> ## Documentation Index
> Fetch the complete documentation index at: https://composio-27-feat-docs-revamp.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Research Agent

> This guide provides detailed steps to create a Demo Assistant using Composio and OpenAI. You will build a system capable of interacting with GitHub to create issues and fetch user information.

This project is an example that uses Composio to seamlessly interact with GitHub through an AI assistant. It automatically creates issues and retrieves user information based on user input.

<Tabs>
  <Tab title="Javascript">
    <Card color="#7bee0c" title="Research Agent GitHub Repository" icon="github" href="https://www.github.com/ComposioHQ/composio/blob/master/js/examples/openai/demo_assistant.mjs">
      Explore the complete source code for the Demo Assistant project. This repository contains all the necessary files and scripts to set up and run the Demo Assistant using Composio and OpenAI.

      <CardBody />
    </Card>

    <Steps>
      <Step title="Import base packages">
        Next, we'll import the essential libraries for our project.

        <CodeGroup>
          ```javascript JS - Import statements
          import express from 'express';
          import { OpenAI } from "openai";
          import { OpenAIToolSet, Action } from "composio-core";
          ```
        </CodeGroup>
      </Step>

      <Step title="Initialize Express App">
        We'll initialize our Express application and set up the necessary configurations.

        <CodeGroup>
          ```javascript Initialize Express App
          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());
          ```
        </CodeGroup>
      </Step>

      <Step title="Define Webhook Endpoint">
        Define the webhook endpoint for JS that will handle incoming requests and interact with the OpenAI API.

        <CodeGroup>
          ```javascript Define Webhook
          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');
              }
          });
          ```
        </CodeGroup>
      </Step>

      <Step title="Start the Server">
        Finally, we'll start the Express server for JS to listen for incoming requests.

        <CodeGroup>
          ```javascript Start Server
          app.listen(PORT, () => {
              console.log(`Server is running on port ${PORT}`);
          });
          ```
        </CodeGroup>
      </Step>
    </Steps>
  </Tab>
</Tabs>

## Putting it All Together

<CodeGroup>
  ```javascript Javascript Final Code
  import express from 'express';
  import { OpenAI } from "openai";
  import { OpenAIToolSet, Action } from "composio-core";

  const app = express();
  const PORT = process.env.PORT || 2001;

  app.use(express.json());

  app.get('/webhook', async (req, res) => {
      try {
          const body = "TITLE: HELLO WORLD, DESCRIPTION: HELLO WORLD for the repo - utkarsh-dixit/speedy";
          
          const toolset = new OpenAIToolSet({
              apiKey: process.env.COMPOSIO_API_KEY,
          });
          const tools = await toolset.get_actions([
              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}`);
  });
  ```
</CodeGroup>