From efc4658a51c8a14a35fe781a5b5145006d777c9a Mon Sep 17 00:00:00 2001
From: Abhishek Hegde <ahegde2021@gmail.com>
Date: Fri, 24 Nov 2023 20:39:13 +0530
Subject: [PATCH] added api/chat/route

---
 src/app/api/chat/route.ts | 59 +++++++++++++++++++++++++++++++++++++++
 1 file changed, 59 insertions(+)
 create mode 100644 src/app/api/chat/route.ts

diff --git a/src/app/api/chat/route.ts b/src/app/api/chat/route.ts
new file mode 100644
index 0000000..fdb2efd
--- /dev/null
+++ b/src/app/api/chat/route.ts
@@ -0,0 +1,59 @@
+import { notesIndex } from "@/lib/db/pinecone";
+import prisma from "@/lib/db/prisma";
+import openai, { getEmbedding } from "@/lib/openai";
+import { auth } from "@clerk/nextjs";
+import { OpenAIStream, StreamingTextResponse } from "ai";
+import { ChatCompletionMessage } from "openai/resources/index.mjs";
+
+export async function POST(req: Request) {
+  try {
+    const body = await req.json();
+    const messages: ChatCompletionMessage[] = body.messages;
+
+    const messagesTruncated = messages.slice(-6);
+
+    const embedding = await getEmbedding(
+      messagesTruncated.map((message) => message.content).join("\n"),
+    );
+
+    const { userId } = auth();
+
+    const vectorQueryResponse = await notesIndex.query({
+      vector: embedding,
+      topK: 4,
+      filter: { userId },
+    });
+
+    const relevantNotes = await prisma.note.findMany({
+      where: {
+        id: {
+          in: vectorQueryResponse.matches.map((match) => match.id),
+        },
+      },
+    });
+
+    console.log("Relevant notes found: ", relevantNotes);
+
+    const systemMessage: ChatCompletionMessage = {
+      role: "system",
+      content:
+        "You are an intelligent note-taking app. You answer the user's question based on their existing notes. " +
+        "The relevant notes for this query are:\n" +
+        relevantNotes
+          .map((note) => `Title: ${note.title}\n\nContent:\n${note.content}`)
+          .join("\n\n"),
+    };
+
+    const response = await openai.chat.completions.create({
+      model: "gpt-3.5-turbo",
+      stream: true,
+      messages: [systemMessage, ...messagesTruncated],
+    });
+
+    const stream = OpenAIStream(response);
+    return new StreamingTextResponse(stream);
+  } catch (error) {
+    console.error(error);
+    return Response.json({ error: "Internal server error" }, { status: 500 });
+  }
+}