Research Agent

import express from 'express';
import { OpenAI } from "openai";
import { OpenAIToolSet, Action } from "composio-core";

const app = express();
const PORT = process.env.PORT || 2001;
const research_topic = "LLM agents function calling"
const target_repo = "composiohq/composio"
app.use(express.json());

app.get('/webhook', async (req, res) => {
    try {
        const body = `Please research on Arxiv about \`${researchTopic}\`, organize 
        the top ${nIssues} results as ${nIssues} issues for 
        a GitHub repository, and finally raise those issues with proper 
        title, body, implementation guidance, and references in 
        the ${targetRepo} repo, as well as relevant tags and assignees as 
        the repo owner.`;
        
        const toolset = new OpenAIToolSet({
            apiKey: process.env.COMPOSIO_API_KEY,
        });
        const tools = await toolset.get_actions([
            Action.SERPAPI_SEARCH,
            Action.GITHUB_USERS_GET_AUTHENTICATED,
            Action.GITHUB_ISSUES_CREATE
        ]);

        const client = new OpenAI({});
        const assistant = await client.beta.assistants.create({
            model: "gpt-4-turbo",
            description: "This is a test assistant",
            instructions: "You are a helpful assistant that takes actions on user's GitHub",
            tools: tools,
        });

        const thread = await client.beta.threads.create({
            messages: [{
                role: "user",
                content: body
            }]
        });

        let run = await client.beta.threads.runs.create(thread.id, {
            assistant_id: assistant.id,
        });

        run = await toolset.wait_and_handle_assistant_tool_calls(client, run, thread);
        
        // Check if the run is completed
        if (run.status === "completed") {
            let messages = await client.beta.threads.messages.list(thread.id);
            console.log(messages.data);
            return messages.data;
        } else if (run.status === "requires_action") {
            console.log(run.status);
            return await toolset.handle_assistant_message(run);
        } else {
            console.error("Run did not complete:", run);
        }
    } catch (error) {
        console.error(error);
        res.status(500).send('Internal Server Error');
    }
});

app.listen(PORT, () => {
    console.log(`Server is running on port ${PORT}`);
});