mirror of
https://github.com/hwchase17/langchain.git
synced 2025-08-17 00:17:47 +00:00
f16456139b
Added support for new Exa API features. Updated Exa docs and python package (langchain-exa). Description Added support for new Exa API features in the langchain-exa package: - Added max_characters option for text content - Added support for summary and custom summary prompts - Added livecrawl option with "always", "fallback", "never" settings - Added "auto" option for search type - Updated documentation and tests Dependencies - No new dependencies required. Using existing features from exa-py. twitter: @theishangoswami --------- Co-authored-by: Chester Curme <chester.curme@gmail.com>
110 lines
4.2 KiB
Python
110 lines
4.2 KiB
Python
from typing import Any, Literal, Optional, Union
|
|
|
|
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,
|
|
}
|
|
if getattr(result, "highlights"):
|
|
metadata["highlights"] = result.highlights
|
|
if getattr(result, "highlight_scores"):
|
|
metadata["highlight_scores"] = result.highlight_scores
|
|
if getattr(result, "summary"):
|
|
metadata["summary"] = result.summary
|
|
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: Optional[list[str]] = None
|
|
"""A list of domains to include in the search."""
|
|
exclude_domains: Optional[list[str]] = None
|
|
"""A list of domains to exclude from the search."""
|
|
start_crawl_date: Optional[str] = None
|
|
"""The start date for the crawl (in YYYY-MM-DD format)."""
|
|
end_crawl_date: Optional[str] = None
|
|
"""The end date for the crawl (in YYYY-MM-DD format)."""
|
|
start_published_date: Optional[str] = None
|
|
"""The start date for when the document was published (in YYYY-MM-DD format)."""
|
|
end_published_date: Optional[str] = None
|
|
"""The end date for when the document was published (in YYYY-MM-DD format)."""
|
|
use_autoprompt: Optional[bool] = None
|
|
"""Whether to use autoprompt for the search."""
|
|
type: str = "neural"
|
|
"""The type of search, 'keyword', 'neural', or 'auto'. Default: neural"""
|
|
highlights: Optional[Union[HighlightsContentsOptions, bool]] = None
|
|
"""Whether to set the page content to the highlights of the results."""
|
|
text_contents_options: Union[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: Optional[Literal["always", "fallback", "never"]] = None
|
|
"""Option to crawl live webpages if content is not in the index. Options: "always",
|
|
"fallback", "never"."""
|
|
summary: Optional[Union[bool, dict[str, str]]] = 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)
|
|
exa_api_key: SecretStr = Field(default=None)
|
|
exa_base_url: Optional[str] = None
|
|
|
|
@model_validator(mode="before")
|
|
@classmethod
|
|
def validate_environment(cls, values: dict) -> Any:
|
|
"""Validate the environment."""
|
|
values = initialize_client(values)
|
|
return values
|
|
|
|
def _get_relevant_documents(
|
|
self, query: str, *, run_manager: CallbackManagerForRetrieverRun
|
|
) -> list[Document]:
|
|
response = self.client.search_and_contents( # type: ignore[misc]
|
|
query,
|
|
num_results=self.k,
|
|
text=self.text_contents_options,
|
|
highlights=self.highlights, # type: ignore
|
|
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,
|
|
)
|
|
|
|
results = response.results
|
|
|
|
return [
|
|
Document(
|
|
page_content=(result.text),
|
|
metadata=_get_metadata(result),
|
|
)
|
|
for result in results
|
|
]
|