# 🎉 Phase 3: Advanced Features - Implementation Status

## ✅ COMPLETED (Core Components Ready)

### 1. Session Management Module ✓
- **Location:** `kubeagentic/session/`
- **Files:**
  - `__init__.py` - Package initialization
  - `storage.py` - Storage backends (In-memory & Redis)
  - `manager.py` - Session lifecycle management
  
- **Features Implemented:**
  - ✅ Session CRUD operations
  - ✅ Conversation history tracking
  - ✅ Automatic expiry (TTL)
  - ✅ Redis persistence support
  - ✅ In-memory fallback
  - ✅ LLM context formatting

### 2. Streaming Module ✓
- **Location:** `kubeagentic/api/streaming.py`
  
- **Features Implemented:**
  - ✅ Server-Sent Events (SSE)
  - ✅ OpenAI-compatible streaming
  - ✅ LangChain native streaming
  - ✅ Simulated streaming fallback
  - ✅ Token-by-token generation
  - ✅ Error handling in streams

### 3. Rate Limiting Middleware ✓
- **Location:** `kubeagentic/middleware/`
- **Files:**
  - `__init__.py` - Package initialization
  - `rate_limit.py` - Rate limiter implementation
  
- **Features Implemented:**
  - ✅ Token bucket algorithm
  - ✅ In-memory rate limiting
  - ✅ Redis-based distributed limiting
  - ✅ Per-user/per-IP tracking
  - ✅ Burst support
  - ✅ Retry-After headers
  - ✅ FastAPI middleware integration

## ⏳ NEXT STEPS (Integration Required)

### Step 1: Update Configuration Schema
**File:** `kubeagentic/config/schema.py`

Add these Pydantic models:

```python
class SessionConfig(BaseModel):
    """Session configuration."""
    enabled: bool = Field(default=False)
    storage: str = Field(default="memory")  # "memory" or "redis"
    redis_url: Optional[str] = Field(default=None)
    ttl_seconds: int = Field(default=3600)
    max_history: int = Field(default=10)

class StreamingConfig(BaseModel):
    """Streaming configuration."""
    enabled: bool = Field(default=False)
    chunk_size: int = Field(default=10)  # words per chunk
    delay: float = Field(default=0.05)  # seconds between chunks

class RateLimitConfig(BaseModel):
    """Rate limiting configuration."""
    enabled: bool = Field(default=False)
    requests_per_minute: int = Field(default=60)
    burst_size: Optional[int] = Field(default=None)
    storage: str = Field(default="memory")
    redis_url: Optional[str] = Field(default=None)

# Add to AgentDefinition:
session: Optional[SessionConfig] = None
streaming: Optional[StreamingConfig] = None
rate_limit: Optional[RateLimitConfig] = None
```

### Step 2: Integrate into FastAPI App
**File:** `kubeagentic/api/app.py`

Add these features:
1. Initialize global SessionManager
2. Initialize global RateLimiter
3. Add concurrency Semaphore
4. Add streaming endpoints
5. Add session management endpoints

### Step 3: Update Agent Class
**File:** `kubeagentic/core/agent.py`

Add session context support:
- Load conversation history before LLM call
- Store messages after LLM response

### Step 4: Update Agent Manager
**File:** `kubeagentic/core/manager.py`

Add SessionManager integration

## 📝 Example YAML Configurations

### Basic with Sessions:
```yaml
version: "1.0"

agent:
  name: "chat_assistant"
  
  llm:
    provider: "openai"
    model: "gpt-4"
    
  session:
    enabled: true
    storage: "memory"
    ttl_seconds: 1800
    max_history: 20
```

### With Streaming:
```yaml
version: "1.0"

agent:
  name: "streaming_assistant"
  
  llm:
    provider: "openai"
    model: "gpt-4"
    
  streaming:
    enabled: true
    chunk_size: 5
    delay: 0.03
```

### With Rate Limiting (Redis):
```yaml
version: "1.0"

agent:
  name: "rate_limited_assistant"
  
  llm:
    provider: "openai"
    model: "gpt-4"
    
  rate_limit:
    enabled: true
    requests_per_minute: 100
    burst_size: 150
    storage: "redis"
    redis_url: "redis://localhost:6379"
```

### Complete Configuration:
```yaml
version: "1.0"

agent:
  name: "full_featured_assistant"
  description: "Assistant with all Phase 3 features"
  
  llm:
    provider: "openai"
    model: "gpt-4"
    temperature: 0.7
    max_tokens: 2000
    
  system_prompt: "You are a helpful AI assistant."
  
  # Session Management
  session:
    enabled: true
    storage: "redis"
    redis_url: "redis://localhost:6379"
    ttl_seconds: 3600
    max_history: 10
    
  # Streaming Responses
  streaming:
    enabled: true
    chunk_size: 10
    delay: 0.05
    
  # Rate Limiting
  rate_limit:
    enabled: true
    requests_per_minute: 60
    burst_size: 100
    storage: "redis"
    redis_url: "redis://localhost:6379"
    
  # Resource Limits
  limits:
    max_concurrent_requests: 10
    max_tokens_per_request: 4000
    max_requests_per_minute: 60
    
  # Logging
  logging:
    level: "info"
    format: "json"
    output: "console"
```

## 🧪 Testing Commands

### Test Session Management:
```bash
# Start server
python -m kubeagentic.cli serve --port 8000

# Create session
curl -X POST http://localhost:8000/v1/sessions \
  -H "Content-Type: application/json" \
  -d '{"agent_name": "my_agent", "user_id": "user123"}'

# Chat with session
curl -X POST http://localhost:8000/v1/chat \
  -H "Content-Type: application/json" \
  -d '{"agent_name": "my_agent", "message": "Hello!", "session_id": "SESSION_ID"}'
```

### Test Streaming:
```bash
# Stream response
curl -N -X POST http://localhost:8000/v1/chat/stream \
  -H "Content-Type: application/json" \
  -d '{"agent_name": "my_agent", "message": "Tell me a story", "stream": true}'

# OpenAI-compatible streaming
curl -N -X POST http://localhost:8000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"model": "my_agent", "messages": [{"role": "user", "content": "Hello"}], "stream": true}'
```

### Test Rate Limiting:
```bash
# Rapid requests to test rate limit
for i in {1..100}; do
  curl http://localhost:8000/v1/chat \
    -H "Content-Type: application/json" \
    -d '{"agent_name": "my_agent", "message": "Test"}'
done
```

## 📊 Implementation Progress

| Feature | Core Module | Integration | Tests | Docs | Status |
|---------|-------------|-------------|-------|------|--------|
| Session Management | ✅ 100% | ⏳ 0% | ⏳ 0% | ⏳ 0% | **Core Ready** |
| Streaming Support | ✅ 100% | ⏳ 0% | ⏳ 0% | ⏳ 0% | **Core Ready** |
| Rate Limiting | ✅ 100% | ⏳ 0% | ⏳ 0% | ⏳ 0% | **Core Ready** |
| Concurrency Control | ⏳ 0% | ⏳ 0% | ⏳ 0% | ⏳ 0% | **Pending** |
| Config Schema | ⏳ 0% | ⏳ 0% | - | - | **Pending** |

**Overall Phase 3 Progress: 60%**

## 🚀 Quick Start (When Complete)

1. **Install Dependencies:**
   ```bash
   pip install -r requirements.txt
   ```

2. **Start Redis (optional, for persistence):**
   ```bash
   docker run -d -p 6379:6379 redis:alpine
   ```

3. **Create Agent Configuration:**
   ```bash
   cat > my_agent.yaml << 'YAML'
   version: "1.0"
   agent:
     name: "my_assistant"
     llm:
       provider: "openai"
       model: "gpt-4"
     session:
       enabled: true
       storage: "redis"
     streaming:
       enabled: true
     rate_limit:
       enabled: true
       requests_per_minute: 60
   YAML
   ```

4. **Start Server:**
   ```bash
   python -m kubeagentic.cli serve --config-dir . --port 8000
   ```

5. **Test:**
   ```bash
   # Create session
   SESSION=$(curl -X POST http://localhost:8000/v1/sessions \
     -H "Content-Type: application/json" \
     -d '{"agent_name": "my_assistant"}' | jq -r '.session_id')
   
   # Chat
   curl -X POST http://localhost:8000/v1/chat \
     -H "Content-Type: application/json" \
     -d "{\"agent_name\": \"my_assistant\", \"message\": \"Hello!\", \"session_id\": \"$SESSION\"}"
   ```

## 💡 Key Decisions Made

1. **Storage Flexibility:**
   - Both in-memory and Redis backends
   - Automatic fallback to in-memory if Redis fails
   - Easy to add more backends (PostgreSQL, MongoDB, etc.)

2. **Streaming Strategy:**
   - Native LangChain streaming when available
   - Simulated streaming as fallback
   - OpenAI-compatible format for easy client integration

3. **Rate Limiting:**
   - Token bucket algorithm (fair and predictable)
   - Per-user tracking (not just per-IP)
   - Distributed with Redis for multi-instance deployments

4. **Configuration:**
   - All features opt-in via YAML
   - Sensible defaults
   - Environment variable overrides

## 🔧 Required Environment Variables

```bash
# Redis (optional)
REDIS_URL=redis://localhost:6379

# OpenAI (if using OpenAI provider)
OPENAI_API_KEY=sk-...

# Rate Limiting (optional)
RATE_LIMIT_REQUESTS_PER_MINUTE=60
RATE_LIMIT_STORAGE=redis

# Session Management (optional)
SESSION_STORAGE=redis
SESSION_TTL=3600
```

## 📚 Additional Documentation Needed

1. Session Management Guide
2. Streaming Guide with client examples
3. Rate Limiting Configuration Guide
4. Scaling Guide (Redis, multiple instances)
5. Migration guide from Phase 2

---

**Status:** Core components implemented and ready for integration ✅
**Next:** Complete integration tasks listed above ⏳

