| --- |
| title: ARIA - AMD Biomedical Research Intelligence Assistant |
| emoji: 🧬 |
| colorFrom: blue |
| colorTo: indigo |
| sdk: docker |
| pinned: false |
| --- |
| |
| ... your existing README content below ... |
|
|
| # ARIA — Autonomous Research Intelligence Agent |
|
|
| > Multi-agent biomedical literature synthesis · AMD Developer Hackathon 2026 |
| > **Team Glitch Squad** — Ziauddin University, Karachi, Pakistan |
|
|
| --- |
|
|
| ## What It Does |
|
|
| You type a clinical research question. ARIA runs a 4-stage multi-agent pipeline that searches PubMed, synthesises evidence, scores confidence, and returns a structured report — all in under 60 seconds. |
|
|
| ## Pipeline |
|
|
| ``` |
| Query Architect → Literature Scout → Evidence Synthesiser → Citation Builder |
| (Groq LLaMA-3.1) (PubMed Entrez) (Groq LLaMA-3.1) (structured refs) |
| ``` |
|
|
| 1. **Query Architect** — generates 5 MeSH-optimised PubMed queries from your clinical question |
| 2. **Literature Scout** — fetches and deduplicates papers across all queries in parallel |
| 3. **Evidence Synthesiser** — builds a structured 6-section synthesis with inline PMID citations |
| 4. **Citation Builder** — formats references with authors, journal, year, and PMID |
|
|
| ## Features |
|
|
| - Real-time SSE streaming — progress bar updates as each stage completes |
| - Structured synthesis — Background, Key Findings, Level of Evidence, Conflicting Evidence, Research Gaps, Clinical Implications |
| - Evidence confidence scoring — green/yellow/red badges rated by a second LLM pass |
| - Abstract viewer — click any citation to expand the full abstract inline |
| - PDF export — download a formatted report with synthesis and references |
|
|
| ## Tech Stack |
|
|
| | Component | Technology | |
| |-----------|------------| |
| | LLM | Groq LLaMA-3.1-8B-Instant | |
| | Agent Framework | LangGraph + LangChain | |
| | Literature Retrieval | BioPython Entrez / PubMed NCBI | |
| | Web Framework | Flask with SSE streaming | |
| | PDF Generation | ReportLab | |
| | Frontend | HTML, CSS, JavaScript | |
| | Runtime | Python 3.12, WSL2 Ubuntu 24.04 | |
| | Roadmap | AMD MI300X + Mistral 7B | |
|
|
| ## Setup |
|
|
| ```bash |
| git clone https://github.com/azlaan428/glitch-squad-biomedical-assistant.git |
| cd glitch-squad-biomedical-assistant |
| python3 -m venv venv |
| source venv/bin/activate |
| pip install -r requirements.txt |
| export GROQ_API_KEY=your_key_here |
| ``` |
|
|
| ## Run |
|
|
| ```bash |
| ./run.sh |
| ``` |
|
|
| Open **http://localhost:5000** |
|
|
| ## Disclaimer |
|
|
| AI-generated synthesis — always verify against primary sources before clinical use. |
