| | --- |
| | title: Data Science Agent |
| | emoji: 🐢 |
| | colorFrom: green |
| | colorTo: red |
| | sdk: gradio |
| | app_file: app.py |
| | license: mit |
| | sdk_version: 5.33.0 |
| | short_description: Agent that solves your AI/ML/Data Science problems |
| | pinned: true |
| | tags: |
| | - agent-demo-track |
| | - Mistral |
| | - LLamaIndex |
| | - Sambanova |
| | - Modal |
| |
|
| | --- |
| | |
| | ## Demo Video |
| | 🎥 Watch the [Demo Video here](https://drive.google.com/file/d/1FlvN_tV1BQ4OmFmGsWPSQt_H6Ok92dmy/view?usp=sharing) |
| |
|
| | More details: [Detailed Talk here](https://drive.google.com/file/d/1edHcyxhYKi6RV8MnCtTkbEf0UAhhhA3D/view?usp=sharing) |
| | ## Acknowledgements |
| | Made with ❤️ by [Bhavish Pahwa](https://huggingface.co/bpHigh) & [Abhinav Bhatnagar](https://huggingface.co/Master-warrier) |
| |
|
| | Here’s the refined **How It Works** section with the iterative back‑and‑forth and LlamaIndex MCP integration clearly outlined: |
| |
|
| | ## 🔧 How It Works |
| |
|
| | ### 1. **Gather Requirements** |
| |
|
| | * The user engages in a conversation with the chatbot, describing their data science / AI / ML problem. |
| | * There’s an iterative back-and-forth between the user and **Gemini‑2.5‑Pro**—the model asks clarifying questions, the user responds, and this continues until Gemini‑2.5‑Pro is satisfied that requirements are complete. Only then does it issue a “satisfied” response and release the structured requirements. ([huggingface.co][1], [youtube.com][2]) |
| |
|
| | ### 2. 🛠️ **Generate Plan** (button) |
| |
|
| | * Clicking **Generate Plan** makes use of **LlamaIndex’s MCP integration**, which: |
| |
|
| | * Discovers all available tools listed via MCP on the Hugging Face server (hf.co/mcp) ([medium.com][3]) |
| | * Prompts **Gemini‑2.5‑Pro** again to select the appropriate tools and construct the plan workflows and call syntax. |
| | * All logic for tool discovery, orchestration, and MCP communication is deployed as a **Modal app**. |
| |
|
| | ### 3. 🚀 **Generate Code** (button) |
| |
|
| | * When the user clicks **Generate Code**, the **Mistral DevStral** model (served via vLLM, OpenAI-compatible) generates runnable code matching the plan and selected tools. This model, and its integration, are hosted on **Modal Labs**. |
| |
|
| | ### 4. ▶️ **Execute Code** (button) |
| |
|
| | * The **Execute Code** button sends the generated script to a sandboxed environment in **Modal Labs**, where it’s securely run. Execution results and any outputs are then presented back to the user. |
| |
|
| | This workflow flows user ↔ requirements collection ↔ tool planning ↔ code generation ↔ secure execution—with each step backed by powerful LLMs (Gemini‑2.5‑Pro, Mistral DevStral), LlamaIndex + MCP, and Modal Labs deployment. Samabanova models with Cline are used as devtools / copilots. |
| |
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| |  |
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| |  |
| |
|
| | ## License |
| | This project is licensed under the MIT License – see the LICENSE file for details. |
| |
|
| | Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference |
