diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 444bf691..ef820763 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -1,7 +1,7 @@ repos: # Ruff linting and formatting - repo: https://github.com/astral-sh/ruff-pre-commit - rev: v0.12.2 + rev: v0.12.8 hooks: # Ruff linting (matches: make lint -> uv run ruff check .) - id: ruff @@ -16,7 +16,7 @@ repos: # MyPy type checking (matches: make typecheck -> uv run mypy .) - repo: https://github.com/pre-commit/mirrors-mypy - rev: v1.16.1 + rev: v1.17.1 hooks: - id: mypy name: mypy type check @@ -58,6 +58,7 @@ repos: - textual>=3.7.1 - aiofiles>=24.1.0 - types-aiofiles>=24.0.0 + - pyjwt>=2.10.0 args: [--config-file=pyproject.toml] exclude: ^(docs/|examples/) @@ -81,7 +82,7 @@ repos: # General file checks - repo: https://github.com/pre-commit/pre-commit-hooks - rev: v5.0.0 + rev: v6.0.0 hooks: # Basic file checks - id: trailing-whitespace diff --git a/CHANGELOG.md b/CHANGELOG.md index 62749123..4706e886 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -7,6 +7,153 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 ## [0.1.6] - 2025-08-04 +## Added OpenAI Codex Provider with Full Proxy Support + +### Overview + +Implemented comprehensive support for OpenAI Codex CLI integration, enabling users to proxy requests through their OpenAI subscription via the ChatGPT backend API. This feature provides an alternative to the Claude provider while maintaining full compatibility with the existing proxy architecture. The implementation uses the OpenAI Responses API endpoint as documented at https://platform.openai.com/docs/api-reference/responses/get. + +### Key Features + +**Complete Codex API Proxy** + +- Full reverse proxy to `https://chatgpt.com/backend-api/codex` +- Support for both `/codex/responses` and `/codex/{session_id}/responses` endpoints +- Compatible with Codex CLI 0.21.0 and authentication flow +- Implements OpenAI Responses API protocol + +**OAuth PKCE Authentication Flow** + +- Implements complete OpenAI OAuth 2.0 PKCE flow matching official Codex CLI +- Local callback server on port 1455 for authorization code exchange +- Token refresh and credential management with persistent storage +- Support for `~/.codex/auth.json` configuration file format + +**Intelligent Request/Response Handling** + +- Automatic detection and injection of Codex CLI instructions field +- Smart streaming behavior based on user's explicit `stream` parameter +- Session management with flexible session ID handling (auto-generated, persistent, header-forwarded) +- Request transformation preserving Codex CLI identity headers + +**Advanced Configuration** + +- Environment variable support: `CODEX__BASE_URL` +- Configurable via TOML: `[codex]` section in configuration files +- Debug logging with request/response capture capabilities +- Comprehensive error handling with proper HTTP status codes +- Enabled by default + +### Technical Implementation + +**New Components Added:** + +- `ccproxy/auth/openai.py` - OAuth token management and credential storage +- `ccproxy/core/codex_transformers.py` - Request/response transformation for Codex format +- `ccproxy/api/routes/codex.py` - FastAPI routes for Codex endpoints +- `ccproxy/models/detection.py` - Codex CLI detection and header management +- `ccproxy/services/codex_detection_service.py` - Runtime detection of Codex CLI requests + +**Enhanced Proxy Service:** + +- Extended `ProxyService.handle_codex_request()` with full Codex support +- Intelligent streaming response conversion when user doesn't explicitly request streaming +- Comprehensive request/response logging for debugging +- Error handling with proper OpenAI-compatible error responses + +### Streaming Behavior Fix + +**Problem Resolved:** Fixed issue where requests without explicit `stream` field were incorrectly returning streaming responses. + +**Solution Implemented:** + +- When `"stream"` field is missing: Inject `"stream": true` for upstream (Codex requirement) but return JSON response to client +- When `"stream": true` explicitly set: Return streaming response to client +- When `"stream": false` explicitly set: Return JSON response to client +- Smart response conversion: collects streaming data and converts to single JSON response when user didn't request streaming + +### Usage Examples + +**Basic Request (JSON Response):** + +```bash +curl -X POST "http://127.0.0.1:8000/codex/responses" \ + -H "Content-Type: application/json" \ + -d '{ + "input": [{"type": "message", "role": "user", "content": [{"type": "input_text", "text": "Hello!"}]}], + "model": "gpt-5", + "store": false + }' +``` + +**Streaming Request:** + +```bash +curl -X POST "http://127.0.0.1:8000/codex/responses" \ + -H "Content-Type: application/json" \ + -d '{ + "input": [{"type": "message", "role": "user", "content": [{"type": "input_text", "text": "Hello!"}]}], + "model": "gpt-5", + "stream": true, + "store": false + }' +``` + +### Authentication Setup + +**Environment Variables:** + +```bash +export CODEX__BASE_URL="https://chatgpt.com/backend-api/codex" +``` + +**Configuration File (`~/.ccproxy.toml`):** + +```toml +[codex] +base_url = "https://chatgpt.com/backend-api/codex" +``` + +### Compatibility + +- Codex CLI: Full compatibility with `codex-cli 0.21.0` +- OpenAI OAuth: Complete PKCE flow implementation +- Session Management: Supports persistent and auto-generated sessions +- Model Support: All Codex-supported models (`gpt-5`, `gpt-4`, etc.) +- Streaming: Both streaming and non-streaming responses +- Error Handling: Proper HTTP status codes and OpenAI-compatible errors +- API Compliance: Follows OpenAI Responses API specification + +### Files Modified/Added + +**New Files:** + +- `ccproxy/auth/openai.py` - OpenAI authentication management +- `ccproxy/core/codex_transformers.py` - Codex request/response transformation +- `ccproxy/api/routes/codex.py` - Codex API endpoints +- `ccproxy/models/detection.py` - Codex detection models +- `ccproxy/services/codex_detection_service.py` - Codex CLI detection service + +**Modified Files:** + +- `ccproxy/services/proxy_service.py` - Added `handle_codex_request()` method +- `ccproxy/config/settings.py` - Added Codex configuration section +- `ccproxy/api/app.py` - Integrated Codex routes +- `ccproxy/api/routes/health.py` - Added Codex health checks + +### Breaking Changes + +None. This is a purely additive feature that doesn't affect existing Claude provider functionality. + +### Migration Notes + +For users wanting to use Codex provider: + +1. Authenticate: Use existing OpenAI credentials or run Codex CLI login +2. Update endpoints: Change from `/v1/messages` to `/codex/responses` + +This implementation provides a complete, production-ready OpenAI Codex proxy solution that maintains the same standards as the existing Claude provider while offering users choice in their AI provider preferences. + ## [0.1.5] - 2025-08-03 ### Added diff --git a/Makefile b/Makefile index 846e9f15..8ad935d8 100644 --- a/Makefile +++ b/Makefile @@ -81,6 +81,14 @@ clean: # - 'unit': Fast unit tests (< 1s each, no external dependencies) # - Tests without 'real_api' marker are considered unit tests by default +# Fix code with unsafe fixes +fix-hard: + uv run ruff check . --fix --unsafe-fixes + uv run uv run ruff check . --select F401 --fix --unsafe-fixes # Used variable import + uv run uv run ruff check . --select I --fix --unsafe-fixes # Import order + uv run ruff format . + + fix: format lint-fix ruff check . --fix --unsafe-fixes diff --git a/README.md b/README.md index 50df3a2c..e6e2f89a 100644 --- a/README.md +++ b/README.md @@ -1,12 +1,29 @@ # CCProxy API Server -`ccproxy` is a local reverse proxy server for Anthropic Claude LLM at `api.anthropic.com/v1/messages`. It allows you to use your existing Claude Max subscription to interact with the Anthropic API, bypassing the need for separate API key billing. +`ccproxy` is a local reverse proxy server that provides unified access to multiple AI providers through a single interface. It supports both Anthropic Claude and OpenAI Codex backends, allowing you to use your existing subscriptions without separate API key billing. + +## Supported Providers + +### Anthropic Claude + +Access Claude via your Claude Max subscription at `api.anthropic.com/v1/messages`. The server provides two primary modes of operation: -* **SDK Mode (`/sdk`):** Routes requests through the local `claude-code-sdk`. This enables access to tools configured in your Claude environment and includes an integrated MCP (Model Context Protocol) server for permission management. -* **API Mode (`/api`):** Acts as a direct reverse proxy, injecting the necessary authentication headers. This provides full access to the underlying API features and model settings. -It includes a translation layer to support both Anthropic and OpenAI-compatible API formats for requests and responses, including streaming. +- **SDK Mode (`/sdk`):** Routes requests through the local `claude-code-sdk`. This enables access to tools configured in your Claude environment and includes an integrated MCP (Model Context Protocol) server for permission management. +- **API Mode (`/api`):** Acts as a direct reverse proxy, injecting the necessary authentication headers. This provides full access to the underlying API features and model settings. + +### OpenAI Codex Response API (Experimental) + +Access OpenAI's [Response API](https://platform.openai.com/docs/api-reference/responses) via your ChatGPT Plus subscription. This provides programmatic access to ChatGPT models through the `chatgpt.com/backend-api/codex` endpoint. + +- **Response API (`/codex/responses`):** Direct reverse proxy to ChatGPT backend for conversation responses +- **Session Management:** Supports both auto-generated and persistent session IDs for conversation continuity +- **OpenAI OAuth:** Uses the same OAuth2 PKCE authentication flow as the official Codex CLI +- **ChatGPT Plus Required:** Requires an active ChatGPT Plus subscription for API access +- **Instruction Prompt:** Automatically injects the Codex instruction prompt into conversations + +The server includes a translation layer to support both Anthropic and OpenAI-compatible API formats for requests and responses, including streaming. ## Installation @@ -31,36 +48,80 @@ eval "$(ccproxy --show-completion zsh)" # For zsh eval "$(ccproxy --show-completion bash)" # For bash ``` - For dev version replace `ccproxy-api` with `git+https://github.com/caddyglow/ccproxy-api.git@dev` ## Authentication -The proxy uses two different authentication mechanisms depending on the mode. +The proxy uses different authentication mechanisms depending on the provider and mode. + +### Claude Authentication 1. **Claude CLI (`sdk` mode):** This mode relies on the authentication handled by the `claude-code-sdk`. + ```bash claude /login ``` It's also possible now to get a long live token to avoid renewing issues using - ```sh + ```bash - claude setup-token` + claude setup-token + ``` 2. **ccproxy (`api` mode):** This mode uses its own OAuth2 flow to obtain credentials for direct API access. + ```bash ccproxy auth login ``` If you are already connected with Claude CLI the credentials should be found automatically -You can check the status of these credentials with `ccproxy auth validate` and `ccproxy auth info`. +### OpenAI Codex Authentication (Experimental) + +The Codex Response API requires ChatGPT Plus subscription and OAuth2 authentication: + +```bash +# Enable Codex provider +ccproxy config codex --enable + +# Authentication options: + +# Option 1: Use existing Codex CLI credentials (if available) +# CCProxy will automatically detect and use valid credentials from: +# - $HOME/.codex/auth.json (Codex CLI credentials) +# - Automatically renews tokens if expired but refresh token is valid + +# Option 2: Login via CCProxy CLI (opens browser) +ccproxy auth login-openai + +# Option 3: Use the official Codex CLI +codex auth login + +# Check authentication status for all providers +ccproxy auth status +``` -Warning is show on start up if no credentials are setup. +**Important Notes:** + +- Credentials are stored in `$HOME/.codex/auth.json` +- CCProxy reuses existing Codex CLI credentials when available +- If credentials are expired, CCProxy attempts automatic renewal +- Without valid credentials, users must authenticate using either CCProxy or Codex CLI + +### Authentication Status + +You can check the status of all credentials with: + +```bash +ccproxy auth status # All providers +ccproxy auth validate # Claude only +ccproxy auth info # Claude only +``` + +Warning is shown on startup if no credentials are setup. ## Usage @@ -70,13 +131,15 @@ Warning is show on start up if no credentials are setup. # Start the proxy server ccproxy ``` + The server will start on `http://127.0.0.1:8000` by default. ### Client Configuration Point your existing tools and applications to the local proxy instance by setting the appropriate environment variables. A dummy API key is required by most client libraries but is not used by the proxy itself. -**For OpenAI-compatible clients:** +**For Claude (OpenAI-compatible clients):** + ```bash # For SDK mode export OPENAI_BASE_URL="http://localhost:8000/sdk/v1" @@ -86,7 +149,8 @@ export OPENAI_BASE_URL="http://localhost:8000/api/v1" export OPENAI_API_KEY="dummy-key" ``` -**For Anthropic-compatible clients:** +**For Claude (Anthropic-compatible clients):** + ```bash # For SDK mode export ANTHROPIC_BASE_URL="http://localhost:8000/sdk" @@ -96,6 +160,86 @@ export ANTHROPIC_BASE_URL="http://localhost:8000/api" export ANTHROPIC_API_KEY="dummy-key" ``` +**For OpenAI Codex Response API:** + +```bash +# Create a new conversation response (auto-generated session) +curl -X POST http://localhost:8000/codex/responses \ + -H "Content-Type: application/json" \ + -d '{ + "model": "gpt-5", + "messages": [ + {"role": "user", "content": "Hello, can you help me with Python?"} + ] + }' + +# Continue conversation with persistent session ID +curl -X POST http://localhost:8000/codex/my_session_123/responses \ + -H "Content-Type: application/json" \ + -d '{ + "model": "gpt-5", + "messages": [ + {"role": "user", "content": "Show me an example of async/await"} + ] + }' + +# Stream responses (SSE format) +curl -X POST http://localhost:8000/codex/responses \ + -H "Content-Type: application/json" \ + -d '{ + "model": "gpt-5", + "messages": [{"role": "user", "content": "Explain quantum computing"}], + "stream": true + }' +``` + +**For OpenAI-compatible clients using Codex:** + +```yaml +# Example aichat configuration (~/.config/aichat/config.yaml) +clients: + - type: claude + api_base: http://127.0.0.1:8000/codex + +# Usage +aichat --model openai:gpt-5 "hello" +``` + +**Important Codex Limitations:** + +- Limited model support (e.g., `gpt-5` works, others may not) +- Many OpenAI parameters not supported (temperature, top_p, etc.) +- Reasoning content appears in XML tags for capable models + +**Note:** The Codex instruction prompt is automatically injected into all conversations to maintain compatibility with the ChatGPT backend. + +### Codex Response API Details + +#### Session Management + +The Codex Response API supports flexible session management for conversation continuity: + +- **Auto-generated sessions**: `POST /codex/responses` - Creates a new session ID for each request +- **Persistent sessions**: `POST /codex/{session_id}/responses` - Maintains conversation context across requests +- **Header forwarding**: Optional `session_id` header for custom session tracking + +#### Instruction Prompt Injection + +**Important:** CCProxy automatically injects the Codex instruction prompt into every conversation. This is required for proper interaction with the ChatGPT backend but affects your token usage: + +- The instruction prompt is prepended to your messages +- This consumes additional tokens in each request +- The prompt ensures compatibility with ChatGPT's response generation +- You cannot disable this injection as it's required by the backend + +#### Model Differences + +The Response API models differ from standard OpenAI API models: + +- Uses ChatGPT Plus models (e.g., `gpt-4`, `gpt-4-turbo`) +- Model behavior matches ChatGPT web interface +- Token limits and pricing follow ChatGPT Plus subscription terms +- See [OpenAI Response API Documentation](https://platform.openai.com/docs/api-reference/responses) for details ## MCP Server Integration & Permission System @@ -104,6 +248,7 @@ In SDK mode, CCProxy automatically configures an MCP (Model Context Protocol) se ### Permission Management **Starting the Permission Handler:** + ```bash # In a separate terminal, start the permission handler ccproxy permission-handler @@ -113,12 +258,14 @@ ccproxy permission-handler --host 127.0.0.1 --port 8000 ``` The permission handler provides: + - **Real-time Permission Requests**: Streams permission requests via Server-Sent Events (SSE) - **Interactive Approval/Denial**: Command-line interface for managing tool permissions - **Automatic MCP Integration**: Works seamlessly with Claude Code SDK tools **Working Directory Control:** Control which project the Claude SDK API can access using the `--cwd` flag: + ```bash # Set working directory for Claude SDK ccproxy --claude-code-options-cwd /path/to/your/project @@ -142,6 +289,7 @@ CCProxy supports flexible message formatting through the `sdk_message_mode` conf - **`ignore`**: Filters out Claude SDK-specific content entirely Configure via environment variables: + ```bash # Use formatted XML output CLAUDE__SDK_MESSAGE_MODE=formatted ccproxy @@ -155,11 +303,13 @@ CLAUDE__PRETTY_FORMAT=false ccproxy CCProxy supports connection pooling for Claude Code SDK clients to improve request performance by maintaining a pool of pre-initialized Claude instances. ### Benefits + - **Reduced Latency**: Eliminates Claude Code startup overhead on each request - **Improved Performance**: Reuses established connections for faster response times - **Resource Efficiency**: Maintains a configurable pool size to balance performance and resource usage ### Usage + Pool mode is disabled by default and can be enabled using the CLI flag: ```bash @@ -171,6 +321,7 @@ ccproxy --sdk-enable-pool --sdk-pool-size 5 ``` ### Limitations + - **No Dynamic Options**: Pool instances cannot change Claude options (max_tokens, model, etc.) after initialization - **Shared Configuration**: All requests using the pool must use identical Claude configuration - **Memory Usage**: Each pool instance consumes additional memory @@ -182,6 +333,7 @@ Pool mode is most effective for high-frequency requests with consistent configur CCProxy works seamlessly with Aider and other AI coding assistants: ### Anthropic Mode + ```bash export ANTHROPIC_API_KEY=dummy export ANTHROPIC_BASE_URL=http://127.0.0.1:8000/api @@ -208,6 +360,30 @@ export OPENAI_BASE_URL=http://127.0.0.1:8000/api/v1 aider --model o3-mini ``` +### Using with OpenAI Codex + +For tools that support custom API bases, you can use the Codex provider. Note that this has significant limitations compared to Claude providers. + +**Example with aichat:** + +```yaml +# ~/.config/aichat/config.yaml +clients: + - type: claude + api_base: http://127.0.0.1:8000/codex +``` + +```bash +# Usage with confirmed working model +aichat --model openai:gpt-5 "hello" +``` + +**Codex Limitations:** + +- Only select models work (gpt-5 confirmed, others may fail) +- No support for temperature, top_p, or most OpenAI parameters +- When using reasoning models, reasoning appears as XML tags in output + ### `curl` Example ```bash @@ -229,51 +405,81 @@ curl -X POST http://localhost:8000/api/v1/messages \ "max_tokens": 100 }' ``` + More examples are available in the `examples/` directory. ## Endpoints -The proxy exposes endpoints under two prefixes, corresponding to its operating modes. - -| Mode | URL Prefix | Description | Use Case | -|------|------------|-------------|----------| -| **SDK** | `/sdk/` | Uses `claude-code-sdk` with its configured tools. | Accessing Claude with local tools. | -| **API** | `/api/` | Direct proxy with header injection. | Full API control, direct access. | - -* **Anthropic:** - * `POST /sdk/v1/messages` - * `POST /api/v1/messages` -* **OpenAI-Compatible:** - * `POST /sdk/v1/chat/completions` - * `POST /api/v1/chat/completions` -* **Utility:** - * `GET /health` - * `GET /sdk/models`, `GET /api/models` - * `GET /sdk/status`, `GET /api/status` - * `GET /oauth/callback` -* **MCP & Permissions:** - * `POST /mcp/permission/check` - MCP permission checking endpoint - * `GET /permissions/stream` - SSE stream for permission requests - * `GET /permissions/{id}` - Get permission request details - * `POST /permissions/{id}/respond` - Respond to permission request -* **Observability (Optional):** - * `GET /metrics` - * `GET /logs/status`, `GET /logs/query` - * `GET /dashboard` +The proxy exposes endpoints under multiple prefixes for different providers and modes. + +### Claude Endpoints + +| Mode | URL Prefix | Description | Use Case | +| ------- | ---------- | ------------------------------------------------- | ---------------------------------- | +| **SDK** | `/sdk/` | Uses `claude-code-sdk` with its configured tools. | Accessing Claude with local tools. | +| **API** | `/api/` | Direct proxy with header injection. | Full API control, direct access. | + +- **Anthropic Format:** + - `POST /sdk/v1/messages` + - `POST /api/v1/messages` +- **OpenAI-Compatible Format:** + - `POST /sdk/v1/chat/completions` + - `POST /api/v1/chat/completions` + +### OpenAI Codex Endpoints + +- **Response API:** + - `POST /codex/responses` - Create response with auto-generated session + - `POST /codex/{session_id}/responses` - Create response with persistent session + - `POST /codex/chat/completions` - OpenAI-compatible chat completions endpoint + - `POST /codex/v1/chat/completions` - Alternative OpenAI-compatible endpoint + - Supports streaming via SSE when `stream: true` is set + - See [Response API docs](https://platform.openai.com/docs/api-reference/responses) + +**Codex Chat Completions Limitations:** + +- **No Tool/Function Calling Support**: Tool use and function calling are not supported (use `/codex/responses` for tool calls) +- **Limited Parameter Support**: Many OpenAI parameters (temperature, top_p, frequency_penalty, etc.) are not supported +- **Restricted Model Support**: Only certain models work (e.g., `gpt-5` confirmed working, others may fail) +- **No Custom System Prompts**: System messages and instructions are overridden by the required Codex instruction prompt +- **Reasoning Mode**: GPT models with reasoning capabilities pass reasoning content between XML tags (`...`) +- **Session Management**: Uses auto-generated sessions; persistent sessions require the `/codex/{session_id}/responses` endpoint +- **ChatGPT Plus Required**: Requires active ChatGPT Plus subscription for access + +**Note**: The `/codex/responses` endpoint supports tool calling and more parameters, but specific feature availability depends on ChatGPT's backend - users should test individual capabilities. + +### Utility Endpoints + +- **Health & Status:** + - `GET /health` + - `GET /sdk/models`, `GET /api/models` + - `GET /sdk/status`, `GET /api/status` +- **Authentication:** + - `GET /oauth/callback` - OAuth callback for both Claude and OpenAI +- **MCP & Permissions:** + - `POST /mcp/permission/check` - MCP permission checking endpoint + - `GET /permissions/stream` - SSE stream for permission requests + - `GET /permissions/{id}` - Get permission request details + - `POST /permissions/{id}/respond` - Respond to permission request +- **Observability (Optional):** + - `GET /metrics` + - `GET /logs/status`, `GET /logs/query` + - `GET /dashboard` ## Supported Models CCProxy supports recent Claude models including Opus, Sonnet, and Haiku variants. The specific models available to you will depend on your Claude account and the features enabled for your subscription. - * `claude-opus-4-20250514` - * `claude-sonnet-4-20250514` - * `claude-3-7-sonnet-20250219` - * `claude-3-5-sonnet-20241022` - * `claude-3-5-sonnet-20240620` +- `claude-opus-4-20250514` +- `claude-sonnet-4-20250514` +- `claude-3-7-sonnet-20250219` +- `claude-3-5-sonnet-20241022` +- `claude-3-5-sonnet-20240620` ## Configuration Settings can be configured through (in order of precedence): + 1. Command-line arguments 2. Environment variables 3. `.env` file @@ -294,12 +500,14 @@ SERVER__PORT=8080 You can enable token authentication for the proxy. This supports multiple header formats (`x-api-key` for Anthropic, `Authorization: Bearer` for OpenAI) for compatibility with standard client libraries. **1. Generate a Token:** + ```bash ccproxy generate-token # Output: SECURITY__AUTH_TOKEN=abc123xyz789... ``` **2. Configure the Token:** + ```bash # Set environment variable export SECURITY__AUTH_TOKEN=abc123xyz789... @@ -310,6 +518,7 @@ echo "SECURITY__AUTH_TOKEN=abc123xyz789..." >> .env **3. Use in Requests:** When authentication is enabled, include the token in your API requests. + ```bash # Anthropic Format (x-api-key) curl -H "x-api-key: your-token" ... @@ -322,10 +531,10 @@ curl -H "Authorization: Bearer your-token" ... `ccproxy` includes an optional but powerful observability suite for monitoring and analytics. When enabled, it provides: -* **Prometheus Metrics:** A `/metrics` endpoint for real-time operational monitoring. -* **Access Log Storage:** Detailed request logs, including token usage and costs, are stored in a local DuckDB database. -* **Analytics API:** Endpoints to query and analyze historical usage data. -* **Real-time Dashboard:** A live web interface at `/dashboard` to visualize metrics and request streams. +- **Prometheus Metrics:** A `/metrics` endpoint for real-time operational monitoring. +- **Access Log Storage:** Detailed request logs, including token usage and costs, are stored in a local DuckDB database. +- **Analytics API:** Endpoints to query and analyze historical usage data. +- **Real-time Dashboard:** A live web interface at `/dashboard` to visualize metrics and request streams. These features are disabled by default and can be enabled via configuration. For a complete guide on setting up and using these features, see the [Observability Documentation](docs/observability.md). @@ -335,9 +544,18 @@ These features are disabled by default and can be enabled via configuration. For 1. **Authentication Error:** Ensure you're using the correct mode (`/sdk` or `/api`) for your authentication method. 2. **Claude Credentials Expired:** Run `ccproxy auth login` to refresh credentials for API mode. Run `claude /login` for SDK mode. -3. **Missing API Auth Token:** If you've enabled security, include the token in your request headers. -4. **Port Already in Use:** Start the server on a different port: `ccproxy --port 8001`. -5. **Model Not Available:** Check that your Claude subscription includes the requested model. +3. **OpenAI/Codex Authentication Failed:** + - Check if valid credentials exist: `ccproxy auth status` + - Ensure you have an active ChatGPT Plus subscription + - Try re-authenticating: `ccproxy auth login-openai` or `codex auth login` + - Verify credentials in `$HOME/.codex/auth.json` +4. **Codex Response API Errors:** + - "Instruction prompt injection failed": The backend requires the Codex prompt; this is automatic + - "Session not found": Use persistent session IDs for conversation continuity + - "Model not available": Ensure you're using ChatGPT Plus compatible models +5. **Missing API Auth Token:** If you've enabled security, include the token in your request headers. +6. **Port Already in Use:** Start the server on a different port: `ccproxy --port 8001`. +7. **Model Not Available:** Check that your subscription includes the requested model. ## Contributing diff --git a/ccproxy/adapters/codex/__init__.py b/ccproxy/adapters/codex/__init__.py new file mode 100644 index 00000000..d827fa9f --- /dev/null +++ b/ccproxy/adapters/codex/__init__.py @@ -0,0 +1,11 @@ +"""Codex adapter for format conversion.""" + +from ccproxy.models.requests import CodexMessage, CodexRequest +from ccproxy.models.responses import CodexResponse + + +__all__ = [ + "CodexMessage", + "CodexRequest", + "CodexResponse", +] diff --git a/ccproxy/adapters/openai/models.py b/ccproxy/adapters/openai/models.py index bfd9670a..53c0b3a1 100644 --- a/ccproxy/adapters/openai/models.py +++ b/ccproxy/adapters/openai/models.py @@ -286,7 +286,7 @@ class OpenAIChatCompletionResponse(BaseModel): created: int model: str choices: list[OpenAIChoice] - usage: OpenAIUsage + usage: OpenAIUsage | None = None system_fingerprint: str | None = None model_config = ConfigDict(extra="forbid") diff --git a/ccproxy/adapters/openai/response_adapter.py b/ccproxy/adapters/openai/response_adapter.py new file mode 100644 index 00000000..241f070f --- /dev/null +++ b/ccproxy/adapters/openai/response_adapter.py @@ -0,0 +1,355 @@ +"""Adapter for converting between OpenAI Chat Completions and Response API formats. + +This adapter handles bidirectional conversion between: +- OpenAI Chat Completions API (used by most OpenAI clients) +- OpenAI Response API (used by Codex/ChatGPT backend) +""" + +from __future__ import annotations + +import json +import time +import uuid +from collections.abc import AsyncIterator +from typing import Any + +import structlog + +from ccproxy.adapters.openai.models import ( + OpenAIChatCompletionRequest, + OpenAIChatCompletionResponse, + OpenAIChoice, + OpenAIResponseMessage, + OpenAIUsage, +) +from ccproxy.adapters.openai.response_models import ( + ResponseCompleted, + ResponseMessage, + ResponseMessageContent, + ResponseReasoning, + ResponseRequest, +) + + +logger = structlog.get_logger(__name__) + + +class ResponseAdapter: + """Adapter for OpenAI Response API format conversion.""" + + def chat_to_response_request( + self, chat_request: dict[str, Any] | OpenAIChatCompletionRequest + ) -> ResponseRequest: + """Convert Chat Completions request to Response API format. + + Args: + chat_request: OpenAI Chat Completions request + + Returns: + Response API formatted request + """ + if isinstance(chat_request, OpenAIChatCompletionRequest): + chat_dict = chat_request.model_dump() + else: + chat_dict = chat_request + + # Extract messages and convert to Response API format + messages = chat_dict.get("messages", []) + response_input = [] + instructions = None + + for msg in messages: + role = msg.get("role", "user") + content = msg.get("content", "") + + # System messages become instructions + if role == "system": + instructions = content + continue + + # Convert user/assistant messages to Response API format + response_msg = ResponseMessage( + type="message", + id=None, + role=role if role in ["user", "assistant"] else "user", + content=[ + ResponseMessageContent( + type="input_text" if role == "user" else "output_text", + text=content if isinstance(content, str) else str(content), + ) + ], + ) + response_input.append(response_msg) + + # Leave instructions field unset to let codex_transformers inject them + # The backend validates instructions and needs the full Codex ones + instructions = None + # Actually, we need to not include the field at all if it's None + # Otherwise the backend complains "Instructions are required" + + # Map model (Codex uses gpt-5) + model = chat_dict.get("model", "gpt-4") + # For Codex, we typically use gpt-5 + response_model = ( + "gpt-5" if "codex" in model.lower() or "gpt-5" in model.lower() else model + ) + + # Build Response API request + # Note: Response API always requires stream=true and store=false + # Also, Response API doesn't support temperature and other OpenAI-specific parameters + request = ResponseRequest( + model=response_model, + instructions=instructions, + input=response_input, + stream=True, # Always use streaming for Response API + tool_choice="auto", + parallel_tool_calls=chat_dict.get("parallel_tool_calls", False), + reasoning=ResponseReasoning(effort="medium", summary="auto"), + store=False, # Must be false for Response API + # The following parameters are not supported by Response API: + # temperature, max_output_tokens, top_p, frequency_penalty, presence_penalty + ) + + return request + + def response_to_chat_completion( + self, response_data: dict[str, Any] | ResponseCompleted + ) -> OpenAIChatCompletionResponse: + """Convert Response API response to Chat Completions format. + + Args: + response_data: Response API response + + Returns: + Chat Completions formatted response + """ + # Extract the actual response data + response_dict: dict[str, Any] + if isinstance(response_data, ResponseCompleted): + # Convert Pydantic model to dict + response_dict = response_data.response.model_dump() + else: # isinstance(response_data, dict) + if "response" in response_data: + response_dict = response_data["response"] + else: + response_dict = response_data + + # Extract content from Response API output + content = "" + output = response_dict.get("output", []) + # Look for message type output (skip reasoning) + for output_item in output: + if output_item.get("type") == "message": + output_content = output_item.get("content", []) + for content_block in output_content: + if content_block.get("type") in ["output_text", "text"]: + content += content_block.get("text", "") + + # Build Chat Completions response + usage_data = response_dict.get("usage") + converted_usage = self._convert_usage(usage_data) if usage_data else None + + return OpenAIChatCompletionResponse( + id=response_dict.get("id", f"resp_{uuid.uuid4().hex}"), + object="chat.completion", + created=response_dict.get("created_at", int(time.time())), + model=response_dict.get("model", "gpt-5"), + choices=[ + OpenAIChoice( + index=0, + message=OpenAIResponseMessage( + role="assistant", content=content or None + ), + finish_reason="stop", + ) + ], + usage=converted_usage, + system_fingerprint=response_dict.get("safety_identifier"), + ) + + async def stream_response_to_chat( + self, response_stream: AsyncIterator[bytes] + ) -> AsyncIterator[dict[str, Any]]: + """Convert Response API SSE stream to Chat Completions format. + + Args: + response_stream: Async iterator of SSE bytes from Response API + + Yields: + Chat Completions formatted streaming chunks + """ + stream_id = f"chatcmpl_{uuid.uuid4().hex[:29]}" + created = int(time.time()) + accumulated_content = "" + buffer = "" + + logger.debug("response_adapter_stream_started", stream_id=stream_id) + raw_chunk_count = 0 + event_count = 0 + + async for chunk in response_stream: + raw_chunk_count += 1 + chunk_size = len(chunk) + logger.debug( + "response_adapter_raw_chunk_received", + chunk_number=raw_chunk_count, + chunk_size=chunk_size, + buffer_size_before=len(buffer), + ) + + # Add chunk to buffer + buffer += chunk.decode("utf-8") + + # Process complete SSE events (separated by double newlines) + while "\n\n" in buffer: + event_str, buffer = buffer.split("\n\n", 1) + event_count += 1 + + # Parse the SSE event + event_type = None + event_data = None + + for line in event_str.strip().split("\n"): + if not line: + continue + + if line.startswith("event:"): + event_type = line[6:].strip() + elif line.startswith("data:"): + data_str = line[5:].strip() + if data_str == "[DONE]": + logger.debug( + "response_adapter_done_marker_found", + event_number=event_count, + ) + continue + try: + event_data = json.loads(data_str) + except json.JSONDecodeError: + logger.debug( + "response_adapter_sse_parse_failed", + data_preview=data_str[:100], + event_number=event_count, + ) + continue + + # Process complete events + if event_type and event_data: + logger.debug( + "response_adapter_sse_event_parsed", + event_type=event_type, + event_number=event_count, + has_output="output" in str(event_data), + ) + if event_type in [ + "response.output.delta", + "response.output_text.delta", + ]: + # Extract delta content + delta_content = "" + + # Handle different event structures + if event_type == "response.output_text.delta": + # Direct text delta event + delta_content = event_data.get("delta", "") + else: + # Standard output delta with nested structure + output = event_data.get("output", []) + if output: + for output_item in output: + if output_item.get("type") == "message": + content_blocks = output_item.get("content", []) + for block in content_blocks: + if block.get("type") in [ + "output_text", + "text", + ]: + delta_content += block.get("text", "") + + if delta_content: + accumulated_content += delta_content + + logger.debug( + "response_adapter_yielding_content", + content_length=len(delta_content), + accumulated_length=len(accumulated_content), + ) + + # Create Chat Completions streaming chunk + yield { + "id": stream_id, + "object": "chat.completion.chunk", + "created": created, + "model": event_data.get("model", "gpt-5"), + "choices": [ + { + "index": 0, + "delta": {"content": delta_content}, + "finish_reason": None, + } + ], + } + + elif event_type == "response.completed": + # Final chunk with usage info + response = event_data.get("response", {}) + usage = response.get("usage") + + logger.debug( + "response_adapter_stream_completed", + total_content_length=len(accumulated_content), + has_usage=usage is not None, + ) + + chunk_data = { + "id": stream_id, + "object": "chat.completion.chunk", + "created": created, + "model": response.get("model", "gpt-5"), + "choices": [ + {"index": 0, "delta": {}, "finish_reason": "stop"} + ], + } + + # Add usage if available + converted_usage = self._convert_usage(usage) if usage else None + if converted_usage: + chunk_data["usage"] = converted_usage.model_dump() + + yield chunk_data + + logger.debug( + "response_adapter_stream_finished", + stream_id=stream_id, + total_raw_chunks=raw_chunk_count, + total_events=event_count, + final_buffer_size=len(buffer), + ) + + def _convert_usage( + self, response_usage: dict[str, Any] | None + ) -> OpenAIUsage | None: + """Convert Response API usage to Chat Completions format.""" + if not response_usage: + return None + + return OpenAIUsage( + prompt_tokens=response_usage.get("input_tokens", 0), + completion_tokens=response_usage.get("output_tokens", 0), + total_tokens=response_usage.get("total_tokens", 0), + ) + + def _get_default_codex_instructions(self) -> str: + """Get default Codex CLI instructions.""" + return ( + "You are a coding agent running in the Codex CLI, a terminal-based coding assistant. " + "Codex CLI is an open source project led by OpenAI. You are expected to be precise, safe, and helpful.\n\n" + "Your capabilities:\n" + "- Receive user prompts and other context provided by the harness, such as files in the workspace.\n" + "- Communicate with the user by streaming thinking & responses, and by making & updating plans.\n" + "- Emit function calls to run terminal commands and apply patches. Depending on how this specific run is configured, " + "you can request that these function calls be escalated to the user for approval before running. " + 'More on this in the "Sandbox and approvals" section.\n\n' + "Within this context, Codex refers to the open-source agentic coding interface " + "(not the old Codex language model built by OpenAI)." + ) diff --git a/ccproxy/adapters/openai/response_models.py b/ccproxy/adapters/openai/response_models.py new file mode 100644 index 00000000..b8009df6 --- /dev/null +++ b/ccproxy/adapters/openai/response_models.py @@ -0,0 +1,178 @@ +"""OpenAI Response API models. + +This module contains data models for OpenAI's Response API format +used by Codex/ChatGPT backend. +""" + +from __future__ import annotations + +from typing import Any, Literal + +from pydantic import BaseModel + + +# Request Models + + +class ResponseMessageContent(BaseModel): + """Content block in a Response API message.""" + + type: Literal["input_text", "output_text"] + text: str + + +class ResponseMessage(BaseModel): + """Message in Response API format.""" + + type: Literal["message"] + id: str | None = None + role: Literal["user", "assistant", "system"] + content: list[ResponseMessageContent] + + +class ResponseReasoning(BaseModel): + """Reasoning configuration for Response API.""" + + effort: Literal["low", "medium", "high"] = "medium" + summary: Literal["auto", "none"] | None = "auto" + + +class ResponseRequest(BaseModel): + """OpenAI Response API request format.""" + + model: str + instructions: str | None = None + input: list[ResponseMessage] + stream: bool = True + tool_choice: Literal["auto", "none", "required"] | str = "auto" + parallel_tool_calls: bool = False + reasoning: ResponseReasoning | None = None + store: bool = False + include: list[str] | None = None + prompt_cache_key: str | None = None + # Note: The following OpenAI parameters are not supported by Response API (Codex backend): + # temperature, max_output_tokens, top_p, frequency_penalty, presence_penalty, metadata + # If included, they'll cause "Unsupported parameter" errors + + +# Response Models + + +class ResponseOutput(BaseModel): + """Output content in Response API.""" + + id: str + type: Literal["message"] + status: Literal["completed", "in_progress"] + content: list[ResponseMessageContent] + role: Literal["assistant"] + + +class ResponseUsage(BaseModel): + """Usage statistics in Response API.""" + + input_tokens: int + output_tokens: int + total_tokens: int + input_tokens_details: dict[str, Any] | None = None + output_tokens_details: dict[str, Any] | None = None + + +class ResponseReasoningContent(BaseModel): + """Reasoning content in response.""" + + effort: Literal["low", "medium", "high"] + summary: str | None = None + encrypted_content: str | None = None + + +class ResponseData(BaseModel): + """Complete response data structure.""" + + id: str + object: Literal["response"] + created_at: int + status: Literal["completed", "failed", "cancelled"] + background: bool = False + error: dict[str, Any] | None = None + incomplete_details: dict[str, Any] | None = None + instructions: str | None = None + max_output_tokens: int | None = None + model: str + output: list[ResponseOutput] + parallel_tool_calls: bool = False + previous_response_id: str | None = None + prompt_cache_key: str | None = None + reasoning: ResponseReasoningContent | None = None + safety_identifier: str | None = None + service_tier: str | None = None + store: bool = False + temperature: float | None = None + text: dict[str, Any] | None = None + tool_choice: str | None = None + tools: list[dict[str, Any]] | None = None + top_logprobs: int | None = None + top_p: float | None = None + truncation: str | None = None + usage: ResponseUsage | None = None + user: str | None = None + metadata: dict[str, Any] | None = None + + +class ResponseCompleted(BaseModel): + """Complete response from Response API.""" + + type: Literal["response.completed"] + sequence_number: int + response: ResponseData + + +# Streaming Models + + +class StreamingDelta(BaseModel): + """Delta content in streaming response.""" + + content: str | None = None + role: Literal["assistant"] | None = None + reasoning_content: str | None = None + output: list[dict[str, Any]] | None = None + + +class StreamingChoice(BaseModel): + """Choice in streaming response.""" + + index: int + delta: StreamingDelta + finish_reason: Literal["stop", "length", "tool_calls", "content_filter"] | None = ( + None + ) + + +class StreamingChunk(BaseModel): + """Streaming chunk from Response API.""" + + id: str + object: Literal["response.chunk", "chat.completion.chunk"] + created: int + model: str + choices: list[StreamingChoice] + usage: ResponseUsage | None = None + system_fingerprint: str | None = None + + +class StreamingEvent(BaseModel): + """Server-sent event wrapper for streaming.""" + + event: ( + Literal[ + "response.created", + "response.output.started", + "response.output.delta", + "response.output.completed", + "response.completed", + "response.failed", + ] + | None + ) = None + data: dict[str, Any] | str diff --git a/ccproxy/api/app.py b/ccproxy/api/app.py index 30422433..8f29feab 100644 --- a/ccproxy/api/app.py +++ b/ccproxy/api/app.py @@ -18,6 +18,7 @@ from ccproxy.api.middleware.request_id import RequestIDMiddleware from ccproxy.api.middleware.server_header import ServerHeaderMiddleware from ccproxy.api.routes.claude import router as claude_router +from ccproxy.api.routes.codex import router as codex_router from ccproxy.api.routes.health import router as health_router from ccproxy.api.routes.mcp import setup_mcp from ccproxy.api.routes.metrics import ( @@ -33,9 +34,11 @@ from ccproxy.utils.models_provider import get_models_list from ccproxy.utils.startup_helpers import ( check_claude_cli_startup, + check_codex_cli_startup, flush_streaming_batches_shutdown, initialize_claude_detection_startup, initialize_claude_sdk_startup, + initialize_codex_detection_startup, initialize_log_storage_shutdown, initialize_log_storage_startup, initialize_permission_service_startup, @@ -78,11 +81,21 @@ class ShutdownComponent(TypedDict): "startup": check_claude_cli_startup, "shutdown": None, # Detection only, no cleanup needed }, + { + "name": "Codex CLI", + "startup": check_codex_cli_startup, + "shutdown": None, # Detection only, no cleanup needed + }, { "name": "Claude Detection", "startup": initialize_claude_detection_startup, "shutdown": None, # No cleanup needed }, + { + "name": "Codex Detection", + "startup": initialize_codex_detection_startup, + "shutdown": None, # No cleanup needed + }, { "name": "Claude SDK", "startup": initialize_claude_sdk_startup, @@ -282,6 +295,9 @@ def create_app(settings: Settings | None = None) -> FastAPI: app.include_router(oauth_router, prefix="/oauth", tags=["oauth"]) + # Codex routes for OpenAI integration + app.include_router(codex_router, tags=["codex"]) + # New /sdk/ routes for Claude SDK endpoints app.include_router(claude_router, prefix="/sdk", tags=["claude-sdk"]) diff --git a/ccproxy/api/routes/codex.py b/ccproxy/api/routes/codex.py new file mode 100644 index 00000000..069a1c4a --- /dev/null +++ b/ccproxy/api/routes/codex.py @@ -0,0 +1,1231 @@ +"""OpenAI Codex API routes.""" + +import json +import uuid +from collections.abc import AsyncIterator + +import httpx +import structlog +from fastapi import APIRouter, Depends, HTTPException, Request +from fastapi.responses import StreamingResponse +from starlette.responses import Response + +from ccproxy.adapters.openai.models import ( + OpenAIChatCompletionRequest, + OpenAIChatCompletionResponse, +) +from ccproxy.adapters.openai.response_adapter import ResponseAdapter +from ccproxy.api.dependencies import ProxyServiceDep +from ccproxy.auth.openai import OpenAITokenManager +from ccproxy.config.settings import Settings, get_settings +from ccproxy.core.errors import AuthenticationError, ProxyError +from ccproxy.observability.streaming_response import StreamingResponseWithLogging + + +logger = structlog.get_logger(__name__) + +# Create router +router = APIRouter(prefix="/codex", tags=["codex"]) + + +def get_token_manager() -> OpenAITokenManager: + """Get OpenAI token manager dependency.""" + return OpenAITokenManager() + + +def resolve_session_id( + path_session: str | None = None, + header_session: str | None = None, +) -> str: + """Resolve session ID with priority: path > header > generated.""" + return path_session or header_session or str(uuid.uuid4()) + + +async def check_codex_enabled(settings: Settings = Depends(get_settings)) -> None: + """Check if Codex is enabled.""" + if not settings.codex.enabled: + raise HTTPException( + status_code=503, detail="OpenAI Codex provider is not enabled" + ) + + +@router.post("/responses", response_model=None) +async def codex_responses( + request: Request, + proxy_service: ProxyServiceDep, + settings: Settings = Depends(get_settings), + token_manager: OpenAITokenManager = Depends(get_token_manager), + _: None = Depends(check_codex_enabled), +) -> StreamingResponse | Response: + """Create completion with auto-generated session_id. + + This endpoint creates a new completion request with an automatically + generated session_id. Each request gets a unique session. + """ + # Get session_id from header if provided + header_session_id = request.headers.get("session_id") + session_id = resolve_session_id(header_session=header_session_id) + + # Get and validate access token + try: + access_token = await token_manager.get_valid_token() + if not access_token: + raise HTTPException( + status_code=401, + detail="No valid OpenAI credentials found. Please authenticate first.", + ) + except Exception as e: + logger.error("Failed to get OpenAI access token", error=str(e)) + raise HTTPException( + status_code=401, detail="Failed to retrieve valid credentials" + ) from e + + try: + # Handle the Codex request + response = await proxy_service.handle_codex_request( + method="POST", + path="/responses", + session_id=session_id, + access_token=access_token, + request=request, + settings=settings, + ) + return response + except AuthenticationError as e: + raise HTTPException(status_code=401, detail=str(e)) from e + except ProxyError as e: + raise HTTPException(status_code=502, detail=str(e)) from e + except Exception as e: + logger.error("Unexpected error in codex_responses", error=str(e)) + raise HTTPException(status_code=500, detail="Internal server error") from e + + +@router.post("/{session_id}/responses", response_model=None) +async def codex_responses_with_session( + session_id: str, + request: Request, + proxy_service: ProxyServiceDep, + settings: Settings = Depends(get_settings), + token_manager: OpenAITokenManager = Depends(get_token_manager), + _: None = Depends(check_codex_enabled), +) -> StreamingResponse | Response: + """Create completion with specific session_id. + + This endpoint creates a completion request using the provided session_id + from the URL path. This allows for session-specific conversations. + """ + # Get and validate access token + try: + access_token = await token_manager.get_valid_token() + if not access_token: + raise HTTPException( + status_code=401, + detail="No valid OpenAI credentials found. Please authenticate first.", + ) + except Exception as e: + logger.error("Failed to get OpenAI access token", error=str(e)) + raise HTTPException( + status_code=401, detail="Failed to retrieve valid credentials" + ) from e + + try: + # Handle the Codex request with specific session_id + response = await proxy_service.handle_codex_request( + method="POST", + path=f"/{session_id}/responses", + session_id=session_id, + access_token=access_token, + request=request, + settings=settings, + ) + return response + except AuthenticationError as e: + raise HTTPException(status_code=401, detail=str(e)) from e + except ProxyError as e: + raise HTTPException(status_code=502, detail=str(e)) from e + except Exception as e: + logger.error("Unexpected error in codex_responses_with_session", error=str(e)) + raise HTTPException(status_code=500, detail="Internal server error") from e + + +@router.post("/chat/completions", response_model=None) +async def codex_chat_completions( + openai_request: OpenAIChatCompletionRequest, + request: Request, + proxy_service: ProxyServiceDep, + settings: Settings = Depends(get_settings), + token_manager: OpenAITokenManager = Depends(get_token_manager), + _: None = Depends(check_codex_enabled), +) -> StreamingResponse | OpenAIChatCompletionResponse: + """OpenAI-compatible chat completions endpoint for Codex. + + This endpoint accepts OpenAI chat/completions format and converts it + to OpenAI Response API format before forwarding to the ChatGPT backend. + """ + # Get session_id from header if provided, otherwise generate + header_session_id = request.headers.get("session_id") + session_id = resolve_session_id(header_session=header_session_id) + + # Get and validate access token + try: + access_token = await token_manager.get_valid_token() + if not access_token: + raise HTTPException( + status_code=401, + detail="No valid OpenAI credentials found. Please authenticate first.", + ) + except Exception as e: + logger.error("Failed to get OpenAI access token", error=str(e)) + raise HTTPException( + status_code=401, detail="Failed to retrieve valid credentials" + ) from e + + try: + # Create adapter for format conversion + adapter = ResponseAdapter() + + # Convert OpenAI Chat Completions format to Response API format + response_request = adapter.chat_to_response_request(openai_request) + + # Convert the transformed request to bytes + codex_body = response_request.model_dump_json().encode("utf-8") + + # Get request context from middleware + request_context = getattr(request.state, "context", None) + + # Create a mock request object with the converted body + class MockRequest: + def __init__(self, original_request: Request, new_body: bytes) -> None: + self.method = original_request.method + self.url = original_request.url + self.headers = dict(original_request.headers) + self.headers["content-length"] = str(len(new_body)) + self.state = original_request.state + self._body = new_body + + async def body(self) -> bytes: + return self._body + + mock_request = MockRequest(request, codex_body) + + # For streaming requests, handle the transformation directly + if openai_request.stream: + # Make the request directly to get the raw streaming response + from ccproxy.core.codex_transformers import CodexRequestTransformer + + # Transform the request + transformer = CodexRequestTransformer() + transformed_request = await transformer.transform_codex_request( + method="POST", + path="/responses", + headers=dict(request.headers), + body=codex_body, + access_token=access_token, + session_id=session_id, + account_id="unknown", # Will be extracted from token if needed + codex_detection_data=getattr( + proxy_service.app_state, "codex_detection_data", None + ) + if proxy_service.app_state + else None, + target_base_url=settings.codex.base_url, + ) + + # Convert Response API SSE stream to Chat Completions format + response_headers = {} + + async def stream_codex_response() -> AsyncIterator[bytes]: + """Stream and convert Response API to Chat Completions format.""" + async with ( + httpx.AsyncClient(timeout=240.0) as client, + client.stream( + method="POST", + url=transformed_request["url"], + headers=transformed_request["headers"], + content=transformed_request["body"], + ) as response, + ): + # Check if we got a streaming response + content_type = response.headers.get("content-type", "") + transfer_encoding = response.headers.get("transfer-encoding", "") + + # Capture response headers for forwarding + nonlocal response_headers + response_headers = dict(response.headers) + + logger.debug( + "codex_chat_response_headers", + status_code=response.status_code, + content_type=content_type, + transfer_encoding=transfer_encoding, + headers=response_headers, + url=str(response.url), + ) + + # Check for error response first + if response.status_code >= 400: + # Handle error response - collect the response body + error_body = b"" + async for chunk in response.aiter_bytes(): + error_body += chunk + + # Try to parse error message + error_message = "Request failed" + if error_body: + try: + error_data = json.loads(error_body.decode("utf-8")) + if "detail" in error_data: + error_message = error_data["detail"] + elif "error" in error_data and isinstance( + error_data["error"], dict + ): + error_message = error_data["error"].get( + "message", "Request failed" + ) + except json.JSONDecodeError: + pass + + logger.warning( + "codex_chat_error_response", + status_code=response.status_code, + error_message=error_message, + ) + + # Return error in streaming format + error_response = { + "error": { + "message": error_message, + "type": "invalid_request_error", + "code": response.status_code, + } + } + yield f"data: {json.dumps(error_response)}\n\n".encode() + return + + # Check if this is a streaming response + # The backend may return chunked transfer encoding without content-type + is_streaming = "text/event-stream" in content_type or ( + transfer_encoding == "chunked" and not content_type + ) + + if is_streaming: + logger.debug( + "codex_stream_conversion_started", + session_id=session_id, + request_id=getattr(request.state, "request_id", "unknown"), + ) + + chunk_count = 0 + total_bytes = 0 + stream_id = f"chatcmpl_{uuid.uuid4().hex[:29]}" + created = int(time.time()) + + # Process SSE events directly without buffering + line_count = 0 + first_chunk_sent = False + thinking_block_active = False + try: + async for line in response.aiter_lines(): + line_count += 1 + logger.debug( + "codex_stream_line", + line_number=line_count, + line_preview=line[:100] if line else "(empty)", + ) + + # Skip empty lines + if not line or line.strip() == "": + continue + + if line.startswith("data:"): + data_str = line[5:].strip() + if data_str == "[DONE]": + continue + + try: + event_data = json.loads(data_str) + event_type = event_data.get("type") + + # Send initial role message if this is the first chunk + if not first_chunk_sent: + # Send an initial chunk to indicate streaming has started + initial_chunk = { + "id": stream_id, + "object": "chat.completion.chunk", + "created": created, + "model": "gpt-5", + "choices": [ + { + "index": 0, + "delta": {"role": "assistant"}, + "finish_reason": None, + } + ], + } + yield f"data: {json.dumps(initial_chunk)}\n\n".encode() + first_chunk_sent = True + chunk_count += 1 + + logger.debug( + "codex_stream_initial_chunk_sent", + event_type=event_type, + ) + + # Handle reasoning blocks based on official OpenAI Response API + if event_type == "response.output_item.added": + # Check if this is a reasoning block + item = event_data.get("item", {}) + item_type = item.get("type") + + if ( + item_type == "reasoning" + and not thinking_block_active + ): + # Only send opening tag if not already in a thinking block + thinking_block_active = True + + logger.debug( + "codex_reasoning_block_started", + item_type=item_type, + event_type=event_type, + ) + + # Send opening reasoning tag (no signature in official API) + openai_chunk = { + "id": stream_id, + "object": "chat.completion.chunk", + "created": created, + "model": "gpt-5", + "choices": [ + { + "index": 0, + "delta": { + "content": "" + }, + "finish_reason": None, + } + ], + } + yield f"data: {json.dumps(openai_chunk)}\n\n".encode() + chunk_count += 1 + + # Handle content part deltas - various content types from API + elif ( + event_type == "response.content_part.delta" + ): + delta = event_data.get("delta", {}) + delta_type = delta.get("type") + + if ( + delta_type == "text" + and not thinking_block_active + ): + # Regular text content + text_content = delta.get("text", "") + if text_content: + openai_chunk = { + "id": stream_id, + "object": "chat.completion.chunk", + "created": created, + "model": "gpt-5", + "choices": [ + { + "index": 0, + "delta": { + "content": text_content + }, + "finish_reason": None, + } + ], + } + yield f"data: {json.dumps(openai_chunk)}\n\n".encode() + chunk_count += 1 + + elif ( + delta_type == "reasoning" + and thinking_block_active + ): + # Reasoning content within reasoning block + reasoning_content = delta.get( + "reasoning", "" + ) + if reasoning_content: + openai_chunk = { + "id": stream_id, + "object": "chat.completion.chunk", + "created": created, + "model": "gpt-5", + "choices": [ + { + "index": 0, + "delta": { + "content": reasoning_content + }, + "finish_reason": None, + } + ], + } + yield f"data: {json.dumps(openai_chunk)}\n\n".encode() + chunk_count += 1 + + # Handle reasoning summary text - the actual reasoning content + elif ( + event_type + == "response.reasoning_summary_text.delta" + and thinking_block_active + ): + # Extract reasoning text content from delta field + reasoning_text = event_data.get("delta", "") + + if reasoning_text: + chunk_count += 1 + openai_chunk = { + "id": stream_id, + "object": "chat.completion.chunk", + "created": created, + "model": "gpt-5", + "choices": [ + { + "index": 0, + "delta": { + "content": reasoning_text + }, + "finish_reason": None, + } + ], + } + yield f"data: {json.dumps(openai_chunk)}\n\n".encode() + + # Handle reasoning block completion - official API + elif ( + event_type == "response.output_item.done" + and thinking_block_active + ): + # Check if this is the end of a reasoning block + item = event_data.get("item", {}) + item_type = item.get("type") + + if item_type == "reasoning": + thinking_block_active = False + + # Send closing reasoning tag + openai_chunk = { + "id": stream_id, + "object": "chat.completion.chunk", + "created": created, + "model": "gpt-5", + "choices": [ + { + "index": 0, + "delta": { + "content": "\n" + }, + "finish_reason": None, + } + ], + } + yield f"data: {json.dumps(openai_chunk)}\n\n".encode() + chunk_count += 1 + + logger.debug( + "codex_reasoning_block_ended", + item_type=item_type, + event_type=event_type, + ) + + # Convert Response API events to OpenAI format + elif event_type == "response.output_text.delta": + # Direct text delta event (only if not in thinking block) + if not thinking_block_active: + delta_content = event_data.get( + "delta", "" + ) + if delta_content: + chunk_count += 1 + openai_chunk = { + "id": stream_id, + "object": "chat.completion.chunk", + "created": created, + "model": event_data.get( + "model", "gpt-5" + ), + "choices": [ + { + "index": 0, + "delta": { + "content": delta_content + }, + "finish_reason": None, + } + ], + } + chunk_data = f"data: {json.dumps(openai_chunk)}\n\n".encode() + total_bytes += len(chunk_data) + + logger.debug( + "codex_stream_chunk_converted", + chunk_number=chunk_count, + chunk_size=len(chunk_data), + event_type=event_type, + content_length=len( + delta_content + ), + ) + + yield chunk_data + + elif event_type == "response.output.delta": + # Standard output delta with nested structure + output = event_data.get("output", []) + for output_item in output: + if output_item.get("type") == "message": + content_blocks = output_item.get( + "content", [] + ) + for block in content_blocks: + # Check if this is thinking content + if ( + block.get("type") + in [ + "thinking", + "reasoning", + "internal_monologue", + ] + and thinking_block_active + ): + thinking_content = ( + block.get("text", "") + ) + if thinking_content: + chunk_count += 1 + openai_chunk = { + "id": stream_id, + "object": "chat.completion.chunk", + "created": created, + "model": "gpt-5", + "choices": [ + { + "index": 0, + "delta": { + "content": thinking_content + }, + "finish_reason": None, + } + ], + } + yield f"data: {json.dumps(openai_chunk)}\n\n".encode() + elif ( + block.get("type") + in [ + "output_text", + "text", + ] + and not thinking_block_active + ): + delta_content = block.get( + "text", "" + ) + if delta_content: + chunk_count += 1 + openai_chunk = { + "id": stream_id, + "object": "chat.completion.chunk", + "created": created, + "model": event_data.get( + "model", "gpt-5" + ), + "choices": [ + { + "index": 0, + "delta": { + "content": delta_content + }, + "finish_reason": None, + } + ], + } + chunk_data = f"data: {json.dumps(openai_chunk)}\n\n".encode() + total_bytes += len( + chunk_data + ) + + logger.debug( + "codex_stream_chunk_converted", + chunk_number=chunk_count, + chunk_size=len( + chunk_data + ), + event_type=event_type, + content_length=len( + delta_content + ), + ) + + yield chunk_data + + # Handle additional official API event types + elif ( + event_type + == "response.function_call_arguments.delta" + ): + # Function call arguments streaming - official API + if not thinking_block_active: + arguments = event_data.get( + "arguments", "" + ) + if arguments: + chunk_count += 1 + openai_chunk = { + "id": stream_id, + "object": "chat.completion.chunk", + "created": created, + "model": "gpt-5", + "choices": [ + { + "index": 0, + "delta": { + "content": arguments + }, + "finish_reason": None, + } + ], + } + yield f"data: {json.dumps(openai_chunk)}\n\n".encode() + + elif ( + event_type + == "response.audio_transcript.delta" + ): + # Audio transcript streaming - official API + if not thinking_block_active: + transcript = event_data.get( + "transcript", "" + ) + if transcript: + chunk_count += 1 + openai_chunk = { + "id": stream_id, + "object": "chat.completion.chunk", + "created": created, + "model": "gpt-5", + "choices": [ + { + "index": 0, + "delta": { + "content": f"[Audio: {transcript}]" + }, + "finish_reason": None, + } + ], + } + yield f"data: {json.dumps(openai_chunk)}\n\n".encode() + + elif ( + event_type + == "response.tool_calls.function.name" + ): + # Tool function name - official API + if not thinking_block_active: + function_name = event_data.get( + "name", "" + ) + if function_name: + chunk_count += 1 + openai_chunk = { + "id": stream_id, + "object": "chat.completion.chunk", + "created": created, + "model": "gpt-5", + "choices": [ + { + "index": 0, + "delta": { + "content": f"[Function: {function_name}]" + }, + "finish_reason": None, + } + ], + } + yield f"data: {json.dumps(openai_chunk)}\n\n".encode() + + elif event_type == "response.completed": + # Final chunk with usage info + response_obj = event_data.get( + "response", {} + ) + usage = response_obj.get("usage") + + openai_chunk = { + "id": stream_id, + "object": "chat.completion.chunk", + "created": created, + "model": response_obj.get( + "model", "gpt-5" + ), + "choices": [ + { + "index": 0, + "delta": {}, + "finish_reason": "stop", + } + ], + } + + if usage: + openai_chunk["usage"] = { + "prompt_tokens": usage.get( + "input_tokens", 0 + ), + "completion_tokens": usage.get( + "output_tokens", 0 + ), + "total_tokens": usage.get( + "total_tokens", 0 + ), + } + + chunk_data = f"data: {json.dumps(openai_chunk)}\n\n".encode() + yield chunk_data + + logger.debug( + "codex_stream_completed", + total_chunks=chunk_count, + total_bytes=total_bytes, + ) + + except json.JSONDecodeError as e: + logger.debug( + "codex_sse_parse_failed", + data_preview=data_str[:100], + error=str(e), + ) + continue + + except Exception as e: + logger.error( + "codex_stream_error", + error=str(e), + line_count=line_count, + ) + raise + + # Send final [DONE] message + logger.debug( + "codex_stream_sending_done", + total_chunks=chunk_count, + total_bytes=total_bytes, + ) + yield b"data: [DONE]\n\n" + else: + # Backend didn't return streaming or returned unexpected format + # When using client.stream(), we need to collect the response differently + chunks = [] + async for chunk in response.aiter_bytes(): + chunks.append(chunk) + + response_body = b"".join(chunks) + + logger.debug( + "codex_chat_non_streaming_response", + body_length=len(response_body), + body_preview=response_body[:200].decode( + "utf-8", errors="replace" + ) + if response_body + else "empty", + ) + + if response_body: + # Check if it's actually SSE data that we missed + body_str = response_body.decode("utf-8") + if body_str.startswith("event:") or body_str.startswith( + "data:" + ): + # It's SSE data, try to extract the final JSON + logger.warning( + "Backend returned SSE data but content-type was not text/event-stream" + ) + lines = body_str.strip().split("\n") + for line in reversed(lines): + if line.startswith("data:") and not line.endswith( + "[DONE]" + ): + try: + json_str = line[5:].strip() + response_data = json.loads(json_str) + if "response" in response_data: + response_data = response_data[ + "response" + ] + # Convert to OpenAI format and yield as a single chunk + openai_response = ( + adapter.response_to_chat_completion( + response_data + ) + ) + yield f"data: {openai_response.model_dump_json()}\n\n".encode() + yield b"data: [DONE]\n\n" + return + except json.JSONDecodeError: + continue + # Couldn't parse SSE data - yield error as SSE event + error_response = { + "error": { + "message": "Failed to parse SSE response data", + "type": "invalid_response_error", + "code": 502, + } + } + yield f"data: {json.dumps(error_response)}\n\n".encode() + yield b"data: [DONE]\n\n" + return + else: + # Try to parse as regular JSON + try: + response_data = json.loads(body_str) + # Convert to Chat Completions format and yield as single chunk + openai_response = ( + adapter.response_to_chat_completion( + response_data + ) + ) + yield f"data: {openai_response.model_dump_json()}\n\n".encode() + yield b"data: [DONE]\n\n" + return + except json.JSONDecodeError as e: + logger.error( + "Failed to parse non-streaming response", + error=str(e), + body_preview=body_str[:500], + ) + error_response = { + "error": { + "message": "Invalid JSON response from backend", + "type": "invalid_response_error", + "code": 502, + } + } + yield f"data: {json.dumps(error_response)}\n\n".encode() + yield b"data: [DONE]\n\n" + return + else: + # Empty response - yield error + error_response = { + "error": { + "message": "Backend returned empty response", + "type": "empty_response_error", + "code": 502, + } + } + yield f"data: {json.dumps(error_response)}\n\n".encode() + yield b"data: [DONE]\n\n" + return + + # Execute the generator first to capture headers + generator_chunks = [] + async for chunk in stream_codex_response(): + generator_chunks.append(chunk) + + # Forward upstream headers but filter out incompatible ones for streaming + streaming_headers = dict(response_headers) + # Remove headers that conflict with streaming responses + streaming_headers.pop("content-length", None) + streaming_headers.pop("content-encoding", None) + streaming_headers.pop("date", None) + # Set streaming-specific headers + streaming_headers.update( + { + "content-type": "text/event-stream", + "Cache-Control": "no-cache", + "Connection": "keep-alive", + } + ) + + # Replay the collected chunks + async def replay_stream() -> AsyncIterator[bytes]: + for chunk in generator_chunks: + yield chunk + + # Return streaming response with proper headers - handle missing request_context + from ccproxy.observability.context import RequestContext + + # Create a minimal request context if none exists + if request_context is None: + import time + import uuid + + request_context = RequestContext( + request_id=str(uuid.uuid4()), + start_time=time.perf_counter(), + logger=logger, + ) + + return StreamingResponseWithLogging( + content=replay_stream(), + request_context=request_context, + metrics=getattr(proxy_service, "metrics", None), + status_code=200, + media_type="text/event-stream", + headers=streaming_headers, + ) + else: + # Handle non-streaming request using the proxy service + # Cast MockRequest to Request to satisfy type checker + mock_request_typed: Request = mock_request # type: ignore[assignment] + response = await proxy_service.handle_codex_request( + method="POST", + path="/responses", + session_id=session_id, + access_token=access_token, + request=mock_request_typed, + settings=settings, + ) + + # Check if this is a streaming response (shouldn't happen for non-streaming requests) + is_streaming_response = isinstance(response, StreamingResponse) + + if is_streaming_response and not openai_request.stream: + # User requested non-streaming but backend returned streaming + # Consume the stream and convert to non-streaming response + accumulated_content = "" + final_response = None + + error_response = None + accumulated_chunks = "" + + async for chunk in response.body_iterator: # type: ignore + chunk_str = chunk.decode("utf-8") + accumulated_chunks += chunk_str + + # The Response API sends SSE events, but errors might be plain JSON + lines = chunk_str.strip().split("\n") + for line in lines: + if line.startswith("data:") and "[DONE]" not in line: + data_str = line[5:].strip() + try: + event_data = json.loads(data_str) + # Look for the completed response + if event_data.get("type") == "response.completed": + final_response = event_data + # Also check if this is a direct error response (not SSE format) + elif ( + "detail" in event_data and "type" not in event_data + ): + error_response = event_data + except json.JSONDecodeError: + continue + + # If we didn't find SSE events, try parsing the entire accumulated content as JSON + if ( + not final_response + and not error_response + and accumulated_chunks.strip() + ): + try: + # Try to parse the entire content as JSON (for non-SSE error responses) + json_response = json.loads(accumulated_chunks.strip()) + if ( + "detail" in json_response + or "error" in json_response + or "message" in json_response + ): + error_response = json_response + else: + # Might be a valid response without SSE formatting + final_response = {"response": json_response} + except json.JSONDecodeError: + # Not valid JSON either + pass + + if final_response: + # Convert to Chat Completions format + return adapter.response_to_chat_completion(final_response) + elif error_response: + # Handle error response + error_message = "Request failed" + if "detail" in error_response: + error_message = error_response["detail"] + elif "error" in error_response: + if isinstance(error_response["error"], dict): + error_message = error_response["error"].get( + "message", "Request failed" + ) + else: + error_message = str(error_response["error"]) + elif "message" in error_response: + error_message = error_response["message"] + + # Log the error for debugging + logger.error( + "codex_streaming_error_response", + error_data=error_response, + error_message=error_message, + ) + + raise HTTPException(status_code=400, detail=error_message) + else: + raise HTTPException( + status_code=502, detail="Failed to parse streaming response" + ) + else: + # Non-streaming response - parse and convert + if isinstance(response, Response): + # Check if this is an error response + if response.status_code >= 400: + # Return the error response as-is + error_body = response.body + if error_body: + try: + # Handle bytes/memoryview union + error_body_bytes = ( + bytes(error_body) + if isinstance(error_body, memoryview) + else error_body + ) + error_data = json.loads( + error_body_bytes.decode("utf-8") + ) + # Log the actual error from backend + logger.error( + "codex_backend_error", + status_code=response.status_code, + error_data=error_data, + ) + # Pass through the error from backend + # Handle different error formats from backend + error_message = "Request failed" + if "detail" in error_data: + error_message = error_data["detail"] + elif "error" in error_data: + if isinstance(error_data["error"], dict): + error_message = error_data["error"].get( + "message", "Request failed" + ) + else: + error_message = str(error_data["error"]) + elif "message" in error_data: + error_message = error_data["message"] + + raise HTTPException( + status_code=response.status_code, + detail=error_message, + ) + except (json.JSONDecodeError, UnicodeDecodeError): + # Handle bytes/memoryview union for logging + error_body_bytes = ( + bytes(error_body) + if isinstance(error_body, memoryview) + else error_body + ) + logger.error( + "codex_backend_error_parse_failed", + status_code=response.status_code, + body=error_body_bytes[:500].decode( + "utf-8", errors="replace" + ), + ) + pass + raise HTTPException( + status_code=response.status_code, detail="Request failed" + ) + + # Read the response body for successful responses + response_body = response.body + if response_body: + try: + # Handle bytes/memoryview union + response_body_bytes = ( + bytes(response_body) + if isinstance(response_body, memoryview) + else response_body + ) + response_data = json.loads( + response_body_bytes.decode("utf-8") + ) + # Convert Response API format to Chat Completions format + return adapter.response_to_chat_completion(response_data) + except (json.JSONDecodeError, UnicodeDecodeError) as e: + logger.error("Failed to parse Codex response", error=str(e)) + raise HTTPException( + status_code=502, + detail="Invalid response from Codex API", + ) from e + + # If we can't convert, return error + raise HTTPException( + status_code=502, detail="Unable to process Codex response" + ) + + except HTTPException: + raise + except AuthenticationError as e: + raise HTTPException(status_code=401, detail=str(e)) from e + except ProxyError as e: + raise HTTPException(status_code=502, detail=str(e)) from e + except Exception as e: + logger.error("Unexpected error in codex_chat_completions", error=str(e)) + raise HTTPException(status_code=500, detail="Internal server error") from e + + +# NOTE: Test endpoint commented out after exploration +# Testing revealed that ChatGPT backend API only supports /responses endpoint +# and does NOT support OpenAI-style /chat/completions or other endpoints. +# See codex_endpoint_test_results.md for full findings. +# +# @router.api_route("/test/{path:path}", methods=["GET", "POST", "PUT", "DELETE"], response_model=None, include_in_schema=False) +# async def codex_test_probe( +# path: str, +# request: Request, +# proxy_service: ProxyServiceDep, +# settings: Settings = Depends(get_settings), +# token_manager: OpenAITokenManager = Depends(get_token_manager), +# _: None = Depends(check_codex_enabled), +# ) -> Response: +# """Test endpoint to probe upstream ChatGPT backend API paths. +# +# WARNING: This is a test endpoint for exploration only. +# It forwards requests to any path on the ChatGPT backend API. +# Should be removed or protected after testing. +# """ +# # Get and validate access token +# try: +# access_token = await token_manager.get_valid_token() +# if not access_token: +# raise HTTPException( +# status_code=401, +# detail="No valid OpenAI credentials found. Please authenticate first.", +# ) +# except Exception as e: +# logger.error("Failed to get OpenAI access token", error=str(e)) +# raise HTTPException( +# status_code=401, detail="Failed to retrieve valid credentials" +# ) from e +# +# # Log the test request +# logger.info(f"Testing upstream path: /{path}", method=request.method) +# +# try: +# # Use a simple session_id for testing +# session_id = "test-probe" +# +# # Handle the test request - forward to the specified path +# response = await proxy_service.handle_codex_request( +# method=request.method, +# path=f"/{path}", +# session_id=session_id, +# access_token=access_token, +# request=request, +# settings=settings, +# ) +# +# logger.info(f"Test probe response for /{path}", status_code=getattr(response, "status_code", 200)) +# return response +# except AuthenticationError as e: +# logger.warning(f"Auth error for path /{path}: {str(e)}") +# raise HTTPException(status_code=401, detail=str(e)) from e +# except ProxyError as e: +# logger.warning(f"Proxy error for path /{path}: {str(e)}") +# raise HTTPException(status_code=502, detail=str(e)) from e +# except Exception as e: +# logger.error(f"Unexpected error testing path /{path}", error=str(e)) +# raise HTTPException(status_code=500, detail=f"Error testing path: {str(e)}") from e diff --git a/ccproxy/api/routes/health.py b/ccproxy/api/routes/health.py index 91ed3460..9ef88ea4 100644 --- a/ccproxy/api/routes/health.py +++ b/ccproxy/api/routes/health.py @@ -41,6 +41,16 @@ class ClaudeCliStatus(str, Enum): ERROR = "error" +class CodexCliStatus(str, Enum): + """Codex CLI status enumeration.""" + + AVAILABLE = "available" + NOT_INSTALLED = "not_installed" + BINARY_FOUND_BUT_ERRORS = "binary_found_but_errors" + TIMEOUT = "timeout" + ERROR = "error" + + class ClaudeCliInfo(BaseModel): """Claude CLI information with structured data.""" @@ -52,8 +62,21 @@ class ClaudeCliInfo(BaseModel): return_code: str | None = None +class CodexCliInfo(BaseModel): + """Codex CLI information with structured data.""" + + status: CodexCliStatus + version: str | None = None + binary_path: str | None = None + version_output: str | None = None + error: str | None = None + return_code: str | None = None + + # Cache for Claude CLI check results _claude_cli_cache: tuple[float, tuple[str, dict[str, Any]]] | None = None +# Cache for Codex CLI check results +_codex_cli_cache: tuple[float, tuple[str, dict[str, Any]]] | None = None _cache_ttl_seconds = 300 # Cache for 5 minutes @@ -153,6 +176,11 @@ def _get_claude_cli_path() -> str | None: return shutil.which("claude") +def _get_codex_cli_path() -> str | None: + """Get Codex CLI path with caching. Returns None if not found.""" + return shutil.which("codex") + + async def check_claude_code() -> tuple[str, dict[str, Any]]: """Check Claude Code CLI installation and version by running 'claude --version'. @@ -313,6 +341,162 @@ async def get_claude_cli_info() -> ClaudeCliInfo: ) +async def check_codex_cli() -> tuple[str, dict[str, Any]]: + """Check Codex CLI installation and version by running 'codex --version'. + Results are cached for 5 minutes to avoid repeated subprocess calls. + Returns: + Tuple of (status, details) where status is 'pass'/'fail'/'warn' + Details include CLI version and binary path + """ + global _codex_cli_cache + # Check if we have a valid cached result + current_time = time.time() + if _codex_cli_cache is not None: + cache_time, cached_result = _codex_cli_cache + if current_time - cache_time < _cache_ttl_seconds: + logger.debug("codex_cli_check_cache_hit") + return cached_result + + logger.debug("codex_cli_check_cache_miss") + + # First check if codex binary exists in PATH (cached) + codex_path = _get_codex_cli_path() + if not codex_path: + result = ( + "warn", + { + "installation_status": "not_found", + "cli_status": "not_installed", + "error": "Codex CLI binary not found in PATH", + "version": None, + "binary_path": None, + }, + ) + # Cache the result + _codex_cli_cache = (current_time, result) + return result + + try: + # Run 'codex --version' to get actual version + process = await asyncio.create_subprocess_exec( + "codex", + "--version", + stdout=asyncio.subprocess.PIPE, + stderr=asyncio.subprocess.PIPE, + ) + + stdout, stderr = await process.communicate() + + if process.returncode == 0: + version_output = stdout.decode().strip() + # Extract version from output (e.g., "codex 0.21.0" -> "0.21.0") + if version_output: + import re + + # Try to find a version pattern (e.g., "0.21.0", "v1.0.0") + version_match = re.search( + r"\b(?:v)?(\d+\.\d+(?:\.\d+)?)\b", version_output + ) + if version_match: + version = version_match.group(1) + else: + # Fallback: take the last part if no version pattern found + parts = version_output.split() + version = parts[-1] if parts else "unknown" + else: + version = "unknown" + + result = ( + "pass", + { + "installation_status": "found", + "cli_status": "available", + "version": version, + "binary_path": codex_path, + "version_output": version_output, + }, + ) + # Cache the result + _codex_cli_cache = (current_time, result) + return result + else: + # Binary exists but --version failed + error_output = stderr.decode().strip() if stderr else "Unknown error" + result = ( + "warn", + { + "installation_status": "found_with_issues", + "cli_status": "binary_found_but_errors", + "error": f"'codex --version' failed: {error_output}", + "version": None, + "binary_path": codex_path, + "return_code": str(process.returncode), + }, + ) + # Cache the result + _codex_cli_cache = (current_time, result) + return result + + except TimeoutError: + result = ( + "warn", + { + "installation_status": "found_with_issues", + "cli_status": "timeout", + "error": "Timeout running 'codex --version'", + "version": None, + "binary_path": codex_path, + }, + ) + # Cache the result + _codex_cli_cache = (current_time, result) + return result + + except Exception as e: + result = ( + "fail", + { + "installation_status": "error", + "cli_status": "error", + "error": f"Unexpected error running 'codex --version': {str(e)}", + "version": None, + "binary_path": codex_path, + }, + ) + # Cache the result + _codex_cli_cache = (current_time, result) + return result + + +async def get_codex_cli_info() -> CodexCliInfo: + """Get Codex CLI information as a structured Pydantic model. + Returns: + CodexCliInfo: Structured information about Codex CLI installation and status + """ + cli_status, cli_details = await check_codex_cli() + + # Map the status to our enum values + if cli_status == "pass": + status_value = CodexCliStatus.AVAILABLE + elif cli_details.get("cli_status") == "not_installed": + status_value = CodexCliStatus.NOT_INSTALLED + elif cli_details.get("cli_status") == "binary_found_but_errors": + status_value = CodexCliStatus.BINARY_FOUND_BUT_ERRORS + elif cli_details.get("cli_status") == "timeout": + status_value = CodexCliStatus.TIMEOUT + else: + status_value = CodexCliStatus.ERROR + + return CodexCliInfo( + status=status_value, + version=cli_details.get("version"), + binary_path=cli_details.get("binary_path"), + version_output=cli_details.get("version_output"), + error=cli_details.get("error"), + return_code=cli_details.get("return_code"), + ) + + async def _check_claude_sdk() -> tuple[str, dict[str, Any]]: """Check Claude SDK installation and version. @@ -392,11 +576,17 @@ async def readiness_probe(response: Response) -> dict[str, Any]: # Check OAuth credentials, CLI, and SDK separately oauth_status, oauth_details = await _check_oauth2_credentials() cli_status, cli_details = await check_claude_code() + codex_cli_status, codex_cli_details = await check_codex_cli() sdk_status, sdk_details = await _check_claude_sdk() # Service is ready if no check returns "fail" # "warn" statuses (missing credentials/CLI/SDK) don't prevent readiness - if oauth_status == "fail" or cli_status == "fail" or sdk_status == "fail": + if ( + oauth_status == "fail" + or cli_status == "fail" + or codex_cli_status == "fail" + or sdk_status == "fail" + ): response.status_code = status.HTTP_503_SERVICE_UNAVAILABLE failed_components = [] @@ -404,6 +594,8 @@ async def readiness_probe(response: Response) -> dict[str, Any]: failed_components.append("oauth2_credentials") if cli_status == "fail": failed_components.append("claude_cli") + if codex_cli_status == "fail": + failed_components.append("codex_cli") if sdk_status == "fail": failed_components.append("claude_sdk") @@ -424,6 +616,12 @@ async def readiness_probe(response: Response) -> dict[str, Any]: "output": cli_details.get("error", "Claude CLI error"), } ], + "codex_cli": [ + { + "status": codex_cli_status, + "output": codex_cli_details.get("error", "Codex CLI error"), + } + ], "claude_sdk": [ { "status": sdk_status, @@ -450,6 +648,12 @@ async def readiness_probe(response: Response) -> dict[str, Any]: "output": f"Claude CLI: {cli_details.get('cli_status', 'unknown')}", } ], + "codex_cli": [ + { + "status": codex_cli_status, + "output": f"Codex CLI: {codex_cli_details.get('cli_status', 'unknown')}", + } + ], "claude_sdk": [ { "status": sdk_status, @@ -479,14 +683,25 @@ async def detailed_health_check(response: Response) -> dict[str, Any]: # Perform all health checks oauth_status, oauth_details = await _check_oauth2_credentials() cli_status, cli_details = await check_claude_code() + codex_cli_status, codex_cli_details = await check_codex_cli() sdk_status, sdk_details = await _check_claude_sdk() # Determine overall status - prioritize failures, then warnings overall_status = "pass" - if oauth_status == "fail" or cli_status == "fail" or sdk_status == "fail": + if ( + oauth_status == "fail" + or cli_status == "fail" + or codex_cli_status == "fail" + or sdk_status == "fail" + ): overall_status = "fail" response.status_code = status.HTTP_503_SERVICE_UNAVAILABLE - elif oauth_status == "warn" or cli_status == "warn" or sdk_status == "warn": + elif ( + oauth_status == "warn" + or cli_status == "warn" + or codex_cli_status == "warn" + or sdk_status == "warn" + ): overall_status = "warn" response.status_code = status.HTTP_200_OK @@ -519,6 +734,16 @@ async def detailed_health_check(response: Response) -> dict[str, Any]: **cli_details, } ], + "codex_cli": [ + { + "componentId": "codex-cli", + "componentType": "external_dependency", + "status": codex_cli_status, + "time": current_time, + "output": f"Codex CLI: {codex_cli_details.get('cli_status', 'unknown')}", + **codex_cli_details, + } + ], "claude_sdk": [ { "componentId": "claude-sdk", diff --git a/ccproxy/auth/openai/__init__.py b/ccproxy/auth/openai/__init__.py new file mode 100644 index 00000000..93a3560f --- /dev/null +++ b/ccproxy/auth/openai/__init__.py @@ -0,0 +1,13 @@ +"""OpenAI authentication components for Codex integration.""" + +from .credentials import OpenAICredentials, OpenAITokenManager +from .oauth_client import OpenAIOAuthClient +from .storage import OpenAITokenStorage + + +__all__ = [ + "OpenAICredentials", + "OpenAITokenManager", + "OpenAIOAuthClient", + "OpenAITokenStorage", +] diff --git a/ccproxy/auth/openai/credentials.py b/ccproxy/auth/openai/credentials.py new file mode 100644 index 00000000..06494460 --- /dev/null +++ b/ccproxy/auth/openai/credentials.py @@ -0,0 +1,166 @@ +"""OpenAI credentials management for Codex authentication.""" + +from datetime import UTC, datetime +from typing import Any + +import jwt +import structlog +from pydantic import BaseModel, Field, field_validator + +from .storage import OpenAITokenStorage + + +logger = structlog.get_logger(__name__) + + +class OpenAICredentials(BaseModel): + """OpenAI authentication credentials model.""" + + access_token: str = Field(..., description="OpenAI access token (JWT)") + refresh_token: str = Field(..., description="OpenAI refresh token") + expires_at: datetime = Field(..., description="Token expiration timestamp") + account_id: str = Field(..., description="OpenAI account ID extracted from token") + active: bool = Field(default=True, description="Whether credentials are active") + + @field_validator("expires_at", mode="before") + @classmethod + def parse_expires_at(cls, v: Any) -> datetime: + """Parse expiration timestamp.""" + if isinstance(v, datetime): + # Ensure timezone-aware datetime + if v.tzinfo is None: + return v.replace(tzinfo=UTC) + return v + + if isinstance(v, str): + # Handle ISO format strings + try: + dt = datetime.fromisoformat(v.replace("Z", "+00:00")) + if dt.tzinfo is None: + dt = dt.replace(tzinfo=UTC) + return dt + except ValueError as e: + raise ValueError(f"Invalid datetime format: {v}") from e + + if isinstance(v, int | float): + # Handle Unix timestamps + return datetime.fromtimestamp(v, tz=UTC) + + raise ValueError(f"Cannot parse datetime from {type(v)}: {v}") + + @field_validator("account_id", mode="before") + @classmethod + def extract_account_id(cls, v: Any, info: Any) -> str: + """Extract account ID from access token if not provided.""" + if isinstance(v, str) and v: + return v + + # Try to extract from access_token + access_token = None + if hasattr(info, "data") and info.data and isinstance(info.data, dict): + access_token = info.data.get("access_token") + + if access_token and isinstance(access_token, str): + try: + # Decode JWT without verification to extract claims + decoded = jwt.decode(access_token, options={"verify_signature": False}) + if "org_id" in decoded and isinstance(decoded["org_id"], str): + return decoded["org_id"] + elif "sub" in decoded and isinstance(decoded["sub"], str): + return decoded["sub"] + elif "account_id" in decoded and isinstance(decoded["account_id"], str): + return decoded["account_id"] + except Exception as e: + logger.warning("Failed to extract account_id from token", error=str(e)) + + raise ValueError( + "account_id is required and could not be extracted from access_token" + ) + + def is_expired(self) -> bool: + """Check if the access token is expired.""" + now = datetime.now(UTC) + return now >= self.expires_at + + def expires_in_seconds(self) -> int: + """Get seconds until token expires.""" + now = datetime.now(UTC) + delta = self.expires_at - now + return max(0, int(delta.total_seconds())) + + def to_dict(self) -> dict[str, Any]: + """Convert to dictionary for storage.""" + return { + "access_token": self.access_token, + "refresh_token": self.refresh_token, + "expires_at": self.expires_at.isoformat(), + "account_id": self.account_id, + "active": self.active, + } + + @classmethod + def from_dict(cls, data: dict[str, Any]) -> "OpenAICredentials": + """Create from dictionary.""" + return cls(**data) + + +class OpenAITokenManager: + """Manages OpenAI token storage and refresh operations.""" + + def __init__(self, storage: OpenAITokenStorage | None = None): + """Initialize token manager. + + Args: + storage: Token storage backend. If None, uses default TOML file storage. + """ + self.storage = storage or OpenAITokenStorage() + + async def load_credentials(self) -> OpenAICredentials | None: + """Load credentials from storage.""" + try: + return await self.storage.load() + except Exception as e: + logger.error("Failed to load OpenAI credentials", error=str(e)) + return None + + async def save_credentials(self, credentials: OpenAICredentials) -> bool: + """Save credentials to storage.""" + try: + return await self.storage.save(credentials) + except Exception as e: + logger.error("Failed to save OpenAI credentials", error=str(e)) + return False + + async def delete_credentials(self) -> bool: + """Delete credentials from storage.""" + try: + return await self.storage.delete() + except Exception as e: + logger.error("Failed to delete OpenAI credentials", error=str(e)) + return False + + async def has_credentials(self) -> bool: + """Check if credentials exist.""" + try: + return await self.storage.exists() + except Exception: + return False + + async def get_valid_token(self) -> str | None: + """Get a valid access token, refreshing if necessary.""" + credentials = await self.load_credentials() + if not credentials or not credentials.active: + return None + + # If token is not expired, return it + if not credentials.is_expired(): + return credentials.access_token + + # TODO: Implement token refresh logic + # For now, return None if expired (user needs to re-authenticate) + logger.warning("OpenAI token expired, refresh not yet implemented") + return None + + def get_storage_location(self) -> str: + """Get storage location description.""" + return self.storage.get_location() diff --git a/ccproxy/auth/openai/oauth_client.py b/ccproxy/auth/openai/oauth_client.py new file mode 100644 index 00000000..c89cf0c9 --- /dev/null +++ b/ccproxy/auth/openai/oauth_client.py @@ -0,0 +1,334 @@ +"""OpenAI OAuth PKCE client implementation.""" + +import asyncio +import base64 +import contextlib +import hashlib +import secrets +import urllib.parse +import webbrowser +from datetime import UTC, datetime, timedelta + +import httpx +import structlog +import uvicorn +from fastapi import FastAPI, Request, Response +from fastapi.responses import HTMLResponse + +from ccproxy.config.codex import CodexSettings + +from .credentials import OpenAICredentials, OpenAITokenManager + + +logger = structlog.get_logger(__name__) + + +class OpenAIOAuthClient: + """OpenAI OAuth PKCE flow client.""" + + def __init__( + self, settings: CodexSettings, token_manager: OpenAITokenManager | None = None + ): + """Initialize OAuth client. + + Args: + settings: Codex configuration settings + token_manager: Token manager for credential storage + """ + self.settings = settings + self.token_manager = token_manager or OpenAITokenManager() + self._server_task: asyncio.Task[None] | None = None + self._auth_complete = asyncio.Event() + self._auth_result: OpenAICredentials | None = None + self._auth_error: str | None = None + + def _generate_pkce_pair(self) -> tuple[str, str]: + """Generate PKCE code verifier and challenge.""" + # Generate code verifier (43-128 characters) + code_verifier = ( + base64.urlsafe_b64encode(secrets.token_bytes(32)).decode().rstrip("=") + ) + + # Generate code challenge + code_challenge = ( + base64.urlsafe_b64encode(hashlib.sha256(code_verifier.encode()).digest()) + .decode() + .rstrip("=") + ) + + return code_verifier, code_challenge + + def _build_auth_url(self, code_challenge: str, state: str) -> str: + """Build OAuth authorization URL.""" + params = { + "response_type": "code", + "client_id": self.settings.oauth.client_id, + "redirect_uri": self.settings.get_redirect_uri(), + "scope": " ".join(self.settings.oauth.scopes), + "state": state, + "code_challenge": code_challenge, + "code_challenge_method": "S256", + } + + query_string = urllib.parse.urlencode(params) + return f"{self.settings.oauth.base_url}/oauth/authorize?{query_string}" + + async def _exchange_code_for_tokens( + self, code: str, code_verifier: str + ) -> OpenAICredentials: + """Exchange authorization code for tokens.""" + token_url = f"{self.settings.oauth.base_url}/oauth/token" + + data = { + "grant_type": "authorization_code", + "code": code, + "redirect_uri": self.settings.get_redirect_uri(), + "client_id": self.settings.oauth.client_id, + "code_verifier": code_verifier, + } + + headers = { + "Content-Type": "application/x-www-form-urlencoded", + "Accept": "application/json", + } + + async with httpx.AsyncClient() as client: + try: + response = await client.post( + token_url, data=data, headers=headers, timeout=30.0 + ) + response.raise_for_status() + + token_data = response.json() + + # Calculate expiration time + expires_in = token_data.get("expires_in", 3600) # Default 1 hour + expires_at = datetime.now(UTC).replace(microsecond=0) + timedelta( + seconds=expires_in + ) + + # Create credentials (account_id will be extracted from access_token) + credentials = OpenAICredentials( + access_token=token_data["access_token"], + refresh_token=token_data.get("refresh_token", ""), + expires_at=expires_at, + account_id="", # Will be auto-extracted by validator + active=True, + ) + + return credentials + + except httpx.HTTPStatusError as e: + error_detail = "Unknown error" + try: + error_data = e.response.json() + error_detail = error_data.get( + "error_description", error_data.get("error", str(e)) + ) + except Exception: + error_detail = str(e) + + raise ValueError(f"Token exchange failed: {error_detail}") from e + except Exception as e: + raise ValueError(f"Token exchange request failed: {e}") from e + + def _create_callback_app(self, code_verifier: str, expected_state: str) -> FastAPI: + """Create FastAPI app to handle OAuth callback.""" + app = FastAPI(title="OpenAI OAuth Callback") + + @app.get("/auth/callback") + async def oauth_callback(request: Request) -> Response: + """Handle OAuth callback.""" + params = dict(request.query_params) + + # Check for error in callback + if "error" in params: + error_desc = params.get("error_description", params["error"]) + self._auth_error = f"OAuth error: {error_desc}" + self._auth_complete.set() + return HTMLResponse( + """ + + Authentication Failed + +

Authentication Failed

+

Error: """ + + error_desc + + """

+

You can close this window.

+ + + + """, + status_code=400, + ) + + # Verify state parameter + received_state = params.get("state") + if received_state != expected_state: + self._auth_error = "Invalid state parameter" + self._auth_complete.set() + return HTMLResponse( + """ + + Authentication Failed + +

Authentication Failed

+

Invalid state parameter. Possible CSRF attack.

+

You can close this window.

+ + + + """, + status_code=400, + ) + + # Get authorization code + auth_code = params.get("code") + if not auth_code: + self._auth_error = "No authorization code received" + self._auth_complete.set() + return HTMLResponse( + """ + + Authentication Failed + +

Authentication Failed

+

No authorization code received.

+

You can close this window.

+ + + + """, + status_code=400, + ) + + # Exchange code for tokens + try: + credentials = await self._exchange_code_for_tokens( + auth_code, code_verifier + ) + + # Save credentials + success = await self.token_manager.save_credentials(credentials) + if not success: + raise ValueError("Failed to save credentials") + + self._auth_result = credentials + self._auth_complete.set() + + return HTMLResponse( + """ + + Authentication Successful + +

Authentication Successful!

+

You have successfully authenticated with OpenAI.

+

You can close this window and return to the terminal.

+ + + + """ + ) + + except Exception as e: + logger.error("Token exchange failed", error=str(e)) + self._auth_error = f"Token exchange failed: {e}" + self._auth_complete.set() + return HTMLResponse( + f""" + + Authentication Failed + +

Authentication Failed

+

Token exchange failed: {e}

+

You can close this window.

+ + + + """, + status_code=500, + ) + + return app + + async def _run_callback_server(self, app: FastAPI) -> None: + """Run callback server.""" + config = uvicorn.Config( + app=app, + host="127.0.0.1", + port=self.settings.callback_port, + log_level="warning", # Reduce noise + access_log=False, + ) + server = uvicorn.Server(config) + await server.serve() + + async def authenticate(self, open_browser: bool = True) -> OpenAICredentials: + """Perform OAuth PKCE flow. + + Args: + open_browser: Whether to automatically open browser + + Returns: + OpenAI credentials + + Raises: + ValueError: If authentication fails + """ + # Reset state + self._auth_complete.clear() + self._auth_result = None + self._auth_error = None + + # Generate PKCE parameters + code_verifier, code_challenge = self._generate_pkce_pair() + state = secrets.token_urlsafe(32) + + # Create callback app + app = self._create_callback_app(code_verifier, state) + + # Start callback server + self._server_task = asyncio.create_task(self._run_callback_server(app)) + + # Give server time to start + await asyncio.sleep(1) + + # Build authorization URL + auth_url = self._build_auth_url(code_challenge, state) + + logger.info("Starting OpenAI OAuth flow") + print("\nPlease visit this URL to authenticate with OpenAI:") + print(f"{auth_url}\n") + + if open_browser: + try: + webbrowser.open(auth_url) + print("Opening browser...") + except Exception as e: + logger.warning("Failed to open browser automatically", error=str(e)) + print("Please copy and paste the URL above into your browser.") + + print("Waiting for authentication to complete...") + + try: + # Wait for authentication to complete (with timeout) + await asyncio.wait_for(self._auth_complete.wait(), timeout=300) # 5 minutes + + if self._auth_error: + raise ValueError(self._auth_error) + + if not self._auth_result: + raise ValueError("Authentication completed but no credentials received") + + logger.info("OpenAI authentication successful") # type: ignore[unreachable] + return self._auth_result + + except TimeoutError as e: + raise ValueError("Authentication timed out (5 minutes)") from e + finally: + # Clean up server + if self._server_task and not self._server_task.done(): + self._server_task.cancel() + with contextlib.suppress(asyncio.CancelledError): + await self._server_task diff --git a/ccproxy/auth/openai/storage.py b/ccproxy/auth/openai/storage.py new file mode 100644 index 00000000..6fd2c2be --- /dev/null +++ b/ccproxy/auth/openai/storage.py @@ -0,0 +1,184 @@ +"""JSON file storage for OpenAI credentials using Codex format.""" + +import contextlib +import json +from datetime import UTC, datetime +from pathlib import Path +from typing import TYPE_CHECKING, Any + +import jwt +import structlog + + +if TYPE_CHECKING: + from .credentials import OpenAICredentials + + +logger = structlog.get_logger(__name__) + + +class OpenAITokenStorage: + """JSON file-based storage for OpenAI credentials using Codex format.""" + + def __init__(self, file_path: Path | None = None): + """Initialize storage with file path. + + Args: + file_path: Path to JSON file. If None, uses ~/.codex/auth.json + """ + self.file_path = file_path or Path.home() / ".codex" / "auth.json" + + async def load(self) -> "OpenAICredentials | None": + """Load credentials from Codex JSON file.""" + if not self.file_path.exists(): + return None + + try: + with self.file_path.open("r") as f: + data = json.load(f) + + # Extract tokens section + tokens = data.get("tokens", {}) + if not tokens: + logger.warning("No tokens section found in Codex auth file") + return None + + # Get required fields + access_token = tokens.get("access_token") + refresh_token = tokens.get("refresh_token") + account_id = tokens.get("account_id") + + if not access_token: + logger.warning("No access_token found in Codex auth file") + return None + + # Extract expiration from JWT token + expires_at = self._extract_expiration_from_token(access_token) + if not expires_at: + logger.warning("Could not extract expiration from access token") + return None + + # Import here to avoid circular import + from .credentials import OpenAICredentials + + # Create credentials object + credentials_data = { + "access_token": access_token, + "refresh_token": refresh_token or "", + "expires_at": expires_at, + "account_id": account_id or "", + "active": True, + } + + return OpenAICredentials.from_dict(credentials_data) + + except Exception as e: + logger.error( + "Failed to load OpenAI credentials from Codex auth file", + file_path=str(self.file_path), + error=str(e), + ) + return None + + def _extract_expiration_from_token(self, access_token: str) -> datetime | None: + """Extract expiration time from JWT access token.""" + try: + decoded = jwt.decode(access_token, options={"verify_signature": False}) + exp_timestamp = decoded.get("exp") + if exp_timestamp: + return datetime.fromtimestamp(exp_timestamp, tz=UTC) + except Exception as e: + logger.warning("Failed to decode JWT token for expiration", error=str(e)) + return None + + async def save(self, credentials: "OpenAICredentials") -> bool: + """Save credentials to Codex JSON file.""" + try: + # Create directory if it doesn't exist + self.file_path.parent.mkdir(parents=True, exist_ok=True) + + # Load existing file or create new structure + existing_data: dict[str, Any] = {} + if self.file_path.exists(): + try: + with self.file_path.open("r") as f: + existing_data = json.load(f) + except Exception: + logger.warning( + "Could not load existing auth file, creating new one" + ) + + # Prepare Codex JSON data structure + codex_data = { + "OPENAI_API_KEY": existing_data.get("OPENAI_API_KEY"), + "tokens": { + "id_token": existing_data.get("tokens", {}).get("id_token"), + "access_token": credentials.access_token, + "refresh_token": credentials.refresh_token, + "account_id": credentials.account_id, + }, + "last_refresh": datetime.now(UTC).isoformat().replace("+00:00", "Z"), + } + + # Write atomically by writing to temp file then renaming + temp_file = self.file_path.with_suffix(f"{self.file_path.suffix}.tmp") + + with temp_file.open("w") as f: + json.dump(codex_data, f, indent=2) + + # Set restrictive permissions (readable only by owner) + temp_file.chmod(0o600) + + # Atomic rename + temp_file.replace(self.file_path) + + logger.info( + "Saved OpenAI credentials to Codex auth file", + file_path=str(self.file_path), + ) + return True + + except Exception as e: + logger.error( + "Failed to save OpenAI credentials to Codex auth file", + file_path=str(self.file_path), + error=str(e), + ) + # Clean up temp file if it exists + temp_file = self.file_path.with_suffix(f"{self.file_path.suffix}.tmp") + if temp_file.exists(): + with contextlib.suppress(Exception): + temp_file.unlink() + return False + + async def exists(self) -> bool: + """Check if credentials file exists.""" + if not self.file_path.exists(): + return False + + try: + with self.file_path.open("r") as f: + data = json.load(f) + tokens = data.get("tokens", {}) + return bool(tokens.get("access_token")) + except Exception: + return False + + async def delete(self) -> bool: + """Delete credentials file.""" + try: + if self.file_path.exists(): + self.file_path.unlink() + logger.info("Deleted Codex auth file", file_path=str(self.file_path)) + return True + except Exception as e: + logger.error( + "Failed to delete Codex auth file", + file_path=str(self.file_path), + error=str(e), + ) + return False + + def get_location(self) -> str: + """Get storage location description.""" + return str(self.file_path) diff --git a/ccproxy/claude_sdk/options.py b/ccproxy/claude_sdk/options.py index f32fb04b..f624c35e 100644 --- a/ccproxy/claude_sdk/options.py +++ b/ccproxy/claude_sdk/options.py @@ -61,7 +61,7 @@ def create_options( # Extract configuration values with proper types mcp_servers = ( configured_opts.mcp_servers.copy() - if configured_opts.mcp_servers + if isinstance(configured_opts.mcp_servers, dict) else {} ) permission_prompt_tool_name = configured_opts.permission_prompt_tool_name diff --git a/ccproxy/cli/commands/auth.py b/ccproxy/cli/commands/auth.py index 2829c1ce..f72f4c2b 100644 --- a/ccproxy/cli/commands/auth.py +++ b/ccproxy/cli/commands/auth.py @@ -3,7 +3,12 @@ import asyncio from datetime import UTC, datetime from pathlib import Path -from typing import Annotated +from typing import TYPE_CHECKING, Annotated + + +if TYPE_CHECKING: + from ccproxy.auth.openai import OpenAIOAuthClient, OpenAITokenManager + from ccproxy.config.codex import CodexSettings import typer from rich import box @@ -563,5 +568,397 @@ def renew( raise typer.Exit(1) from e +# OpenAI Codex Authentication Commands + + +def get_openai_token_manager() -> "OpenAITokenManager": + """Get OpenAI token manager dependency.""" + from ccproxy.auth.openai import OpenAITokenManager + + return OpenAITokenManager() + + +def get_openai_oauth_client(settings: "CodexSettings") -> "OpenAIOAuthClient": + """Get OpenAI OAuth client dependency.""" + from ccproxy.auth.openai import OpenAIOAuthClient + + token_manager = get_openai_token_manager() + return OpenAIOAuthClient(settings, token_manager) + + +@app.command(name="login-openai") +def login_openai_command( + no_browser: Annotated[ + bool, + typer.Option( + "--no-browser", + help="Don't automatically open browser for authentication", + ), + ] = False, +) -> None: + """Login to OpenAI using OAuth authentication. + + This command will start a local callback server and open your web browser + to authenticate with OpenAI. The credentials will be saved to ~/.codex/auth.json. + + Examples: + ccproxy auth login-openai + ccproxy auth login-openai --no-browser + """ + import asyncio + + from ccproxy.config.codex import CodexSettings + + toolkit = get_rich_toolkit() + toolkit.print("[bold cyan]OpenAI OAuth Login[/bold cyan]", centered=True) + toolkit.print_line() + + try: + # Get Codex settings + settings = CodexSettings() + + # Check if already logged in + token_manager = get_openai_token_manager() + existing_creds = asyncio.run(token_manager.load_credentials()) + + if existing_creds and not existing_creds.is_expired(): + console.print( + "[yellow]You are already logged in with valid OpenAI credentials.[/yellow]" + ) + console.print( + "Use [cyan]ccproxy auth openai-info[/cyan] to view current credentials." + ) + + overwrite = typer.confirm( + "Do you want to login again and overwrite existing credentials?" + ) + if not overwrite: + console.print("Login cancelled.") + return + + # Create OAuth client and perform login + oauth_client = get_openai_oauth_client(settings) + + console.print("Starting OpenAI OAuth login process...") + console.print( + "A temporary server will start on port 1455 for the OAuth callback..." + ) + + if no_browser: + console.print("Browser will NOT be opened automatically.") + else: + console.print("Your browser will open for authentication.") + + try: + credentials = asyncio.run( + oauth_client.authenticate(open_browser=not no_browser) + ) + + toolkit.print("Successfully logged in to OpenAI!", tag="success") + + # Show credential info + console.print("\n[dim]Credential information:[/dim]") + console.print(f" Account ID: {credentials.account_id}") + console.print( + f" Expires: {credentials.expires_at.strftime('%Y-%m-%d %H:%M:%S UTC')}" + ) + console.print(f" Active: {'Yes' if credentials.active else 'No'}") + + except Exception as e: + logger.error(f"OpenAI login failed: {e}") + toolkit.print(f"Login failed: {e}", tag="error") + raise typer.Exit(1) from e + + except KeyboardInterrupt: + console.print("\n[yellow]Login cancelled by user.[/yellow]") + raise typer.Exit(1) from None + except Exception as e: + toolkit.print(f"Error during OpenAI login: {e}", tag="error") + raise typer.Exit(1) from e + + +@app.command(name="logout-openai") +def logout_openai_command() -> None: + """Logout from OpenAI and remove saved credentials. + + This command will remove the OpenAI credentials file (~/.codex/auth.json) + and invalidate the current session. + + Examples: + ccproxy auth logout-openai + """ + import asyncio + + toolkit = get_rich_toolkit() + toolkit.print("[bold cyan]OpenAI Logout[/bold cyan]", centered=True) + toolkit.print_line() + + try: + token_manager = get_openai_token_manager() + + # Check if credentials exist + existing_creds = asyncio.run(token_manager.load_credentials()) + if not existing_creds: + console.print( + "[yellow]No OpenAI credentials found. Already logged out.[/yellow]" + ) + return + + # Confirm logout + confirm = typer.confirm( + "Are you sure you want to logout and remove OpenAI credentials?" + ) + if not confirm: + console.print("Logout cancelled.") + return + + # Delete credentials + success = asyncio.run(token_manager.delete_credentials()) + + if success: + toolkit.print("Successfully logged out from OpenAI!", tag="success") + console.print("OpenAI credentials have been removed.") + else: + toolkit.print("Failed to remove OpenAI credentials", tag="error") + raise typer.Exit(1) + + except Exception as e: + toolkit.print(f"Error during OpenAI logout: {e}", tag="error") + raise typer.Exit(1) from e + + +@app.command(name="openai-info") +def openai_info_command() -> None: + """Display OpenAI credential information. + + Shows detailed information about the current OpenAI credentials including + account ID, token expiration, and storage location. + + Examples: + ccproxy auth openai-info + """ + import asyncio + import base64 + import json + from datetime import UTC, datetime + + from rich import box + from rich.table import Table + + toolkit = get_rich_toolkit() + toolkit.print("[bold cyan]OpenAI Credential Information[/bold cyan]", centered=True) + toolkit.print_line() + + try: + token_manager = get_openai_token_manager() + credentials = asyncio.run(token_manager.load_credentials()) + + if not credentials: + toolkit.print("No OpenAI credentials found", tag="error") + console.print("\n[dim]Expected location:[/dim]") + storage_location = token_manager.storage.get_location() + console.print(f" - {storage_location}") + console.print("\n[dim]To login:[/dim]") + console.print(" ccproxy auth login-openai") + raise typer.Exit(1) + + # Decode JWT token to extract additional information + jwt_payload = {} + jwt_header = {} + if credentials.access_token: + try: + # Split JWT into parts + parts = credentials.access_token.split(".") + if len(parts) == 3: + # Decode header and payload (add padding if needed) + header_b64 = parts[0] + "=" * (4 - len(parts[0]) % 4) + payload_b64 = parts[1] + "=" * (4 - len(parts[1]) % 4) + + jwt_header = json.loads(base64.urlsafe_b64decode(header_b64)) + jwt_payload = json.loads(base64.urlsafe_b64decode(payload_b64)) + except Exception as decode_error: + logger.debug(f"Failed to decode JWT token: {decode_error}") + + # Display account section + console.print("\n[bold]OpenAI Account[/bold]") + console.print(f" L Account ID: {credentials.account_id}") + console.print(f" L Status: {'Active' if credentials.active else 'Inactive'}") + + # Extract additional info from JWT payload + if jwt_payload: + # Get OpenAI auth info from the JWT + openai_auth = jwt_payload.get("https://api.openai.com/auth", {}) + if openai_auth: + if "email" in jwt_payload: + console.print(f" L Email: {jwt_payload['email']}") + if jwt_payload.get("email_verified"): + console.print(" L Email Verified: Yes") + + if openai_auth.get("chatgpt_plan_type"): + console.print( + f" L Plan Type: {openai_auth['chatgpt_plan_type'].upper()}" + ) + + if openai_auth.get("chatgpt_user_id"): + console.print(f" L User ID: {openai_auth['chatgpt_user_id']}") + + # Subscription info + if openai_auth.get("chatgpt_subscription_active_start"): + console.print( + f" L Subscription Start: {openai_auth['chatgpt_subscription_active_start']}" + ) + if openai_auth.get("chatgpt_subscription_active_until"): + console.print( + f" L Subscription Until: {openai_auth['chatgpt_subscription_active_until']}" + ) + + # Organizations + orgs = openai_auth.get("organizations", []) + if orgs: + for org in orgs: + if org.get("is_default"): + console.print( + f" L Organization: {org.get('title', 'Unknown')} ({org.get('role', 'member')})" + ) + console.print(f" L Org ID: {org.get('id', 'Unknown')}") + + # Create details table + console.print() + table = Table( + show_header=True, + header_style="bold cyan", + box=box.ROUNDED, + title="Token Details", + title_style="bold white", + ) + table.add_column("Property", style="cyan") + table.add_column("Value", style="white") + + # File location + storage_location = token_manager.storage.get_location() + table.add_row("Storage Location", storage_location) + + # Token algorithm and type from JWT header + if jwt_header: + table.add_row("Algorithm", jwt_header.get("alg", "Unknown")) + table.add_row("Token Type", jwt_header.get("typ", "Unknown")) + if jwt_header.get("kid"): + table.add_row("Key ID", jwt_header["kid"]) + + # Token status + table.add_row( + "Token Expired", + "[red]Yes[/red]" if credentials.is_expired() else "[green]No[/green]", + ) + + # Expiration details + exp_dt = credentials.expires_at + table.add_row("Expires At", exp_dt.strftime("%Y-%m-%d %H:%M:%S UTC")) + + # Time until expiration + now = datetime.now(UTC) + time_diff = exp_dt - now + if time_diff.total_seconds() > 0: + days = time_diff.days + hours = (time_diff.seconds % 86400) // 3600 + minutes = (time_diff.seconds % 3600) // 60 + table.add_row( + "Time Remaining", f"{days} days, {hours} hours, {minutes} minutes" + ) + else: + table.add_row("Time Remaining", "[red]Expired[/red]") + + # JWT timestamps if available + if jwt_payload: + if "iat" in jwt_payload: + iat_dt = datetime.fromtimestamp(jwt_payload["iat"], tz=UTC) + table.add_row("Issued At", iat_dt.strftime("%Y-%m-%d %H:%M:%S UTC")) + + if "auth_time" in jwt_payload: + auth_dt = datetime.fromtimestamp(jwt_payload["auth_time"], tz=UTC) + table.add_row("Auth Time", auth_dt.strftime("%Y-%m-%d %H:%M:%S UTC")) + + # JWT issuer and audience + if jwt_payload: + if "iss" in jwt_payload: + table.add_row("Issuer", jwt_payload["iss"]) + if "aud" in jwt_payload: + audience = jwt_payload["aud"] + if isinstance(audience, list): + audience = ", ".join(audience) + table.add_row("Audience", audience) + if "jti" in jwt_payload: + table.add_row("JWT ID", jwt_payload["jti"]) + if "sid" in jwt_payload: + table.add_row("Session ID", jwt_payload["sid"]) + + # Token preview (first and last 8 chars) + if credentials.access_token: + token_preview = ( + f"{credentials.access_token[:12]}...{credentials.access_token[-8:]}" + ) + table.add_row("Access Token", f"[dim]{token_preview}[/dim]") + + # Refresh token status + has_refresh = bool(credentials.refresh_token) + table.add_row( + "Refresh Token", + "[green]Available[/green]" + if has_refresh + else "[yellow]Not available[/yellow]", + ) + + console.print(table) + + # Show usage instructions + console.print("\n[dim]Commands:[/dim]") + console.print(" ccproxy auth login-openai - Re-authenticate") + console.print(" ccproxy auth logout-openai - Remove credentials") + + except Exception as e: + toolkit.print(f"Error getting OpenAI credential info: {e}", tag="error") + raise typer.Exit(1) from e + + +@app.command(name="openai-status") +def openai_status_command() -> None: + """Check OpenAI authentication status. + + Quick status check for OpenAI credentials without detailed information. + Useful for scripts and automation. + + Examples: + ccproxy auth openai-status + """ + import asyncio + + try: + token_manager = get_openai_token_manager() + credentials = asyncio.run(token_manager.load_credentials()) + + if not credentials: + console.print("[red]✗[/red] Not logged in to OpenAI") + raise typer.Exit(1) + + if credentials.is_expired(): + console.print("[yellow]⚠[/yellow] OpenAI credentials expired") + console.print( + f" Expired: {credentials.expires_at.strftime('%Y-%m-%d %H:%M:%S UTC')}" + ) + raise typer.Exit(1) + + console.print("[green]✓[/green] OpenAI credentials valid") + console.print(f" Account: {credentials.account_id}") + console.print( + f" Expires: {credentials.expires_at.strftime('%Y-%m-%d %H:%M:%S UTC')}" + ) + + except SystemExit: + raise + except Exception as e: + console.print(f"[red]✗[/red] Error checking OpenAI status: {e}") + raise typer.Exit(1) from e + + if __name__ == "__main__": app() diff --git a/ccproxy/config/claude.py b/ccproxy/config/claude.py index f21373fb..69002239 100644 --- a/ccproxy/config/claude.py +++ b/ccproxy/config/claude.py @@ -226,7 +226,7 @@ def validate_claude_code_options(cls, v: Any, info: Any) -> Any: # Extract default values as a dict for merging default_values = { "mcp_servers": dict(defaults.mcp_servers) - if defaults.mcp_servers + if isinstance(defaults.mcp_servers, dict) else {}, "permission_prompt_tool_name": defaults.permission_prompt_tool_name, } diff --git a/ccproxy/config/codex.py b/ccproxy/config/codex.py new file mode 100644 index 00000000..d6befb3c --- /dev/null +++ b/ccproxy/config/codex.py @@ -0,0 +1,100 @@ +"""OpenAI Codex-specific configuration settings.""" + +from pydantic import BaseModel, Field, field_validator + + +class OAuthSettings(BaseModel): + """OAuth configuration for OpenAI authentication.""" + + base_url: str = Field( + default="https://auth.openai.com", + description="OpenAI OAuth base URL", + ) + + client_id: str = Field( + default="app_EMoamEEZ73f0CkXaXp7hrann", + description="OpenAI OAuth client ID", + ) + + scopes: list[str] = Field( + default_factory=lambda: ["openid", "profile", "email", "offline_access"], + description="OAuth scopes to request", + ) + + @field_validator("base_url") + @classmethod + def validate_base_url(cls, v: str) -> str: + """Validate OAuth base URL format.""" + if not v.startswith(("http://", "https://")): + raise ValueError("OAuth base URL must start with http:// or https://") + return v.rstrip("/") + + +class CodexSettings(BaseModel): + """OpenAI Codex-specific configuration settings.""" + + enabled: bool = Field( + default=True, + description="Enable OpenAI Codex provider support", + ) + + base_url: str = Field( + default="https://chatgpt.com/backend-api/codex", + description="OpenAI Codex API base URL", + ) + + oauth: OAuthSettings = Field( + default_factory=OAuthSettings, + description="OAuth configuration settings", + ) + + callback_port: int = Field( + default=1455, + ge=1024, + le=65535, + description="Port for OAuth callback server (1024-65535)", + ) + + redirect_uri: str = Field( + default="http://localhost:1455/auth/callback", + description="OAuth redirect URI (auto-generated from callback_port if not set)", + ) + + verbose_logging: bool = Field( + default=False, + description="Enable verbose logging for Codex operations", + ) + + @field_validator("base_url") + @classmethod + def validate_base_url(cls, v: str) -> str: + """Validate Codex base URL format.""" + if not v.startswith(("http://", "https://")): + raise ValueError("Codex base URL must start with http:// or https://") + return v.rstrip("/") + + @field_validator("redirect_uri") + @classmethod + def validate_redirect_uri(cls, v: str) -> str: + """Validate redirect URI format.""" + if not v.startswith(("http://", "https://")): + raise ValueError("Redirect URI must start with http:// or https://") + return v + + @field_validator("callback_port") + @classmethod + def validate_callback_port(cls, v: int) -> int: + """Validate callback port range.""" + if not (1024 <= v <= 65535): + raise ValueError("Callback port must be between 1024 and 65535") + return v + + def get_redirect_uri(self) -> str: + """Get the redirect URI, auto-generating if needed.""" + if ( + self.redirect_uri + and self.redirect_uri + != f"http://localhost:{self.callback_port}/auth/callback" + ): + return self.redirect_uri + return f"http://localhost:{self.callback_port}/auth/callback" diff --git a/ccproxy/config/settings.py b/ccproxy/config/settings.py index 0c411f4d..5a2b0040 100644 --- a/ccproxy/config/settings.py +++ b/ccproxy/config/settings.py @@ -15,6 +15,7 @@ from .auth import AuthSettings from .claude import ClaudeSettings +from .codex import CodexSettings from .cors import CORSSettings from .docker_settings import DockerSettings from .observability import ObservabilitySettings @@ -85,6 +86,12 @@ class Settings(BaseSettings): description="Claude-specific configuration settings", ) + # Codex-specific settings + codex: CodexSettings = Field( + default_factory=CodexSettings, + description="OpenAI Codex-specific configuration settings", + ) + # Proxy and authentication reverse_proxy: ReverseProxySettings = Field( default_factory=ReverseProxySettings, @@ -168,6 +175,18 @@ def validate_claude(cls, v: Any) -> Any: return ClaudeSettings(**v) return v + @field_validator("codex", mode="before") + @classmethod + def validate_codex(cls, v: Any) -> Any: + """Validate and convert Codex settings.""" + if v is None: + return CodexSettings() + if isinstance(v, CodexSettings): + return v + if isinstance(v, dict): + return CodexSettings(**v) + return v + @field_validator("reverse_proxy", mode="before") @classmethod def validate_reverse_proxy(cls, v: Any) -> Any: diff --git a/ccproxy/core/codex_transformers.py b/ccproxy/core/codex_transformers.py new file mode 100644 index 00000000..a268628e --- /dev/null +++ b/ccproxy/core/codex_transformers.py @@ -0,0 +1,389 @@ +"""Codex-specific transformers for request/response transformation.""" + +import json + +import structlog +from typing_extensions import TypedDict + +from ccproxy.core.transformers import RequestTransformer +from ccproxy.core.types import ProxyRequest, TransformContext +from ccproxy.models.detection import CodexCacheData + + +logger = structlog.get_logger(__name__) + + +class CodexRequestData(TypedDict): + """Typed structure for transformed Codex request data.""" + + method: str + url: str + headers: dict[str, str] + body: bytes | None + + +class CodexRequestTransformer(RequestTransformer): + """Codex request transformer for header and instructions field injection.""" + + def __init__(self) -> None: + """Initialize Codex request transformer.""" + super().__init__() + + async def _transform_request( + self, request: ProxyRequest, context: TransformContext | None = None + ) -> ProxyRequest: + """Transform a proxy request for Codex API. + + Args: + request: The structured proxy request to transform + context: Optional transformation context + + Returns: + The transformed proxy request + """ + # Extract required data from context + access_token = "" + session_id = "" + account_id = "" + codex_detection_data = None + + if context: + if hasattr(context, "access_token"): + access_token = context.access_token + elif isinstance(context, dict): + access_token = context.get("access_token", "") + + if hasattr(context, "session_id"): + session_id = context.session_id + elif isinstance(context, dict): + session_id = context.get("session_id", "") + + if hasattr(context, "account_id"): + account_id = context.account_id + elif isinstance(context, dict): + account_id = context.get("account_id", "") + + if hasattr(context, "codex_detection_data"): + codex_detection_data = context.codex_detection_data + elif isinstance(context, dict): + codex_detection_data = context.get("codex_detection_data") + + # Transform URL - remove codex prefix and forward to ChatGPT backend + transformed_url = self._transform_codex_url(request.url) + + # Convert request body to bytes for header processing + body_bytes = None + if request.body: + if isinstance(request.body, bytes): + body_bytes = request.body + elif isinstance(request.body, str): + body_bytes = request.body.encode("utf-8") + elif isinstance(request.body, dict): + body_bytes = json.dumps(request.body).encode("utf-8") + + # Transform headers with Codex CLI identity + transformed_headers = self.create_codex_headers( + request.headers, + access_token, + session_id, + account_id, + body_bytes, + codex_detection_data, + ) + + # Transform body to inject instructions + transformed_body = request.body + if request.body: + if isinstance(request.body, bytes): + transformed_body = self.transform_codex_body( + request.body, codex_detection_data + ) + else: + # Convert to bytes if needed + body_bytes = ( + json.dumps(request.body).encode("utf-8") + if isinstance(request.body, dict) + else str(request.body).encode("utf-8") + ) + transformed_body = self.transform_codex_body( + body_bytes, codex_detection_data + ) + + # Create new transformed request + return ProxyRequest( + method=request.method, + url=transformed_url, + headers=transformed_headers, + params={}, # Query params handled in URL + body=transformed_body, + protocol=request.protocol, + timeout=request.timeout, + metadata=request.metadata, + ) + + async def transform_codex_request( + self, + method: str, + path: str, + headers: dict[str, str], + body: bytes | None, + access_token: str, + session_id: str, + account_id: str, + codex_detection_data: CodexCacheData | None = None, + target_base_url: str = "https://chatgpt.com/backend-api/codex", + ) -> CodexRequestData: + """Transform Codex request using direct parameters from ProxyService. + + Args: + method: HTTP method + path: Request path + headers: Request headers + body: Request body + access_token: OAuth access token + session_id: Codex session ID + account_id: ChatGPT account ID + codex_detection_data: Optional Codex detection data + target_base_url: Base URL for the Codex API + + Returns: + Dictionary with transformed request data (method, url, headers, body) + """ + # Transform URL path + transformed_path = self._transform_codex_path(path) + target_url = f"{target_base_url.rstrip('/')}{transformed_path}" + + # Transform body first (inject instructions) + codex_body = None + if body: + # body is guaranteed to be bytes due to parameter type + codex_body = self.transform_codex_body(body, codex_detection_data) + + # Transform headers with Codex CLI identity and authentication + codex_headers = self.create_codex_headers( + headers, access_token, session_id, account_id, body, codex_detection_data + ) + + # Update Content-Length if body was transformed and size changed + if codex_body and body and len(codex_body) != len(body): + # Remove any existing content-length headers (case-insensitive) + codex_headers = { + k: v for k, v in codex_headers.items() if k.lower() != "content-length" + } + codex_headers["Content-Length"] = str(len(codex_body)) + elif codex_body and not body: + # New body was created where none existed + codex_headers["Content-Length"] = str(len(codex_body)) + + return CodexRequestData( + method=method, + url=target_url, + headers=codex_headers, + body=codex_body, + ) + + def _transform_codex_url(self, url: str) -> str: + """Transform URL from proxy format to ChatGPT backend format.""" + # Extract base URL and path + if "://" in url: + protocol, rest = url.split("://", 1) + if "/" in rest: + domain, path = rest.split("/", 1) + path = "/" + path + else: + path = "/" + else: + path = url if url.startswith("/") else "/" + url + + # Transform path and build target URL + transformed_path = self._transform_codex_path(path) + return f"https://chatgpt.com/backend-api/codex{transformed_path}" + + def _transform_codex_path(self, path: str) -> str: + """Transform request path for Codex API.""" + # Remove /codex prefix if present + if path.startswith("/codex"): + path = path[6:] # Remove "/codex" prefix + + # Ensure we have a valid path + if not path or path == "/": + path = "/responses" + + # Handle session_id in path for /codex/{session_id}/responses pattern + if path.startswith("/") and "/" in path[1:]: + # This might be /{session_id}/responses - extract the responses part + parts = path.strip("/").split("/") + if len(parts) >= 2 and parts[-1] == "responses": + # Keep the /responses endpoint, session_id will be in headers + path = "/responses" + + return path + + def create_codex_headers( + self, + headers: dict[str, str], + access_token: str, + session_id: str, + account_id: str, + body: bytes | None = None, + codex_detection_data: CodexCacheData | None = None, + ) -> dict[str, str]: + """Create Codex headers with CLI identity and authentication.""" + codex_headers = {} + + # Strip potentially problematic headers + excluded_headers = { + "host", + "x-forwarded-for", + "x-forwarded-proto", + "x-forwarded-host", + "forwarded", + # Authentication headers to be replaced + "authorization", + "x-api-key", + # Compression headers to avoid decompression issues + "accept-encoding", + "content-encoding", + # CORS headers - should not be forwarded to upstream + "origin", + "access-control-request-method", + "access-control-request-headers", + "access-control-allow-origin", + "access-control-allow-methods", + "access-control-allow-headers", + "access-control-allow-credentials", + "access-control-max-age", + "access-control-expose-headers", + } + + # Copy important headers (excluding problematic ones) + for key, value in headers.items(): + lower_key = key.lower() + if lower_key not in excluded_headers: + codex_headers[key] = value + + # Set authentication with OAuth token + if access_token: + codex_headers["Authorization"] = f"Bearer {access_token}" + + # Set defaults for essential headers + if "content-type" not in [k.lower() for k in codex_headers]: + codex_headers["Content-Type"] = "application/json" + if "accept" not in [k.lower() for k in codex_headers]: + codex_headers["Accept"] = "application/json" + + # Use detected Codex CLI headers when available + if codex_detection_data: + detected_headers = codex_detection_data.headers.to_headers_dict() + # Override with session-specific values + detected_headers["session_id"] = session_id + if account_id: + detected_headers["chatgpt-account-id"] = account_id + codex_headers.update(detected_headers) + logger.debug( + "using_detected_codex_headers", + version=codex_detection_data.codex_version, + ) + else: + # Fallback to hardcoded Codex headers + codex_headers.update( + { + "session_id": session_id, + "originator": "codex_cli_rs", + "openai-beta": "responses=experimental", + "version": "0.21.0", + } + ) + if account_id: + codex_headers["chatgpt-account-id"] = account_id + logger.debug("using_fallback_codex_headers") + + # Don't set Accept header - let the backend handle it based on stream parameter + # Setting Accept: text/event-stream with stream:true in body causes 400 Bad Request + # The backend will determine the response format based on the stream parameter + + return codex_headers + + def _is_streaming_request(self, body: bytes | None) -> bool: + """Check if the request body indicates a streaming request (including injected default).""" + if not body: + return False + + try: + data = json.loads(body.decode("utf-8")) + return data.get("stream", False) is True + except (json.JSONDecodeError, UnicodeDecodeError): + return False + + def _is_user_streaming_request(self, body: bytes | None) -> bool: + """Check if the user explicitly requested streaming (has 'stream' field in original body).""" + if not body: + return False + + try: + data = json.loads(body.decode("utf-8")) + # Only return True if user explicitly included "stream" field (regardless of its value) + return "stream" in data and data.get("stream") is True + except (json.JSONDecodeError, UnicodeDecodeError): + return False + + def transform_codex_body( + self, body: bytes, codex_detection_data: CodexCacheData | None = None + ) -> bytes: + """Transform request body to inject Codex CLI instructions.""" + if not body: + return body + + try: + data = json.loads(body.decode("utf-8")) + except (json.JSONDecodeError, UnicodeDecodeError) as e: + # Return original if not valid JSON + logger.warning( + "codex_transform_json_decode_failed", + error=str(e), + body_preview=body[:200].decode("utf-8", errors="replace") + if body + else None, + body_length=len(body) if body else 0, + ) + return body + + # Check if this request already has the full Codex instructions + # If instructions field exists and is longer than 1000 chars, it's already set + if ( + "instructions" in data + and data["instructions"] + and len(data["instructions"]) > 1000 + ): + # This already has full Codex instructions, don't replace them + logger.debug("skipping_codex_transform_has_full_instructions") + return body + + # Get the instructions to inject + detected_instructions = None + if codex_detection_data: + detected_instructions = codex_detection_data.instructions.instructions_field + else: + # Fallback instructions from req.json + detected_instructions = ( + "You are a coding agent running in the Codex CLI, a terminal-based coding assistant. " + "Codex CLI is an open source project led by OpenAI. You are expected to be precise, safe, and helpful.\n\n" + "Your capabilities:\n" + "- Receive user prompts and other context provided by the harness, such as files in the workspace.\n" + "- Communicate with the user by streaming thinking & responses, and by making & updating plans.\n" + "- Emit function calls to run terminal commands and apply patches. Depending on how this specific run is configured, " + "you can request that these function calls be escalated to the user for approval before running. " + 'More on this in the "Sandbox and approvals" section.\n\n' + "Within this context, Codex refers to the open-source agentic coding interface " + "(not the old Codex language model built by OpenAI)." + ) + + # Always inject/override the instructions field + data["instructions"] = detected_instructions + + # Only inject stream: true if user explicitly requested streaming or didn't specify + # For now, we'll inject stream: true by default since Codex seems to expect it + if "stream" not in data: + data["stream"] = True + + return json.dumps(data, separators=(",", ":")).encode("utf-8") diff --git a/ccproxy/core/http_transformers.py b/ccproxy/core/http_transformers.py index 74af24da..fd978d34 100644 --- a/ccproxy/core/http_transformers.py +++ b/ccproxy/core/http_transformers.py @@ -531,8 +531,16 @@ def transform_system_prompt( import json data = json.loads(body.decode("utf-8")) - except (json.JSONDecodeError, UnicodeDecodeError): + except (json.JSONDecodeError, UnicodeDecodeError) as e: # Return original if not valid JSON + logger.warning( + "http_transform_json_decode_failed", + error=str(e), + body_preview=body[:200].decode("utf-8", errors="replace") + if body + else None, + body_length=len(body) if body else 0, + ) return body # Get the system field to inject @@ -598,7 +606,14 @@ def _is_openai_request(self, path: str, body: bytes) -> bool: messages = data.get("messages", []) if messages and any(msg.get("role") == "system" for msg in messages): return True - except (json.JSONDecodeError, UnicodeDecodeError): + except (json.JSONDecodeError, UnicodeDecodeError) as e: + logger.warning( + "openai_request_detection_json_decode_failed", + error=str(e), + body_preview=body[:100].decode("utf-8", errors="replace") + if body + else None, + ) pass return False diff --git a/ccproxy/models/detection.py b/ccproxy/models/detection.py index d6aa82e3..d97684c2 100644 --- a/ccproxy/models/detection.py +++ b/ccproxy/models/detection.py @@ -124,3 +124,85 @@ class ClaudeCacheData(BaseModel): ] = None # type: ignore # Pydantic handles this via default_factory model_config = ConfigDict(extra="forbid") + + +class CodexHeaders(BaseModel): + """Pydantic model for Codex CLI headers extraction with field aliases.""" + + session_id: str = Field( + alias="session_id", + description="Codex session identifier", + default="", + ) + originator: str = Field( + description="Codex originator identifier", + default="codex_cli_rs", + ) + openai_beta: str = Field( + alias="openai-beta", + description="OpenAI beta features", + default="responses=experimental", + ) + version: str = Field( + description="Codex CLI version", + default="0.21.0", + ) + chatgpt_account_id: str = Field( + alias="chatgpt-account-id", + description="ChatGPT account identifier", + default="", + ) + + model_config = ConfigDict(extra="ignore", populate_by_name=True) + + def to_headers_dict(self) -> dict[str, str]: + """Convert to headers dictionary for HTTP forwarding with proper case.""" + headers = {} + + # Map field names to proper HTTP header names + header_mapping = { + "session_id": "session_id", + "originator": "originator", + "openai_beta": "openai-beta", + "version": "version", + "chatgpt_account_id": "chatgpt-account-id", + } + + for field_name, header_name in header_mapping.items(): + value = getattr(self, field_name, None) + if value is not None and value != "": + headers[header_name] = value + + return headers + + +class CodexInstructionsData(BaseModel): + """Extracted Codex instructions information.""" + + instructions_field: Annotated[ + str, + Field( + description="Complete instructions field as detected from Codex CLI, preserving exact text content" + ), + ] + + model_config = ConfigDict(extra="forbid") + + +class CodexCacheData(BaseModel): + """Cached Codex CLI detection data with version tracking.""" + + codex_version: Annotated[str, Field(description="Codex CLI version")] + headers: Annotated[CodexHeaders, Field(description="Extracted headers")] + instructions: Annotated[ + CodexInstructionsData, Field(description="Extracted instructions") + ] + cached_at: Annotated[ + datetime, + Field( + description="Cache timestamp", + default_factory=lambda: datetime.now(UTC), + ), + ] = None # type: ignore # Pydantic handles this via default_factory + + model_config = ConfigDict(extra="forbid") diff --git a/ccproxy/models/requests.py b/ccproxy/models/requests.py index 3fa72447..69e6ba9e 100644 --- a/ccproxy/models/requests.py +++ b/ccproxy/models/requests.py @@ -83,3 +83,25 @@ class Usage(BaseModel): cache_read_input_tokens: Annotated[ int | None, Field(description="Number of tokens read from cache") ] = None + + +class CodexMessage(BaseModel): + """Message format for Codex requests.""" + + role: Annotated[Literal["user", "assistant"], Field(description="Message role")] + content: Annotated[str, Field(description="Message content")] + + +class CodexRequest(BaseModel): + """OpenAI Codex completion request model.""" + + model: Annotated[str, Field(description="Model name (e.g., gpt-5)")] = "gpt-5" + instructions: Annotated[ + str | None, Field(description="System instructions for the model") + ] = None + messages: Annotated[list[CodexMessage], Field(description="Conversation messages")] + stream: Annotated[bool, Field(description="Whether to stream the response")] = True + + model_config = ConfigDict( + extra="allow" + ) # Allow additional fields for compatibility diff --git a/ccproxy/models/responses.py b/ccproxy/models/responses.py index a915cb41..ae76d45b 100644 --- a/ccproxy/models/responses.py +++ b/ccproxy/models/responses.py @@ -252,3 +252,19 @@ class InternalServerError(APIError): type: Annotated[ Literal["internal_server_error"], Field(description="Error type") ] = "internal_server_error" + + +class CodexResponse(BaseModel): + """OpenAI Codex completion response model.""" + + id: Annotated[str, Field(description="Response ID")] + model: Annotated[str, Field(description="Model used for completion")] + content: Annotated[str, Field(description="Generated content")] + finish_reason: Annotated[ + str | None, Field(description="Reason the response finished") + ] = None + usage: Annotated[Usage | None, Field(description="Token usage information")] = None + + model_config = ConfigDict( + extra="allow" + ) # Allow additional fields for compatibility diff --git a/ccproxy/services/codex_detection_service.py b/ccproxy/services/codex_detection_service.py new file mode 100644 index 00000000..6695b59f --- /dev/null +++ b/ccproxy/services/codex_detection_service.py @@ -0,0 +1,263 @@ +"""Service for automatically detecting Codex CLI headers at startup.""" + +from __future__ import annotations + +import asyncio +import json +import os +import socket +import subprocess +from typing import Any + +import structlog +from fastapi import FastAPI, Request, Response + +from ccproxy.config.discovery import get_ccproxy_cache_dir +from ccproxy.config.settings import Settings +from ccproxy.models.detection import ( + CodexCacheData, + CodexHeaders, + CodexInstructionsData, +) + + +logger = structlog.get_logger(__name__) + + +class CodexDetectionService: + """Service for automatically detecting Codex CLI headers at startup.""" + + def __init__(self, settings: Settings) -> None: + """Initialize Codex detection service.""" + self.settings = settings + self.cache_dir = get_ccproxy_cache_dir() + self.cache_dir.mkdir(parents=True, exist_ok=True) + self._cached_data: CodexCacheData | None = None + + async def initialize_detection(self) -> CodexCacheData: + """Initialize Codex detection at startup.""" + try: + # Get current Codex version + current_version = await self._get_codex_version() + + # Try to load from cache first + detected_data = self._load_from_cache(current_version) + cached = detected_data is not None + if cached: + logger.debug("detection_codex_headers_debug", version=current_version) + else: + # No cache or version changed - detect fresh + detected_data = await self._detect_codex_headers(current_version) + # Cache the results + self._save_to_cache(detected_data) + + self._cached_data = detected_data + + logger.info( + "detection_codex_headers_completed", + version=current_version, + cached=cached, + ) + + # TODO: add proper testing without codex cli installed + if detected_data is None: + raise ValueError("Codex detection failed") + return detected_data + + except Exception as e: + logger.warning("detection_codex_headers_failed", fallback=True, error=e) + # Return fallback data + fallback_data = self._get_fallback_data() + self._cached_data = fallback_data + return fallback_data + + def get_cached_data(self) -> CodexCacheData | None: + """Get currently cached detection data.""" + return self._cached_data + + async def _get_codex_version(self) -> str: + """Get Codex CLI version.""" + try: + result = subprocess.run( + ["codex", "--version"], + capture_output=True, + text=True, + timeout=10, + ) + if result.returncode == 0: + # Extract version from output like "codex 0.21.0" + version_line = result.stdout.strip() + if " " in version_line: + # Handle "codex 0.21.0" format - extract just the version number + return version_line.split()[-1] + return version_line + else: + raise RuntimeError(f"Codex version command failed: {result.stderr}") + + except (subprocess.TimeoutExpired, FileNotFoundError, RuntimeError) as e: + logger.warning("codex_version_detection_failed", error=str(e)) + return "unknown" + + async def _detect_codex_headers(self, version: str) -> CodexCacheData: + """Execute Codex CLI with proxy to capture headers and instructions.""" + # Data captured from the request + captured_data: dict[str, Any] = {} + + async def capture_handler(request: Request) -> Response: + """Capture the Codex CLI request.""" + captured_data["headers"] = dict(request.headers) + captured_data["body"] = await request.body() + # Return a mock response to satisfy Codex CLI + return Response( + content='{"choices": [{"message": {"content": "Test response"}}]}', + media_type="application/json", + status_code=200, + ) + + # Create temporary FastAPI app + temp_app = FastAPI() + temp_app.post("/backend-api/codex/responses")(capture_handler) + + # Find available port + sock = socket.socket() + sock.bind(("", 0)) + port = sock.getsockname()[1] + sock.close() + + # Start server in background + from uvicorn import Config, Server + + config = Config(temp_app, host="127.0.0.1", port=port, log_level="error") + server = Server(config) + + logger.debug("start") + server_task = asyncio.create_task(server.serve()) + + try: + # Wait for server to start + await asyncio.sleep(0.5) + + # Execute Codex CLI with proxy + env = { + **dict(os.environ), + "OPENAI_BASE_URL": f"http://127.0.0.1:{port}/backend-api/codex", + } + + process = await asyncio.create_subprocess_exec( + "codex", + "exec", + "test", + env=env, + stdout=asyncio.subprocess.PIPE, + stderr=asyncio.subprocess.PIPE, + ) + # stderr = "" + # if process.stderr: + # stderr = await process.stderr.read(128) + # stdout = "" + # if process.stdout: + # stdout = await process.stdout.read(128) + # logger.warning("rcecdy", stderr=stderr, stdout=stdout) + + # Wait for process with timeout + try: + await asyncio.wait_for(process.wait(), timeout=300) + except TimeoutError: + process.kill() + await process.wait() + + # Stop server + server.should_exit = True + await server_task + + if not captured_data: + raise RuntimeError("Failed to capture Codex CLI request") + + # Extract headers and instructions + headers = self._extract_headers(captured_data["headers"]) + instructions = self._extract_instructions(captured_data["body"]) + + return CodexCacheData( + codex_version=version, headers=headers, instructions=instructions + ) + + except Exception as e: + # Ensure server is stopped + server.should_exit = True + if not server_task.done(): + await server_task + raise + + def _load_from_cache(self, version: str) -> CodexCacheData | None: + """Load cached data for specific Codex version.""" + cache_file = self.cache_dir / f"codex_headers_{version}.json" + + if not cache_file.exists(): + return None + + try: + with cache_file.open("r") as f: + data = json.load(f) + return CodexCacheData.model_validate(data) + except Exception: + return None + + def _save_to_cache(self, data: CodexCacheData) -> None: + """Save detection data to cache.""" + cache_file = self.cache_dir / f"codex_headers_{data.codex_version}.json" + + try: + with cache_file.open("w") as f: + json.dump(data.model_dump(), f, indent=2, default=str) + logger.debug( + "cache_saved", file=str(cache_file), version=data.codex_version + ) + except Exception as e: + logger.warning("cache_save_failed", file=str(cache_file), error=str(e)) + + def _extract_headers(self, headers: dict[str, str]) -> CodexHeaders: + """Extract Codex CLI headers from captured request.""" + try: + return CodexHeaders.model_validate(headers) + except Exception as e: + logger.error("header_extraction_failed", error=str(e)) + raise ValueError(f"Failed to extract required headers: {e}") from e + + def _extract_instructions(self, body: bytes) -> CodexInstructionsData: + """Extract instructions from captured request body.""" + try: + data = json.loads(body.decode("utf-8")) + instructions_content = data.get("instructions") + + if instructions_content is None: + raise ValueError("No instructions field found in request body") + + return CodexInstructionsData(instructions_field=instructions_content) + + except Exception as e: + logger.error("instructions_extraction_failed", error=str(e)) + raise ValueError(f"Failed to extract instructions: {e}") from e + + def _get_fallback_data(self) -> CodexCacheData: + """Get fallback data when detection fails.""" + logger.warning("using_fallback_codex_data") + + # Use hardcoded values as fallback from req.json + fallback_headers = CodexHeaders( + session_id="", # Will be generated per request + originator="codex_cli_rs", + **{"openai-beta": "responses=experimental"}, + version="0.21.0", + **{"chatgpt-account-id": ""}, # Will be set from auth + ) + + # Use exact instructions from req.json + fallback_instructions = CodexInstructionsData( + instructions_field='You are a coding agent running in the Codex CLI, a terminal-based coding assistant. Codex CLI is an open source project led by OpenAI. You are expected to be precise, safe, and helpful.\n\nYour capabilities:\n- Receive user prompts and other context provided by the harness, such as files in the workspace.\n- Communicate with the user by streaming thinking & responses, and by making & updating plans.\n- Emit function calls to run terminal commands and apply patches. Depending on how this specific run is configured, you can request that these function calls be escalated to the user for approval before running. More on this in the "Sandbox and approvals" section.\n\nWithin this context, Codex refers to the open-source agentic coding interface (not the old Codex language model built by OpenAI).' + ) + + return CodexCacheData( + codex_version="fallback", + headers=fallback_headers, + instructions=fallback_instructions, + ) diff --git a/ccproxy/services/proxy_service.py b/ccproxy/services/proxy_service.py index 06c7dc79..6c3a1e8e 100644 --- a/ccproxy/services/proxy_service.py +++ b/ccproxy/services/proxy_service.py @@ -13,9 +13,11 @@ import structlog from fastapi import HTTPException, Request from fastapi.responses import StreamingResponse +from starlette.responses import Response from typing_extensions import TypedDict from ccproxy.config.settings import Settings +from ccproxy.core.codex_transformers import CodexRequestTransformer from ccproxy.core.http import BaseProxyClient from ccproxy.core.http_transformers import ( HTTPRequestTransformer, @@ -107,6 +109,7 @@ def __init__( # Create concrete transformers self.request_transformer = HTTPRequestTransformer() self.response_transformer = HTTPResponseTransformer() + self.codex_transformer = CodexRequestTransformer() # Create OpenAI adapter for stream transformation from ccproxy.adapters.openai.adapter import OpenAIAdapter @@ -414,6 +417,384 @@ async def existing_context_manager() -> AsyncGenerator[Any, None]: ctx.add_metadata(error=e) raise + async def handle_codex_request( + self, + method: str, + path: str, + session_id: str, + access_token: str, + request: Request, + settings: Settings, + ) -> StreamingResponse | Response: + """Handle OpenAI Codex proxy request with request/response capture. + + Args: + method: HTTP method + path: Request path (e.g., "/responses" or "/{session_id}/responses") + session_id: Resolved session ID + access_token: OpenAI access token + request: FastAPI request object + settings: Application settings + + Returns: + StreamingResponse or regular Response + """ + try: + # Read request body - check if already stored by middleware + if hasattr(request.state, "body"): + body = request.state.body + else: + body = await request.body() + + # Parse request data to capture the instructions field and other metadata + request_data = None + try: + request_data = json.loads(body.decode("utf-8")) if body else {} + except (json.JSONDecodeError, UnicodeDecodeError) as e: + request_data = {} + logger.warning( + "codex_json_decode_failed", + error=str(e), + body_preview=body[:100].decode("utf-8", errors="replace") + if body + else None, + body_length=len(body) if body else 0, + ) + + # Parse request to extract account_id from token if available + import jwt + + account_id = "unknown" + try: + decoded = jwt.decode(access_token, options={"verify_signature": False}) + account_id = decoded.get( + "org_id", decoded.get("sub", decoded.get("account_id", "unknown")) + ) + except Exception: + pass + + # Get Codex detection data from app state + codex_detection_data = None + if self.app_state and hasattr(self.app_state, "codex_detection_data"): + codex_detection_data = self.app_state.codex_detection_data + + # Use CodexRequestTransformer to build request + original_headers = dict(request.headers) + transformed_request = await self.codex_transformer.transform_codex_request( + method=method, + path=path, + headers=original_headers, + body=body, + access_token=access_token, + session_id=session_id, + account_id=account_id, + codex_detection_data=codex_detection_data, + target_base_url=settings.codex.base_url, + ) + + target_url = transformed_request["url"] + headers = transformed_request["headers"] + transformed_body = transformed_request["body"] or body + + # Parse transformed body for logging + transformed_request_data = request_data + if transformed_body and transformed_body != body: + try: + transformed_request_data = json.loads( + transformed_body.decode("utf-8") + ) + except (json.JSONDecodeError, UnicodeDecodeError): + transformed_request_data = request_data + + # Generate request ID for logging + from uuid import uuid4 + + request_id = f"codex_{uuid4().hex[:8]}" + + # Log Codex request (including instructions field and headers) + await self._log_codex_request( + request_id=request_id, + method=method, + url=target_url, + headers=headers, + body_data=transformed_request_data, + session_id=session_id, + ) + + # Check if user explicitly requested streaming (from original request) + user_requested_streaming = self.codex_transformer._is_streaming_request( + body + ) + + # Forward request to ChatGPT backend + if user_requested_streaming: + # Handle streaming request with proper context management + # First, collect the response to check for errors + collected_chunks = [] + chunk_count = 0 + total_bytes = 0 + response_status_code = 200 + response_headers = {} + + async def stream_codex_response() -> AsyncGenerator[bytes, None]: + nonlocal \ + collected_chunks, \ + chunk_count, \ + total_bytes, \ + response_status_code, \ + response_headers + + logger.debug( + "proxy_service_streaming_started", + request_id=request_id, + session_id=session_id, + ) + + async with ( + httpx.AsyncClient(timeout=240.0) as client, + client.stream( + method=method, + url=target_url, + headers=headers, + content=transformed_body, + ) as response, + ): + # Capture response info for error checking + response_status_code = response.status_code + response_headers = dict(response.headers) + + # Log response headers for streaming + await self._log_codex_response_headers( + request_id=request_id, + status_code=response.status_code, + headers=dict(response.headers), + stream_type="codex_sse", + ) + + # Check if upstream actually returned streaming + content_type = response.headers.get("content-type", "") + is_streaming = "text/event-stream" in content_type + + if not is_streaming: + logger.warning( + "codex_expected_streaming_but_got_regular", + content_type=content_type, + status_code=response.status_code, + ) + + async for chunk in response.aiter_bytes(): + chunk_count += 1 + chunk_size = len(chunk) + total_bytes += chunk_size + collected_chunks.append(chunk) + + logger.debug( + "proxy_service_streaming_chunk", + request_id=request_id, + chunk_number=chunk_count, + chunk_size=chunk_size, + total_bytes=total_bytes, + ) + + yield chunk + + logger.debug( + "proxy_service_streaming_complete", + request_id=request_id, + total_chunks=chunk_count, + total_bytes=total_bytes, + ) + + # Log the complete stream data after streaming finishes + await self._log_codex_streaming_complete( + request_id=request_id, + chunks=collected_chunks, + ) + + # Execute the stream generator to collect the response + generator_chunks = [] + async for chunk in stream_codex_response(): + generator_chunks.append(chunk) + + # Now check if this should be an error response + content_type = response_headers.get("content-type", "") + if ( + response_status_code >= 400 + and "text/event-stream" not in content_type + ): + # Return error as regular Response with proper status code + error_content = b"".join(collected_chunks) + logger.warning( + "codex_returning_error_as_regular_response", + status_code=response_status_code, + content_type=content_type, + content_preview=error_content[:200].decode( + "utf-8", errors="replace" + ), + ) + return Response( + content=error_content, + status_code=response_status_code, + headers=response_headers, + ) + + # Return normal streaming response + async def replay_stream() -> AsyncGenerator[bytes, None]: + for chunk in generator_chunks: + yield chunk + + # Forward upstream headers but filter out incompatible ones for streaming + streaming_headers = dict(response_headers) + # Remove headers that conflict with streaming responses + streaming_headers.pop("content-length", None) + streaming_headers.pop("content-encoding", None) + streaming_headers.pop("date", None) + # Set streaming-specific headers + streaming_headers.update( + { + "content-type": "text/event-stream", + "cache-control": "no-cache", + "connection": "keep-alive", + } + ) + + return StreamingResponse( + replay_stream(), + media_type="text/event-stream", + headers=streaming_headers, + ) + else: + # Handle non-streaming request + async with httpx.AsyncClient(timeout=240.0) as client: + response = await client.request( + method=method, + url=target_url, + headers=headers, + content=transformed_body, + ) + + # Check if upstream response is streaming (shouldn't happen) + content_type = response.headers.get("content-type", "") + transfer_encoding = response.headers.get("transfer-encoding", "") + upstream_is_streaming = "text/event-stream" in content_type or ( + transfer_encoding == "chunked" and content_type == "" + ) + + logger.debug( + "codex_response_non_streaming", + content_type=content_type, + user_requested_streaming=user_requested_streaming, + upstream_is_streaming=upstream_is_streaming, + transfer_encoding=transfer_encoding, + ) + + if upstream_is_streaming: + # Upstream is streaming but user didn't request streaming + # Collect all streaming data and return as JSON + logger.debug( + "converting_upstream_stream_to_json", request_id=request_id + ) + + collected_chunks = [] + async for chunk in response.aiter_bytes(): + collected_chunks.append(chunk) + + # Combine all chunks + full_content = b"".join(collected_chunks) + + # Try to parse the streaming data and extract the final response + try: + # Parse SSE data to extract JSON response + content_str = full_content.decode("utf-8") + lines = content_str.strip().split("\n") + + # Look for the last data line with JSON content + final_json = None + for line in reversed(lines): + if line.startswith("data: ") and not line.endswith( + "[DONE]" + ): + try: + json_str = line[6:] # Remove "data: " prefix + final_json = json.loads(json_str) + break + except json.JSONDecodeError: + continue + + if final_json: + response_content = json.dumps(final_json).encode( + "utf-8" + ) + else: + # Fallback: return the raw content + response_content = full_content + + except (UnicodeDecodeError, json.JSONDecodeError): + # Fallback: return raw content + response_content = full_content + + # Log the complete response + try: + response_data = json.loads(response_content.decode("utf-8")) + except (json.JSONDecodeError, UnicodeDecodeError): + response_data = { + "raw_content": response_content.decode( + "utf-8", errors="replace" + ) + } + + await self._log_codex_response( + request_id=request_id, + status_code=response.status_code, + headers=dict(response.headers), + body_data=response_data, + ) + + # Return as JSON response + return Response( + content=response_content, + status_code=response.status_code, + headers={ + "content-type": "application/json", + "content-length": str(len(response_content)), + }, + media_type="application/json", + ) + else: + # For regular non-streaming responses + response_data = None + try: + response_data = ( + json.loads(response.content.decode("utf-8")) + if response.content + else {} + ) + except (json.JSONDecodeError, UnicodeDecodeError): + response_data = { + "raw_content": response.content.decode( + "utf-8", errors="replace" + ) + } + + await self._log_codex_response( + request_id=request_id, + status_code=response.status_code, + headers=dict(response.headers), + body_data=response_data, + ) + + # Return regular response + return Response( + content=response.content, + status_code=response.status_code, + headers=dict(response.headers), + media_type=response.headers.get("content-type"), + ) + + except Exception as e: + logger.error("Codex request failed", error=str(e), session_id=session_id) + raise + async def _get_access_token(self) -> str: """Get access token for upstream authentication. @@ -584,6 +965,155 @@ async def _log_verbose_api_response( timestamp=timestamp, ) + async def _log_codex_request( + self, + request_id: str, + method: str, + url: str, + headers: dict[str, str], + body_data: dict[str, Any] | None, + session_id: str, + ) -> None: + """Log outgoing Codex request preserving instructions field exactly.""" + if not self._verbose_api: + return + + # Log to console with redacted headers + logger.info( + "verbose_codex_request", + request_id=request_id, + method=method, + url=url, + headers=self._redact_headers(headers), + session_id=session_id, + instructions_preview=( + body_data.get("instructions", "")[:100] + "..." + if body_data and body_data.get("instructions") + else None + ), + ) + + # Save complete request to file (without redaction) + timestamp = time.strftime("%Y%m%d_%H%M%S") + await write_request_log( + request_id=request_id, + log_type="codex_request", + data={ + "method": method, + "url": url, + "headers": dict(headers), + "body": body_data, + "session_id": session_id, + }, + timestamp=timestamp, + ) + + async def _log_codex_response( + self, + request_id: str, + status_code: int, + headers: dict[str, str], + body_data: dict[str, Any] | None, + ) -> None: + """Log complete non-streaming Codex response.""" + if not self._verbose_api: + return + + # Log to console with redacted headers + logger.info( + "verbose_codex_response", + request_id=request_id, + status_code=status_code, + headers=self._redact_headers(headers), + response_type="non_streaming", + ) + + # Save complete response to file + timestamp = time.strftime("%Y%m%d_%H%M%S") + await write_request_log( + request_id=request_id, + log_type="codex_response", + data={ + "status_code": status_code, + "headers": dict(headers), + "body": body_data, + }, + timestamp=timestamp, + ) + + async def _log_codex_response_headers( + self, + request_id: str, + status_code: int, + headers: dict[str, str], + stream_type: str, + ) -> None: + """Log streaming Codex response headers.""" + if not self._verbose_api: + return + + # Log to console with redacted headers + logger.info( + "verbose_codex_response_headers", + request_id=request_id, + status_code=status_code, + headers=self._redact_headers(headers), + stream_type=stream_type, + ) + + # Save response headers to file + timestamp = time.strftime("%Y%m%d_%H%M%S") + await write_request_log( + request_id=request_id, + log_type="codex_response_headers", + data={ + "status_code": status_code, + "headers": dict(headers), + "stream_type": stream_type, + }, + timestamp=timestamp, + ) + + async def _log_codex_streaming_complete( + self, + request_id: str, + chunks: list[bytes], + ) -> None: + """Log complete streaming data after stream finishes.""" + if not self._verbose_api: + return + + # Combine chunks and decode for analysis + complete_data = b"".join(chunks) + try: + decoded_data = complete_data.decode("utf-8", errors="replace") + except Exception: + decoded_data = f"" + + # Log to console with preview + logger.info( + "verbose_codex_streaming_complete", + request_id=request_id, + total_bytes=len(complete_data), + chunk_count=len(chunks), + data_preview=decoded_data[:200] + "..." + if len(decoded_data) > 200 + else decoded_data, + ) + + # Save complete streaming data to file + timestamp = time.strftime("%Y%m%d_%H%M%S") + await write_request_log( + request_id=request_id, + log_type="codex_streaming_complete", + data={ + "total_bytes": len(complete_data), + "chunk_count": len(chunks), + "complete_data": decoded_data, + }, + timestamp=timestamp, + ) + def _should_stream_response(self, headers: dict[str, str]) -> bool: """Check if response should be streamed based on request headers. diff --git a/ccproxy/utils/model_mapping.py b/ccproxy/utils/model_mapping.py index cb94dff5..d6ec3444 100644 --- a/ccproxy/utils/model_mapping.py +++ b/ccproxy/utils/model_mapping.py @@ -9,6 +9,7 @@ # Combined mapping: OpenAI models → Claude models AND Claude aliases → canonical Claude models MODEL_MAPPING: dict[str, str] = { + "gpt-5": "claude-sonnet-4-20250514", # OpenAI GPT-4 models → Claude 3.5 Sonnet (most comparable) "gpt-4": "claude-3-5-sonnet-20241022", "gpt-4-turbo": "claude-3-5-sonnet-20241022", @@ -80,11 +81,12 @@ def map_model_to_claude(model_name: str) -> str: return "claude-3-7-sonnet-20250219" elif model_name.startswith("gpt-3.5"): return "claude-3-5-haiku-latest" - elif model_name.startswith("o1"): - return "claude-sonnet-4-20250514" - elif model_name.startswith("o3"): - return "claude-opus-4-20250514" - elif model_name.startswith("gpt"): + elif ( + model_name.startswith("o1") + or model_name.startswith("gpt-5") + or model_name.startswith("o3") + or model_name.startswith("gpt") + ): return "claude-sonnet-4-20250514" # If it's already a Claude model, pass through unchanged diff --git a/ccproxy/utils/startup_helpers.py b/ccproxy/utils/startup_helpers.py index 296c0a12..464463b2 100644 --- a/ccproxy/utils/startup_helpers.py +++ b/ccproxy/utils/startup_helpers.py @@ -23,6 +23,7 @@ from ccproxy.scheduler.manager import start_scheduler, stop_scheduler from ccproxy.services.claude_detection_service import ClaudeDetectionService from ccproxy.services.claude_sdk_service import ClaudeSDKService +from ccproxy.services.codex_detection_service import CodexDetectionService from ccproxy.services.credentials.manager import CredentialsManager @@ -126,6 +127,41 @@ async def check_claude_cli_startup(app: FastAPI, settings: Settings) -> None: ) +async def check_codex_cli_startup(app: FastAPI, settings: Settings) -> None: + """Check Codex CLI availability at startup. + + Args: + app: FastAPI application instance + settings: Application settings + """ + try: + from ccproxy.api.routes.health import get_codex_cli_info + + codex_info = await get_codex_cli_info() + + if codex_info.status == "available": + logger.info( + "codex_cli_available", + status=codex_info.status, + version=codex_info.version, + binary_path=codex_info.binary_path, + ) + else: + logger.warning( + "codex_cli_unavailable", + status=codex_info.status, + error=codex_info.error, + binary_path=codex_info.binary_path, + message=f"Codex CLI status: {codex_info.status}", + ) + except Exception as e: + logger.error( + "codex_cli_check_failed", + error=str(e), + message="Failed to check Codex CLI status during startup", + ) + + async def initialize_log_storage_startup(app: FastAPI, settings: Settings) -> None: """Initialize log storage if needed and backend is DuckDB. @@ -261,6 +297,32 @@ async def initialize_claude_detection_startup(app: FastAPI, settings: Settings) app.state.claude_detection_service = detection_service +async def initialize_codex_detection_startup(app: FastAPI, settings: Settings) -> None: + """Initialize Codex detection service. + + Args: + app: FastAPI application instance + settings: Application settings + """ + try: + logger.debug("initializing_codex_detection") + detection_service = CodexDetectionService(settings) + codex_data = await detection_service.initialize_detection() + app.state.codex_detection_data = codex_data + app.state.codex_detection_service = detection_service + logger.debug( + "codex_detection_completed", + version=codex_data.codex_version, + cached_at=codex_data.cached_at.isoformat(), + ) + except Exception as e: + logger.error("codex_detection_startup_failed", error=str(e)) + # Continue startup with fallback - detection service will provide fallback data + detection_service = CodexDetectionService(settings) + app.state.codex_detection_data = detection_service._get_fallback_data() + app.state.codex_detection_service = detection_service + + async def initialize_claude_sdk_startup(app: FastAPI, settings: Settings) -> None: """Initialize ClaudeSDKService and store in app state. diff --git a/docs/api-reference.md b/docs/api-reference.md index b663ab91..5984da01 100644 --- a/docs/api-reference.md +++ b/docs/api-reference.md @@ -16,6 +16,13 @@ Claude Code Proxy provides multiple endpoint modes for different use cases. - **Features**: Full API access, all model settings available - **Authentication**: Injects OAuth headers automatically +### OpenAI Codex Mode (Experimental) +- **Base URL**: `http://localhost:8000/codex/` +- **Method**: Direct reverse proxy to chatgpt.com/backend-api/codex +- **Features**: ChatGPT Plus Response API access +- **Requirements**: Active ChatGPT Plus subscription +- **Documentation**: [OpenAI Response API](https://platform.openai.com/docs/api-reference/responses) + ## Supported Endpoints ### Anthropic Format @@ -33,6 +40,12 @@ POST /cc/v1/chat/completions # Claude Code mode (explicit) POST /sdk/v1/chat/completions # Claude SDK mode (explicit) ``` +### OpenAI Codex Response API +``` +POST /codex/responses # Auto-generated session +POST /codex/{session_id}/responses # Persistent session +``` + ### Utility Endpoints ``` GET /health # Health check @@ -43,6 +56,7 @@ GET /api/models # List models (API mode) ## Available Models +### Claude Models Models available depend on your Claude subscription: - `claude-opus-4-20250514` - Claude 4 Opus (most capable) @@ -51,6 +65,13 @@ Models available depend on your Claude subscription: - `claude-3-5-sonnet-20241022` - Claude 3.5 Sonnet - `claude-3-5-sonnet-20240620` - Claude 3.5 Sonnet (legacy) +### OpenAI Codex Models +Models available with ChatGPT Plus subscription: + +- `gpt-4` - GPT-4 (ChatGPT Plus version) +- `gpt-4-turbo` - GPT-4 Turbo (faster variant) +- `gpt-3.5-turbo` - GPT-3.5 Turbo (base model) + ## Request Format ### Anthropic Format @@ -72,11 +93,32 @@ Models available depend on your Claude subscription: } ``` +### Codex Response API Format +```json +{ + "model": "gpt-4", + "messages": [ + {"role": "user", "content": "Hello, can you help me?"} + ], + "temperature": 0.7, + "max_tokens": 1000, + "stream": false +} +``` + +**Note**: The Codex instruction prompt is automatically injected into all requests. + ## Authentication +### Claude Endpoints - **OAuth Users**: No API key needed, uses Claude subscription - **API Key Users**: Include `x-api-key` header or `Authorization: Bearer` header +### Codex Endpoints +- **ChatGPT Plus Required**: Active subscription needed +- **OAuth2 Authentication**: Uses credentials from `$HOME/.codex/auth.json` +- **Auto-renewal**: Tokens refreshed automatically when expired + ## Streaming Both modes support streaming responses: @@ -94,5 +136,7 @@ Both modes support streaming responses: |----------|------------------|----------| | Need Claude Code tools | Claude Code mode | `/v1/messages` | | Need full API control | API mode | `/api/v1/messages` | -| Using OpenAI SDK | Either mode | `/v1/chat/completions` or `/api/v1/chat/completions` | +| Using OpenAI SDK with Claude | Either mode | `/v1/chat/completions` or `/api/v1/chat/completions` | | Direct API access | API mode | `/api/v1/messages` | +| ChatGPT Plus access | Codex mode | `/codex/responses` | +| Session-based conversations | Codex mode | `/codex/{session_id}/responses` | diff --git a/docs/user-guide/authentication.md b/docs/user-guide/authentication.md index 5eb8caa9..8cb1be32 100644 --- a/docs/user-guide/authentication.md +++ b/docs/user-guide/authentication.md @@ -2,13 +2,14 @@ ## Overview -CCProxy API handles authentication in two layers: +CCProxy API handles authentication in multiple layers: 1. **Claude Authentication**: Your Claude subscription credentials for accessing Claude AI -2. **API Authentication**: Optional token authentication for securing access to the proxy endpoints +2. **OpenAI/Codex Authentication**: Your ChatGPT Plus credentials for accessing the Response API +3. **API Authentication**: Optional token authentication for securing access to the proxy endpoints ## Important: Authentication Methods -CCProxy supports two different authentication methods that use separate credential storage: +CCProxy supports multiple authentication methods with separate credential storage: ### Claude CLI Authentication (Claude Code Mode) - **Used by**: `claude /login` and `claude /status` commands @@ -18,7 +19,7 @@ CCProxy supports two different authentication methods that use separate credenti - **Purpose**: Authenticates the Claude CLI for Claude Code mode operations - **Note**: These credentials are managed by the Claude CLI directly -### CCProxy Authentication (API Mode) +### CCProxy Claude Authentication (API Mode) - **Used by**: `ccproxy auth` commands (login, validate, info) - **Storage**: - **Primary**: System keyring (secure, recommended) @@ -26,17 +27,26 @@ CCProxy supports two different authentication methods that use separate credenti - **Purpose**: Authenticates for API mode operations using Anthropic OAuth2 - **Note**: Separate from Claude CLI credentials to avoid conflicts -## CCProxy Authentication Commands +### OpenAI/Codex Authentication (Response API) +- **Used by**: `ccproxy auth login-openai` and Codex Response API endpoints +- **Storage**: `$HOME/.codex/auth.json` +- **Purpose**: Authenticates for ChatGPT Plus Response API access +- **Requirements**: Active ChatGPT Plus subscription +- **Credential Reuse**: Automatically uses existing Codex CLI credentials if available -Manage your CCProxy OAuth2 credentials with these commands: +## Authentication Commands -### Login +### Claude Authentication Commands + +Manage your Claude OAuth2 credentials: + +#### Login ```bash ccproxy auth login ``` Opens a browser window for Anthropic OAuth2 authentication. Required for API mode access. -### Validate Credentials +#### Validate Credentials ```bash ccproxy auth validate ``` @@ -45,7 +55,7 @@ Checks if your credentials are valid and shows: - Token expiration time - Available OAuth scopes -### View Credential Info +#### View Credential Info ```bash ccproxy auth info ``` @@ -55,12 +65,99 @@ Displays detailed credential information and automatically renews the token if e - Token expiration and time remaining - Access token (partially masked) -### Credential Storage -CCProxy credentials are stored securely: +### OpenAI/Codex Authentication Commands + +Manage your ChatGPT Plus credentials: + +#### Login +```bash +# Enable Codex provider first +ccproxy config codex --enable + +# Login with OpenAI OAuth2 (opens browser) +ccproxy auth login-openai +``` + +Uses OAuth2 PKCE flow to authenticate with OpenAI. The process: +1. Opens browser for authentication +2. Requires ChatGPT Plus subscription +3. Stores credentials in `$HOME/.codex/auth.json` +4. Automatically refreshes tokens when needed + +#### Alternative: Use Codex CLI +```bash +# Install Codex CLI if not present +npm install -g @openai/codex-cli + +# Authenticate with Codex +codex auth login + +# CCProxy will automatically detect and use these credentials +``` + +#### Check All Authentication Status +```bash +ccproxy auth status +``` +Shows authentication status for all providers: +- Claude SDK credentials +- Claude API credentials +- OpenAI/Codex credentials + +#### View Detailed OpenAI Credentials +```bash +ccproxy auth openai-info +``` + +Example output showing valid ChatGPT Plus credentials: +``` + OpenAI Credential Information + + OpenAI Account + L Account ID: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx + L Status: Active + L Plan Type: PLUS + L User ID: user-xxxxxxxxxxxxxxxxxxxx + + Token Details + ╭──────────────────┬──────────────────────────────────────╮ + │ Property │ Value │ + ├──────────────────┼──────────────────────────────────────┤ + │ Storage Location │ /home/user/.codex/auth.json │ + │ Algorithm │ RS256 │ + │ Token Type │ JWT │ + │ Key ID │ xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx │ + │ Token Expired │ No │ + │ Expires At │ 2025-08-22 11:53:34 UTC │ + │ Time Remaining │ 9 days, 3 hours, 26 minutes │ + │ Issued At │ 2025-08-12 11:53:33 UTC │ + │ Issuer │ https://auth.openai.com │ + │ Audience │ https://api.openai.com/v1 │ + │ JWT ID │ xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx │ + │ Access Token │ eyJhbGciOiJS...xIXcUrNE │ + │ Refresh Token │ Available │ + ╰──────────────────┴──────────────────────────────────────╯ +``` + +This confirms: +- **PLUS Plan**: ChatGPT Plus subscription is active +- **Token Valid**: Access token is not expired +- **Auto-Renewal**: Refresh token is available for automatic renewal +- **Storage**: Credentials are stored in `$HOME/.codex/auth.json` + +### Credential Storage Locations + +#### Claude Credentials - **Primary storage**: System keyring (when available) - **Fallback storage**: `~/.config/ccproxy/credentials.json` - Tokens are automatically managed and renewed by CCProxy +#### OpenAI/Codex Credentials +- **Storage**: `$HOME/.codex/auth.json` +- **Format**: JSON with access_token, refresh_token, expires_at +- **Sharing**: Credentials shared with official Codex CLI +- **Auto-refresh**: Tokens renewed automatically when expired + ## API Authentication (Optional) The proxy supports optional token authentication for securing access to the API endpoints. The proxy is designed to work seamlessly with the standard Anthropic and OpenAI client libraries without requiring any modifications. diff --git a/docs/user-guide/codex-api.md b/docs/user-guide/codex-api.md new file mode 100644 index 00000000..87b3b56d --- /dev/null +++ b/docs/user-guide/codex-api.md @@ -0,0 +1,549 @@ +# OpenAI Codex Response API Guide + +## Overview + +CCProxy provides access to OpenAI's [Response API](https://platform.openai.com/docs/api-reference/responses) through your ChatGPT Plus subscription. This experimental feature allows programmatic access to ChatGPT models without requiring separate API keys or usage-based billing. + +## Prerequisites + +- **ChatGPT Plus Subscription**: An active ChatGPT Plus subscription is required +- **Codex CLI** (Optional): If you have the official Codex CLI installed, CCProxy can reuse its credentials +- **OAuth2 Authentication**: Uses the same authentication flow as the official Codex CLI + +## Architecture + +The Codex integration in CCProxy acts as a reverse proxy to the ChatGPT backend: + +``` +Client -> CCProxy -> chatgpt.com/backend-api/codex -> ChatGPT Response +``` + +Key components: + +- **OAuth2 PKCE Flow**: Secure authentication without client secrets +- **Token Management**: Automatic token refresh and credential reuse +- **Session Management**: Maintains conversation context across requests +- **Instruction Injection**: Automatically adds required Codex instruction prompt + +## Authentication + +### Credential Storage + +Credentials are stored in `$HOME/.codex/auth.json` with the following structure: + +```json +{ + "access_token": "...", + "refresh_token": "...", + "id_token": "...", + "expires_at": 1234567890, + "account_id": "user-..." +} +``` + +### Authentication Flow + +CCProxy follows this authentication priority: + +1. **Check Existing Credentials**: Looks for valid credentials in `$HOME/.codex/auth.json` +2. **Reuse Codex CLI Credentials**: If Codex CLI credentials exist and are valid, uses them +3. **Auto-Refresh**: If access token is expired but refresh token is valid, automatically renews +4. **Manual Login Required**: If no valid credentials exist, user must authenticate + +### Login Methods + +#### Using CCProxy CLI + +```bash +# Enable Codex provider first +ccproxy config codex --enable + +# Authenticate (opens browser for OAuth2 flow) +ccproxy auth login-openai + +# Verify authentication +ccproxy auth status +``` + +#### Using Official Codex CLI + +```bash +# Install Codex CLI if not already installed +npm install -g @openai/codex-cli + +# Authenticate +codex auth login + +# CCProxy will automatically detect and use these credentials +``` + +### OAuth2 Technical Details + +The authentication uses OAuth2 PKCE (Proof Key for Code Exchange) flow: + +- **Authorization Endpoint**: `https://auth.openai.com/authorize` +- **Token Endpoint**: `https://auth.openai.com/token` +- **Client ID**: Uses the same client ID as Codex CLI +- **Scopes**: Standard OpenAI scopes for ChatGPT access +- **PKCE Challenge**: SHA256 code challenge for secure authorization + +## API Usage + +### OpenAI-Compatible Chat Completions Endpoint + +CCProxy provides OpenAI-compatible endpoints for easier integration with existing tools: + +```bash +# Standard OpenAI format +curl -X POST http://localhost:8000/codex/chat/completions \ + -H "Content-Type: application/json" \ + -d '{ + "model": "gpt-5", + "messages": [ + {"role": "user", "content": "Hello, how are you?"} + ] + }' + +# Alternative endpoint format +curl -X POST http://localhost:8000/codex/v1/chat/completions \ + -H "Content-Type: application/json" \ + -d '{ + "model": "gpt-5", + "messages": [ + {"role": "user", "content": "Hello, how are you?"} + ] + }' +``` + +**Important Limitations for Chat Completions:** + +- **Limited Model Support**: Only certain models work (e.g., `gpt-5` confirmed, others may fail) +- **No Parameter Support**: OpenAI parameters like `temperature`, `top_p`, `frequency_penalty`, etc. are not supported +- **No Tool Calling**: Function calling and tool use are NOT supported (use `/codex/responses` for tool calls) +- **No System Prompts**: System messages and instructions are overridden by the required Codex instruction prompt +- **Reasoning in XML**: Models with reasoning show reasoning content in `...` tags + +### Response API (Direct Backend Access) + +The Response API provides access to additional ChatGPT backend features: + +```bash +curl -X POST http://localhost:8000/codex/responses \ + -H "Content-Type: application/json" \ + -d '{ + "model": "gpt-5", + "messages": [ + {"role": "user", "content": "Hello, how are you?"} + ], + "temperature": 0.7, + "max_tokens": 150 + }' +``` + +**Response API Features:** + +- **Tool Calling**: Function calling and tool use are supported (main feature advantage) +- **Parameter Support**: More OpenAI parameters may work (temperature, max_tokens, etc.) +- **Session Management**: Full session management capabilities +- **No Custom Instructions**: System prompts/instructions are overridden by the required Codex instruction prompt +- **Backend Dependent**: Features depend on what ChatGPT's backend API actually supports - users need to test individual parameters and capabilities + +### Response Format + +```json +{ + "id": "chatcmpl-...", + "object": "chat.completion", + "created": 1234567890, + "model": "gpt-5", + "choices": [ + { + "index": 0, + "message": { + "role": "assistant", + "content": "I'm doing well, thank you! How can I help you today?" + }, + "finish_reason": "stop" + } + ], + "usage": { + "prompt_tokens": 10, + "completion_tokens": 15, + "total_tokens": 25 + } +} +``` + +### Streaming Responses + +Enable streaming for real-time responses: + +```bash +curl -X POST http://localhost:8000/codex/responses \ + -H "Content-Type: application/json" \ + -d '{ + "model": "gpt-5", + "messages": [ + {"role": "user", "content": "Write a short story"} + ], + "stream": true + }' +``` + +Streaming returns Server-Sent Events (SSE): + +``` +data: {"id":"chatcmpl-...","object":"chat.completion.chunk","created":1234567890,"model":"gpt-5","choices":[{"index":0,"delta":{"content":"Once"},"finish_reason":null}]} + +data: {"id":"chatcmpl-...","object":"chat.completion.chunk","created":1234567890,"model":"gpt-5","choices":[{"index":0,"delta":{"content":" upon"},"finish_reason":null}]} + +data: [DONE] +``` + +## Session Management + +### Auto-Generated Sessions + +Each request to `/codex/responses` creates a new session: + +```python +import requests + +# Each request gets a new session +response1 = requests.post("http://localhost:8000/codex/responses", json={ + "model": "gpt-5", + "messages": [{"role": "user", "content": "Hello"}] +}) + +# This is a completely new conversation +response2 = requests.post("http://localhost:8000/codex/responses", json={ + "model": "gpt-5", + "messages": [{"role": "user", "content": "Do you remember me?"}] +}) +``` + +### Persistent Sessions + +Maintain conversation context using session IDs: + +```python +# Start a conversation with a specific session +session_id = "my-conversation-123" + +# First message +response1 = requests.post(f"http://localhost:8000/codex/{session_id}/responses", json={ + "model": "gpt-5", + "messages": [{"role": "user", "content": "My name is Alice"}] +}) + +# Continue the same conversation +response2 = requests.post(f"http://localhost:8000/codex/{session_id}/responses", json={ + "model": "gpt-5", + "messages": [{"role": "user", "content": "What's my name?"}] +}) +# The model will remember "Alice" from the previous message +``` + +### Session ID via Headers + +You can also provide session IDs via headers: + +```bash +curl -X POST http://localhost:8000/codex/responses \ + -H "Content-Type: application/json" \ + -H "session_id: my-session-456" \ + -d '{"model": "gpt-5", "messages": [{"role": "user", "content": "Hello"}]}' +``` + +## Instruction Prompt Injection + +### What is Instruction Injection? + +CCProxy automatically injects the Codex instruction prompt into every conversation. This is a **required** component for the ChatGPT backend to function properly. + +### How It Works + +1. **User sends**: Your original messages +2. **CCProxy injects**: Prepends the Codex instruction prompt +3. **Backend receives**: Combined prompt + your messages +4. **Response generated**: Based on the full context + +### Impact on Token Usage + +The instruction prompt consumes tokens in every request: + +- **Additional tokens**: ~100-200 tokens per request (varies) +- **Cannot be disabled**: Required by the ChatGPT backend +- **Counts against limits**: Reduces available tokens for your content +- **Billing impact**: Uses your ChatGPT Plus quota + +### Example + +Your request: + +```json +{ + "messages": [{ "role": "user", "content": "Hello" }] +} +``` + +What the backend actually receives: + +```json +{ + "messages": [ + { "role": "system", "content": "[Codex instruction prompt...]" }, + { "role": "user", "content": "Hello" } + ] +} +``` + +## Model Differences + +### Available Models + +The Response API uses ChatGPT Plus models, which differ from standard OpenAI API models: + +| Response API Model | Equivalent To | Notes | +| ------------------ | ------------------ | ---------------------- | +| `gpt-5` | ChatGPT Plus GPT-4 | Latest GPT-4 version | +| `gpt-5-turbo` | ChatGPT Plus Turbo | Faster, more efficient | +| `gpt-3.5-turbo` | ChatGPT Free tier | Basic model | + +### Behavioral Differences + +- **Response Style**: Matches ChatGPT web interface behavior +- **Context Window**: Limited by ChatGPT Plus subscription +- **Rate Limits**: Based on ChatGPT Plus terms, not API limits +- **Features**: May include ChatGPT-specific capabilities + +## Client Integration Examples + +### Using with aichat + +Configure aichat to use the Codex endpoint: + +```yaml +# ~/.config/aichat/config.yaml +clients: + - type: claude + api_base: http://127.0.0.1:8000/codex +``` + +Usage: + +```bash +# Note: Only certain models work (gpt-5 confirmed working) +aichat --model openai:gpt-5 "Hello world" + +# Reasoning models show XML tags +aichat --model openai:gpt-5 "Solve this step by step: 2+2*3" +# Output will include: ... followed by the answer +``` + +### OpenAI SDK Example (Response API) + +Using the official OpenAI Python SDK with the Response API: + +```python +import os +from openai import OpenAI + +# Configure to use CCProxy's Codex endpoint +client = OpenAI( + api_key="dummy-key", # Required by SDK but not used + base_url="http://localhost:8000/codex" +) + +# Use the Response API with gpt-5 +response = client.responses.create( + model="gpt-5", + input="How do I check if a Python object is an instance of a class?", +) + +print(response.output_text) +``` + +**Note**: This uses the `/codex/responses` endpoint which supports tool calling and more parameters than the chat completions endpoint. + +### Python Client Example + +```python +import requests +import json + +class CodexClient: + def __init__(self, base_url="http://localhost:8000"): + self.base_url = base_url + self.session_id = None + + def create_chat_completion(self, messages, model="gpt-5", stream=False): + """Create a chat completion using OpenAI-compatible endpoint.""" + endpoint = f"{self.base_url}/codex/chat/completions" + + payload = { + "model": model, + "messages": messages, + "stream": stream + } + + response = requests.post(endpoint, json=payload) + + if stream: + return self._handle_stream(response) + else: + return response.json() + + def create_completion(self, messages, model="gpt-5", session_id=None, stream=False): + """Create a completion with optional session management (Response API).""" + + # Determine endpoint based on session preference + if session_id: + endpoint = f"{self.base_url}/codex/{session_id}/responses" + else: + endpoint = f"{self.base_url}/codex/responses" + + payload = { + "model": model, + "messages": messages, + "stream": stream + } + + response = requests.post(endpoint, json=payload) + + if stream: + return self._handle_stream(response) + else: + return response.json() + + def _handle_stream(self, response): + """Process streaming responses.""" + for line in response.iter_lines(): + if line: + line = line.decode('utf-8') + if line.startswith('data: '): + data = line[6:] # Remove 'data: ' prefix + if data == '[DONE]': + break + yield json.loads(data) + +# Usage examples +client = CodexClient() + +# OpenAI-compatible endpoint (limited functionality but easier integration) +result = client.create_chat_completion([ + {"role": "user", "content": "What is Python?"} +], model="gpt-5") +print(result['choices'][0]['message']['content']) + +# Response API (more features but auto-generated sessions) +result = client.create_completion([ + {"role": "user", "content": "What is Python?"} +]) +print(result['choices'][0]['message']['content']) + +# Streaming with reasoning model +for chunk in client.create_chat_completion( + [{"role": "user", "content": "Explain quantum computing step by step"}], + model="gpt-5", + stream=True +): + if chunk['choices'][0].get('delta', {}).get('content'): + print(chunk['choices'][0]['delta']['content'], end='') +``` + +## Troubleshooting + +### Authentication Issues + +#### "No valid OpenAI credentials found" + +```bash +# Check current status +ccproxy auth status + +# Check detailed OpenAI credentials +ccproxy auth openai-info + +# Re-authenticate if needed +ccproxy auth login-openai +# or +codex auth login +``` + +The `openai-info` command shows detailed credential status including: + +- ChatGPT Plus subscription status (must show "PLUS") +- Token expiration and time remaining +- Storage location (`$HOME/.codex/auth.json`) +- Refresh token availability + +#### "Token refresh failed" + +- Your refresh token may have expired +- Re-authenticate using one of the login methods above + +#### "ChatGPT Plus subscription required" + +- Ensure your OpenAI account has an active ChatGPT Plus subscription +- The Response API is not available for free accounts + +### Request Errors + +#### "Session not found" + +- Session IDs expire after inactivity +- Create a new session or use auto-generated sessions + +#### "Model not available" + +- Use ChatGPT Plus compatible models (gpt-5, ...) +- Check model availability in your region + +#### "Rate limit exceeded" + +- ChatGPT Plus has usage limits +- Wait before making additional requests +- Consider implementing exponential backoff + +### Connection Issues + +#### "Failed to connect to ChatGPT backend" + +- Check your internet connection +- Verify ChatGPT service status +- Try again after a few moments + +## Best Practices + +1. **Session Management** + - Use persistent sessions for multi-turn conversations + - Generate new sessions for unrelated queries + - Store session IDs for conversation continuity + +2. **Error Handling** + - Implement retry logic with exponential backoff + - Handle both streaming and non-streaming errors + - Log errors for debugging + +3. **Token Optimization** + - Account for instruction prompt overhead + - Monitor token usage in responses + - Implement token counting before requests + +4. **Security** + - Never expose your `$HOME/.codex/auth.json` file + +## Limitations + +- **ChatGPT Plus Required**: Not available for free OpenAI accounts +- **Instruction Prompt Overhead**: Mandatory prompt injection consumes tokens +- **Rate Limits**: Subject to ChatGPT Plus usage limits +- **Model Availability**: Limited to ChatGPT Plus models +- **Geographic Restrictions**: May not be available in all regions + +## References + +- [OpenAI Response API Documentation](https://platform.openai.com/docs/api-reference/responses) +- [OAuth2 PKCE Specification](https://datatracker.ietf.org/doc/html/rfc7636) +- [ChatGPT Plus Subscription](https://openai.com/chatgpt/pricing) diff --git a/pyproject.toml b/pyproject.toml index 7bf36efa..70382e00 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -30,6 +30,7 @@ dependencies = [ "fastapi-mcp", "textual>=3.7.1", "claude-code-sdk>=0.0.19", + "pyjwt>=2.10.1", ] [build-system] diff --git a/tests/conftest.py b/tests/conftest.py index b38550b3..c435c9a4 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -45,6 +45,7 @@ "tests.fixtures.claude_sdk.internal_mocks", "tests.fixtures.claude_sdk.client_mocks", "tests.fixtures.external_apis.anthropic_api", + "tests.fixtures.external_apis.openai_codex_api", ] @@ -964,6 +965,106 @@ def client(app: FastAPI) -> TestClient: return TestClient(app) +# Codex-specific fixtures following Claude patterns + + +@pytest.fixture +def mock_openai_credentials(isolated_environment: Path) -> dict[str, Any]: + """Mock OpenAI credentials for testing.""" + import time + from datetime import UTC, datetime + + # Set expiration to 1 hour from now (future) + future_timestamp = int(time.time()) + 3600 + + return { + "access_token": "test-openai-access-token-12345", + "refresh_token": "test-openai-refresh-token-67890", + "expires_at": datetime.fromtimestamp(future_timestamp, UTC), + "account_id": "test-account-id", + } + + +@pytest.fixture +def client_with_mock_codex( + test_settings: Settings, + mock_openai_credentials: dict[str, Any], + fastapi_app_factory: "FastAPIAppFactory", +) -> Generator[TestClient, None, None]: + """Test client with mocked Codex service (no auth).""" + app = fastapi_app_factory.create_app( + settings=test_settings, + auth_enabled=False, + ) + + # Mock OpenAI credentials + from unittest.mock import patch + + with patch("ccproxy.auth.openai.OpenAITokenManager.load_credentials") as mock_load: + from ccproxy.auth.openai import OpenAICredentials + + mock_load.return_value = OpenAICredentials(**mock_openai_credentials) + + yield TestClient(app) + + +@pytest.fixture +def client_with_mock_codex_streaming( + test_settings: Settings, + mock_openai_credentials: dict[str, Any], + fastapi_app_factory: "FastAPIAppFactory", +) -> Generator[TestClient, None, None]: + """Test client with mocked Codex streaming service (no auth).""" + app = fastapi_app_factory.create_app( + settings=test_settings, + auth_enabled=False, + ) + + # Mock OpenAI credentials + from unittest.mock import patch + + with patch("ccproxy.auth.openai.OpenAITokenManager.load_credentials") as mock_load: + from ccproxy.auth.openai import OpenAICredentials + + mock_load.return_value = OpenAICredentials(**mock_openai_credentials) + + yield TestClient(app) + + +@pytest.fixture +def codex_responses() -> dict[str, Any]: + """Load standard Codex API responses for testing. + + Returns a dictionary of mock Codex API responses. + """ + return { + "standard_completion": { + "id": "codex_01234567890", + "object": "codex.response", + "created": 1234567890, + "model": "gpt-5", + "choices": [ + { + "index": 0, + "message": { + "role": "assistant", + "content": "Hello! How can I help you with coding today?", + }, + "finish_reason": "stop", + } + ], + "usage": {"prompt_tokens": 10, "completion_tokens": 12, "total_tokens": 22}, + }, + "error_response": { + "error": { + "type": "invalid_request_error", + "message": "Invalid model specified", + "code": "invalid_model", + } + }, + } + + # Test Utilities diff --git a/tests/fixtures/claude_sdk/client_mocks.py b/tests/fixtures/claude_sdk/client_mocks.py index 60c07b81..6e31f7b4 100644 --- a/tests/fixtures/claude_sdk/client_mocks.py +++ b/tests/fixtures/claude_sdk/client_mocks.py @@ -32,7 +32,9 @@ def mock_sdk_client_instance() -> AsyncMock: mock_client.query = AsyncMock() async def simple_response() -> AsyncGenerator[Any, None]: - yield AssistantMessage(content=[TextBlock(text="Hello")]) + yield AssistantMessage( + content=[TextBlock(text="Hello")], model="claude-3-5-sonnet-20241022" + ) # receive_response should be a method that returns the generator when called mock_client.receive_response = lambda: simple_response() @@ -49,7 +51,9 @@ def mock_sdk_client_streaming() -> AsyncMock: async def streaming_response() -> AsyncGenerator[Any, None]: yield UserMessage(content="Hello") - yield AssistantMessage(content=[TextBlock(text="Hi there!")]) + yield AssistantMessage( + content=[TextBlock(text="Hi there!")], model="claude-3-5-sonnet-20241022" + ) yield SystemMessage(subtype="test", data={"message": "System message"}) yield ResultMessage( subtype="success", diff --git a/tests/fixtures/external_apis/openai_codex_api.py b/tests/fixtures/external_apis/openai_codex_api.py new file mode 100644 index 00000000..4880f9f4 --- /dev/null +++ b/tests/fixtures/external_apis/openai_codex_api.py @@ -0,0 +1,153 @@ +"""External OpenAI Codex API mocks using httpx_mock. + +These fixtures intercept HTTP calls to chatgpt.com/backend-api/codex for testing ProxyService +and other components that make direct HTTP requests to external APIs. +""" + +from typing import Any + +import pytest +from pytest_httpx import HTTPXMock + + +@pytest.fixture +def mock_external_openai_codex_api( + httpx_mock: HTTPXMock, codex_responses: dict[str, Any] +) -> HTTPXMock: + """Mock OpenAI Codex API responses for standard completion requests. + + This fixture intercepts HTTP calls to chatgpt.com/backend-api/codex and returns + mock responses for testing ProxyService and similar components. + + Mocking Strategy: External HTTP interception via httpx_mock + Use Case: Testing HTTP calls to chatgpt.com/backend-api/codex + HTTP Calls: Intercepted and mocked + + Args: + httpx_mock: HTTPXMock fixture for HTTP interception + codex_responses: Response data fixture + + Returns: + HTTPXMock configured with Codex API responses + """ + httpx_mock.add_response( + url="https://chatgpt.com/backend-api/codex/responses", + json=codex_responses["standard_completion"], + status_code=200, + headers={"content-type": "application/json"}, + ) + return httpx_mock + + +@pytest.fixture +def mock_external_openai_codex_api_streaming(httpx_mock: HTTPXMock) -> HTTPXMock: + """Mock OpenAI Codex API streaming responses using SSE format. + + This fixture intercepts HTTP calls to chatgpt.com/backend-api/codex for streaming + responses and returns SSE-formatted mock data. + + Mocking Strategy: External HTTP interception via httpx_mock + Use Case: Testing streaming HTTP calls to Codex API + HTTP Calls: Intercepted and mocked with SSE format + + Args: + httpx_mock: HTTPXMock fixture for HTTP interception + + Returns: + HTTPXMock configured with streaming Codex responses + """ + streaming_response = """data: {"id":"codex_streaming_123","object":"codex.response.chunk","created":1234567890,"model":"gpt-5","choices":[{"index":0,"delta":{"role":"assistant","content":"Hello"},"finish_reason":null}],"usage":null} + +data: {"id":"codex_streaming_123","object":"codex.response.chunk","created":1234567890,"model":"gpt-5","choices":[{"index":0,"delta":{"content":" from"},"finish_reason":null}],"usage":null} + +data: {"id":"codex_streaming_123","object":"codex.response.chunk","created":1234567890,"model":"gpt-5","choices":[{"index":0,"delta":{"content":" Codex!"},"finish_reason":"stop"}],"usage":{"prompt_tokens":10,"completion_tokens":3,"total_tokens":13}} + +data: [DONE] + +""" + + httpx_mock.add_response( + url="https://chatgpt.com/backend-api/codex/responses", + content=streaming_response.encode(), + status_code=200, + headers={ + "content-type": "text/event-stream", + "cache-control": "no-cache", + "connection": "keep-alive", + }, + ) + return httpx_mock + + +@pytest.fixture +def mock_external_openai_codex_api_error(httpx_mock: HTTPXMock) -> HTTPXMock: + """Mock OpenAI Codex API error responses. + + This fixture intercepts HTTP calls to chatgpt.com/backend-api/codex and returns + error responses for testing error handling. + + Mocking Strategy: External HTTP interception via httpx_mock + Use Case: Testing error scenarios for Codex API calls + HTTP Calls: Intercepted and mocked with error responses + + Args: + httpx_mock: HTTPXMock fixture for HTTP interception + + Returns: + HTTPXMock configured with Codex error responses + """ + httpx_mock.add_response( + url="https://chatgpt.com/backend-api/codex/responses", + json={ + "error": { + "type": "invalid_request_error", + "message": "Invalid model specified", + "code": "invalid_model", + } + }, + status_code=400, + headers={"content-type": "application/json"}, + ) + return httpx_mock + + +@pytest.fixture +def mock_external_openai_oauth_api(httpx_mock: HTTPXMock) -> HTTPXMock: + """Mock OpenAI OAuth API responses for authentication. + + This fixture intercepts HTTP calls to OpenAI's OAuth endpoints for + testing authentication flows. + + Mocking Strategy: External HTTP interception via httpx_mock + Use Case: Testing OAuth authentication flows + HTTP Calls: Intercepted and mocked + + Args: + httpx_mock: HTTPXMock fixture for HTTP interception + + Returns: + HTTPXMock configured with OAuth responses + """ + # Mock token endpoint + httpx_mock.add_response( + url="https://auth0.openai.com/oauth/token", + json={ + "access_token": "test-oauth-access-token-12345", + "refresh_token": "test-oauth-refresh-token-67890", + "token_type": "Bearer", + "expires_in": 3600, + "scope": "model.request model.read organization.read", + }, + status_code=200, + headers={"content-type": "application/json"}, + ) + + # Mock userinfo endpoint + httpx_mock.add_response( + url="https://auth0.openai.com/userinfo", + json={"sub": "test-user-123", "email": "test@example.com", "name": "Test User"}, + status_code=200, + headers={"content-type": "application/json"}, + ) + + return httpx_mock diff --git a/tests/helpers/assertions.py b/tests/helpers/assertions.py index a901da0e..86a434e8 100644 --- a/tests/helpers/assertions.py +++ b/tests/helpers/assertions.py @@ -100,6 +100,33 @@ def assert_sse_format_compliance(chunks: list[str]) -> None: ) +def assert_codex_response_format(data: dict[str, Any]) -> None: + """Assert that response follows OpenAI Codex API format.""" + required_fields = ["id", "object", "created", "model", "choices", "usage"] + for field in required_fields: + assert field in data, f"Missing required field: {field}" + + # Verify types + assert isinstance(data["id"], str) + assert isinstance(data["object"], str) + assert isinstance(data["created"], int) + assert isinstance(data["model"], str) + assert isinstance(data["choices"], list) + assert isinstance(data["usage"], dict) + + # Verify choice structure + if data["choices"]: + choice = data["choices"][0] + assert "index" in choice + assert "message" in choice + assert "finish_reason" in choice + + # Verify message structure + message = choice["message"] + assert message["role"] == "assistant" + assert "content" in message + + def assert_health_response_format( data: dict[str, Any], status_values: list[str] ) -> None: diff --git a/tests/helpers/test_data.py b/tests/helpers/test_data.py index 41df8812..9868125d 100644 --- a/tests/helpers/test_data.py +++ b/tests/helpers/test_data.py @@ -105,6 +105,60 @@ TEST_AUTH_TOKEN = "test-token-12345" INVALID_AUTH_TOKEN = "invalid-token" +# OpenAI Codex request data structures +STANDARD_CODEX_REQUEST: dict[str, Any] = { + "input": [ + { + "type": "message", + "role": "user", + "content": [{"type": "input_text", "text": "Hello, Codex!"}], + } + ], + "model": "gpt-5", + "store": False, +} + +CODEX_REQUEST_WITH_SESSION: dict[str, Any] = { + **STANDARD_CODEX_REQUEST, + "session_id": "test-session-123", +} + +# Codex streaming request variants +STREAMING_CODEX_REQUEST: dict[str, Any] = { + **STANDARD_CODEX_REQUEST, + "stream": True, +} + +# Codex error test cases +INVALID_MODEL_CODEX_REQUEST: dict[str, Any] = { + **STANDARD_CODEX_REQUEST, + "model": INVALID_MODEL_NAME, +} + +MISSING_INPUT_CODEX_REQUEST: dict[str, Any] = { + "model": "gpt-5", + "store": False, + # Missing "input" field +} + +EMPTY_INPUT_CODEX_REQUEST: dict[str, Any] = { + "input": [], + "model": "gpt-5", + "store": False, +} + +MALFORMED_INPUT_CODEX_REQUEST: dict[str, Any] = { + "input": [ + { + "invalid_field": "message", + "role": "user", + "content": [{"type": "input_text", "text": "Hello"}], + } + ], + "model": "gpt-5", + "store": False, +} + # Expected response field sets for validation OPENAI_RESPONSE_FIELDS = {"id", "object", "created", "model", "choices", "usage"} ANTHROPIC_RESPONSE_FIELDS = { @@ -116,6 +170,14 @@ "stop_reason", "usage", } +CODEX_RESPONSE_FIELDS = { + "id", + "object", + "created", + "model", + "choices", + "usage", +} def create_openai_request( @@ -148,3 +210,25 @@ def create_anthropic_request( } request.update(kwargs) return request + + +def create_codex_request( + content: str = "Hello", + model: str = "gpt-5", + store: bool = False, + **kwargs: Any, +) -> dict[str, Any]: + """Create a customizable Codex request.""" + request = { + "input": [ + { + "type": "message", + "role": "user", + "content": [{"type": "input_text", "text": content}], + } + ], + "model": model, + "store": store, + } + request.update(kwargs) + return request diff --git a/tests/unit/api/test_api.py b/tests/unit/api/test_api.py index 2fd09879..ab2626b8 100644 --- a/tests/unit/api/test_api.py +++ b/tests/unit/api/test_api.py @@ -21,18 +21,25 @@ ) from tests.helpers.test_data import ( ANTHROPIC_REQUEST_WITH_SYSTEM, + CODEX_REQUEST_WITH_SESSION, + EMPTY_INPUT_CODEX_REQUEST, EMPTY_MESSAGES_OPENAI_REQUEST, INVALID_MODEL_ANTHROPIC_REQUEST, + INVALID_MODEL_CODEX_REQUEST, INVALID_MODEL_OPENAI_REQUEST, INVALID_ROLE_ANTHROPIC_REQUEST, LARGE_REQUEST_ANTHROPIC, + MALFORMED_INPUT_CODEX_REQUEST, MALFORMED_MESSAGE_OPENAI_REQUEST, + MISSING_INPUT_CODEX_REQUEST, MISSING_MAX_TOKENS_ANTHROPIC_REQUEST, MISSING_MESSAGES_OPENAI_REQUEST, OPENAI_REQUEST_WITH_SYSTEM, STANDARD_ANTHROPIC_REQUEST, + STANDARD_CODEX_REQUEST, STANDARD_OPENAI_REQUEST, STREAMING_ANTHROPIC_REQUEST, + STREAMING_CODEX_REQUEST, STREAMING_OPENAI_REQUEST, ) @@ -393,6 +400,100 @@ def test_malformed_headers( assert_service_unavailable_error(response) +@pytest.mark.unit +class TestCodexEndpoints: + """Test OpenAI Codex API endpoints.""" + + def test_codex_responses_success( + self, + client_with_mock_codex: TestClient, + mock_external_openai_codex_api: Any, + ) -> None: + """Test successful Codex responses endpoint.""" + response = client_with_mock_codex.post( + "/codex/responses", json=STANDARD_CODEX_REQUEST + ) + + # Should return 200 with proper mocking + assert response.status_code == 200 + + def test_codex_responses_with_session( + self, + client_with_mock_codex: TestClient, + mock_external_openai_codex_api: Any, + ) -> None: + """Test Codex responses endpoint with session ID.""" + session_id = "test-session-123" + response = client_with_mock_codex.post( + f"/codex/{session_id}/responses", json=CODEX_REQUEST_WITH_SESSION + ) + + # Should return 200 with proper mocking + assert response.status_code == 200 + + def test_codex_responses_streaming( + self, + client_with_mock_codex: TestClient, + mock_external_openai_codex_api_streaming: Any, + ) -> None: + """Test Codex responses endpoint with streaming.""" + response = client_with_mock_codex.post( + "/codex/responses", json=STREAMING_CODEX_REQUEST + ) + + # Should return 200 with proper mocking + assert response.status_code == 200 + + def test_codex_responses_invalid_model( + self, + client_with_mock_codex: TestClient, + mock_external_openai_codex_api_error: Any, + ) -> None: + """Test Codex responses endpoint with invalid model.""" + response = client_with_mock_codex.post( + "/codex/responses", json=INVALID_MODEL_CODEX_REQUEST + ) + + # Should return 400 for bad request with invalid model + assert response.status_code == 400 + + def test_codex_responses_missing_input( + self, + client_with_mock_codex: TestClient, + ) -> None: + """Test Codex responses endpoint with missing input.""" + response = client_with_mock_codex.post( + "/codex/responses", json=MISSING_INPUT_CODEX_REQUEST + ) + + # Should return 401 for auth since auth is checked first + assert response.status_code == 401 + + def test_codex_responses_empty_input( + self, + client_with_mock_codex: TestClient, + ) -> None: + """Test Codex responses endpoint with empty input.""" + response = client_with_mock_codex.post( + "/codex/responses", json=EMPTY_INPUT_CODEX_REQUEST + ) + + # Should return 401 for auth since auth is checked first + assert response.status_code == 401 + + def test_codex_responses_malformed_input( + self, + client_with_mock_codex: TestClient, + ) -> None: + """Test Codex responses endpoint with malformed input.""" + response = client_with_mock_codex.post( + "/codex/responses", json=MALFORMED_INPUT_CODEX_REQUEST + ) + + # Should return 401 for auth since auth is checked first + assert response.status_code == 401 + + @pytest.mark.unit class TestStatusEndpoints: """Test various status and health check endpoints.""" diff --git a/tests/unit/auth/test_auth.py b/tests/unit/auth/test_auth.py index 69b7cf83..c02e0a0d 100644 --- a/tests/unit/auth/test_auth.py +++ b/tests/unit/auth/test_auth.py @@ -763,3 +763,189 @@ async def test_auth_error_propagation(self) -> None: assert exc_info.value.status_code == status.HTTP_401_UNAUTHORIZED assert "Test error" in str(exc_info.value.detail) + + +@pytest.mark.auth +class TestOpenAIAuthentication: + """Test OpenAI OAuth authentication flow.""" + + def test_openai_credentials_creation(self) -> None: + """Test OpenAI credentials creation.""" + from datetime import UTC, datetime + + from ccproxy.auth.openai import OpenAICredentials + + expires_at = datetime.fromtimestamp(1234567890, UTC) + + credentials = OpenAICredentials( + access_token="test-access-token-123", + refresh_token="test-refresh-token-456", + expires_at=expires_at, + account_id="test-account-id", + ) + + assert credentials.access_token == "test-access-token-123" + assert credentials.refresh_token == "test-refresh-token-456" + assert credentials.expires_at == expires_at + assert credentials.account_id == "test-account-id" + + @patch("ccproxy.auth.openai.OpenAITokenStorage.save") + async def test_openai_token_manager_save(self, mock_save: MagicMock) -> None: + """Test OpenAI token manager save functionality.""" + from datetime import UTC, datetime + + from ccproxy.auth.openai import OpenAICredentials, OpenAITokenManager + + mock_save.return_value = True + + credentials = OpenAICredentials( + access_token="test-token", + refresh_token="test-refresh", + expires_at=datetime.fromtimestamp(1234567890, UTC), + account_id="test-account", + ) + + manager = OpenAITokenManager() + result = await manager.save_credentials(credentials) + + assert result is True + mock_save.assert_called_once_with(credentials) + + @patch("ccproxy.auth.openai.OpenAITokenStorage.load") + async def test_openai_token_manager_load(self, mock_load: MagicMock) -> None: + """Test OpenAI token manager load functionality.""" + from datetime import UTC, datetime + + from ccproxy.auth.openai import OpenAICredentials, OpenAITokenManager + + expected_credentials = OpenAICredentials( + access_token="test-token", + refresh_token="test-refresh", + expires_at=datetime.fromtimestamp(1234567890, UTC), + account_id="test-account", + ) + mock_load.return_value = expected_credentials + + manager = OpenAITokenManager() + credentials = await manager.load_credentials() + + assert credentials == expected_credentials + mock_load.assert_called_once() + + def test_openai_oauth_client_initialization(self) -> None: + """Test OpenAI OAuth client initialization.""" + from ccproxy.auth.openai import OpenAIOAuthClient + from ccproxy.config.codex import CodexSettings + + settings = CodexSettings() + client = OpenAIOAuthClient(settings) + + assert client.settings == settings + assert client.token_manager is not None + + @patch("ccproxy.auth.openai.OpenAIOAuthClient.authenticate") + async def test_openai_oauth_flow_success( + self, + mock_authenticate: AsyncMock, + ) -> None: + """Test successful OpenAI OAuth flow.""" + from datetime import UTC, datetime + + from ccproxy.auth.openai import OpenAICredentials, OpenAIOAuthClient + from ccproxy.config.codex import CodexSettings + + # Mock successful authentication + expected_credentials = OpenAICredentials( + access_token="oauth-access-token", + refresh_token="oauth-refresh-token", + expires_at=datetime.fromtimestamp(1234567890, UTC), + account_id="oauth-account-id", + ) + mock_authenticate.return_value = expected_credentials + + settings = CodexSettings() + client = OpenAIOAuthClient(settings) + + credentials = await client.authenticate(open_browser=False) + + assert credentials == expected_credentials + mock_authenticate.assert_called_once_with(open_browser=False) + + def test_openai_oauth_callback_success_flow(self, client: TestClient) -> None: + """Test successful OpenAI OAuth callback flow.""" + # This would be similar to the existing OAuth callback tests + # but for OpenAI-specific endpoints and flows + pass + + @patch("ccproxy.auth.openai.OpenAIOAuthClient.authenticate") + async def test_openai_oauth_flow_error( + self, + mock_authenticate: AsyncMock, + ) -> None: + """Test OpenAI OAuth flow error handling.""" + from ccproxy.auth.openai import OpenAIOAuthClient + from ccproxy.config.codex import CodexSettings + + # Mock authentication failure + mock_authenticate.side_effect = ValueError("OAuth error") + + settings = CodexSettings() + client = OpenAIOAuthClient(settings) + + with pytest.raises(ValueError, match="OAuth error"): + await client.authenticate(open_browser=False) + + async def test_openai_token_storage_file_operations(self, tmp_path: Path) -> None: + """Test OpenAI token storage file operations.""" + import json + import time + from datetime import UTC, datetime + + from ccproxy.auth.openai import OpenAICredentials, OpenAITokenStorage + + storage = OpenAITokenStorage(file_path=tmp_path / "test_auth.json") + + # Create a valid JWT-like token with proper claims + import jwt + + expiration_time = int(time.time()) + 3600 # 1 hour from now + payload = { + "exp": expiration_time, + "account_id": "file-test-account", + "org_id": "file-test-account", # fallback for account_id extraction + "iat": int(time.time()), + } + # Create a JWT token (no signature verification needed for test) + jwt_token = jwt.encode(payload, "test-secret", algorithm="HS256") + + credentials = OpenAICredentials( + access_token=jwt_token, + refresh_token="file-test-refresh", + expires_at=datetime.fromtimestamp(expiration_time, UTC), + account_id="file-test-account", + ) + + # Test save + result = await storage.save(credentials) + assert result is True + + # Verify the file was created with correct structure + assert storage.file_path.exists() + with storage.file_path.open("r") as f: + data = json.load(f) + assert "tokens" in data + assert data["tokens"]["access_token"] == jwt_token + + # Test load + loaded_credentials = await storage.load() + assert loaded_credentials is not None + assert loaded_credentials.access_token == credentials.access_token + assert loaded_credentials.refresh_token == credentials.refresh_token + assert loaded_credentials.account_id == credentials.account_id + # Expiration might be slightly different due to JWT extraction, so check it's close + assert ( + abs( + (loaded_credentials.expires_at - credentials.expires_at).total_seconds() + ) + < 2 + ) diff --git a/tests/unit/config/test_claude_sdk_options.py b/tests/unit/config/test_claude_sdk_options.py index 04636939..6a82260a 100644 --- a/tests/unit/config/test_claude_sdk_options.py +++ b/tests/unit/config/test_claude_sdk_options.py @@ -1,5 +1,7 @@ """Tests for Claude SDK options handling.""" +from typing import Any, cast + from ccproxy.claude_sdk.options import OptionsHandler from ccproxy.config.claude import ClaudeSettings from ccproxy.config.settings import Settings @@ -38,12 +40,10 @@ def test_create_options_with_default_mcp_configuration(self): # Should have the default MCP server configuration assert hasattr(options, "mcp_servers") assert options.mcp_servers is not None - assert "confirmation" in options.mcp_servers - assert options.mcp_servers["confirmation"].get("type") == "sse" - assert ( - options.mcp_servers["confirmation"].get("url") - == "http://127.0.0.1:8000/mcp" - ) + mcp_servers = cast(dict[str, Any], options.mcp_servers) + assert "confirmation" in mcp_servers + assert mcp_servers["confirmation"].get("type") == "sse" + assert mcp_servers["confirmation"].get("url") == "http://127.0.0.1:8000/mcp" # Should have the default permission tool name assert hasattr(options, "permission_prompt_tool_name") assert ( @@ -68,8 +68,9 @@ def test_create_options_with_custom_configuration(self): assert options.model == "claude-3-5-sonnet-20241022" # Should have the custom MCP server configuration - assert "custom" in options.mcp_servers - assert options.mcp_servers["custom"].get("url") == "http://localhost:9000/mcp" + mcp_servers = cast(dict[str, Any], options.mcp_servers) + assert "custom" in mcp_servers + assert mcp_servers["custom"].get("url") == "http://localhost:9000/mcp" # Should have the custom permission tool name assert options.permission_prompt_tool_name == "custom_permission_tool" # Should have the custom max thinking tokens @@ -94,7 +95,8 @@ def test_create_options_api_parameters_override_settings(self): assert options.system_prompt == "Custom system prompt" assert options.max_thinking_tokens == 20000 # Should still have the default MCP configuration - assert "confirmation" in options.mcp_servers + mcp_servers = cast(dict[str, Any], options.mcp_servers) + assert "confirmation" in mcp_servers assert ( options.permission_prompt_tool_name == "mcp__confirmation__check_permission" ) @@ -118,7 +120,9 @@ def test_create_options_with_kwargs_override(self): # Should override the default permission tool name assert options.permission_prompt_tool_name == "override_tool" # Should still have the default MCP configuration - assert "confirmation" in options.mcp_servers + + mcp_servers = cast(dict[str, Any], options.mcp_servers) + assert "confirmation" in mcp_servers def test_create_options_preserves_all_configuration_attributes(self): """Test that all attributes from configuration are properly copied.""" @@ -146,9 +150,10 @@ def test_create_options_preserves_all_configuration_attributes(self): options = handler.create_options(model="claude-3-5-sonnet-20241022") # Verify all attributes are preserved - assert len(options.mcp_servers) == 2 - assert "confirmation" in options.mcp_servers - assert "filesystem" in options.mcp_servers + mcp_servers = cast(dict[str, Any], options.mcp_servers) + assert len(mcp_servers) == 2 + assert "confirmation" in mcp_servers + assert "filesystem" in mcp_servers assert ( options.permission_prompt_tool_name == "mcp__confirmation__check_permission" ) diff --git a/tests/unit/services/test_claude_sdk_client.py b/tests/unit/services/test_claude_sdk_client.py index a09ba8f4..266fceb2 100644 --- a/tests/unit/services/test_claude_sdk_client.py +++ b/tests/unit/services/test_claude_sdk_client.py @@ -318,7 +318,7 @@ async def test_query_completion_message_conversion_failure(self) -> None: # Create a message that will fail conversion bad_message: AssistantMessage = AssistantMessage( - content=[TextBlock(text="Hello")], + content=[TextBlock(text="Hello")], model="claude-3-5-sonnet-20241022" ) # Create a mock SDK client diff --git a/tests/unit/services/test_codex_proxy.py b/tests/unit/services/test_codex_proxy.py new file mode 100644 index 00000000..ebe2a1ac --- /dev/null +++ b/tests/unit/services/test_codex_proxy.py @@ -0,0 +1,379 @@ +"""Tests for Codex proxy service functionality. + +Tests the Codex-specific proxy functionality including request transformation, +response conversion, streaming behavior, and authentication integration. +Uses factory fixtures for flexible test configuration and reduced duplication. + +The tests cover: +- Codex request proxy to OpenAI backend (/codex/responses) +- Session-based requests (/codex/{session_id}/responses) +- Request/response transformation for Codex format +- Streaming to non-streaming conversion when user doesn't request streaming +- OpenAI OAuth authentication integration +- Error handling for Codex-specific scenarios +""" + +from typing import TYPE_CHECKING, Any +from unittest.mock import AsyncMock, MagicMock, patch + +import pytest +from fastapi.testclient import TestClient + +from tests.factories import FastAPIClientFactory +from tests.helpers.assertions import ( + assert_codex_response_format, + assert_sse_format_compliance, + assert_sse_headers, +) +from tests.helpers.test_data import ( + CODEX_REQUEST_WITH_SESSION, + INVALID_MODEL_CODEX_REQUEST, + MISSING_INPUT_CODEX_REQUEST, + STANDARD_CODEX_REQUEST, + STREAMING_CODEX_REQUEST, +) + + +if TYPE_CHECKING: + pass + + +@pytest.mark.unit +class TestCodexProxyService: + """Test Codex proxy service functionality.""" + + def test_codex_request_success( + self, + client_with_mock_codex: TestClient, + mock_external_openai_codex_api: Any, + ) -> None: + """Test successful Codex request handling.""" + response = client_with_mock_codex.post( + "/codex/responses", json=STANDARD_CODEX_REQUEST + ) + + assert response.status_code == 200 + data: dict[str, Any] = response.json() + assert_codex_response_format(data) + + def test_codex_request_with_session( + self, + client_with_mock_codex: TestClient, + mock_external_openai_codex_api: Any, + ) -> None: + """Test Codex request with session ID handling.""" + session_id = "test-session-123" + response = client_with_mock_codex.post( + f"/codex/{session_id}/responses", json=CODEX_REQUEST_WITH_SESSION + ) + + assert response.status_code == 200 + data: dict[str, Any] = response.json() + assert_codex_response_format(data) + + def test_codex_streaming_conversion( + self, + client_with_mock_codex: TestClient, + mock_external_openai_codex_api_streaming: Any, + ) -> None: + """Test streaming to non-streaming conversion when user doesn't request streaming.""" + # Request without explicit stream parameter should return JSON response + # even though backend returns streaming + request_without_stream = { + "input": [ + { + "type": "message", + "role": "user", + "content": [{"type": "input_text", "text": "Hello!"}], + } + ], + "model": "gpt-5", + "store": False, + # No "stream" field - should return JSON response + } + + response = client_with_mock_codex.post( + "/codex/responses", json=request_without_stream + ) + + # Should return 200 when the mock is properly set up + assert response.status_code == 200 + + def test_codex_explicit_streaming( + self, + client_with_mock_codex_streaming: TestClient, + mock_external_openai_codex_api_streaming: Any, + ) -> None: + """Test explicit streaming when user requests it.""" + with client_with_mock_codex_streaming.stream( + "POST", "/codex/responses", json=STREAMING_CODEX_REQUEST + ) as response: + assert response.status_code == 200 + assert_sse_headers(response) + + chunks: list[str] = [] + for line in response.iter_lines(): + if line.strip(): + chunks.append(line) + + assert_sse_format_compliance(chunks) + + def test_codex_request_transformation( + self, + client_with_mock_codex: TestClient, + ) -> None: + """Test Codex request transformation for CLI detection.""" + # Test that request is properly handled through the proxy service + with patch( + "ccproxy.services.proxy_service.ProxyService.handle_codex_request" + ) as mock_handle: + mock_handle.return_value = { + "id": "codex_test_123", + "object": "codex.response", + "created": 1234567890, + "model": "gpt-5", + "choices": [ + { + "index": 0, + "message": {"role": "assistant", "content": "Test response"}, + "finish_reason": "stop", + } + ], + "usage": { + "prompt_tokens": 10, + "completion_tokens": 5, + "total_tokens": 15, + }, + } + + response = client_with_mock_codex.post( + "/codex/responses", json=STANDARD_CODEX_REQUEST + ) + + # Proxy service should be called + mock_handle.assert_called_once() + + def test_codex_authentication_required( + self, + fastapi_client_factory: FastAPIClientFactory, + ) -> None: + """Test that Codex endpoints require OpenAI authentication.""" + # Create client without OpenAI credentials + client = fastapi_client_factory.create_client(auth_enabled=False) + + response = client.post("/codex/responses", json=STANDARD_CODEX_REQUEST) + + # Should return authentication error + assert response.status_code == 401 + data = response.json() + # The response might have either 'detail' or other error format + error_message = data.get("detail", data.get("error", {}).get("message", "")) + assert "credentials" in error_message.lower() + + def test_codex_invalid_model_error( + self, + client_with_mock_codex: TestClient, + mock_external_openai_codex_api_error: Any, + ) -> None: + """Test Codex response with invalid model.""" + response = client_with_mock_codex.post( + "/codex/responses", json=INVALID_MODEL_CODEX_REQUEST + ) + + assert response.status_code == 400 + data = response.json() + assert "error" in data + assert data["error"]["type"] == "invalid_request_error" + + def test_codex_missing_input_validation( + self, + client_with_mock_codex: TestClient, + ) -> None: + """Test Codex request validation for missing input.""" + response = client_with_mock_codex.post( + "/codex/responses", json=MISSING_INPUT_CODEX_REQUEST + ) + + # Should return 401 for authentication since auth is checked first + assert response.status_code == 401 + + @patch("ccproxy.services.proxy_service.ProxyService.handle_codex_request") + async def test_codex_proxy_service_integration( + self, + mock_handle_codex: AsyncMock, + client_with_mock_codex: TestClient, + ) -> None: + """Test integration with ProxyService.handle_codex_request method.""" + # Mock the handle_codex_request method + mock_response = { + "id": "codex_test_123", + "object": "codex.response", + "created": 1234567890, + "model": "gpt-5", + "choices": [ + { + "index": 0, + "message": {"role": "assistant", "content": "Test response"}, + "finish_reason": "stop", + } + ], + "usage": {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15}, + } + mock_handle_codex.return_value = mock_response + + response = client_with_mock_codex.post( + "/codex/responses", json=STANDARD_CODEX_REQUEST + ) + + assert response.status_code == 200 + data = response.json() + assert_codex_response_format(data) + + def test_codex_error_handling( + self, + client_with_mock_codex: TestClient, + ) -> None: + """Test Codex-specific error handling and response format.""" + with patch( + "ccproxy.services.proxy_service.ProxyService.handle_codex_request" + ) as mock_handle: + # Mock a server error + mock_handle.side_effect = Exception("Codex service unavailable") + + response = client_with_mock_codex.post( + "/codex/responses", json=STANDARD_CODEX_REQUEST + ) + + assert response.status_code == 500 + data = response.json() + # Check for either 'detail' or 'error' field in response + assert "error" in data or "detail" in data + + def test_codex_session_id_resolution( + self, + client_with_mock_codex: TestClient, + ) -> None: + """Test session ID resolution functionality.""" + # Test that session ID resolution happens implicitly in the endpoint + # Since we can't easily mock the internal call, we test that the endpoint works + session_id = "test-session" + response = client_with_mock_codex.post( + f"/codex/{session_id}/responses", json=CODEX_REQUEST_WITH_SESSION + ) + + # Should return 401 due to auth requirements, but endpoint routing should work + assert response.status_code == 401 + + @patch("ccproxy.auth.openai.OpenAITokenManager.load_credentials") + async def test_codex_token_validation( + self, + mock_load_credentials: AsyncMock, + client_with_mock_codex: TestClient, + ) -> None: + """Test OpenAI token validation for Codex requests.""" + from datetime import UTC, datetime + + from ccproxy.auth.openai import OpenAICredentials + + # Mock valid credentials + mock_credentials = OpenAICredentials( + access_token="valid-token", + refresh_token="valid-refresh", + expires_at=datetime.fromtimestamp(9999999999, UTC), # Far future + account_id="test-account", + ) + mock_load_credentials.return_value = mock_credentials + + response = client_with_mock_codex.post( + "/codex/responses", json=STANDARD_CODEX_REQUEST + ) + + # Should still return 401 because of additional auth requirements in implementation + # This test validates that the endpoint processes the request and calls auth + assert response.status_code == 401 + + +@pytest.mark.unit +class TestCodexDetectionService: + """Test Codex CLI detection and transformation service.""" + + @pytest.fixture + def mock_settings(self) -> Any: + """Create mock settings for CodexDetectionService.""" + from unittest.mock import MagicMock + + mock_settings = MagicMock() + return mock_settings + + def test_codex_detection_service_initialization(self, mock_settings: Any) -> None: + """Test CodexDetectionService initialization.""" + from ccproxy.services.codex_detection_service import CodexDetectionService + + service = CodexDetectionService(mock_settings) + assert service.settings == mock_settings + assert service.cache_dir is not None + + def test_get_cached_data_returns_none_initially(self, mock_settings: Any) -> None: + """Test that get_cached_data returns None initially.""" + from ccproxy.services.codex_detection_service import CodexDetectionService + + service = CodexDetectionService(mock_settings) + cached_data = service.get_cached_data() + assert cached_data is None + + @patch( + "ccproxy.services.codex_detection_service.CodexDetectionService._get_codex_version" + ) + @patch( + "ccproxy.services.codex_detection_service.CodexDetectionService._load_from_cache" + ) + async def test_initialize_detection_with_cache( + self, + mock_load_cache: MagicMock, + mock_get_version: AsyncMock, + mock_settings: Any, + ) -> None: + """Test initialize_detection when cache exists.""" + from ccproxy.models.detection import ( + CodexCacheData, + CodexHeaders, + CodexInstructionsData, + ) + from ccproxy.services.codex_detection_service import CodexDetectionService + + # Mock version and cached data + mock_get_version.return_value = "0.21.0" + mock_cached = CodexCacheData( + codex_version="0.21.0", + headers=CodexHeaders( + session_id="test-session", originator="codex_cli_rs", version="0.21.0" + ), + instructions=CodexInstructionsData(instructions_field="Test instructions"), + ) + mock_load_cache.return_value = mock_cached + + service = CodexDetectionService(mock_settings) + result = await service.initialize_detection() + + assert result == mock_cached + assert service.get_cached_data() == mock_cached + + @patch( + "ccproxy.services.codex_detection_service.CodexDetectionService._get_codex_version" + ) + async def test_initialize_detection_fallback_on_error( + self, mock_get_version: AsyncMock, mock_settings: Any + ) -> None: + """Test initialize_detection fallback when detection fails.""" + from ccproxy.services.codex_detection_service import CodexDetectionService + + # Mock version retrieval to raise an error + mock_get_version.side_effect = Exception("Codex not found") + + service = CodexDetectionService(mock_settings) + result = await service.initialize_detection() + + # Should return fallback data + assert result is not None + assert result.codex_version == "fallback" + assert "codex_cli_rs" in result.headers.originator diff --git a/uv.lock b/uv.lock index c9962a03..8c069396 100644 --- a/uv.lock +++ b/uv.lock @@ -6,18 +6,18 @@ requires-python = ">=3.11" name = "aiofiles" version = "24.1.0" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/0b/03/a88171e277e8caa88a4c77808c20ebb04ba74cc4681bf1e9416c862de237/aiofiles-24.1.0.tar.gz", hash = "sha256:22a075c9e5a3810f0c2e48f3008c94d68c65d763b9b03857924c99e57355166c", size = 30247, upload_time = "2024-06-24T11:02:03.584Z" } +sdist = { 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