github/langchain
1
0
Fork 0
mirror of https://github.com/hwchase17/langchain.git synced 2026-06-09 10:17:00 +00:00
Code Issues Packages Projects Releases Wiki Activity

chore: enrich pyproject.toml files with links to new references, others (#33343)

Browse Source
This commit is contained in:
Mason Daugherty
2025-10-07 16:17:14 -04:00
committed by GitHub
parent 02f4256cb6
commit cda336295f
37 changed files with 159 additions and 621 deletions
Download Patch File Download Diff File Expand all files Collapse all files

102
libs/partners/exa/README.md
View File

@@ -2,104 +2,4 @@
This package contains the LangChain integrations for Exa Cloud generative models.
## Installation
```bash
pip install -U langchain-exa
```
## Exa Search Retriever
You can retrieve search results as follows
```python
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)
```
### Advanced Features
You can use advanced features like text limits, summaries, and live crawling:
```python
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
)
```
## Exa Search Results
You can run the ExaSearchResults module as follows
```python
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
```python
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)
```
## 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)
View the [documentation](https://docs.langchain.com/oss/python/integrations/providers/exa_search) for more details.