Spaces:
Sleeping
Sleeping
| title: CineMatch AI (Powered by Modal & Nebius) | |
| emoji: 🎬 | |
| colorFrom: blue | |
| colorTo: red | |
| sdk: gradio | |
| sdk_version: 6.0.1 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| short_description: Multi-Agent RAG for Semantic Movie Discovery | |
| tags: | |
| - mcp-in-action-track-01 # Уточни номер трека в правилах, обычно это 01 или текущий месяц | |
| - agents | |
| - rag | |
| - modal | |
| - nebius | |
| - search | |
| # 🎬 CineMatch AI: Semantic Movie Discovery via Multi-Agent RAG | |
| ### 🏆 Submission for MCP 1st Birthday Hackathon | |
| **Track:** MCP in Action | |
| **Special Category:** Modal Innovation Award | |
| --- | |
| ### 🚀 Elevator Pitch | |
| **Describe your story, find its cinematic soulmates.** | |
| CineMatch AI is a creative partner for movie discovery. Instead of keywords, users describe their own original story ideas, dreams, or real-life situations (50+ words). A team of **5 Autonomous Agents** collaborates to refine this narrative, retrieve semantic matches from a vector database (FAISS running on **Modal GPU**), and expertly justify *why* these movies fit the user's concept. | |
| Crucially, the system features a **Shadow Evaluation Agent (AgentOps)** that runs silently in the background via MCP, auditing recommendations for hallucinations and logical coherence. | |
| --- | |
| ### 🛠️ Architecture & MCP Integration | |
| The system uses a **Hierarchical Multi-Agent Architecture** orchestrated on **Modal (Serverless GPU)** and powered by **Llama-3.3-70B** (via Nebius AI). | |
| #### The Agentic Pipeline: | |
| 1. **👮♂️ Coordinator Agent:** Validates input and manages the conversation state machine. Uses **Context Engineering** to guide users. | |
| 2. **📝 Editor & 🎞️ Critic Agents:** Refine the user's raw text into a professional synopsis optimized for embedding. | |
| 3. **🔍 Retriever Agent (MCP Tool User):** | |
| * Acts as a bridge to our Vector Database. | |
| * Calls the semantic search tool (hosted on Modal) which queries a **FAISS index** of thousands of movies. | |
| * Uses **all-MiniLM-L6-v2** for embedding generation. | |
| 4. **🏆 Expert Agent:** Performs parallel evaluation of candidates and generates persuasive justifications. | |
| 5. **🕵️ Shadow Evaluator (AgentOps):** | |
| * Demonstrates the power of MCP for monitoring. | |
| * Runs asynchronously to audit the expert's output against ground truth metadata, detecting hallucinations without disrupting the UX. | |
| --- | |
| ### 🔌 Dual-Layer Architecture (MCP Integration) | |
| CineMatch AI features a unique dual-layer approach to balance speed and standardization: | |
| 1. **Direct RPC Layer:** Used by the Gradio Web UI for **low-latency** user interactions. It communicates directly with Modal functions via optimized RPC calls. | |
| 2. **MCP Layer (`tools/`):** A fully compliant **Model Context Protocol** implementation. This allows external agents (like Claude Desktop or other MCP clients) to discover and connect to our Movie Search Engine as a standard tool, fulfilling the hackathon's interoperability requirements. | |
| --- | |
| ### 🏗️ Technical Stack | |
| * **Infrastructure:** [Modal](https://modal.com) (Serverless Python, GPU A10G for FAISS/Embeddings). | |
| * **LLM:** Meta Llama 3.3 70B Instruct (via Nebius AI). | |
| * **Protocol:** Agents communicate using structured tool calls (MCP pattern). | |
| * **Interface:** Gradio 6. | |
| ### 🎥 Demo Video | |
| [[LINK TO YOUR VIDEO HERE](https://drive.google.com/file/d/16s1PH7T3sfaGebbhyHfBzCOG0cFF2cJA/view?usp=sharing)] | |
| ### 🔗 Social Media Post | |
| [[LINK TO YOUR SOCIAL MEDIA POST HERE](https://www.linkedin.com/posts/dmitry-badeev-7234a91a9_ai-multiagent-rag-activity-7401030457754091520-gpLf?utm_source=share&utm_medium=member_desktop&rcm=ACoAADCpKssB9RwEKiQBmAkxhLZgt_56k2Ikd-M)] | |
| --- | |
| ### 🚀 How to Use | |
| 1. Enter a detailed description of a story, dream, or life situation (e.g., *"A story about a lonely botanist on Mars who learns to communicate with rocks. He was ..." (50+ words)*). | |
| 2. Watch the agents collaborate in real-time. | |
| 3. Receive 3 highly relevant movie recommendations with expert justifications. | |
| 4. (Optional) Check the logs to see the Shadow Evaluator's quality audit. | |