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--- |
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title: MCP Hackathon Deepfake Watchdog |
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emoji: 🛡️ |
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colorFrom: green |
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colorTo: gray |
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sdk: gradio |
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sdk_version: 5.33.1 |
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app_file: app.py |
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pinned: false |
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license: mit |
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short_description: Upload your image and/or voice to scan for deepfake misuse o |
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--- |
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# 🛡️ Deepfake Watchdog 🤖 |
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🏷️ Tags: `mcp-server-track` `agent-demo-track` |
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[Video Link](https://www.dropbox.com/scl/fi/bibsndi4tazikhozreg7m/2025-06-09-23-39-26.mkv?rlkey=mhq1mgbr1wuhr1k48hv49i1ga&st=7hbov0m4&dl=0) |
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A multimodal AI agent that detects deepfake content using **face**, **voice**, and **video** verification. Built with 🧠 DeepFace, 🗣️ SpeechBrain, 🎥 OpenCV, and accelerated with ☁️ Modal for serverless GPU-powered execution. Designed for the **MCP HuggingFace's Hackathon**. |
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--- |
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## 🚀 Features |
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- 🧑🦱 **Face Verification**: Compare two faces and detect if they belong to the same person using DeepFace. |
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- 🎙️ **Voice Verification**: Determine if two audio samples are from the same speaker with SpeechBrain. |
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- 🎞️ **Video Scan for Deepfakes**: Scan a video (or YouTube link) and match all faces against a reference image. |
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- 📄 **PDF Report**: Generate a downloadable report with all scan results. |
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- 🧠 **Runs as an MCP Agent**: Compatible with [Gradio MCP](https://huggingface.co/docs/mcp), fully pluggable into agentic workflows. |
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- ⚡ **Modal Offloading**: GPU-backed execution for DeepFace & SpeechBrain using [Modal](https://modal.com). |
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--- |
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## 🧱 Architecture |
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Gradio UI ──> MCP Agent ──> Modal Functions |
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└─> verify_faces_remote() |
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└─> verify_voices_remote() |
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└─> verify_faces_in_video_remote() |
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--- |
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## 🧩 Tech Stack |
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| Tool | Purpose | |
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|--------------|----------------------------------| |
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| `Gradio` | Frontend UI + MCP integration | |
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| `Modal` | GPU offloading for ML workloads | |
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| `DeepFace` | Face verification | |
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| `SpeechBrain`| Voice verification | |
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| `OpenCV` | Video processing | |
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| `Pillow` | Image manipulation | |
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| `TensorFlow` | Required by DeepFace | |
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| `FFmpeg` | (Optional) for YouTube downloads | |
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--- |
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## 🛠️ Setup Instructions |
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### 1. Clone the repo |
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```bash |
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git clone https://huggingface.co/spaces/abetavarez/MCP-Hackathon-Deepfake-Watchdog |
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cd MCP-Hackathon-Deepfake-Watchdog |
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``` |
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### 2. Create .env |
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```bash |
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cp .env.example .env |
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# Add your API keys or configs if required |
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``` |
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### 3. Install dependencies (locally) |
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```bash |
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pip install -r requirements.txt |
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``` |
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### 4. Run the app (with MCP) |
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```bash |
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modal run app.py |
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``` |
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or for development:: |
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```bash |
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python app.py |
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``` |
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## ⚙️ Modal Setup |
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The app uses a single modal_app/backend.py file that defines: |
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verify_faces_remote |
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verify_voices_remote |
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verify_faces_in_video_remote |
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Each function is GPU-accelerated and runs independently on demand. |
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```bash |
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modal deploy modal_app.py |
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``` |
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## 🧠 Agent MCP Integration |
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This app runs as an MCP server using: |
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```python |
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demo.launch(mcp_server=True) |
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``` |
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You can use this tool in your LlamaIndex, Hugging Face or LangChain agent as a remote service. |
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🏆 Hackathon Tracks |
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✅ Track 1: MCP Tool — Turned into a reusable tool with mcp_server=True |
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✅ Track 3: Agentic Demo — A fully capable AI agent for deepfake detection (LlamaIndex) |
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✅ Modal — Offloaded heavy tasks to Modal’s GPU cloud |
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## 🧱 Folder Structure |
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. |
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├── app.py # Main app entry point (Gradio + MCP) |
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├── llama_agent.py # LlamaIndex Agent implementation |
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├── tools.py # Tools for LlamaIndex Agent and MCP |
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├── modal_app/ |
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│ ├── backend.py # Modal remote functions |
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├── detector/ |
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│ ├── face.py # Local face verification logic |
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│ ├── voice.py # Local voice verification logic |
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│ └── video.py # Local video scan logic |
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├── reports/ |
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│ └── pdf_report.py # PDF report generation |
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├── utils/ |
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│ └── youtube_utils.py # YouTube download helper |
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├── README.md |
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├── requirements.txt |
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└── .env.example |
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##🧑💻 Author |
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Abraham Efren Tavarez |
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GitHub - [@AbeTavarez](https://github.com/AbeTavarez) |
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LinkedIn — [@abrahametavarez](https://www.linkedin.com/in/abrahametavarez/) |
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## ✨ Future Improvements |
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Add S3-compatible cloud storage or video ingest |
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Add Nebius S3 support for video uploads |
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Add RAG-based evidence summarizer |
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Enable auto-scan via background agent |
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Add QR code for mobile voice capture |
