ChatGPT Datasource Plugin

Link to Plugin Source Code

The ChatGPT plugin for Godspeed allows seamless integration with OpenAI’s language models, enabling dynamic AI-driven responses in your workflows and APIs.

1. Install the Plugin

First, add the ChatGPT plugin using

godspeed plugin add @godspeedsystems/plugins-chatgpt-as-datasource

2. Set Up Environment Variables

In your .env file, add your OpenAI API key to securely access the OpenAI models:

OPENAI_API_KEY="your_openai_api_key"

This key is required by the plugin to authenticate with OpenAI.

3. Check the Datasource Configuration

Check the file src/datasources/chatgpt.yaml:

type: chatgpt
model: gpt-4o
temperature: 1
max_tokens: 200

• type: Must be chatgpt to register correctly with Godspeed.
• model: The model name to use (e.g., gpt-4o, gpt-4, gpt-3.5-turbo).
• temperature: Controls the randomness of the output.
• max_tokens: The maximum number of tokens to generate in the completion.

4. Define the Event (API Endpoint)

Create the file src/events/chatgpt_event.yaml to expose an HTTP POST endpoint for ChatGPT interaction:

http.post./chatgpt:
  summary: "Generate response from ChatGPT"
  description: "Endpoint to send a user prompt to ChatGPT and retrieve the AI-generated response."
  fn: prompt
  authn: false
  body:
    content:
      application/json:
        schema:
          type: object
          properties:
            prompt:
              type: string
              description: "The user's prompt or question for ChatGPT to respond to."
          required:
            - prompt
  responses:
    200:
      description: "Successful response from ChatGPT"
      content:
        application/json:
          schema:
            type: string

This creates a REST API at POST /chatgpt.

5. Add the Function Logic

Create the file src/functions/prompt.ts for the actual function that interacts with the ChatGPT datasource:

import { GSContext, GSDataSource, GSStatus } from "@godspeedsystems/core";

export default async function (ctx: GSContext, args: any) {
    const {
        inputs: {
            data: { body }
        }
    } = ctx;
    const prompt = body.prompt;
    const ds: GSDataSource = ctx.datasources.chatgpt;

    const response = await ds.execute(ctx, {
        prompt,
        meta: { method: 'chat' }
    });

    return response;
}

• ctx.datasources.chatgpt: Loads the plugin's configured datasource.
• ds.execute(...): Invokes the chat method on the ChatGPT API with your prompt.

6. Test the Endpoint

Once your Godspeed server is running (godspeed serve), you can test the API:

curl -X POST http://localhost:4000/chatgpt \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Explain quantum computing in simple terms."}'

You should receive a response directly from the ChatGPT model as JSON.

7. Notes

• ✅ No manual axios or fetch setup needed — the plugin handles it.
• ✅ You can adjust temperature, model, and tokens in chatgpt.yaml.
• ✅ Extend the plugin with retry logic, caching, or prompt templates using standard Godspeed techniques.

---

Summary

File	Purpose
.env	Stores your OpenAI API key
src/datasources/chatgpt.yaml	Datasource config for the plugin
src/events/chatgpt_event.yaml	HTTP API event to invoke ChatGPT
src/functions/prompt.ts	Function that calls OpenAI’s model

---