mirror of
https://github.com/hwchase17/langchain.git
synced 2025-08-14 23:26:34 +00:00
Co-authored-by: Maxime Grenu <69890511+cluster2600@users.noreply.github.com> Co-authored-by: Claude <claude@anthropic.com> Co-authored-by: Claude <noreply@anthropic.com> Co-authored-by: jmaillefaud <jonathan.maillefaud@evooq.ch> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com> Co-authored-by: tanwirahmad <tanwirahmad@users.noreply.github.com> Co-authored-by: Christophe Bornet <cbornet@hotmail.com> Co-authored-by: Copilot <198982749+Copilot@users.noreply.github.com> Co-authored-by: niceg <79145285+growmuye@users.noreply.github.com> Co-authored-by: Chaitanya varma <varmac301@gmail.com> Co-authored-by: dishaprakash <57954147+dishaprakash@users.noreply.github.com> Co-authored-by: Chester Curme <chester.curme@gmail.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> Co-authored-by: Kanav Bansal <13186335+bansalkanav@users.noreply.github.com> Co-authored-by: Aleksandr Filippov <71711753+alex-feel@users.noreply.github.com> Co-authored-by: Alex Feel <afilippov@spotware.com> |
||
---|---|---|
.. | ||
langchain_exa | ||
scripts | ||
tests | ||
.gitignore | ||
LICENSE | ||
Makefile | ||
pyproject.toml | ||
README.md | ||
uv.lock |
langchain-exa
This package contains the LangChain integrations for Exa Cloud generative models.
Installation
pip install -U langchain-exa
Exa Search Retriever
You can retrieve search results as follows
from langchain_exa import ExaSearchRetriever
exa_api_key = "YOUR API KEY"
# Create a new instance of the ExaSearchRetriever
exa = ExaSearchRetriever(exa_api_key=exa_api_key)
# Search for a query and save the results
results = exa.invoke("What is the capital of France?")
# Print the results
print(results)
Advanced Features
You can use advanced features like text limits, summaries, and live crawling:
from langchain_exa import ExaSearchRetriever, TextContentsOptions
# Create a new instance with advanced options
exa = ExaSearchRetriever(
exa_api_key="YOUR API KEY",
k=20, # Number of results (1-100)
type="auto", # Can be "neural", "keyword", or "auto"
livecrawl="always", # Can be "always", "fallback", or "never"
summary=True, # Get an AI-generated summary of each result
text_contents_options={"max_characters": 3000} # Limit text length
)
# Search for a query with custom summary prompt
exa_with_custom_summary = ExaSearchRetriever(
exa_api_key="YOUR API KEY",
summary={"query": "generate one line summary in simple words."} # Custom summary prompt
)
Exa Search Results
You can run the ExaSearchResults module as follows
from langchain_exa import ExaSearchResults
# Initialize the ExaSearchResults tool
search_tool = ExaSearchResults(exa_api_key="YOUR API KEY")
# Perform a search query
search_results = search_tool._run(
query="When was the last time the New York Knicks won the NBA Championship?",
num_results=5,
text_contents_options=True,
highlights=True
)
print("Search Results:", search_results)
Exa Find Similar Results
You can run the ExaFindSimilarResults module as follows
from langchain_exa import ExaFindSimilarResults
# Initialize the ExaFindSimilarResults tool
find_similar_tool = ExaFindSimilarResults(exa_api_key="YOUR API KEY")
# Find similar results based on a URL
similar_results = find_similar_tool._run(
url="http://espn.com",
num_results=5,
text_contents_options=True,
highlights=True
)
print("Similar Results:", similar_results)
Configuration Options
All Exa tools support the following common parameters:
num_results
(1-100): Number of search results to returntype
: Search type - "neural", "keyword", or "auto"livecrawl
: Live crawling mode - "always", "fallback", or "never"summary
: Get AI-generated summaries (True/False or custom prompt dict)text_contents_options
: Dict to limit text length (e.g.{"max_characters": 2000}
)highlights
: Include highlighted text snippets (True/False)