false, "type": "dict", "_input_type": "DictInput" }, "seed": { "trace_as_metadata": true, "list": false, "required": false, "placeholder": "", "show": true, "name": "seed", "value": 1, "display_name": "Seed", "advanced": true, "dynamic": false, "info": "The seed controls the reproducibility of the job.", "title_case": false, "type": "int", "_input_type": "IntInput" }, "sender": { "tool_mode": false, "trace_as_metadata": true, "options": [ "Machine", "User", "Machine and User" ], "combobox": false, "required": false, "placeholder": "", "show": true, "name": "sender", "value": "Machine and User", "display_name": "Sender Type", "advanced": true, "dynamic": false, "info": "Filter by sender type.", "title_case": false, "type": "str", "_input_type": "DropdownInput" }, "sender_name": { "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "sender_name", "value": "", "display_name": "Sender Name", "advanced": true, "input_types": [ "Message" ], "dynamic": false, "info": "Filter by sender name.", "title_case": false, "type": "str", "_input_type": "MessageTextInput" }, "session_id": { "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "session_id", "value": "", "display_name": "Session ID", "advanced": true, "input_types": [ "Message" ], "dynamic": false, "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", "title_case": false, "type": "str", "_input_type": "MessageTextInput" }, "system_prompt": { "tool_mode": false, "trace_as_input": true, "multiline": true, "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "system_prompt", "value": "Você é um assistente que utiliza as tools para interagir com dados de uma planilha via API.\nPode ler, buscar, contar e inserir dados.\n\nRegras:\n\n- Entenda o pedido do usuário.\n\n- Use a ferramenta certa:\n\nReads all data:ler todos os dados\n\nFetch the Column Names:obter nomes das colunas\n\nFetches the number of data rows: contar linhas\n\nSearch Rows:buscar com filtro\n\nInsert New Row: adicionar nova linha\n\n- Antes de buscar ou inserir, use Fetch the Column Names para saber os nomes corretos.\n\n- Se o pedido for muito longo, sugira dividir em partes menores.\n\n- Ao inserir dados, ajude o usuário a preencher colunas faltantes.\n\n- Sempre responda de forma clara e direta, com listas ou tabelas, se necessário.", "display_name": "Agent Instructions", "advanced": false, "input_types": [ "Message" ], "dynamic": false, "info": "System Prompt: Initial instructions and context provided to guide the agent's behavior.", "title_case": false, "type": "str", "_input_type": "MultilineInput" }, "temperature": { "trace_as_metadata": true, "list": false, "required": false, "placeholder": "", "show": true, "name": "temperature", "value": 0.1, "display_name": "Temperature", "advanced": true, "dynamic": false, "info": "", "title_case": false, "type": "float", "_input_type": "FloatInput" }, "template": { "tool_mode": false, "trace_as_input": true, "multiline": true, "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "template", "value": "{sender_name}: {text}", "display_name": "Template", "advanced": true, "input_types": [ "Message" ], "dynamic": false, "info": "The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.", "title_case": false, "type": "str", "_input_type": "MultilineInput" }, "verbose": { "trace_as_metadata": true, "list": false, "required": false, "placeholder": "", "show": true, "name": "verbose", "value": true, "display_name": "Verbose", "advanced": true, "dynamic": false, "info": "", "title_case": false, "type": "bool", "_input_type": "BoolInput" } }, "description": "Define the agent's instructions, then enter a task to complete using tools.", "icon": "bot", "base_classes": [ "Message" ], "display_name": "Agent", "documentation": "", "custom_fields": {}, "output_types": [], "pinned": false, "conditional_paths": [], "frozen": false, "outputs": [ { "types": [ "Message" ], "selected": "Message", "name": "response", "display_name": "Response", "method": "message_response", "value": "__UNDEFINED__", "cache": true } ], "field_order": [ "agent_llm", "max_tokens", "model_kwargs", "json_mode", "output_schema", "model_name", "openai_api_base", "api_key", "temperature", "seed", "output_parser", "system_prompt", "tools", "input_value", "handle_parsing_errors", "verbose", "max_iterations", "agent_description", "memory", "sender", "sender_name", "n_messages", "session_id", "order", "template", "add_current_date_tool" ], "beta": false, "legacy": false, "edited": false, "metadata": {}, "tool_mode": false, "category": "agents", "key": "Agent", "score": 5.283996070936036e-7, "lf_version": "1.1.1" }, "type": "Agent", "id": "Agent-XtQp3" }, "selected": false, "width": 320, "height": 643, "positionAbsolute": { "x": 823.4221991899246, "y": 80.89232362913731 }, "dragging": false }, { "id": "ChatInput-yAxS8", "type": "genericNode", "position": { "x": -66.60812772687495, "y": -134.6086961552964 }, "data": { "node": { "template": { "_type": "Component", "files": { "trace_as_metadata": true, "file_path": "", "fileTypes": [ "txt", "md", "mdx", "csv", "json", "yaml", "yml", "xml", "html", "htm", "pdf", "docx", "py", "sh", "sql", "js", "ts", "tsx", "jpg", "jpeg", "png", "bmp", "image" ], "list": true, "required": false, "placeholder": "", "show": true, "name": "files", "value": "", "display_name": "Files", "advanced": true, "dynamic": false, "info": "Files to be sent with the message.", "title_case": false, "type": "file", "_input_type": "FileInput" }, "background_color": { "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "background_color", "value": "", "display_name": "Background Color", "advanced": true, "input_types": [ "Message" ], "dynamic": false, "info": "The background color of the icon.", "title_case": false, "type": "str", "_input_type": "MessageTextInput" }, "chat_icon": { "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "chat_icon", "value": "", "display_name": "Icon", "advanced": true, "input_types": [ "Message" ], "dynamic": false, "info": "The icon of the message.", "title_case": false, "type": "str", "_input_type": "MessageTextInput" }, "code": { "type": "code", "required": true, "placeholder": "", "list": false, "show": true, "multiline": true, "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_USER, MESSAGE_SENDER_USER\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"table\"\n name = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\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 ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n _background_color = self.background_color\n _text_color = self.text_color\n _icon = self.chat_icon\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n properties={\"background_color\": _background_color, \"text_color\": _text_color, \"icon\": _icon},\n )\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = 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", "fileTypes": [], "file_path": "", "password": false, "name": "code", "advanced": true, "dynamic": true, "info": "", "load_from_db": false, "title_case": false }, "input_value": { "tool_mode": false, "trace_as_input": true, "multiline": true, "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "input_value", "value": "", "display_name": "Text", "advanced": false, "input_types": [ "Message" ], "dynamic": false, "info": "Message to be passed as input.", "title_case": false, "type": "str", "_input_type": "MultilineInput" }, "sender": { "tool_mode": false, "trace_as_metadata": true, "options": [ "Machine", "User" ], "combobox": false, "required": false, "placeholder": "", "show": true, "name": "sender", "value": "User", "display_name": "Sender Type", "advanced": true, "dynamic": false, "info": "Type of sender.", "title_case": false, "type": "str", "_input_type": "DropdownInput" }, "sender_name": { "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "sender_name", "value": "User", "display_name": "Sender Name", "advanced": true, "input_types": [ "Message" ], "dynamic": false, "info": "Name of the sender.", "title_case": false, "type": "str", "_input_type": "MessageTextInput" }, "session_id": { "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "session_id", "value": "", "display_name": "Session ID", "advanced": true, "input_types": [ "Message" ], "dynamic": false, "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", "title_case": false, "type": "str", "_input_type": "MessageTextInput" }, "should_store_message": { "trace_as_metadata": true, "list": false, "required": false, "placeholder": "", "show": true, "name": "should_store_message", "value": true, "display_name": "Store Messages", "advanced": true, "dynamic": false, "info": "Store the message in the history.", "title_case": false, "type": "bool", "_input_type": "BoolInput" }, "text_color": { "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "text_color", "value": "", "display_name": "Text Color", "advanced": true, "input_types": [ "Message" ], "dynamic": false, "info": "The text color of the name", "title_case": false, "type": "str", "_input_type": "MessageTextInput" } }, "description": "Get chat inputs from the Playground.", "icon": "table", "base_classes": [ "Message" ], "display_name": "Chat Input", "documentation": "", "custom_fields": {}, "output_types": [], "pinned": false, "conditional_paths": [], "frozen": false, "outputs": [ { "types": [ "Message" ], "selected": "Message", "name": "message", "display_name": "Message", "method": "message_response", "value": "__UNDEFINED__", "cache": true } ], "field_order": [ "input_value", "should_store_message", "sender", "sender_name", "session_id", "files", "background_color", "chat_icon", "text_color" ], "beta": false, "legacy": false, "edited": true, "metadata": {}, "tool_mode": false }, "type": "ChatInput", "id": "ChatInput-yAxS8" }, "selected": false, "width": 320, "height": 232, "positionAbsolute": { "x": -66.60812772687495, "y": -134.6086961552964 }, "dragging": false }, { "id": "ChatOutput-nfWQn", "type": "genericNode", "position": { "x": 1280.5795643095823, "y": 448.0929121965131 }, "data": { "node": { "template": { "_type": "Component", "background_color": { "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "background_color", "value": "", "display_name": "Background Color", "advanced": true, "input_types": [ "Message" ], "dynamic": false, "info": "The background color of the icon.", "title_case": false, "type": "str", "_input_type": "MessageTextInput" }, "chat_icon": { "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "chat_icon", "value": "", "display_name": "Icon", "advanced": true, "input_types": [ "Message" ], "dynamic": false, "info": "The icon of the message.", "title_case": false, "type": "str", "_input_type": "MessageTextInput" }, "code": { "type": "code", "required": true, "placeholder": "", "list": false, "show": true, "multiline": true, "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_NAME_AI, MESSAGE_SENDER_USER\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n\n inputs = [\n MessageInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\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 MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"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 source_dict[\"source\"] = source\n return Source(**source_dict)\n\n def message_response(self) -> Message:\n _source, _icon, _display_name, _source_id = self.get_properties_from_source_component()\n _background_color = self.background_color\n _text_color = self.text_color\n if self.chat_icon:\n _icon = self.chat_icon\n message = self.input_value if isinstance(self.input_value, Message) else Message(text=self.input_value)\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 message.properties.icon = _icon\n message.properties.background_color = _background_color\n message.properties.text_color = _text_color\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = 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", "fileTypes": [], "file_path": "", "password": false, "name": "code", "advanced": true, "dynamic": true, "info": "", "load_from_db": false, "title_case": false }, "data_template": { "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "data_template", "value": "{text}", "display_name": "Data Template", "advanced": true, "input_types": [ "Message" ], "dynamic": false, "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", "title_case": false, "type": "str", "_input_type": "MessageTextInput" }, "input_value": { "trace_as_input": true, "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "input_value", "value": "", "display_name": "Text", "advanced": false, "input_types": [ "Message" ], "dynamic": false, "info": "Message to be passed as output.", "title_case": false, "type": "str", "_input_type": "MessageInput" }, "sender": { "tool_mode": false, "trace_as_metadata": true, "options": [ "Machine", "User" ], "combobox": false, "required": false, "placeholder": "", "show": true, "name": "sender", "value": "Machine", "display_name": "Sender Type", "advanced": true, "dynamic": false, "info": "Type of sender.", "title_case": false, "type": "str", "_input_type": "DropdownInput" }, "sender_name": { "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "sender_name", "value": "AI", "display_name": "Sender Name", "advanced": true, "input_types": [ "Message" ], "dynamic": false, "info": "Name of the sender.", "title_case": false, "type": "str", "_input_type": "MessageTextInput" }, "session_id": { "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "session_id", "value": "", "display_name": "Session ID", "advanced": true, "input_types": [ "Message" ], "dynamic": false, "info": "The session ID of the chat. If empty, the current session ID parameter will be used.", "title_case": false, "type": "str", "_input_type": "MessageTextInput" }, "should_store_message": { "trace_as_metadata": true, "list": false, "required": false, "placeholder": "", "show": true, "name": "should_store_message", "value": true, "display_name": "Store Messages", "advanced": true, "dynamic": false, "info": "Store the message in the history.", "title_case": false, "type": "bool", "_input_type": "BoolInput" }, "text_color": { "tool_mode": false, "trace_as_input": true, "trace_as_metadata": true, "load_from_db": false, "list": false, "required": false, "placeholder": "", "show": true, "name": "text_color", "value": "", "display_name": "Text Color", "advanced": true, "input_types": [ "Message" ], "dynamic": false, "info": "The text color of the name", "title_case": false, "type": "str", "_input_type": "MessageTextInput" } }, "description": "Display a chat message in the Playground.", "icon": "MessagesSquare", "base_classes": [ "Message" ], "display_name": "Chat Output", "documentation": "", "custom_fields": {}, "output_types": [], "pinned": false, "conditional_paths": [], "frozen": false, "outputs": [ { "types": [ "Message" ], "selected": "Message", "name": "message", "display_name": "Message", "method": "message_response", "value": "__UNDEFINED__", "cache": true } ], "field_order": [ "input_value", "should_store_message", "sender", "sender_name", "session_id", "data_template", "background_color", "chat_icon", "text_color" ], "beta": false, "legacy": false, "edited": false, "metadata": {}, "tool_mode": false, "category": "outputs", "key": "ChatOutput", "score": 0.00012027401062119145, "lf_version": "1.1.1" }, "type": "ChatOutput", "id": "ChatOutput-nfWQn" }, "selected": false, "width": 320, "height": 232, "positionAbsolute": { "x": 1280.5795643095823, "y": 448.0929121965131 }, "dragging": false }, { "id": "CustomComponent-fTDig", "type": "genericNode", "position": { "x": -63.369001666858026, "y": 308.87286497089485 }, "data": { "node": { "template": { "_type": "Component", "api_id": { "load_from_db": false, "required": true, "placeholder": "", "show": true, "name": "api_id", "value": "", "display_name": "API ID", "advanced": false, "input_types": [ "Message" ], "dynamic": false, "info": "Your SheetDB API ID (e.g., 58f61be4dda40).", "title_case": false, "password": true, "type": "str", "_input_type": "SecretStrInput" }, "code": { "type": "code", "required": true, "placeholder": "", "list": false, "show": true, "multiline": true, "value": "import requests\r\nfrom typing import List\r\nfrom pydantic import BaseModel\r\nfrom langchain.tools import StructuredTool\r\nfrom langflow.base.langchain_utilities.model import LCToolComponent\r\nfrom langflow.field_typing import Data, Tool\r\nfrom langflow.inputs import SecretStrInput\r\n\r\n\r\nclass SheetDBKeysToolComponent(LCToolComponent):\r\n display_name = \"Sheet DB Keys\"\r\n description = \"Fetches the column names (keys) from the first row of a SheetDB spreadsheet.\"\r\n documentation = \"https://sheetdb.io/documentation\"\r\n icon = \"table\"\r\n name = \"SheetDBKeys\"\r\n\r\n inputs = [\r\n SecretStrInput(\r\n name=\"api_id\",\r\n display_name=\"API ID\",\r\n info=\"Your SheetDB API ID (e.g., 58f61be4dda40).\",\r\n required=True,\r\n ),\r\n ]\r\n\r\n class SheetDBKeysSchema(BaseModel):\r\n # Nenhum parâmetro no schema porque o api_id é usado apenas no nível da instância\r\n pass\r\n\r\n def _fetch_keys(self) -> List[Data]:\r\n url = f\"https://sheetdb.io/api/v1/{self.api_id}/keys\"\r\n\r\n try:\r\n response = requests.get(url)\r\n response.raise_for_status()\r\n keys = response.json()\r\n\r\n if isinstance(keys, list):\r\n return [Data(data={\"columns\": keys})]\r\n else:\r\n return [Data(data={\"error\": \"Unexpected response format\", \"raw\": keys})]\r\n\r\n except Exception as e:\r\n return [Data(data={\"error\": str(e)})]\r\n\r\n def build_tool(self) -> Tool:\r\n return StructuredTool.from_function(\r\n name=\"fetch_sheetdb_keys\",\r\n description=\"Get the column names from a SheetDB spreadsheet (first row headers).\",\r\n func=self._fetch_keys,\r\n args_schema=self.SheetDBKeysSchema,\r\n )\r\n\r\n def run_model(self) -> List[Data]:\r\n return self._fetch_keys()\r\n", "fileTypes": [], "file_path": "", "password": false, "name": "code", "advanced": true, "dynamic": true, "info": "", "load_from_db": false, "title_case": false } }, "description": "Fetches the column names (keys) from the first row of a SheetDB spreadsheet.", "icon": "table", "base_classes": [ "Data", "Tool" ], "display_name": "Fetchs the Colum Names - SheetDB", "documentation": "https://sheetdb.io/documentation", "custom_fields": {}, "output_types": [], "pinned": false, "conditional_paths": [], "frozen": false, "outputs": [ { "types": [ "Data" ], "selected": "Data", "name": "api_run_model", "display_name": "Data", "method": "run_model", "value": "__UNDEFINED__", "cache": true, "required_inputs": [ "api_id" ] }, { "types": [ "Tool" ], "selected": "Tool", "name": "api_build_tool", "display_name": "Tool", "method": "build_tool", "value": "__UNDEFINED__", "cache": true, "required_inputs": [ "api_id" ] } ], "field_order": [ "api_id" ], "beta": false, "legacy": false, "edited": true, "metadata": {}, "tool_mode": false }, "type": "CustomComponent", "id": "CustomComponent-fTDig" }, "selected": false, "width": 320, "height": 300, "positionAbsolute": { "x": -63.369001666858026, "y": 308.87286497089485 }, "dragging": false }, { "id": "CustomComponent-LXya1", "type": "genericNode", "position": { "x": -596.2868568952289, "y": 1115.5923638986396 }, "data": { "node": { "template": { "_type": "Component", "api_id": { "load_from_db": false, "required": true, "placeholder": "", "show": true, "name": "api_id", "value": "", "display_name": "API ID", "advanced": false, "input_types": [ "Message" ], "dynamic": false, "info": "Your SheetDB API ID (e.g., 58f61be4dda40).", "title_case": false, "password": true, "type": "str", "_input_type": "SecretStrInput" }, "code": { "type": "code", "required": true, "placeholder": "", "list": false, "show": true, "multiline": true, "value": "import requests\r\nfrom typing import List\r\nfrom pydantic import BaseModel\r\nfrom langchain.tools import StructuredTool\r\nfrom langflow.base.langchain_utilities.model import LCToolComponent\r\nfrom langflow.field_typing import Data, Tool\r\nfrom langflow.inputs import SecretStrInput\r\n\r\n\r\nclass SheetDBCountToolComponent(LCToolComponent):\r\n display_name = \"Sheet DB Row Count\"\r\n description = \"Fetches the number of data rows (excluding the header) from a SheetDB spreadsheet.\"\r\n documentation = \"https://sheetdb.io/documentation\"\r\n icon = \"table\"\r\n name = \"SheetDBRowCount\"\r\n\r\n inputs = [\r\n SecretStrInput(\r\n name=\"api_id\",\r\n display_name=\"API ID\",\r\n info=\"Your SheetDB API ID (e.g., 58f61be4dda40).\",\r\n required=True,\r\n ),\r\n ]\r\n\r\n class SheetDBCountSchema(BaseModel):\r\n # Nenhum parâmetro no schema porque o api_id é usado apenas no nível da instância\r\n pass\r\n\r\n def _fetch_row_count(self) -> List[Data]:\r\n url = f\"https://sheetdb.io/api/v1/{self.api_id}/count\"\r\n\r\n try:\r\n response = requests.get(url)\r\n response.raise_for_status()\r\n data = response.json()\r\n\r\n if isinstance(data, dict) and \"rows\" in data:\r\n return [Data(data={\"status\": \"success\", \"rows\": data[\"rows\"]})]\r\n else:\r\n return [Data(data={\"status\": \"error\", \"message\": \"Unexpected response format\", \"raw\": data})]\r\n\r\n except Exception as e:\r\n return [Data(data={\"status\": \"error\", \"message\": str(e)})]\r\n\r\n def build_tool(self) -> Tool:\r\n return StructuredTool.from_function(\r\n name=\"fetch_sheetdb_row_count\",\r\n description=\"Returns the number of rows in a SheetDB spreadsheet (excluding the header).\",\r\n func=self._fetch_row_count,\r\n args_schema=self.SheetDBCountSchema,\r\n )\r\n\r\n def run_model(self) -> List[Data]:\r\n return self._fetch_row_count()\r\n", "fileTypes": [], "file_path": "", "password": false, "name": "code", "advanced": true, "dynamic": true, "info": "", "load_from_db": false, "title_case": false } }, "description": "Fetches the number of data rows (excluding the header) from a SheetDB spreadsheet.", "icon": "table", "base_classes": [ "Data", "Tool" ], "display_name": "Fetches the number of data rows - SheetDB", "documentation": "https://sheetdb.io/documentation", "custom_fields": {}, "output_types": [], "pinned": false, "conditional_paths": [], "frozen": false, "outputs": [ { "types": [ "Data" ], "selected": "Data", "name": "api_run_model", "display_name": "Data", "method": "run_model", "value": "__UNDEFINED__", "cache": true, "required_inputs": [ "api_id" ] }, { "types": [ "Tool" ], "selected": "Tool", "name": "api_build_tool", "display_name": "Tool", "method": "build_tool", "value": "__UNDEFINED__", "cache": true, "required_inputs": [ "api_id" ] } ], "field_order": [ "api_id" ], "beta": false, "legacy": false, "edited": true, "metadata": {}, "tool_mode": false }, "type": "CustomComponent", "id": "CustomComponent-LXya1" }, "selected": false, "width": 320, "height": 300, "positionAbsolute": { "x": -596.2868568952289, "y": 1115.5923638986396 }, "dragging": false }, { "id": "CustomComponent-AAPMp", "type": "genericNode", "position": { "x": -36.90680092851096, "y": 640.750873765787 }, "data": { "node": { "template": { "_type": "Component", "api_id": { "load_from_db": false, "required": true, "placeholder": "", "show": true, "name": "api_id", "value": "", "display_name": "API ID", "advanced": false, "input_types": [ "Message" ], "dynamic": false, "info": "The unique SheetDB API ID.", "title_case": false, "password": true, "type": "str", "_input_type": "SecretStrInput" }, "code": { "type": "code", "required": true, "placeholder": "", "list": false, "show": true, "multiline": true, "value": "import requests\r\nfrom typing import Dict, Any, List, Optional\r\nfrom pydantic import BaseModel, Field\r\nfrom langchain.tools import StructuredTool\r\nfrom langflow.base.langchain_utilities.model import LCToolComponent\r\nfrom langflow.field_typing import Data, Tool\r\nfrom langflow.inputs import SecretStrInput, NestedDictInput\r\nfrom loguru import logger\r\n\r\n\r\nclass SheetDBSearchToolComponent(LCToolComponent):\r\n display_name = \"SheetDB Search Tool\"\r\n description = \"Search rows in a SheetDB spreadsheet based on query conditions.\"\r\n documentation = \"https://sheetdb.io/api#search\"\r\n icon = \"table\"\r\n name = \"SheetDBSearch\"\r\n\r\n inputs = [\r\n SecretStrInput(\r\n name=\"api_id\",\r\n display_name=\"API ID\",\r\n info=\"The unique SheetDB API ID.\",\r\n required=True,\r\n ),\r\n NestedDictInput(\r\n name=\"query\",\r\n display_name=\"Query Conditions\",\r\n info=\"Dictionary of conditions. Example: {'Cliente': 'Equatorial'} or {'id[]': '>1', 'id[]': '<5'}\",\r\n input_types=[\"Data\"],\r\n required=False,\r\n ),\r\n ]\r\n\r\n class SheetDBSearchSchema(BaseModel):\r\n query: Optional[Dict[str, Any]] = Field(\r\n default_factory=dict,\r\n description=\"Dictionary of search conditions. Example: {'Cliente': 'Equatorial'}\"\r\n )\r\n\r\n def _search_sheetdb(self, query: Optional[Dict[str, Any]] = None) -> List[Data]:\r\n if not query:\r\n return [Data(data={\"status\": \"error\", \"message\": \"Missing query parameters. Provide a query like {'Cliente': 'Equatorial'}.\"})]\r\n\r\n url = f\"https://sheetdb.io/api/v1/{self.api_id}/search\"\r\n params = {**query}\r\n\r\n try:\r\n response = requests.get(url, params=params)\r\n response.raise_for_status()\r\n results = response.json()\r\n\r\n return [Data(data=result) for result in results]\r\n\r\n except requests.RequestException as e:\r\n logger.error(f\"SheetDB search failed: {str(e)}\")\r\n return [Data(data={\"status\": \"error\", \"message\": str(e)})]\r\n\r\n def build_tool(self) -> Tool:\r\n return StructuredTool.from_function(\r\n name=\"sheetdb_search\",\r\n description=(\r\n \"Search SheetDB rows by passing a dictionary in 'query', where keys are column names and values are filter values. \"\r\n \"Supports operators like >, <, !, and wildcards (*). Example: query={'Cliente': 'Equatorial'} or {'id[]': '>1', 'id[]': '<5'}.\"\r\n ),\r\n func=self._search_sheetdb,\r\n args_schema=self.SheetDBSearchSchema,\r\n )\r\n\r\n def run_model(self) -> List[Data]:\r\n return self._search_sheetdb(query=self.query)\r\n", "fileTypes": [], "file_path": "", "password": false, "name": "code", "advanced": true, "dynamic": true, "info": "", "load_from_db": false, "title_case": false }, "query": { "trace_as_input": true, "trace_as_metadata": true, "list": false, "required": false, "placeholder": "", "show": true, "name": "query", "value": {}, "display_name": "Query Conditions", "advanced": false, "input_types": [ "Data" ], "dynamic": false, "info": "Dictionary of conditions. Example: {'Cliente': 'Equatorial'} or {'id[]': '>1', 'id[]': '<5'}", "title_case": false, "type": "NestedDict", "_input_type": "NestedDictInput" } }, "description": "Search rows in a SheetDB spreadsheet based on query conditions.", "icon": "table", "base_classes": [ "Data", "Tool" ], "display_name": "Search Rows - SheetDB", "documentation": "https://sheetdb.io/api#search", "custom_fields": {}, "output_types": [], "pinned": false, "conditional_paths": [], "frozen": false, "outputs": [ { "types": [ "Data" ], "selected": "Data", "name": "api_run_model", "display_name": "Data", "method": "run_model", "value": "__UNDEFINED__", "cache": true, "required_inputs": [ "api_id" ] }, { "types": [ "Tool" ], "selected": "Tool", "name": "api_build_tool", "display_name": "Tool", "method": "build_tool", "value": "__UNDEFINED__", "cache": true, "required_inputs": [ "api_id" ] } ], "field_order": [ "api_id", "query" ], "beta": false, "legacy": false, "edited": true, "metadata": {}, "tool_mode": false }, "type": "CustomComponent", "id": "CustomComponent-AAPMp" }, "selected": false, "width": 320, "height": 384, "positionAbsolute": { "x": -36.90680092851096, "y": 640.750873765787 }, "dragging": false }, { "id": "CustomComponent-qUhcc", "type": "genericNode", "position": { "x": -89.14778908915298, "y": 1139.0215971342059 }, "data": { "node": { "template": { "_type": "Component", "api_id": { "load_from_db": false, "required": true, "placeholder": "", "show": true, "name": "api_id", "value": "", "display_name": "SheetDB API ID", "advanced": false, "input_types": [ "Message" ], "dynamic": false, "info": "The SheetDB API ID (found in your SheetDB endpoint URL).", "title_case": false, "password": true, "type": "str", "_input_type": "SecretStrInput" }, "code": { "type": "code", "required": true, "placeholder": "", "list": false, "show": true, "multiline": true, "value": "import requests\r\nfrom typing import List, Dict, Any, Union\r\nfrom pydantic import BaseModel, Field\r\nfrom langchain.tools import StructuredTool\r\nfrom langflow.base.langchain_utilities.model import LCToolComponent\r\nfrom langflow.field_typing import Data, Tool\r\nfrom langflow.inputs import NestedDictInput, SecretStrInput\r\nfrom loguru import logger\r\n\r\n\r\nclass SheetDBCreateToolComponent(LCToolComponent):\r\n display_name = \"SheetDB Create Tool\"\r\n description = (\r\n \"Adds one or more rows to a SheetDB spreadsheet.\\n\\n\"\r\n \"You must provide a row (or a list of rows) with keys matching the spreadsheet columns.\\n\"\r\n \"Use 'INCREMENT' for auto-incrementing numeric IDs, 'DATETIME' or 'TIMESTAMP' to use current date/time.\\n\\n\"\r\n \"⚠️ If the user passes partial data (e.g., only 3 out of 5 columns), the assistant should ask for the remaining fields.\"\r\n )\r\n documentation = \"https://sheetdb.io/api#post\"\r\n icon = \"table\"\r\n name = \"SheetDBCreateTool\"\r\n\r\n inputs = [\r\n SecretStrInput(\r\n name=\"api_id\",\r\n display_name=\"SheetDB API ID\",\r\n info=\"The SheetDB API ID (found in your SheetDB endpoint URL).\",\r\n required=True,\r\n ),\r\n NestedDictInput(\r\n name=\"data_rows\",\r\n display_name=\"Row Data\",\r\n info=\"Provide a single row as a dict or multiple rows as a list of dicts. \"\r\n \"Keys must match your spreadsheet columns.\",\r\n input_types=[\"Data\"],\r\n ),\r\n ]\r\n\r\n class SheetDBCreateSchema(BaseModel):\r\n data_rows: Union[List[Dict[str, Any]], Dict[str, Any]] = Field(\r\n ..., description=(\r\n \"A single row (as dict) or multiple rows (as list of dicts). \"\r\n \"Use 'INCREMENT' for ID, 'DATETIME' or 'TIMESTAMP' for date/time. \"\r\n \"Example: [{'id': 'INCREMENT', 'name': 'Maria', 'age': 28}]\"\r\n )\r\n )\r\n\r\n def _create_rows(self, data_rows: Union[List[Dict[str, Any]], Dict[str, Any]]) -> List[Data]:\r\n url = f\"https://sheetdb.io/api/v1/{self.api_id}\"\r\n headers = {\"Content-Type\": \"application/json\"}\r\n\r\n if isinstance(data_rows, dict):\r\n data_rows = [data_rows]\r\n\r\n payload = {\"data\": data_rows}\r\n\r\n try:\r\n response = requests.post(url, json=payload, headers=headers)\r\n response.raise_for_status()\r\n return [Data(data={\"status\": \"success\", \"created\": response.json().get(\"created\", 0)})]\r\n except requests.RequestException as e:\r\n logger.error(f\"SheetDB row creation failed: {str(e)}\")\r\n return [Data(data={\"status\": \"error\", \"message\": str(e)})]\r\n\r\n def build_tool(self) -> Tool:\r\n return StructuredTool.from_function(\r\n name=\"sheetdb_create_rows\",\r\n description=\"Create rows in SheetDB using a single row dict or a list of rows.\",\r\n func=self._create_rows,\r\n args_schema=self.SheetDBCreateSchema,\r\n )\r\n\r\n def run_model(self) -> List[Data]:\r\n return self._create_rows(data_rows=self.data_rows)\r\n", "fileTypes": [], "file_path": "", "password": false, "name": "code", "advanced": true, "dynamic": true, "info": "", "load_from_db": false, "title_case": false }, "data_rows": { "trace_as_input": true, "trace_as_metadata": true, "list": false, "required": false, "placeholder": "", "show": true, "name": "data_rows", "value": {}, "display_name": "Row Data", "advanced": false, "input_types": [ "Data" ], "dynamic": false, "info": "Provide a single row as a dict or multiple rows as a list of dicts. Keys must match your spreadsheet columns.", "title_case": false, "type": "NestedDict", "_input_type": "NestedDictInput" } }, "description": "Adds one or more rows to a SheetDB spreadsheet.\n\nYou must provide a row (or a list of rows) with keys matching the spreadsheet columns.\nUse 'INCREMENT' for auto-incrementing numeric IDs, 'DATETIME' or 'TIMESTAMP' to use current date/time.\n\n⚠️ If the user passes partial data (e.g., only 3 out of 5 columns), the assistant should ask for the remaining fields.", "icon": "table", "base_classes": [ "Data", "Tool" ], "display_name": "Insert New Row - SheetDB", "documentation": "https://sheetdb.io/api#post", "custom_fields": {}, "output_types": [], "pinned": false, "conditional_paths": [], "frozen": false, "outputs": [ { "types": [ "Data" ], "selected": "Data", "name": "api_run_model", "display_name": "Data", "method": "run_model", "value": "__UNDEFINED__", "cache": true, "required_inputs": [ "api_id" ] }, { "types": [ "Tool" ], "selected": "Tool", "name": "api_build_tool", "display_name": "Tool", "method": "build_tool", "value": "__UNDEFINED__", "cache": true, "required_inputs": [ "api_id" ] } ], "field_order": [ "api_id", "data_rows" ], "beta": false, "legacy": false, "edited": true, "metadata": {}, "tool_mode": false }, "type": "CustomComponent", "id": "CustomComponent-qUhcc" }, "selected": false, "width": 320, "height": 609, "positionAbsolute": { "x": -89.14778908915298, "y": 1139.0215971342059 }, "dragging": false }, { "id": "note-3eHEE", "type": "noteNode", "position": { "x": -1509.499784437431, "y": 506.0519601933015 }, "data": { "node": { "description": "Este agente é um assistente inteligente desenvolvido para interagir com planilhas do Google Sheets usando a API da SheetDB. Ele é capaz de consultar, ler, inserir e analisar dados de forma automatizada a partir de comandos fornecidos pelo usuário em linguagem natural\n\n## Componentes utilizados\nChat Input: Componente onde o usuário digita sua solicitação (prompt).\n\n**Agent:** Agente baseado no modelo OpenAI gpt-4-0613, configurado para interpretar comandos e acionar ferramentas conectadas.\n\n**Chat Output:** Exibe a resposta do agente para o usuário.\n\n**Fetch the Column Names:** Recupera os nomes das colunas de uma planilha específica.\n\n**Read the data:** Lê os dados de uma planilha Google Sheets via SheetDB API, com suporte para paginação, ordenação e filtros.\n\n**Search Rows:** Realiza buscas condicionais (queries) dentro da planilha.\n\n**Insert New Row:** Insere uma nova linha na planilha com base nos dados fornecidos.\n\nFetch the number of rows: Recupera a quantidade de linhas presentes na planilha, excluindo o cabeçalho.\n\n## 🛠️ Como funciona?\nO usuário envia uma solicitação no Chat 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