# Phase 2 Implementation Summary: OpenAIGPT Integration

## Changes Made

### 1. Updated `langroid/language_models/openai_gpt.py`

- **Added imports** for client cache wrapper functions
- **Replaced direct client instantiation** with wrapper functions:
  - `Groq()` → `get_groq_client()`
  - `AsyncGroq()` → `get_async_groq_client()`
  - `Cerebras()` → `get_cerebras_client()`
  - `AsyncCerebras()` → `get_async_cerebras_client()`
  - `OpenAI()` → `get_openai_client()`
  - `AsyncOpenAI()` → `get_async_openai_client()`

### 2. Fixed Async Client Cleanup

Updated `_cleanup_clients()` to properly handle async clients by checking if `close()` is a coroutine function and skipping await (since atexit can't handle async).

### 3. Created Integration Tests

`tests/main/test_openai_gpt_client_cache.py` with tests verifying:
- Multiple OpenAIGPT instances with same config share clients
- Different configurations create different clients
- Works correctly for OpenAI, Groq, and Cerebras models
- Different base URLs and headers create different clients

## Results

### Before (Anti-pattern)
```python
# Creating 100 agents = 100 OpenAI clients
for row in data[:100]:
    agent = ChatAgent(config)  # Each creates new OpenAI client
    result = agent.run(row)
```

### After (With caching)
```python
# Creating 100 agents = 1 OpenAI client (reused)
for row in data[:100]:
    agent = ChatAgent(config)  # Reuses existing OpenAI client
    result = agent.run(row)
```

## Testing Results

- ✅ All 9 client cache unit tests pass
- ✅ All 6 OpenAIGPT integration tests pass
- ✅ Existing LLM tests continue to pass
- ✅ Type checking passes
- ✅ Linting passes

## Benefits

1. **Resource Efficiency**: Dramatically reduces file descriptor usage
2. **Performance**: Eliminates repeated client initialization overhead
3. **Transparent**: No API changes required - existing code benefits automatically
4. **Configurable**: Each unique configuration gets its own cached client
5. **Safe**: Thread-safe implementation with proper cleanup

## Implementation Notes

- Used SHA256 hashing for cache keys (consistent with existing Redis cache)
- Handles all configuration parameters (API key, base URL, timeout, headers, etc.)
- Async client cleanup deferred to OS (atexit can't await)
- Weak references allow garbage collection when clients no longer needed