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+# Reactive Resume v5 - AI Model Configuration Guide
+
+## 🤖 Current AI Setup
+
+### Ollama Configuration
+- **Model**: `llama3.2:3b`
+- **Provider**: `ollama`
+- **Endpoint**: `http://ollama:11434` (internal)
+- **External API**: `http://192.168.0.250:11434`
+
+## 📋 Model Details for Reactive Resume v5
+
+### Environment Variables
+Add these to your `docker-compose.yml` environment section:
+
+```yaml
+environment:
+  # AI Integration (Ollama) - v5 uses OpenAI-compatible API
+  OPENAI_API_KEY: "ollama"  # Dummy key for local Ollama
+  OPENAI_BASE_URL: "http://ollama:11434/v1"  # Ollama OpenAI-compatible endpoint
+  OPENAI_MODEL: "llama3.2:3b"  # Model name
+```
+
+### Model Specifications
+
+#### llama3.2:3b
+- **Size**: ~2GB download
+- **Parameters**: 3 billion
+- **Context Length**: 8,192 tokens
+- **Use Case**: General text generation, resume assistance
+- **Performance**: Fast inference on CPU
+- **Memory**: ~4GB RAM during inference
+
+## 🔧 Alternative Models
+
+If you want to use different models, here are recommended options:
+
+### Lightweight Options (< 4GB RAM)
+```yaml
+# Fastest, smallest
+OLLAMA_MODEL: "llama3.2:1b"     # ~1GB, very fast
+
+# Balanced performance
+OLLAMA_MODEL: "llama3.2:3b"     # ~2GB, good quality (current)
+
+# Better quality, still reasonable
+OLLAMA_MODEL: "qwen2.5:3b"      # ~2GB, good for professional text
+```
+
+### High-Quality Options (8GB+ RAM)
+```yaml
+# Better reasoning
+OLLAMA_MODEL: "llama3.2:7b"     # ~4GB, higher quality
+
+# Excellent for professional content
+OLLAMA_MODEL: "qwen2.5:7b"      # ~4GB, great for business writing
+
+# Best quality (if you have the resources)
+OLLAMA_MODEL: "llama3.2:11b"    # ~7GB, excellent quality
+```
+
+### Specialized Models
+```yaml
+# Code-focused (good for tech resumes)
+OLLAMA_MODEL: "codellama:7b"    # ~4GB, code-aware
+
+# Instruction-following
+OLLAMA_MODEL: "mistral:7b"      # ~4GB, good at following prompts
+```
+
+## 🚀 Model Management Commands
+
+### Pull New Models
+```bash
+# Pull a different model
+ssh Vish@192.168.0.250 -p 62000 "sudo /usr/local/bin/docker exec Resume-OLLAMA-V5 ollama pull qwen2.5:3b"
+
+# List available models
+ssh Vish@192.168.0.250 -p 62000 "sudo /usr/local/bin/docker exec Resume-OLLAMA-V5 ollama list"
+
+# Remove unused models
+ssh Vish@192.168.0.250 -p 62000 "sudo /usr/local/bin/docker exec Resume-OLLAMA-V5 ollama rm llama3.2:1b"
+```
+
+### Change Active Model
+1. Update `OLLAMA_MODEL` in `docker-compose.yml`
+2. Redeploy: `./deploy.sh restart`
+3. Pull new model if needed: `./deploy.sh setup-ollama`
+
+## 🧪 Testing AI Features
+
+### Direct API Test
+```bash
+# Test the AI API directly
+curl -X POST http://192.168.0.250:11434/api/generate \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "llama3.2:3b",
+    "prompt": "Write a professional summary for a software engineer with 5 years experience in Python and React",
+    "stream": false
+  }'
+```
+
+### Expected Response
+```json
+{
+  "model": "llama3.2:3b",
+  "created_at": "2026-02-16T10:00:00.000Z",
+  "response": "Experienced Software Engineer with 5+ years of expertise in full-stack development using Python and React. Proven track record of building scalable web applications...",
+  "done": true
+}
+```
+
+## 🎯 AI Features in Reactive Resume v5
+
+### 1. Resume Content Suggestions
+- **Trigger**: Click "AI Assist" button in any text field
+- **Function**: Suggests professional content based on context
+- **Model Usage**: Generates 2-3 sentence suggestions
+
+### 2. Job Description Analysis
+- **Trigger**: Paste job description in "Job Match" feature
+- **Function**: Analyzes requirements and suggests skill additions
+- **Model Usage**: Extracts key requirements and matches to profile
+
+### 3. Skills Optimization
+- **Trigger**: "Optimize Skills" button in Skills section
+- **Function**: Suggests relevant skills based on experience
+- **Model Usage**: Analyzes work history and recommends skills
+
+### 4. Cover Letter Generation
+- **Trigger**: "Generate Cover Letter" in Documents section
+- **Function**: Creates personalized cover letter
+- **Model Usage**: Uses resume data + job description to generate letter
+
+## 📊 Performance Tuning
+
+### Model Performance Comparison
+| Model | Size | Speed | Quality | RAM Usage | Best For |
+|-------|------|-------|---------|-----------|----------|
+| llama3.2:1b | 1GB | Very Fast | Good | 2GB | Quick suggestions |
+| llama3.2:3b | 2GB | Fast | Very Good | 4GB | **Recommended** |
+| qwen2.5:3b | 2GB | Fast | Very Good | 4GB | Professional content |
+| llama3.2:7b | 4GB | Medium | Excellent | 8GB | High quality |
+
+### Optimization Settings
+```yaml
+# In docker-compose.yml for Ollama service
+environment:
+  OLLAMA_HOST: "0.0.0.0"
+  OLLAMA_KEEP_ALIVE: "5m"        # Keep model loaded for 5 minutes
+  OLLAMA_MAX_LOADED_MODELS: "1"  # Only keep one model in memory
+  OLLAMA_NUM_PARALLEL: "1"       # Number of parallel requests
+```
+
+## 🔍 Troubleshooting AI Issues
+
+### Model Not Loading
+```bash
+# Check if model exists
+ssh Vish@192.168.0.250 -p 62000 "sudo /usr/local/bin/docker exec Resume-OLLAMA-V5 ollama list"
+
+# Pull model manually
+ssh Vish@192.168.0.250 -p 62000 "sudo /usr/local/bin/docker exec Resume-OLLAMA-V5 ollama pull llama3.2:3b"
+
+# Check Ollama logs
+ssh Vish@192.168.0.250 -p 62000 "sudo /usr/local/bin/docker logs Resume-OLLAMA-V5"
+```
+
+### Slow AI Responses
+1. **Check CPU usage**: `htop` on Calypso
+2. **Reduce model size**: Switch to `llama3.2:1b`
+3. **Increase keep-alive**: Set `OLLAMA_KEEP_ALIVE: "30m"`
+
+### AI Features Not Appearing in UI
+1. **Check environment variables**: Ensure `AI_PROVIDER=ollama` is set
+2. **Verify connectivity**: Test API endpoint from app container
+3. **Check app logs**: Look for AI-related errors
+
+### Memory Issues
+```bash
+# Check memory usage
+ssh Vish@192.168.0.250 -p 62000 "free -h"
+
+# If low memory, switch to smaller model
+OLLAMA_MODEL: "llama3.2:1b"  # Uses ~2GB instead of 4GB
+```
+
+## 🔄 Model Updates
+
+### Updating to Newer Models
+1. **Check available models**: https://ollama.ai/library
+2. **Pull new model**: `ollama pull model-name`
+3. **Update compose file**: Change `OLLAMA_MODEL` value
+4. **Restart services**: `./deploy.sh restart`
+
+### Model Versioning
+```yaml
+# Pin to specific version
+OLLAMA_MODEL: "llama3.2:3b-q4_0"  # Specific quantization
+
+# Use latest (auto-updates)
+OLLAMA_MODEL: "llama3.2:3b"       # Latest version
+```
+
+## 📈 Monitoring AI Performance
+
+### Metrics to Watch
+- **Response Time**: Should be < 10s for most prompts
+- **Memory Usage**: Monitor RAM consumption
+- **Model Load Time**: First request after idle takes longer
+- **Error Rate**: Check for failed AI requests
+
+### Performance Commands
+```bash
+# Check AI API health
+curl http://192.168.0.250:11434/api/tags
+
+# Monitor resource usage
+ssh Vish@192.168.0.250 -p 62000 "docker stats Resume-OLLAMA-V5"
+
+# Check AI request logs
+ssh Vish@192.168.0.250 -p 62000 "sudo /usr/local/bin/docker logs Resume-ACCESS-V5 | grep -i ollama"
+```
+
+---
+
+**Current Configuration**: llama3.2:3b (Recommended)  
+**Last Updated**: 2026-02-16  
+**Performance**: ✅ Optimized for Calypso hardware