Source code for langchain.chains.router.llm_router
"""Base classes for LLM-powered router chains."""
from __future__ import annotations
from typing import Any, Dict, List, Optional, Type, cast
from langchain.callbacks.manager import (
    AsyncCallbackManagerForChainRun,
    CallbackManagerForChainRun,
)
from langchain.chains import LLMChain
from langchain.chains.router.base import RouterChain
from langchain.output_parsers.json import parse_and_check_json_markdown
from langchain.pydantic_v1 import root_validator
from langchain.schema import BaseOutputParser, BasePromptTemplate, OutputParserException
from langchain.schema.language_model import BaseLanguageModel
[docs]class LLMRouterChain(RouterChain):
    """A router chain that uses an LLM chain to perform routing."""
    llm_chain: LLMChain
    """LLM chain used to perform routing"""
    @root_validator()
    def validate_prompt(cls, values: dict) -> dict:
        prompt = values["llm_chain"].prompt
        if prompt.output_parser is None:
            raise ValueError(
                "LLMRouterChain requires base llm_chain prompt to have an output"
                " parser that converts LLM text output to a dictionary with keys"
                " 'destination' and 'next_inputs'. Received a prompt with no output"
                " parser."
            )
        return values
    @property
    def input_keys(self) -> List[str]:
        """Will be whatever keys the LLM chain prompt expects.
        :meta private:
        """
        return self.llm_chain.input_keys
    def _validate_outputs(self, outputs: Dict[str, Any]) -> None:
        super()._validate_outputs(outputs)
        if not isinstance(outputs["next_inputs"], dict):
            raise ValueError
    def _call(