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langchain/templates/extraction-anthropic-functions
Erick Friis d83b720c40
templates: readme langsmith not private beta (#20173)
1 month ago
..
extraction_anthropic_functions core[patch], langchain[patch], templates: move openai functions parsers to core (#18060) 3 months ago
tests various templates improvements (#12500) 7 months ago
LICENSE various templates improvements (#12500) 7 months ago
README.md templates: readme langsmith not private beta (#20173) 1 month ago
extraction_anthropic_functions.ipynb docs, experimental[patch], langchain[patch], community[patch]: update storage imports (#15429) 4 months ago
poetry.lock template: bump more lockfiles (#19003) 2 months ago
pyproject.toml template: bump more lockfiles (#19003) 2 months ago

README.md

extraction-anthropic-functions

This template enables Anthropic function calling.

This can be used for various tasks, such as extraction or tagging.

The function output schema can be set in chain.py.

Environment Setup

Set the ANTHROPIC_API_KEY environment variable to access the Anthropic models.

Usage

To use this package, you should first have the LangChain CLI installed:

pip install -U langchain-cli

To create a new LangChain project and install this as the only package, you can do:

langchain app new my-app --package extraction-anthropic-functions

If you want to add this to an existing project, you can just run:

langchain app add extraction-anthropic-functions

And add the following code to your server.py file:

from extraction_anthropic_functions import chain as extraction_anthropic_functions_chain

add_routes(app, extraction_anthropic_functions_chain, path="/extraction-anthropic-functions")

(Optional) Let's now configure LangSmith. LangSmith will help us trace, monitor and debug LangChain applications. You can sign up for LangSmith here. If you don't have access, you can skip this section

export LANGCHAIN_TRACING_V2=true
export LANGCHAIN_API_KEY=<your-api-key>
export LANGCHAIN_PROJECT=<your-project>  # if not specified, defaults to "default"

If you are inside this directory, then you can spin up a LangServe instance directly by:

langchain serve

This will start the FastAPI app with a server is running locally at http://localhost:8000

We can see all templates at http://127.0.0.1:8000/docs We can access the playground at http://127.0.0.1:8000/extraction-anthropic-functions/playground

We can access the template from code with:

from langserve.client import RemoteRunnable

runnable = RemoteRunnable("http://localhost:8000/extraction-anthropic-functions")

By default, the package will extract the title and author of papers from the information you specify in chain.py. This template will use Claude2 by default.