langserve_launch_example

Customise

To customise this project, edit the following files:

• langserve_launch_example/chain.py contains an example chain, which you can edit to suit your needs.
• langserve_launch_example/server.py contains a FastAPI app that serves that chain using langserve. You can edit this to add more endpoints or customise your server.
• tests/test_chain.py contains tests for the chain. You can edit this to add more tests.
• pyproject.toml contains the project metadata, including the project name, version, and dependencies. You can edit this to add more dependencies or customise your project metadata.

Install dependencies

If using poetry:

poetry install

If using vanilla pip:

pip install .

Usage

By default, this uses OpenAI. So you will need to set your OpenAI API key:

export OPENAI_API_KEY="sk-..."

To run the project locally, run

make start

This will launch a webserver on port 8001.

Or via docker compose (does not use hot reload by default):

docker compose up

Deploy

To deploy the project, first build the docker image:

docker build . -t langserve_launch_example:latest

Then run the image:

docker run -p 8001:8001 -e PORT=8001 langserve_launch_example:latest

Don't forget to add any needed environment variables!

Deploy to GCP

You can deploy to GCP Cloud Run using the following command:

First create a .env.gcp.yaml file with the contents from .env.gcp.yaml.example and fill in the values. Then run:

make deploy_gcp

Contributing

For information on how to set up your dev environment and contribute, see here.