langchain/libs/partners/exa
Erick Friis 1a225fad03
multiple: fix uv path deps (#29790)
file:// format wasn't working with updates - it doesn't install as an
editable dep

move to tool.uv.sources with path= instead
2025-02-13 21:32:34 +00:00
..
langchain_exa infra: migrate to uv (#29566) 2025-02-06 13:36:26 -05:00
scripts multiple: pydantic 2 compatibility, v0.3 (#26443) 2024-09-13 14:38:45 -07:00
tests
.gitignore
LICENSE
Makefile infra: add UV_FROZEN to makefiles (#29642) 2025-02-06 14:36:54 -05:00
pyproject.toml multiple: fix uv path deps (#29790) 2025-02-13 21:32:34 +00:00
README.md
uv.lock multiple: fix uv path deps (#29790) 2025-02-13 21:32:34 +00:00

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)

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)