Merge pull request #1419 from jmorganca/mattw/typescript-simplechat

Simple chat example for typescript
This commit is contained in:
Matt Williams 2023-12-07 14:42:24 -08:00 committed by GitHub
commit dd427f499a
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
3 changed files with 117 additions and 0 deletions

View file

@ -0,0 +1,77 @@
import * as readline from "readline";
const model = "llama2";
type Message = {
role: "assistant" | "user" | "system";
content: string;
}
const messages: Message[] = [{
role: "system",
content: "You are a helpful AI agent."
}]
const rl = readline.createInterface({
input: process.stdin,
output: process.stdout
})
async function chat(messages: Message[]): Promise<Message> {
const body = {
model: model,
messages: messages
}
const response = await fetch("http://localhost:11434/api/chat", {
method: "POST",
body: JSON.stringify(body)
})
const reader = response.body?.getReader()
if (!reader) {
throw new Error("Failed to read response body")
}
let content = ""
while (true) {
const { done, value } = await reader.read()
if (done) {
break;
}
const rawjson = new TextDecoder().decode(value);
const json = JSON.parse(rawjson)
if (json.done === false) {
process.stdout.write(json.message.content);
content += json.message.content
}
}
return { role: "assistant", content: content };
}
async function askQuestion(): Promise<void> {
return new Promise<void>((resolve) => {
rl.question("\n\nAsk a question: (press enter alone to quit)\n\n", async (user_input) => {
if (user_input.trim() === "") {
rl.close();
console.log("Thankyou. Goodbye.\n")
console.log("=======\nHere is the message history that was used in this conversation.\n=======\n")
messages.forEach(message => {
console.log(message)
})
resolve();
} else {
console.log();
messages.push({ role: "user", content: user_input });
messages.push(await chat(messages));
await askQuestion(); // Ask the next question
}
});
});
}
async function main() {
await askQuestion();
}
main();

View file

@ -0,0 +1 @@
{ "dependencies": { "@types/node": "^20.10.4", "prompt-sync": "^4.2.0", "readline": "^1.3.0" } }

View file

@ -0,0 +1,39 @@
# Simple Chat Example
The **chat** endpoint is one of two ways to generate text from an LLM with Ollama. At a high level you provide the endpoint an array of message objects with a role and content specified. Then with each output and prompt, you add more messages, which builds up the history.
## Run the Example
There are a few ways to run this, just like any Typescript code:
1. Compile with `tsc` and then run it with `node client.js`.
2. Install `tsx` and run it with `tsx client.ts`.
3. Install `bun` and run it with `bun client.ts`.
## Review the Code
You can see in the **chat** function that is actually calling the endpoint is simply done with:
```typescript
const body = {
model: model,
messages: messages
}
const response = await fetch("http://localhost:11434/api/chat", {
method: "POST",
body: JSON.stringify(body)
})
```
With the **generate** endpoint, you need to provide a `prompt`. But with **chat**, you provide `messages`. And the resulting stream of responses includes a `message` object with a `content` field.
The final JSON object doesn't provide the full content, so you will need to build the content yourself. In this example, **chat** takes the full array of messages and outputs the resulting message from this call of the chat endpoint.
In the **askQuestion** function, we collect `user_input` and add it as a message to our messages and that is passed to the chat function. When the LLM is done responding the output is added as another message to the messages array.
At the end, you will see a printout of all the messages.
## Next Steps
In this example, all generations are kept. You might want to experiment with summarizing everything older than 10 conversations to enable longer history with less context being used.