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import { HF_TOKEN } from "$env/static/private";
import { PUBLIC_MODEL_ENDPOINT, PUBLIC_SEP_TOKEN } from "$env/static/public";
import { buildPrompt } from "$lib/buildPrompt.js";
import { collections } from "$lib/server/database.js";
import type { Message } from "$lib/types/Message.js";
import { streamToAsyncIterable } from "$lib/utils/streamToAsyncIterable";
import { sum } from "$lib/utils/sum";
import { trimPrefix } from "$lib/utils/trimPrefix.js";
import { trimSuffix } from "$lib/utils/trimSuffix.js";
import { error } from "@sveltejs/kit";
import { ObjectId } from "mongodb";
export async function POST({ request, fetch, locals, params }) {
// todo: add validation on params.id
const convId = new ObjectId(params.id);
const conv = await collections.conversations.findOne({
_id: convId,
sessionId: locals.sessionId,
});
if (!conv) {
throw error(404, "Conversation not found");
}
// Todo: validate prompt with zod? or aktype
const json = await request.json();
const messages = [...conv.messages, { from: "user", content: json.inputs }] satisfies Message[];
const prompt = buildPrompt(messages);
const resp = await fetch(PUBLIC_MODEL_ENDPOINT, {
headers: {
"Content-Type": request.headers.get("Content-Type") ?? "application/json",
Authorization: `Basic ${HF_TOKEN}`,
},
method: "POST",
body: JSON.stringify({
...json,
inputs: prompt,
}),
});
const [stream1, stream2] = resp.body!.tee();
async function saveMessage() {
let generated_text = await parseGeneratedText(stream2);
// We could also check if PUBLIC_ASSISTANT_MESSAGE_TOKEN is present and use it to slice the text
if (generated_text.startsWith(prompt)) {
generated_text = generated_text.slice(prompt.length);
}
generated_text = trimSuffix(trimPrefix(generated_text, "<|startoftext|>"), PUBLIC_SEP_TOKEN);
messages.push({ from: "assistant", content: generated_text });
await collections.conversations.updateOne(
{
_id: convId,
},
{
$set: {
messages,
updatedAt: new Date(),
},
}
);
}
saveMessage().catch(console.error);
// Todo: maybe we should wait for the message to be saved before ending the response - in case of errors
return new Response(stream1, {
headers: Object.fromEntries(resp.headers.entries()),
status: resp.status,
statusText: resp.statusText,
});
}
export async function DELETE({ locals, params }) {
const convId = new ObjectId(params.id);
const conv = await collections.conversations.findOne({
_id: convId,
sessionId: locals.sessionId,
});
if (!conv) {
throw error(404, "Conversation not found");
}
await collections.conversations.deleteOne({ _id: conv._id });
return new Response();
}
async function parseGeneratedText(stream: ReadableStream): Promise<string> {
const inputs: Uint8Array[] = [];
for await (const input of streamToAsyncIterable(stream)) {
inputs.push(input);
}
// Merge inputs into a single Uint8Array
const completeInput = new Uint8Array(sum(inputs.map((input) => input.length)));
let offset = 0;
for (const input of inputs) {
completeInput.set(input, offset);
offset += input.length;
}
// Get last line starting with "data:" and parse it as JSON to get the generated text
const message = new TextDecoder().decode(completeInput);
let lastIndex = message.lastIndexOf("\ndata:");
if (lastIndex === -1) {
lastIndex = message.indexOf("data");
}
if (lastIndex === -1) {
console.error("Could not parse in last message");
}
let lastMessage = message.slice(lastIndex).trim().slice("data:".length);
if (lastMessage.includes("\n")) {
lastMessage = lastMessage.slice(0, lastMessage.indexOf("\n"));
}
const res = JSON.parse(lastMessage).generated_text;
if (typeof res !== "string") {
throw new Error("Could not parse generated text");
}
return res;
}