DocuSwarm: Parallel Due-Diligence on AMD GPUs

DocuSwarm is a parallel document due-diligence agent swarm built for the AMD Developer Hackathon: ACT III — "AI agents and high-performance AI applications on AMD GPUs in the cloud." Reviewing contracts, NDAs, and reports for risky clauses is slow, manual work done one document at a time. DocuSwarm turns it into a single upload: drop in up to 20 documents and a swarm of async agents analyzes them concurrently against the same LLM endpoint, surfacing risk level, red flags, key dates, and parties per document, with a consolidated Excel/JSON report. This isn't a chatbot demo — it's built to make AMD GPU throughput visible. Every document gets its own async task bounded by a semaphore; all of them hit the same vLLM server, which is exactly the continuous-batching workload AMD Instinct GPUs + ROCm + vLLM are built for. A live dashboard streams completed/total, tokens/sec, elapsed time, and active concurrency in real time. Tested end-to-end on an AMD Instinct MI300X (AMD Developer Cloud) serving Qwen3-8B via vLLM: 6 documents processed concurrently in 1.5 seconds at 1,653.9 tokens/sec — real GPU throughput, not a simulation. Each result reflects genuine LLM judgment (e.g., a contract flagged MEDIUM risk with specific red flags like termination penalties and liquidated damages), not keyword matching. The backend is provider-agnostic by design: it talks to any OpenAI-compatible endpoint, so moving from a laptop to an AMD GPU instance is a one-line config change. Tech stack: FastAPI + asyncio backend, React/Vite dashboard streaming over Server-Sent Events, vLLM serving on AMD Instinct GPUs (ROCm), openpyxl for Excel export. Repo: https://github.com/yanerox69/docuswarm