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**TL;DR much of the provided `Makefile` targets were broken, and any
time I wanted to preview changes locally I either had to refer to a
command Chester gave me or try waiting on a Vercel preview deployment.
With this PR, everything should behave like normal.**
Significant updates to the `Makefile` and documentation files, focusing
on improving usability, adding clear messaging, and fixing/enhancing
documentation workflows.
### Updates to `Makefile`:
#### Enhanced build and cleaning processes:
- Added informative messages (e.g., "📚 Building LangChain
documentation...") to makefile targets like `docs_build`, `docs_clean`,
and `api_docs_build` for better user feedback during execution.
- Introduced a `clean-cache` target to the `docs` `Makefile` to clear
cached dependencies and ensure clean builds.
#### Improved dependency handling:
- Modified `install-py-deps` to create a `.venv/deps_installed` marker,
preventing redundant/duplicate dependency installations and improving
efficiency.
#### Streamlined file generation and infrastructure setup:
- Added caching for the LangServe README download and parallelized
feature table generation
- Added user-friendly completion messages for targets like `copy-infra`
and `render`.
#### Documentation server updates:
- Enhanced the `start` target with messages indicating server start and
URL for local documentation viewing.
---
### Documentation Improvements:
#### Content clarity and consistency:
- Standardized section titles for consistency across documentation
files.
[[1]](diffhunk://#diff-9b1a85ea8a9dcf79f58246c88692cd7a36316665d7e05a69141cfdc50794c82aL1-R1)
[[2]](diffhunk://#diff-944008ad3a79d8a312183618401fcfa71da0e69c75803eff09b779fc8e03183dL1-R1)
- Refined phrasing and formatting in sections like "Dependency
management" and "Formatting and linting" for better readability.
[[1]](diffhunk://#diff-2069d4f956ab606ae6d51b191439283798adaf3a6648542c409d258131617059L6-R6)
[[2]](diffhunk://#diff-2069d4f956ab606ae6d51b191439283798adaf3a6648542c409d258131617059L84-R82)
#### Enhanced workflows:
- Updated instructions for building and viewing documentation locally,
including tips for specifying server ports and handling API reference
previews.
[[1]](diffhunk://#diff-048deddcfd44b242e5b23aed9f2e9ec73afc672244ce14df2a0a316d95840c87L60-R94)
[[2]](diffhunk://#diff-048deddcfd44b242e5b23aed9f2e9ec73afc672244ce14df2a0a316d95840c87L82-R126)
- Expanded guidance on cleaning documentation artifacts and using
linting tools effectively.
[[1]](diffhunk://#diff-048deddcfd44b242e5b23aed9f2e9ec73afc672244ce14df2a0a316d95840c87L82-R126)
[[2]](diffhunk://#diff-048deddcfd44b242e5b23aed9f2e9ec73afc672244ce14df2a0a316d95840c87L107-R142)
#### API reference documentation:
- Improved instructions for generating and formatting in-code
documentation, highlighting best practices for docstring writing.
[[1]](diffhunk://#diff-048deddcfd44b242e5b23aed9f2e9ec73afc672244ce14df2a0a316d95840c87L107-R142)
[[2]](diffhunk://#diff-048deddcfd44b242e5b23aed9f2e9ec73afc672244ce14df2a0a316d95840c87L144-R186)
---
### Minor Changes:
- Added support for a new package name (`langchain_v1`) in the API
documentation generation script.
- Fixed minor capitalization and formatting issues in documentation
files.
[[1]](diffhunk://#diff-2069d4f956ab606ae6d51b191439283798adaf3a6648542c409d258131617059L40-R40)
[[2]](diffhunk://#diff-2069d4f956ab606ae6d51b191439283798adaf3a6648542c409d258131617059L166-R160)
---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
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.. | ||
langchain_exa | ||
scripts | ||
tests | ||
.gitignore | ||
LICENSE | ||
Makefile | ||
pyproject.toml | ||
README.md | ||
uv.lock |
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)
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
)
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)
Configuration Options
All Exa tools support the following common parameters:
num_results
(1-100): Number of search results to returntype
: 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)