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Documentation Index

Fetch the complete documentation index at: https://docs.langchain.com/llms.txt

Use this file to discover all available pages before exploring further.

Exa is a knowledge API for AI and developers.

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Installation and setup

Exa integration exists in its own partner package. You can install it with: 
pip install -qU langchain-exa
In order to use the package, you will also need to set the EXA_API_KEY environment variable to your Exa API key.

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Retriever

You can use the ExaSearchRetriever in a standard retrieval pipeline. You can import it as follows. See a usage example. 
from langchain_exa import ExaSearchRetriever

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Tools

You can use Exa as an agent tool as described in the Exa tool calling docs. See a usage example.

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ExaFindSimilarResults

A tool that queries the Metaphor Search API and gets back JSON. 
from langchain_exa.tools import ExaFindSimilarResults

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ExaSearchResults

Exa Search tool. 
from langchain_exa.tools import ExaSearchResults

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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)

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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
)

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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)

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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)

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Configuration options

All Exa tools support the following common parameters:
  • num_results (1-100): Number of search results to return
  • type: 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)
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