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**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> |
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langchain_exa | ||
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poetry.lock | ||
pyproject.toml | ||
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)