# Specification: OpenAI Provider Integration

## Overview
This track introduces support for OpenAI as a first-class model provider. It involves implementing a dedicated client in `src/ai_client.py`, updating configuration models, enhancing the GUI for provider selection, and integrating OpenAI into the tiered MMA architecture.

## Functional Requirements

### 1. Core AI Client (`src/ai_client.py`)
- **OpenAI Integration:**
    - Implement `_send_openai()` to handle communication with OpenAI's Chat Completions API.
    - Implement a tool-call loop similar to `_send_gemini` and `_send_anthropic`.
    - Support for function calling (using `tools` and `tool_choice`).
    - Support for multi-modal input (Vision) by encoding screenshots as base64 data URIs in the message payload.
    - Implement response streaming support compatible with the existing GUI mechanism.
- **State Management:**
    - Define module-level `_openai_client` and `_openai_history`.
    - Ensure `ai_client.reset_session()` clears OpenAI-specific history.
- **Error Handling:**
    - Implement `_classify_openai_error()` to map OpenAI API exceptions to `ProviderError` types (`quota`, `rate_limit`, `auth`, `balance`, `network`).
- **Model Discovery:**
    - Implement `_list_openai_models()` to fetch available models from the API.

### 2. Configuration & Authentication
- **Credentials:**
    - Update `_load_credentials()` to support an `[openai]` section in `credentials.toml`.
    - Update the `FileNotFoundError` message in `_load_credentials()` to include the OpenAI example.
- **Cost Tracking:**
    - Update `src/cost_tracker.py` with pricing for `gpt-4o`, `gpt-4o-mini`, `o1`, and `o3-mini`.

### 3. GUI & Controller Integration
- **Provider Lists:**
    - Add `openai` to the `PROVIDERS` list in `src/gui_2.py` and `src/app_controller.py`.
- **Model Fetching:**
    - Ensure `AppController._fetch_models()` correctly dispatches to `ai_client.list_models("openai")`.
- **Settings UI:**
    - The AI Settings panel should automatically handle the new provider and its models once added to the lists.

### 4. MMA Orchestration
- **Tier Support:**
    - Verify that agents in all tiers (1-4) can be configured to use OpenAI models via the `mma_tier_usage` dict in `AppController`.
    - Ensure `run_worker_lifecycle` in `src/multi_agent_conductor.py` correctly passes OpenAI model names to `ai_client.send()`.

## Non-Functional Requirements
- **Consistency:** Follow the established pattern of module-level singleton state in `ai_client.py`.
- **Latency:** Ensure the tool-call loop overhead is minimal.
- **Security:** Rigorously protect the OpenAI API key; ensure it is never logged or exposed in the GUI.

## Acceptance Criteria
- [ ] OpenAI can be selected as a provider in the AI Settings panel.
- [ ] Models like `gpt-4o` and `gpt-4o-mini` are listed and selectable.
- [ ] Agents can successfully use tools (e.g., `read_file`, `run_powershell`) using OpenAI models.
- [ ] Screenshots are correctly processed and described by vision-capable OpenAI models.
- [ ] Response streaming is functional in the Discussion panel.
- [ ] Estimated costs for OpenAI calls are displayed in the MMA Dashboard.

## Out of Scope
- Support for the legacy `gpt-3.5-turbo-instruct` or other non-chat models.
- Batch API support.
- Fine-tuning management.
