feat: Table Input for tools metadata (tool name and description) in component as tools (#4961)
* ✨ (endpoints.py): Add support for tool_mode field in custom component update 🔧 (schemas.py): Add tool_mode field to UpdateCustomComponentRequest schema ♻️ (component.py): Refactor run_and_validate_update_outputs method to handle tool_mode field 🔧 (index.tsx): Add tool_mode property to NodeInputField component 🔧 (index.tsx): Refactor hasToolMode logic to use checkHasToolMode utility function 🔧 (mutate-template.ts): Add callback parameter to mutateTemplate function 🔧 (use-handle-new-value.tsx): Add tool_mode property to useHandleOnNewValue hook 🔧 (popover/index.tsx): Add console.log for placeholder, value, and id 🔧 (inputGlobalComponent/index.tsx): Add tool_mode property to InputGlobalComponent 🔧 (refreshParameterComponent/index.tsx): Add tool_mode property to RefreshParameterComponent 🔧 (use-post-template-value.ts): Add tool_mode parameter to usePostTemplateValue function 🔧 (nodeToolbarComponent/index.tsx): Add support for tool_mode functionality in NodeToolbarComponent 🔧 (reactflowUtils.ts): Add checkHasToolMode utility function to check for tool_mode field in template * fix: Set default value for tool_mode in UpdateCustomComponentRequest schema * adding table input in tool mode adding table input * Update component.py update real-time refresh * added dynamic tool description input added dynamic tool description input * [autofix.ci] apply automated fixes * Update component.py simplifying the tool mode logic * Update component_tool.py updated logic to be more readable * Update component.py * adding tool table schema as constant --------- Co-authored-by: cristhianzl <cristhian.lousa@gmail.com> Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@langflow.org> Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
This commit is contained in:
Edwin Jose
GitHub
parent
505368ece7
commit
2c56177ef1
4 changed files with 74 additions and 7 deletions
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@ -609,7 +609,6 @@ async def custom_component_update(
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"""
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try:
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component = Component(_code=code_request.code)
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component_node, cc_instance = build_custom_component_template(
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component,
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user_id=user.id,
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@ -4,7 +4,8 @@ import asyncio
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import re
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from typing import TYPE_CHECKING, Literal
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from langchain_core.tools import ToolException
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import pandas as pd
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from langchain_core.tools import BaseTool, ToolException
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from langchain_core.tools.structured import StructuredTool
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from loguru import logger
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from pydantic import BaseModel
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@ -18,7 +19,6 @@ if TYPE_CHECKING:
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from collections.abc import Callable
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from langchain_core.callbacks import Callbacks
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from langchain_core.tools import BaseTool
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from langflow.custom.custom_component.component import Component
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from langflow.events.event_manager import EventManager
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@ -160,8 +160,9 @@ def _format_tool_name(name: str):
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class ComponentToolkit:
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def __init__(self, component: Component):
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def __init__(self, component: Component, metadata: pd.DataFrame | None = None):
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self.component = component
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self.metadata = metadata
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def get_tools(
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self, tool_name: str | None = None, tool_description: str | None = None, callbacks: Callbacks | None = None
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@ -241,3 +242,19 @@ class ComponentToolkit:
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)
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raise ValueError(msg)
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return tools
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def update_tools_metadata(
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self,
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tools: list[BaseTool | StructuredTool],
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) -> list[BaseTool]:
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# update the tool_name and description according to the name and secriotion mentioned in the list
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if isinstance(self.metadata, pd.DataFrame):
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metadata_dict = self.metadata.to_dict(orient="records")
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for tool, metadata in zip(tools, metadata_dict, strict=False):
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if isinstance(tool, StructuredTool | BaseTool):
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tool.name = metadata.get("name", tool.name)
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tool.description = metadata.get("description", tool.description)
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else:
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msg = f"Expected a StructuredTool or BaseTool, got {type(tool)}"
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raise TypeError(msg)
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return tools
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@ -1,2 +1,17 @@
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TOOL_OUTPUT_NAME = "component_as_tool"
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TOOL_OUTPUT_DISPLAY_NAME = "Toolset"
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TOOLS_METADATA_INPUT_NAME = "tools_metadata"
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TOOL_TABLE_SCHEMA = [
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{
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"name": "name",
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"display_name": "Name",
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"type": "str",
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"description": "Specify the name of the output field.",
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},
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{
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"name": "description",
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"display_name": "Description",
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"type": "str",
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"description": "Describe the purpose of the output field.",
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},
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]
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@ -13,7 +13,12 @@ import yaml
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from langchain_core.tools import StructuredTool
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from pydantic import BaseModel, ValidationError
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from langflow.base.tools.constants import TOOL_OUTPUT_DISPLAY_NAME, TOOL_OUTPUT_NAME
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from langflow.base.tools.constants import (
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TOOL_OUTPUT_DISPLAY_NAME,
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TOOL_OUTPUT_NAME,
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TOOL_TABLE_SCHEMA,
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TOOLS_METADATA_INPUT_NAME,
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)
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from langflow.custom.tree_visitor import RequiredInputsVisitor
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from langflow.exceptions.component import StreamingError
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from langflow.field_typing import Tool # noqa: TCH001 Needed by _add_toolkit_output
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@ -399,7 +404,12 @@ class Component(CustomComponent):
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if field_name == "tool_mode" or frontend_node.get("tool_mode"):
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is_tool_mode = field_value or frontend_node.get("tool_mode")
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frontend_node["outputs"] = [self._build_tool_output()] if is_tool_mode else frontend_node["outputs"]
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if is_tool_mode:
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frontend_node.setdefault("template", {})
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frontend_node["template"][TOOLS_METADATA_INPUT_NAME] = self._build_tools_metadata_input().to_dict()
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elif "template" in frontend_node:
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frontend_node["template"].pop(TOOLS_METADATA_INPUT_NAME, None)
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self.tools_metadata = frontend_node.get("template", {}).get(TOOLS_METADATA_INPUT_NAME, {}).get("value")
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return self._validate_frontend_node(frontend_node)
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def _validate_frontend_node(self, frontend_node: dict):
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@ -966,7 +976,10 @@ class Component(CustomComponent):
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def to_toolkit(self) -> list[Tool]:
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component_toolkit = _get_component_toolkit()
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return component_toolkit(component=self).get_tools(callbacks=self.get_langchain_callbacks())
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tools = component_toolkit(component=self).get_tools(callbacks=self.get_langchain_callbacks())
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if hasattr(self, TOOLS_METADATA_INPUT_NAME):
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tools = component_toolkit(component=self, metadata=self.tools_metadata).update_tools_metadata(tools=tools)
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return tools
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def get_project_name(self):
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if hasattr(self, "_tracing_service") and self._tracing_service:
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@ -1137,6 +1150,29 @@ class Component(CustomComponent):
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def _append_tool_to_outputs_map(self):
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self._outputs_map[TOOL_OUTPUT_NAME] = self._build_tool_output()
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# add a new input for the tool schema
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# self.inputs.append(self._build_tool_schema())
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def _build_tool_output(self) -> Output:
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return Output(name=TOOL_OUTPUT_NAME, display_name=TOOL_OUTPUT_DISPLAY_NAME, method="to_toolkit", types=["Tool"])
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def _build_tools_metadata_input(self):
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tools = self.to_toolkit()
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tool_data = (
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self.tools_metadata
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if hasattr(self, TOOLS_METADATA_INPUT_NAME)
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else [{"name": tool.name, "description": tool.description} for tool in tools]
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)
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try:
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from langflow.io import TableInput
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except ImportError as e:
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msg = "Failed to import TableInput from langflow.io"
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raise ImportError(msg) from e
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return TableInput(
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name=TOOLS_METADATA_INPUT_NAME,
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display_name="Tools Metadata",
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real_time_refresh=True,
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table_schema=TOOL_TABLE_SCHEMA,
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value=tool_data,
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)
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