mirror of
https://github.com/hwchase17/langchain
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52 lines
1.5 KiB
Python
52 lines
1.5 KiB
Python
from typing import Literal, Optional, Type, TypedDict
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from langchain_core.pydantic_v1 import BaseModel
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from langchain_core.utils.json_schema import dereference_refs
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class FunctionDescription(TypedDict):
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"""Representation of a callable function to the Ernie API."""
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name: str
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"""The name of the function."""
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description: str
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"""A description of the function."""
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parameters: dict
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"""The parameters of the function."""
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class ToolDescription(TypedDict):
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"""Representation of a callable function to the Ernie API."""
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type: Literal["function"]
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function: FunctionDescription
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def convert_pydantic_to_ernie_function(
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model: Type[BaseModel],
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*,
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name: Optional[str] = None,
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description: Optional[str] = None,
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) -> FunctionDescription:
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"""Convert a Pydantic model to a function description for the Ernie API."""
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schema = dereference_refs(model.schema())
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schema.pop("definitions", None)
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return {
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"name": name or schema["title"],
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"description": description or schema["description"],
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"parameters": schema,
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}
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def convert_pydantic_to_ernie_tool(
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model: Type[BaseModel],
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*,
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name: Optional[str] = None,
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description: Optional[str] = None,
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) -> ToolDescription:
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"""Convert a Pydantic model to a function description for the Ernie API."""
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function = convert_pydantic_to_ernie_function(
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model, name=name, description=description
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)
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return {"type": "function", "function": function}
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