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langchain/libs/partners/exa
Danny McAteer e42110f720
docs: Additional examples for partners/exa README (#18081)
**Description:** Add additional examples for other modules to
partners/exa README
**Issue:** #17545
**Dependencies:** None
**Twitter handle:** @DannyMcAteer8

---------

Co-authored-by: Daniel McAteer <danielmcateer@Daniels-MBP.attlocal.net>
Co-authored-by: Daniel McAteer <danielmcateer@Daniels-MacBook-Pro.local>
7 months ago
..
langchain_exa exa[patch]: fix lint (#17610) 7 months ago
scripts infra: add print rule to ruff (#16221) 7 months ago
tests infra: add print rule to ruff (#16221) 7 months ago
.gitignore exa: init pkg (#16553) 8 months ago
LICENSE exa: init pkg (#16553) 8 months ago
Makefile exa: init pkg (#16553) 8 months ago
README.md docs: Additional examples for partners/exa README (#18081) 7 months ago
poetry.lock exa[patch]: fix lint (#17610) 7 months ago
pyproject.toml exa[patch]: fix lint (#17610) 7 months ago

README.md

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.get_relevant_documents(query="What is the capital of France?")

# Print the results
print(results)

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)