"""Retriever using Exa Search API.""" from __future__ import annotations from typing import Any, Literal from exa_py import Exa # type: ignore[untyped-import] from exa_py.api import ( HighlightsContentsOptions, # type: ignore[untyped-import] TextContentsOptions, # type: ignore[untyped-import] ) from langchain_core.callbacks import CallbackManagerForRetrieverRun from langchain_core.documents import Document from langchain_core.retrievers import BaseRetriever from pydantic import Field, SecretStr, model_validator from langchain_exa._utilities import initialize_client def _get_metadata(result: Any) -> dict[str, Any]: """Get the metadata from a result object.""" metadata = { "title": result.title, "url": result.url, "id": result.id, "score": result.score, "published_date": result.published_date, "author": result.author, } for attribute in ("highlights", "highlight_scores", "summary"): if value := getattr(result, attribute, None): metadata[attribute] = value return metadata class ExaSearchRetriever(BaseRetriever): """Exa Search retriever.""" k: int = 10 # num_results """The number of search results to return (1 to 100).""" include_domains: list[str] | None = None """A list of domains to include in the search.""" exclude_domains: list[str] | None = None """A list of domains to exclude from the search.""" start_crawl_date: str | None = None """The start date for the crawl (in YYYY-MM-DD format).""" end_crawl_date: str | None = None """The end date for the crawl (in YYYY-MM-DD format).""" start_published_date: str | None = None """The start date for when the document was published (in YYYY-MM-DD format).""" end_published_date: str | None = None """The end date for when the document was published (in YYYY-MM-DD format).""" use_autoprompt: bool | None = None """Whether to use autoprompt for the search.""" type: str = "auto" """The type of search, 'auto', 'deep', or 'fast'. Default: auto""" highlights: HighlightsContentsOptions | bool | None = None """Whether to set the page content to the highlights of the results.""" text_contents_options: TextContentsOptions | dict[str, Any] | Literal[True] = True """How to set the page content of the results. Can be True or a dict with options like max_characters.""" livecrawl: Literal["always", "fallback", "never"] | None = None """Option to crawl live webpages if content is not in the index. Options: "always", "fallback", "never".""" summary: bool | dict[str, str] | None = None """Whether to include a summary of the content. Can be a boolean or a dict with a custom query.""" client: Exa = Field(default=None) # type: ignore[assignment] exa_api_key: SecretStr = Field(default=SecretStr("")) exa_base_url: str | None = None @model_validator(mode="before") @classmethod def validate_environment(cls, values: dict) -> Any: """Validate the environment.""" return initialize_client(values) def _get_relevant_documents( self, query: str, *, run_manager: CallbackManagerForRetrieverRun ) -> list[Document]: response = self.client.search_and_contents( # type: ignore[call-overload] query, num_results=self.k, text=self.text_contents_options, highlights=self.highlights, include_domains=self.include_domains, exclude_domains=self.exclude_domains, start_crawl_date=self.start_crawl_date, end_crawl_date=self.end_crawl_date, start_published_date=self.start_published_date, end_published_date=self.end_published_date, use_autoprompt=self.use_autoprompt, livecrawl=self.livecrawl, summary=self.summary, type=self.type, ) # type: ignore[call-overload, misc] results = response.results return [ Document( page_content=(result.text), metadata=_get_metadata(result), ) for result in results ]