Convex Component: Persistent Text Streaming

This Convex component enables persistent text streaming. It provides a React hook
for streaming text from HTTP actions while simultaneously storing the data in the
database. This persistence allows the text to be accessed after the stream ends
or by other users.
The most common use case is for AI chat applications. The example app (found in the
example directory) is a just such a simple chat app that demonstrates use of the
component.
Here's what you'll end up with! The left browser window is streaming the chat body to the client,
and the right browser window is subscribed to the chat body via a database query. The
message is only updated in the database on sentence boundaries, whereas the HTTP
stream sends tokens as they come:

Pre-requisite: Convex
You'll need an existing Convex project to use the component.
Convex is a hosted backend platform, including a database, serverless functions,
and a ton more you can learn about here.
Run npm create convex or follow any of the quickstarts to set one up.
Installation
See example/ for a working demo.
- Install the Persistent Text Streaming component:
npm install @convex-dev/persistent-text-streaming
- Create a
convex.config.ts file in your
app's convex/ folder and install the component by calling use:
import { defineApp } from "convex/server";
import persistentTextStreaming from "@convex-dev/persistent-text-streaming/convex.config";
const app = defineApp();
app.use(persistentTextStreaming);
export default app;
Usage
Here's a simple example of how to use the component:
In convex/chat.ts:
const persistentTextStreaming = new PersistentTextStreaming(
components.persistentTextStreaming
);
export const createChat = mutation({
args: {
prompt: v.string(),
},
handler: async (ctx, args) => {
const streamId = await persistentTextStreaming.createStream(ctx);
const chatId = await ctx.db.insert("chats", {
title: "...",
prompt: args.prompt,
stream: streamId,
});
return chatId;
},
});
export const getChatBody = query({
args: {
streamId: StreamIdValidator,
},
handler: async (ctx, args) => {
return await persistentTextStreaming.getStreamBody(
ctx,
args.streamId as StreamId
);
},
});
export const streamChat = httpAction(async (ctx, request) => {
const body = (await request.json()) as {streamId: string};
const generateChat = async (ctx, request, streamId, chunkAppender) => {
await chunkAppender("Hi there!");
await chunkAppender("How are you?");
await chunkAppender("Pretend I'm an AI or something!");
};
const response = await persistentTextStreaming.stream(
ctx,
request,
body.streamId as StreamId,
generateChat
);
response.headers.set("Access-Control-Allow-Origin", "*");
response.headers.set("Vary", "Origin");
return response;
});
You need to expose this HTTP endpoint in your backend, so in convex/http.ts:
http.route({
path: "/chat-stream",
method: "POST",
handler: streamChat,
});
Finally, in your app, you can now create chats and them subscribe to them
via stream and/or database query as optimal:
const createChat = useMutation(api.chat.createChat);
const formSubmit = async (e: React.FormEvent) => {
e.preventDefault();
const chatId = await createChat({
prompt: inputValue,
});
};
import { useStream } from "@convex-dev/persistent-text-streaming/react";
const { text, status } = useStream(
api.chat.getChatBody,
new URL(`${convexSiteUrl}/chat-stream`),
driven,
chat.streamId as StreamId
);
Design Philosophy
This component balances HTTP streaming with database persistence to try to
maximize the benefits of both. To understand why this balance is beneficial,
let's examine each approach in isolation.
-
HTTP streaming only: If your app only uses HTTP streaming, then the
original browser that made the request will have a great, high-performance
streaming experience. But if that HTTP connection is lost, if the browser
window is reloaded, if other users want to view the same chat, or this
users wants to revisit the conversation later, it won't be possible. The
conversation is only ephemeral because it was never stored on the server.
-
Database Persistence Only: If your app only uses database persistence,
it's true that the conversation will be available for as long as you want.
Additionally, Convex's subscriptions will ensure the chat message is updated
as new text chunks are generated. However, there are a few downsides: one,
the entire chat body needs to be resent every time it is changed, which is a
lot redundant bandwidth to push into the database and over the websockets to
all connected clients. Two, you'll need to make a difficult tradeoff between
interactivity and efficiency. If you write every single small chunk to the
database, this will get quite slow and expensive. But if you batch up the chunks
into, say, paragraphs, then the user experience will feel laggy.
This component combines the best of both worlds. The original browser that
makes the request will still have a great, high-performance streaming experience.
But the chat body is also stored in the database, so it can be accessed by the
client even after the stream has finished, or by other users, etc.
Background
This component is largely based on the Stack post AI Chat with HTTP Streaming.