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import type { RequestHandler } from "./$types";
import { collections } from "$lib/server/database";
import { ObjectId } from "mongodb";
import { error, redirect } from "@sveltejs/kit";
import { base } from "$app/paths";
import { z } from "zod";
import type { Message } from "$lib/types/Message";
import { models, validateModel } from "$lib/server/models";
import { defaultEmbeddingModel } from "$lib/server/embeddingModels";
import { v4 } from "uuid";
import { authCondition } from "$lib/server/auth";
import { usageLimits } from "$lib/server/usageLimits";
import { MetricsServer } from "$lib/server/metrics";
export const POST: RequestHandler = async ({ locals, request }) => {
const body = await request.text();
let title = "";
const parsedBody = z
.object({
fromShare: z.string().optional(),
model: validateModel(models),
assistantId: z.string().optional(),
preprompt: z.string().optional(),
})
.safeParse(JSON.parse(body));
if (!parsedBody.success) {
error(400, "Invalid request");
}
const values = parsedBody.data;
const convCount = await collections.conversations.countDocuments(authCondition(locals));
if (usageLimits?.conversations && convCount > usageLimits?.conversations) {
error(429, "You have reached the maximum number of conversations. Delete some to continue.");
}
const model = models.find((m) => (m.id || m.name) === values.model);
if (!model) {
error(400, "Invalid model");
}
let messages: Message[] = [
{
id: v4(),
from: "system",
content: values.preprompt ?? "",
createdAt: new Date(),
updatedAt: new Date(),
children: [],
ancestors: [],
},
];
let rootMessageId: Message["id"] = messages[0].id;
let embeddingModel: string;
if (values.fromShare) {
const conversation = await collections.sharedConversations.findOne({
_id: values.fromShare,
});
if (!conversation) {
error(404, "Conversation not found");
}
title = conversation.title;
messages = conversation.messages;
rootMessageId = conversation.rootMessageId ?? rootMessageId;
values.model = conversation.model;
values.preprompt = conversation.preprompt;
values.assistantId = conversation.assistantId?.toString();
embeddingModel = conversation.embeddingModel;
}
embeddingModel ??= model.embeddingModel ?? defaultEmbeddingModel.name;
if (model.unlisted) {
error(400, "Can't start a conversation with an unlisted model");
}
// get preprompt from assistant if it exists
const assistant = await collections.assistants.findOne({
_id: new ObjectId(values.assistantId),
});
if (assistant) {
values.preprompt = assistant.preprompt;
} else {
values.preprompt ??= model?.preprompt ?? "";
}
if (messages && messages.length > 0 && messages[0].from === "system") {
messages[0].content = values.preprompt;
}
const res = await collections.conversations.insertOne({
_id: new ObjectId(),
title: title || "New Chat",
rootMessageId,
messages,
model: values.model,
preprompt: values.preprompt,
assistantId: values.assistantId ? new ObjectId(values.assistantId) : undefined,
createdAt: new Date(),
updatedAt: new Date(),
userAgent: request.headers.get("User-Agent") ?? undefined,
embeddingModel,
...(locals.user ? { userId: locals.user._id } : { sessionId: locals.sessionId }),
...(values.fromShare ? { meta: { fromShareId: values.fromShare } } : {}),
});
MetricsServer.getMetrics().model.conversationsTotal.inc({ model: values.model });
return new Response(
JSON.stringify({
conversationId: res.insertedId.toString(),
}),
{ headers: { "Content-Type": "application/json" } }
);
};
export const GET: RequestHandler = async () => {
redirect(302, `${base}/`);
};
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