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mirror of https://github.com/hwchase17/langchain.git synced 2025-05-08 00:28:47 +00:00
langchain/libs/partners/exa
Sydney Runkle 7e926520d5
packaging: remove Python upper bound for langchain and co libs ()
Follow up to https://github.com/langchain-ai/langsmith-sdk/pull/1696,
I've bumped the `langsmith` version where applicable in `uv.lock`.

Type checking problems here because deps have been updated in
`pyproject.toml` and `uv lock` hasn't been run - we should enforce that
in the future - goes with the other dependabot todos :).
2025-04-28 14:44:28 -04:00
..
langchain_exa partners[lint]: run pyupgrade to get code in line with 3.9 standards () 2025-04-11 07:18:44 -04:00
scripts multiple: pydantic 2 compatibility, v0.3 () 2024-09-13 14:38:45 -07:00
tests
.gitignore
LICENSE
Makefile infra: add UV_FROZEN to makefiles () 2025-02-06 14:36:54 -05:00
pyproject.toml packaging: remove Python upper bound for langchain and co libs () 2025-04-28 14:44:28 -04:00
README.md
uv.lock packaging: remove Python upper bound for langchain and co libs () 2025-04-28 14:44:28 -04:00

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)