Abraham E. Tavarez
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Browse files- .env.example +1 -0
- .gitattributes +35 -0
- .gitignore +2 -1
- README.md +150 -3
- requirements.txt +12 -0
.env.example
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ANTHROPIC_API_KEY="sdk-"
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.gitattributes
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.gitignore
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# Virtual environments
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.venv
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app.copy.py
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app.audio.tool.py
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# Virtual environments
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.venv
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app.copy.py
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app.audio.tool.py
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assets/
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README.md
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---
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title: MCP Hackathon Deepfake Watchdog
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emoji: π‘οΈ
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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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# π‘οΈ Deepfake Watchdog π€
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π·οΈ Tags: `mcp-server-track` `agent-demo-track`
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A multimodal AI agent that detects deepfake content using **face**, **voice**, and **video** verification. Built with π§ DeepFace, π£οΈ SpeechBrain, π₯ OpenCV, and accelerated with βοΈ Modal for serverless GPU-powered execution. Designed for the **MCP HuggingFace's Hackathon**.
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---
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## π Features
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- π§β𦱠**Face Verification**: Compare two faces and detect if they belong to the same person using DeepFace.
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- ποΈ **Voice Verification**: Determine if two audio samples are from the same speaker with SpeechBrain.
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- ποΈ **Video Scan for Deepfakes**: Scan a video (or YouTube link) and match all faces against a reference image.
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- π **PDF Report**: Generate a downloadable report with all scan results.
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- π§ **Runs as an MCP Agent**: Compatible with [Gradio MCP](https://huggingface.co/docs/mcp), fully pluggable into agentic workflows.
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- β‘ **Modal Offloading**: GPU-backed execution for DeepFace & SpeechBrain using [Modal](https://modal.com).
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---
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## π§± Architecture
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Gradio UI ββ> MCP Agent ββ> Modal Functions
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ββ> verify_faces_remote()
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ββ> verify_voices_remote()
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ββ> verify_faces_in_video_remote()
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---
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## π§© 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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## π οΈ 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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## βοΈ 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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## π§ 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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π Hackathon Tracks
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β
Track 1: MCP Tool β Turned into a reusable tool with mcp_server=True
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β
Track 3: Agentic Demo β A fully capable AI agent for deepfake detection (LlamaIndex)
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β
Modal β Offloaded heavy tasks to Modalβs GPU cloud
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## π§± Folder Structure
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.
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βββ app.py # Main app entry point (Gradio + MCP)
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βββ llama_agent.py # LlamaIndex Agent implementation
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βββ tools.py # Tools for LlamaIndex Agent and MCP
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βββ modal_app/
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β βββ backend.py # Modal remote functions
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βββ detector/
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β βββ face.py # Local face verification logic
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β βββ voice.py # Local voice verification logic
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β βββ video.py # Local video scan logic
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βββ reports/
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β βββ pdf_report.py # PDF report generation
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βββ utils/
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β βββ youtube_utils.py # YouTube download helper
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βββ README.md
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βββ requirements.txt
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βββ .env.example
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##π§βπ» Author
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Abraham Efren Tavarez
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GitHub - [@AbeTavarez](https://github.com/AbeTavarez)
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LinkedIn β [@abrahametavarez](https://www.linkedin.com/in/abrahametavarez/)
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## β¨ 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
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requirements.txt
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anthropic>=0.53.0
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deepface>=0.0.93
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fpdf>=1.7.2
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gradio[mcp]>=5.32.1
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llama-index>=0.12.41
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llama-index-llms-anthropic>=0.7.2
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modal>=1.0.3
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opencv-python-headless>=4.11.0.86
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pydub>=0.25.1
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resemblyzer>=0.1.4
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tf-keras>=2.19.0
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yt-dlp>=2025.5.22
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