Spaces:
Runtime error
Runtime error
File size: 6,668 Bytes
eeb0f9c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 |
# Scripts Documentation π
Automated scripts for HeoCare Chatbot setup and maintenance.
## π Quick Start
### One-Command Setup (Recommended)
```bash
# Run everything in one command
bash scripts/setup_rag.sh
```
**What it does:**
1. β
Check Python & dependencies
2. β
Install required packages
3. β
Download 6 medical datasets from HuggingFace
4. β
Build ChromaDB vector stores (~160 MB)
5. β
Generate training data (200 conversations)
6. β
Optional: Fine-tune agents
**Time:** ~15-20 minutes (depends on internet speed)
---
## π Available Scripts
### 1. `setup_rag.sh` β Main Setup
```bash
bash scripts/setup_rag.sh
```
**Features:**
- Downloads 6 datasets from HuggingFace:
- ViMedical (603 diseases)
- MentalChat16K (16K conversations)
- Nutrition recommendations
- Vietnamese food nutrition
- Fitness exercises (1.66K)
- Medical Q&A (9.3K pairs)
- Builds ChromaDB vector stores
- Generates training data
- Optional fine-tuning
**Skip existing databases automatically!**
---
### 2. `generate_training_data.py` - Training Data
```bash
python scripts/generate_training_data.py
```
**What it does:**
- Generates 200 synthetic conversations
- 50 scenarios per agent (nutrition, symptom, exercise, mental_health)
- Uses GPT-4o-mini
- Output: `fine_tuning/training_data/*.jsonl`
**Cost:** ~$0.50 (OpenAI API)
---
### 3. `auto_finetune.py` - Batch Fine-tuning
```bash
python scripts/auto_finetune.py
```
**What it does:**
- Fine-tunes all 4 agents automatically
- Uploads training files
- Creates fine-tuning jobs
- Tracks progress
- Updates model config
**Requirements:** OpenAI official API (custom APIs not supported)
---
### 4. `fine_tune_agent.py` - Single Agent Fine-tuning
```bash
python scripts/fine_tune_agent.py nutrition_agent
```
**What it does:**
- Fine-tune one specific agent
- Manual control over the process
- Alternative to auto_finetune.py
**Agents:** `nutrition_agent`, `symptom_agent`, `exercise_agent`, `mental_health_agent`
---
### 5. `check_rag_status.py` - Diagnostic Tool
```bash
python scripts/check_rag_status.py
```
**What it checks:**
- β
ChromaDB folders exist
- π Database sizes
- π Document counts
- π§ͺ Test queries
**Note:** May need updates for new vector store paths
---
## π Directory Structure
```
scripts/
βββ setup_rag.sh # β Main setup script
βββ generate_training_data.py # Generate synthetic data
βββ auto_finetune.py # Batch fine-tuning
βββ fine_tune_agent.py # Single agent fine-tuning
βββ check_rag_status.py # Diagnostic tool
βββ README.md # This file
data_mining/ # Dataset downloaders
βββ mining_vimedical.py # ViMedical diseases
βββ mining_mentalchat.py # Mental health conversations
βββ mining_nutrition.py # Nutrition recommendations
βββ mining_vietnamese_food.py # Vietnamese food data
βββ mining_fitness.py # Fitness exercises
βββ mining_medical_qa.py # Medical Q&A pairs
rag/vector_store/ # ChromaDB (NOT committed)
βββ medical_diseases/ # ViMedical (603 diseases)
βββ mental_health/ # MentalChat (16K conversations)
βββ nutrition/ # Nutrition plans
βββ vietnamese_nutrition/ # Vietnamese foods (73)
βββ fitness/ # Exercises (1.66K)
βββ symptom_qa/ # Medical Q&A
βββ general_health_qa/ # General health Q&A
fine_tuning/training_data/ # Generated data (NOT committed)
βββ nutrition_training.jsonl
βββ symptom_training.jsonl
βββ exercise_training.jsonl
βββ mental_health_training.jsonl
```
---
## π Team Workflow
### First Time Setup (New Team Member)
```bash
# 1. Clone repo
git clone <repo-url>
cd heocare-chatbot
# 2. Create .env file
cp .env.example .env
# Add your OPENAI_API_KEY
# 3. Setup everything (one command)
bash scripts/setup_rag.sh
# 4. Run app
python app.py
```
**Time:** ~15-20 minutes
---
### Daily Development
```bash
# Pull latest code
git pull
# If setup_rag.sh was updated, run it again
# (It will skip existing databases automatically)
bash scripts/setup_rag.sh
# Run app
python app.py
```
---
### Regenerate Training Data
```bash
# If you updated agent prompts or scenarios
python scripts/generate_training_data.py
# Optional: Fine-tune with new data
python scripts/auto_finetune.py
```
---
### Reset Everything
```bash
# Delete all generated data
rm -rf rag/vector_store/*
rm -rf fine_tuning/training_data/*
rm -rf data_mining/datasets/*
rm -rf data_mining/output/*
# Setup from scratch
bash scripts/setup_rag.sh
```
---
## π Troubleshooting
### Setup Failed
```bash
# Check Python version (need 3.8+)
python --version
# Check dependencies
pip install -r requirements.txt
# Check API key
echo $OPENAI_API_KEY
```
---
### Dataset Download Failed
```bash
# Check internet connection
ping huggingface.co
# Try manual download for specific dataset
python data_mining/mining_vimedical.py
python data_mining/mining_mentalchat.py
```
---
### ChromaDB Issues
```bash
# Check status
python scripts/check_rag_status.py
# Delete and rebuild specific database
rm -rf rag/vector_store/medical_diseases
python data_mining/mining_vimedical.py
# Move to correct location
mkdir -p rag/vector_store
mv data_mining/output/medical_chroma rag/vector_store/medical_diseases
```
---
### Fine-tuning 404 Error
```
Error: 404 - {'detail': 'Not Found'}
```
**Cause:** Custom API endpoint doesn't support fine-tuning
**Solution:**
1. Use OpenAI official API for fine-tuning
2. Or skip fine-tuning (app works fine with base model + RAG)
```bash
# Option 1: Update .env to use official API
OPENAI_BASE_URL=https://api.openai.com/v1
OPENAI_API_KEY=sk-proj-your-official-key
# Option 2: Skip fine-tuning
# Just run the app without fine-tuning
python app.py
```
---
## π Performance
| Task | Time | Size |
|------|------|------|
| Download datasets | ~5-8 min | ~50 MB |
| Build ChromaDB | ~5-7 min | ~160 MB |
| Generate training data | ~2-3 min | ~500 KB |
| Fine-tuning (optional) | ~30-60 min | - |
| **Total Setup** | **~15-20 min** | **~160 MB** |
---
## π Support
If you encounter issues:
1. Run `python scripts/check_rag_status.py` for diagnostics
2. Check console logs for errors
3. Verify `.gitignore` is correct
4. Try deleting and rebuilding specific databases
5. Check that `.env` has valid API key
---
**Happy Coding! π**
|