| --- |
| title: DriveCore |
| emoji: 🚗 |
| colorFrom: indigo |
| colorTo: purple |
| sdk: docker |
| pinned: false |
| --- |
| |
| # DriveCore 🚗⚡ |
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| **An AI-powered incident response, forensic analysis, and branch debugging platform for autonomous vehicle fleets.** |
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| > Built for the AMD Developer Cloud Hackathon — Track 1: AI Agents & Agentic Workflows |
| > Powered by **Qwen3** running on **AMD Instinct GPU** via **LangChain** multi-agent pipeline. |
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|
| --- |
| Quick Start Instructions to Run on AMD GPU Droplet: |
| 1) Start Ollama |
| ollama serve & |
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| 2) Start Qwen backend |
| cd /app/Autopulse |
| uvicorn backend:app --host 0.0.0.0 --port 8006 & |
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| 3) Start frontend |
| bun run dev --host 0.0.0.0 --port 30000 & |
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| 4) Go to Website |
| http://165.245.137.74:30000 |
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| ## What is DriveCore? |
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| DriveCore routes every autonomous vehicle incident, near miss, and sensor log through a multi-step AI agent pipeline — surfacing root causes, compliance concerns, and operator coaching plans in seconds. |
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| ## 🤖 AI Agent Pipeline |
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| Step 1: Intake Agent → Classifies incident, extracts vehicle ID, timestamp, severity |
| Step 2: Enrichment Agent → Identifies affected AV subsystems |
| Step 3: Risk Agent → Root cause analysis ranked by confidence |
| Step 4: Response Agent → Immediate actions, short-term fixes, long-term prevention |
| Step 5: Documentation Agent → Formal Markdown safety report + Qwen's Personal Recommendation |
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| ## 🏗 Tech Stack |
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| - AI Model: Qwen3 via Ollama |
| - Agent Framework: LangChain |
| - GPU Compute: AMD Instinct MI300X via AMD Developer Cloud |
| - Backend: FastAPI (Python) |
| - Frontend: React 19 + TanStack Start + Vite + Tailwind CSS v4 |
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| ## 🏆 Hackathon |
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| Built for AMD Developer Cloud Hackathon — Track 1: AI Agents & Agentic Workflows |
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| *Powered by AMD Instinct GPU ⚡* |
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|
