base.py — langchain Source File

Source Code

"""Chain that does self-ask with search."""

from __future__ import annotations

from collections.abc import Sequence
from typing import TYPE_CHECKING, Any

from langchain_core._api import deprecated
from langchain_core.language_models import BaseLanguageModel
from langchain_core.prompts import BasePromptTemplate
from langchain_core.runnables import Runnable, RunnablePassthrough
from langchain_core.tools import BaseTool, Tool
from pydantic import Field
from typing_extensions import override

from langchain_classic.agents.agent import Agent, AgentExecutor, AgentOutputParser
from langchain_classic.agents.agent_types import AgentType
from langchain_classic.agents.format_scratchpad import format_log_to_str
from langchain_classic.agents.self_ask_with_search.output_parser import (
    SelfAskOutputParser,
)
from langchain_classic.agents.self_ask_with_search.prompt import PROMPT
from langchain_classic.agents.utils import validate_tools_single_input

if TYPE_CHECKING:
    from langchain_community.utilities.google_serper import GoogleSerperAPIWrapper
    from langchain_community.utilities.searchapi import SearchApiAPIWrapper
    from langchain_community.utilities.serpapi import SerpAPIWrapper


@deprecated("0.1.0", alternative="create_self_ask_with_search", removal="1.0")
class SelfAskWithSearchAgent(Agent):
    """Agent for the self-ask-with-search paper."""

    output_parser: AgentOutputParser = Field(default_factory=SelfAskOutputParser)

    @classmethod
    @override
    def _get_default_output_parser(cls, **kwargs: Any) -> AgentOutputParser:
        return SelfAskOutputParser()

    @property
    def _agent_type(self) -> str:
        """Return Identifier of an agent type."""
        return AgentType.SELF_ASK_WITH_SEARCH

    @classmethod
    @override
    def create_prompt(cls, tools: Sequence[BaseTool]) -> BasePromptTemplate:
        """Prompt does not depend on tools."""
        return PROMPT

    @classmethod
    def _validate_tools(cls, tools: Sequence[BaseTool]) -> None:
        validate_tools_single_input(cls.__name__, tools)
        super()._validate_tools(tools)
        if len(tools) != 1:
            msg = f"Exactly one tool must be specified, but got {tools}"
            raise ValueError(msg)
        tool_names = {tool.name for tool in tools}
// ... (157 more lines)