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Async Pipeline Haystack Streaming over FastAPI Endpoint
- This tutorial explains how to use Server-Sent Events (SSE) in a Python-based pipeline and how to serve the processed query results over an endpoint using FastAPI with an asynchronous, non-blocking solution.
- The post describes a workaraound approach to create a pipeline task and set "sync" streaming callbacks on the event loop for chunk collection and yield the chunks in a server-sent event.
- The pipeline is designed synchronously, and components to the pipeline can be added dynamically. The API KEY is passed through the end-point, and the openai generator is used to create a pipeline component, which is used to generate responses for user input.
- The AsyncPipeline is defined to run the pipeline, and the server-sent event is used to stream the generated answers in SSE format.
- The ChunkCollector is defined to handle and queue the generated answers and yield them in SSE formatting in an end-point.
- The end-point can be served using fetch-event-source as a frontend to display the streams of generated answers.
- The post concludes by suggesting that the use of sockets would be useful considering performance issues while handling a large volume of data.
- The packages required for the tutorial include fastapi, uvicorn, haystack-ai, haystak-experimental, pydantic, and python, above version 3.10 and below 3.13.
- The complete code, snippets, and a full explanation for each function are provided above.
- The tutorial is meant for experts who are familiar with FastAPI and python programming languages, as it does not provide a guide for the FastAPI process.
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