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title: PsyPredict [Backend]
emoji: 🧠
colorFrom: indigo
colorTo: purple
sdk: docker
pinned: false
---
# PsyPredict - Backend
**FastAPI** backend for PsyPredict — production-grade multimodal clinical AI system.
## What Runs Here
| Service | Technology |
|---------|-----------|
| API Framework | FastAPI + Uvicorn |
| LLM Inference | Ollama / Llama3 (local) |
| Text Emotion | DistilBERT (`bhadresh-savani/distilbert-base-uncased-emotion`) |
| Crisis Detection | Zero-shot NLI (MiniLM) |
| Face Emotion | Keras CNN (custom trained, `emotion_model_trained.h5`) |
| Remedies | CSV lookup (`MEDICATION.csv`) |
## Endpoints
| Method | Path | Description |
|--------|------|-------------|
| `POST` | `/api/chat` | Main therapist — returns `PsychReport` |
| `POST` | `/api/predict/emotion` | Facial emotion detection |
| `GET` | `/api/get_advice` | Remedy/condition lookup |
| `POST` | `/api/analyze/text` | Text emotion + crisis score |
| `GET` | `/api/health` | System health check |
## Running Locally
```bash
# 1. Install Ollama + LLaMA 3 (one-time)
winget install Ollama.Ollama
ollama pull llama3
# 2. Install dependencies
pip install -r requirements.txt
# 3. Start server
uvicorn app.main:app --host 0.0.0.0 --port 7860 --reload
```
Swagger docs: http://localhost:7860/docs
## Key Files
```
app/
├── main.py # FastAPI app factory
├── config.py # Pydantic Settings
├── schemas.py # All request/response models (PsychReport etc.)
├── services/
│ ├── ollama_engine.py # LLaMA 3 async client
│ ├── text_emotion_engine.py# DistilBERT classifier
│ ├── crisis_engine.py # Zero-shot NLI crisis detection
│ ├── fusion_engine.py # Multimodal weighted fusion
│ ├── emotion_engine.py # Keras CNN face emotion (preserved)
│ └── remedy_engine.py # CSV remedy lookup (preserved)
└── api/endpoints/
├── therapist.py # POST /api/chat
├── facial.py # POST /api/predict/emotion
├── remedies.py # GET /api/get_advice
└── analysis.py # POST /api/analyze/text + GET /api/health
```
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