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title: Sanjeevani AI API
emoji: 🏥
colorFrom: blue
colorTo: indigo
sdk: docker
app_port: 7860
pinned: false
---
# Sanjeevani AI API
AI-powered healthcare backend API for the Sanjeevani platform.
# SanjeevaniAI — Industry-Grade Healthcare AI Platform
[](https://fastapi.tiangolo.com)
[](https://pytorch.org)
[](https://huggingface.co/tner/roberta-large-bc5cdr)
[](https://nextjs.org)
[](https://tailwindcss.com)
[](https://www.docker.com)
[](backend/tests)
> **Clinical Notice & Positioning**: SanjeevaniAI provides **AI-assisted healthcare information and clinical decision-support insights**. It is **not an autonomous diagnostic system** and is not a substitute for direct clinical examination, laboratory diagnosis, or emergency medical care.
---
## 🏥 Architecture Overview
```
SanjeevaniAI Platform
├── Frontend (Next.js 14 + Tailwind CSS + Lucide Icons)
│ ├── / -> Landing page with medical disclaimer & capabilities
│ ├── /dashboard -> Clinical intelligence overview & metrics
│ ├── /ner -> Real-time local RoBERTa BC5CDR NER visualizer
│ ├── /reports -> Document upload, SHA-256 integrity & analysis
│ ├── /reports/[id] -> Structured clinical findings & raw text
│ ├── /assistant -> Conversational AI with emergency triage
│ ├── /profile -> Patient physiological profile & BMI
│ ├── /history -> Traceable medical timeline
│ ├── /admin -> System telemetry & security audit logs
│ └── /demo -> Guided 5-step mentor presentation walkthrough
│
├── Backend (FastAPI + Async SQLAlchemy + PyTorch)
│ ├── Core & Security -> JWT, bcrypt hashing, RBAC, Request ID, CSP headers
│ ├── ML Engine -> Local RoBERTa-large BC5CDR (355M params, CUDA/CPU)
│ ├── Document Pipeline-> PDF/DOCX/TXT parser, chunker, entity aggregator
│ ├── AI Assistant -> Multi-provider LLM (Gemini + Mock) & triage engine
│ └── Persistence -> Async SQLite / PostgreSQL with audit trail
```
---
## ⚡ Quick Start
### 1. Prerequisites
- **Python**: 3.10+ (Recommended: Python 3.11)
- **Node.js**: 18.x or 20+ (with npm)
- **NVIDIA GPU (Optional)**: CUDA 11.8+ for accelerated inference (CPU fallback automatic)
- **Pretrained NER Model**: Stored locally in `models/bc5cdr-ner`
### 2. Backend Setup
```bash
# Activate virtual environment
python -m venv .venv
.\.venv\Scripts\Activate.ps1 # Windows PowerShell
# source .venv/bin/activate # Linux / macOS
# Install dependencies
pip install -r requirements.txt
# Run synthetic demo database seeder
python scripts/seed_demo_data.py
# Launch FastAPI backend
uvicorn backend.app.main:app --host 0.0.0.0 --port 8000 --reload
```
*API Swagger UI will be live at `http://localhost:8000/docs`.*
### 3. Frontend Setup
```bash
cd frontend
# Install npm dependencies
npm install
# Run Next.js development server
npm run dev
```
*Application UI will be live at `http://localhost:3000`.*
---
## 🐳 Docker Deployment
To launch the full containerized stack:
```bash
docker-compose up --build
```
- Frontend: `http://localhost:3000`
- Backend API: `http://localhost:8000`
- Health Check: `http://localhost:8000/api/v1/health`
---
## 🧪 Test Suite & Verification
The platform includes a comprehensive automated test suite in `backend/tests/`:
```bash
pytest backend/tests -v
```
### Verified Test Results (16/16 Passing):
- `test_auth.py`: User registration, login, JWT validation, and invalid credential handling.
- `test_ner.py`: BC5CDR model info, entity extraction, character span alignment, and 422 validation.
- `test_documents.py`: File upload, SHA-256 fingerprinting, raw text extraction, and entity linking.
- `test_chat.py`: Multi-turn consultation, patient profile injection, and heuristic red-flag emergency detection.
- `test_profile.py`: Patient profile updates, vitals calculations, and RBAC admin permission enforcement.
- `test_health.py`: Liveness and readiness probes.
---
## 👨🏫 Mentor Demonstration Credentials
Use the **"Demo Roles"** dropdown in the navigation bar or log in with these pre-seeded accounts:
| Account | Email | Password | Role / Access Level |
| :--- | :--- | :--- | :--- |
| **Patient** | `demo.patient@sanjeevani.ai` | `DemoPatient2026!` | Health profile, documents, AI consultation |
| **Doctor** | `demo.doctor@sanjeevani.ai` | `DemoDoctor2026!` | Clinical decision support & document review |
| **Administrator** | `demo.admin@sanjeevani.ai` | `DemoAdmin2026!` | Platform telemetry, model status, security audit logs |
---
## 📚 Technical Documentation
- 📐 [**System Architecture & Mermaid Diagrams**](docs/ARCHITECTURE.md)
- 🔌 [**REST API Catalog & OpenAPI Specification**](docs/API.md)
- 🧠 [**Machine Learning & Local RoBERTa BC5CDR Specs**](docs/ML_MODELS.md)
- 🎯 [**10-Minute Mentor Presentation Script**](docs/MENTOR_DEMO.md)
- 🔍 [**Initial Project Audit & Gap Analysis**](docs/PROJECT_AUDIT.md)
---
## 🛡️ Medical Safety & Privacy Disclaimers
1. **AI-Assisted Decision Support**: SanjeevaniAI generates educational insights to assist healthcare providers and patients. It does not issue binding clinical diagnoses or prescribe treatment plans.
2. **Emergency Triage Protocol**: If severe acute symptoms (e.g. crushing chest pain, difficulty breathing, stroke symptoms) are entered, the platform immediately presents an emergency escalation alert advising immediate contact with emergency medical services (911 / 112 / 108).
3. **Data Security**: Uploaded files are fingerprinted with SHA-256, sensitive credentials hashed with direct bcrypt, and all administrative events logged in an immutable audit table.
---
## 📄 License
MIT License. Developed for healthcare AI intelligence and clinical decision-support research.
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