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### Summary Added a new documentation page and images for integrating AI/ML API with AutoGPT, including step-by-step instructions. Updated LLM block to send additional headers for requests to aimlapi.com. Improved provider listing in index.md and added the new guide to mkdocs navigation. Builds on and extends the integration work from https://github.com/Significant-Gravitas/AutoGPT/pull/9996 ### Changes 🏗️ This PR introduces official support and documentation for using **AI/ML API** with the **AutoGPT platform**: * 📄 **Added a new documentation page** `platform/aimlapi.md` with a detailed step-by-step integration guide. * 🖼️ **Added 12+ reference images** to `docs/content/imgs/aimlapi/` for clear visual walkthrough. * 🧠 **Updated the LLM block** (`llm.py`) to send extra headers (`X-Project`, `X-Title`, `Referer`) in requests to `aimlapi.com` for analytics and source attribution. * 📚 **Improved provider listing** in `index.md` — added section about AI/ML API models and benefits. * 🧭 **Added the new guide to the mkdocs navigation** via `mkdocs.yml`. --- ### Checklist 📋 #### For code changes: * [x] I have clearly listed my changes in the PR description * [x] I have made a test plan * [x] I have tested my changes according to the test plan: * [x] Successfully authenticated against `api.aimlapi.com` * [x] Verified requests use correct headers * [x] Confirmed `AI Text Generator` block returns completions for all supported models * [x] End-to-end tested: created, saved, and ran agent with AI/ML API successfully * [x] Verified outputs render correctly in the Output panel No breaking changes introduced. Let me know if you'd like this guide cross-referenced from other onboarding pages. ✅ --------- Co-authored-by: Nicholas Tindle <nicholas.tindle@agpt.co>
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🧠 Running AI/ML API with AutoGPT
Follow these steps to connect AI/ML API with the AutoGPT platform for high-performance AI text generation.
✅ Prerequisites
- Make sure you have gone through and completed the AutoGPT Setup Guide, and AutoGPT is running locally at
http://localhost:3000. - You have an API key from AI/ML API.
⚙️ Setup Steps
1. Start AutoGPT Locally
Follow the official guide: 📖 AutoGPT Getting Started Guide
Make sure AutoGPT is running and accessible at: http://localhost:3000
💡 Keep AutoGPT running in a terminal or Docker throughout the session.
2. Open the Visual Builder
Open your browser and go to: http://localhost:3000/build
Or click “Build” in the navigation bar.
3. Add an AI Text Generator Block
- Click the "Blocks" button on the left sidebar.
- In the search bar, type
AI Text Generator. - Drag the block into the canvas.
4. Select an AI/ML API Model
Click the AI Text Generator block to configure it.
In the LLM Model dropdown, select one of the supported models from AI/ML API:
| Model ID | Speed | Reasoning Quality | Best For |
|---|---|---|---|
Qwen/Qwen2.5-72B-Instruct-Turbo |
Medium | High | Text-based tasks |
nvidia/llama-3.1-nemotron-70b-instruct |
Medium | High | Analytics and reasoning |
meta-llama/Llama-3.3-70B-Instruct-Turbo |
Low | Very High | Complex multi-step tasks |
meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo |
Low | Very High | Deep reasoning |
meta-llama/Llama-3.2-3B-Instruct-Turbo |
High | Medium | Fast responses |
✅ These models are available via OpenAI-compatible API from AI/ML API
5. Configure the Prompt and API Key
Inside the AI Text Generator block:
- Enter your prompt text in the Prompt field.
- Enter your AI/ML API Key in the designated field.
🔐 You can get your key from: https://aimlapi.com/app/keys/
6. Save Your Agent
Click the “Save” button at the top-right of the builder interface:
- Give your agent a name (e.g.,
aimlapi_test_agent). - Click “Save Agent” to confirm.
💡 Saving allows reuse, scheduling, and chaining in larger workflows.
7. Run Your Agent
From the workspace:
- Press “Run” next to your saved agent.
- The request will be sent to the selected AI/ML API model.
8. View the Output
- Scroll to the AI Text Generator block.
- Check the Output panel below it.
- You can copy, export, or pass the result to further blocks.
🔄 Expand Your Agent
Now that AI/ML API is connected, expand your workflow by chaining additional blocks:
- 🔧 Tools – fetch URLs, call APIs, scrape data
- 🧠 Memory – retain context across interactions
- ⚙️ Actions / Chains – create full pipelines
🎉 You’re now generating AI responses using enterprise-grade models from AI/ML API in AutoGPT!