extraction.py — langchain Source File

Source Code

from typing import Any

from langchain_core._api import deprecated
from langchain_core.language_models import BaseLanguageModel
from langchain_core.output_parsers.openai_functions import (
    JsonKeyOutputFunctionsParser,
    PydanticAttrOutputFunctionsParser,
)
from langchain_core.prompts import BasePromptTemplate, ChatPromptTemplate
from pydantic import BaseModel

from langchain_classic.chains.base import Chain
from langchain_classic.chains.llm import LLMChain
from langchain_classic.chains.openai_functions.utils import (
    _convert_schema,
    _resolve_schema_references,
    get_llm_kwargs,
)


def _get_extraction_function(entity_schema: dict) -> dict:
    return {
        "name": "information_extraction",
        "description": "Extracts the relevant information from the passage.",
        "parameters": {
            "type": "object",
            "properties": {
                "info": {"type": "array", "items": _convert_schema(entity_schema)},
            },
            "required": ["info"],
        },
    }


_EXTRACTION_TEMPLATE = """Extract and save the relevant entities mentioned \
in the following passage together with their properties.

Only extract the properties mentioned in the 'information_extraction' function.

If a property is not present and is not required in the function parameters, do not include it in the output.

Passage:
{input}
"""  # noqa: E501


@deprecated(
    since="0.1.14",
    message=(
        "LangChain has introduced a method called `with_structured_output` that"
        "is available on ChatModels capable of tool calling."
        "You can read more about the method here: "
        "<https://docs.langchain.com/oss/python/langchain/models#structured-outputs>."
    ),
    removal="1.0",
    alternative=(
        """
            from pydantic import BaseModel, Field
            from langchain_anthropic import ChatAnthropic

// ... (131 more lines)