Skip to main content
This guide shows you how to expose a W&B Weave Model as a FastAPI endpoint using weave serve, so you can query the model interactively and integrate it into production inference workflows. To start a FastAPI server for any Weave Model, pass the Weave ref to weave serve. Replace [REF] with your Weave Model ref. 
weave serve [REF]
To query the model interactively, open the Swagger UI at http://0.0.0.0:9996/docs.

​
Install FastAPI

weave serve uses FastAPI and Uvicorn to host the model, so you must install both packages before serving. 
pip install fastapi uvicorn

​
Serve model

After installing the dependencies, start the server from a terminal. Replace [YOUR-MODEL-REF] with your Weave Model ref. 
weave serve [YOUR-MODEL-REF]
Get your model ref by navigating to the model and copying it from the UI. It should look like the following, where [ENTITY] is your W&B entity, [PROJECT-NAME] is your project name, [MODEL-NAME] is the model name, and [HASH] is the model version hash: 
weave://[ENTITY]/[PROJECT-NAME]/[MODEL-NAME]:[HASH]
To test the endpoint, open the Swagger UI, click the predict endpoint, then click Try it out. You now have a local FastAPI endpoint that serves predictions from your Weave Model.