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