🚀 feat(customs.py): re-add PythonFunction to CUSTOM_NODES (#450)
This commit is contained in:
commit
9823b4c9c5
9 changed files with 135 additions and 73 deletions
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@ -84,6 +84,7 @@ tools:
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- Serper Search
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- Tool
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- PythonFunctionTool
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- PythonFunction
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- JsonSpec
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- News API
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- TMDB API
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@ -5,6 +5,7 @@ CUSTOM_NODES = {
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"prompts": {"ZeroShotPrompt": frontend_node.prompts.ZeroShotPromptNode()},
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"tools": {
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"PythonFunctionTool": frontend_node.tools.PythonFunctionToolNode(),
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"PythonFunction": frontend_node.tools.PythonFunctionNode(),
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"Tool": frontend_node.tools.ToolNode(),
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},
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"agents": {
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@ -24,7 +24,7 @@ from langflow.interface.importing.utils import get_function, import_by_type
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from langflow.interface.toolkits.base import toolkits_creator
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from langflow.interface.types import get_type_list
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from langflow.interface.utils import load_file_into_dict
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from langflow.utils import util
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from langflow.utils import util, validate
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def instantiate_class(node_type: str, base_type: str, params: Dict) -> Any:
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@ -101,6 +101,12 @@ def instantiate_tool(node_type, class_object, params):
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elif node_type == "PythonFunctionTool":
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params["func"] = get_function(params.get("code"))
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return class_object(**params)
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# For backward compatibility
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elif node_type == "PythonFunction":
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function_string = params["code"]
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if isinstance(function_string, str):
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return validate.eval_function(function_string)
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raise ValueError("Function should be a string")
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elif node_type.lower() == "tool":
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return class_object(**params)
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return class_object(**params)
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@ -9,10 +9,14 @@ from langchain.agents.load_tools import (
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from langchain.tools.json.tool import JsonSpec
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from langflow.interface.importing.utils import import_class
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from langflow.interface.tools.custom import PythonFunctionTool
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from langflow.interface.tools.custom import PythonFunctionTool, PythonFunction
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FILE_TOOLS = {"JsonSpec": JsonSpec}
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CUSTOM_TOOLS = {"Tool": Tool, "PythonFunctionTool": PythonFunctionTool}
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CUSTOM_TOOLS = {
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"Tool": Tool,
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"PythonFunctionTool": PythonFunctionTool,
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"PythonFunction": PythonFunction,
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}
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OTHER_TOOLS = {tool: import_class(f"langchain.tools.{tool}") for tool in tools.__all__}
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@ -1,4 +1,4 @@
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from typing import Optional
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from typing import Callable, Optional
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from langflow.interface.importing.utils import get_function
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from pydantic import BaseModel, validator
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@ -9,6 +9,7 @@ from langchain.agents.tools import Tool
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class Function(BaseModel):
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code: str
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function: Optional[Callable] = None
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imports: Optional[str] = None
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# Eval code and store the function
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@ -25,6 +26,12 @@ class Function(BaseModel):
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return v
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def get_function(self):
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"""Get the function"""
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function_name = validate.extract_function_name(self.code)
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return validate.create_function(self.code, function_name)
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class PythonFunctionTool(Function, Tool):
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"""Python function"""
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@ -39,3 +46,9 @@ class PythonFunctionTool(Function, Tool):
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self.code = code
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self.func = get_function(self.code)
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super().__init__(name=name, description=description, func=self.func)
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class PythonFunction(Function):
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"""Python function"""
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code: str
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@ -66,5 +66,5 @@ class LLMFrontendNode(FrontendNode):
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field.show = True
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LLMFrontendNode.format_openai_field(field)
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if "azure" in name.lower():
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if name and "azure" in name.lower():
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LLMFrontendNode.format_azure_field(field)
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@ -103,3 +103,27 @@ class PythonFunctionToolNode(FrontendNode):
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def to_dict(self):
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return super().to_dict()
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class PythonFunctionNode(FrontendNode):
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name: str = "PythonFunction"
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template: Template = Template(
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type_name="python_function",
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fields=[
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TemplateField(
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field_type="code",
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required=True,
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placeholder="",
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is_list=False,
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show=True,
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value=DEFAULT_PYTHON_FUNCTION,
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name="code",
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advanced=False,
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)
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],
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)
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description: str = "Python function to be executed."
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base_classes: list[str] = ["function"]
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def to_dict(self):
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return super().to_dict()
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