Clean up documentation to reflect current implementation
Remove confusing references to unimplemented features and clarify what's currently working vs prepared for future integration. README.md Changes: - Update title to reflect mock API (not "with Ollama Backend") - Remove architecture diagram showing Ollama/PydanticAI integration - Clarify current status section (mock API, integration prepared) - Fix uvicorn command: main:app → src.main:app - Update model examples: llama2 → mistral-nemo:latest - Mark Ollama requirements as future (not currently needed) - Update environment variables (Ollama config commented out) - Clarify API endpoints return mock responses - Update CVE check date: 2025-12-05 → 2025-12-06 - Fix testing section to use requirements-dev.txt - Remove Ollama troubleshooting (not connected yet) - Mark production Ollama considerations as future - Remove redundant changelog section (use CHANGELOG.md) AGENTS.md Changes: - Clarify project overview (mock API, not integrated) - Add status indicators to components section - Mark PydanticAI section as "for future implementation" - Mark Ollama section as "ready for future integration" - Add target model: mistral-nemo:latest - Update OpenAI compatibility section with implemented status - Fix Pydantic version: 2.10+ → 2.11+ (matches requirements) - Add implementation status to development guidelines - Mark common patterns as implemented vs future reference - Update CVE check date: 2025-12-05 → 2025-12-06 CHANGELOG.md Changes: - Clarify PydanticAI line: "for LLM integration" → "dependency (ready for future integration)" Key Improvements: - Clear distinction between implemented vs prepared features - No misleading references to Ollama/PydanticAI integration - Accurate model names (mistral-nemo:latest) - Correct command examples (src.main:app) - Proper date stamps (2025-12-06) - Removed confusing troubleshooting for unconnected services Status: Documentation now accurately reflects v0.1.0 mock API 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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# OpenAI-Compatible API with Ollama Backend
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# OpenAI-Compatible API
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A FastAPI-based service that provides an OpenAI-compatible API endpoint, powered by PydanticAI and Ollama for LLM inference.
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A FastAPI-based service that provides OpenAI-compatible API endpoints with streaming support. Currently returns mock responses - ready for future Ollama/PydanticAI integration.
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## Architecture
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## Current Status
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```
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┌─────────────┐ ┌──────────────────┐ ┌─────────────┐
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│ Client │─────▶│ FastAPI Server │─────▶│ Ollama │
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│ │◀─────│ (Stream Coord.) │◀─────│ Container │
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└─────────────┘ └──────────────────┘ └─────────────┘
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│
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▼
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┌──────────┐
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│Pydantic │
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│ AI │
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└──────────┘
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```
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**✅ Production-ready mock API** with OpenAI-compatible format
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**🚧 Ollama/PydanticAI integration** prepared but not connected
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### Components
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## Components
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- **FastAPI**: High-performance web framework providing the API layer
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- **Stream Coordinator**: Manages streaming responses in OpenAI-compatible format
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- **PydanticAI**: Agent framework handling LLM integration and structured outputs
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- **Ollama**: External LLM backend (networked, managed separately)
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- **SSE-Starlette**: Server-Sent Events for streaming responses
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- **Pydantic**: Type-safe request/response handling and validation
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- **Ollama Client**: Async HTTP client prepared for future integration
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- **PydanticAI**: Ready for LLM integration (not yet connected)
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## Features
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- OpenAI-compatible API endpoints
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- Streaming responses with Server-Sent Events
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- PydanticAI integration for robust LLM interactions
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- Networked Ollama support
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- Type-safe request/response handling with Pydantic
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- Async/await throughout for optimal performance
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- ✅ OpenAI-compatible API endpoints (`/v1/chat/completions`, `/v1/models`)
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- ✅ Streaming responses with Server-Sent Events (SSE)
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- ✅ Type-safe request/response handling with Pydantic
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- ✅ Async/await throughout for optimal performance
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- ✅ Comprehensive test suite (62% coverage)
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- ✅ Domain-based architecture following FastAPI best practices
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- 🚧 Ollama integration (client ready, not connected)
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- 🚧 PydanticAI integration (dependency installed, not connected)
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## Requirements
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- Python 3.12+ (Python 3.12.11 recommended for security)
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- Network access to an existing Ollama instance (managed externally)
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- No external dependencies required for mock API
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- (Future: Network access to Ollama instance for LLM integration)
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## Installation
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@@ -61,32 +54,32 @@ source venv/bin/activate # On Windows: venv\Scripts\activate
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pip install -r requirements.txt
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```
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### 4. Configure environment variables
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### 4. Configure environment variables (Optional)
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Create a `.env` file in the project root:
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Create a `.env` file in the project root for custom configuration:
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```env
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# Ollama Configuration (point to your existing Ollama instance)
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OLLAMA_HOST=http://your-ollama-host:11434
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OLLAMA_MODEL=llama2
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# API Configuration
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API_HOST=0.0.0.0
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API_PORT=8000
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API_RELOAD=true
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# Logging
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LOG_LEVEL=info
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LOG_LEVEL=INFO
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# Future Ollama Configuration (not yet integrated)
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# OLLAMA_HOST=http://localhost:11434
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# OLLAMA_DEFAULT_MODEL=mistral-nemo:latest
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# OLLAMA_TIMEOUT=120
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```
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**Note**: Update `OLLAMA_HOST` to point to your existing Ollama instance. Ensure the Ollama service is accessible from your network and has the required models installed.
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**Note**: The API works with defaults. Environment variables are optional for customization. Ollama configuration is prepared but not currently used.
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## Usage
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### Start the development server
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```bash
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uvicorn main:app --reload
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uvicorn src.main:app --reload
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```
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The API will be available at `http://localhost:8000`
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@@ -95,11 +88,13 @@ The API will be available at `http://localhost:8000`
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#### Chat Completions (OpenAI-compatible)
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Returns mock lorem ipsum responses:
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```bash
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curl http://localhost:8000/v1/chat/completions \
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-H "Content-Type: application/json" \
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-d '{
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"model": "llama2",
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"model": "mistral-nemo:latest",
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"messages": [
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{"role": "user", "content": "Hello, how are you?"}
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],
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@@ -109,10 +104,14 @@ curl http://localhost:8000/v1/chat/completions \
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#### List Models
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Returns mock model listing:
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```bash
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curl http://localhost:8000/v1/models
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```
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Response: `{"object": "list", "data": [{"id": "mistral-nemo:latest", ...}]}`
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### Interactive API Documentation
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- Swagger UI: `http://localhost:8000/docs`
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@@ -124,11 +123,11 @@ curl http://localhost:8000/v1/models
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This project uses minor version locking (`>=X.Y,<X.(Y+1)`) to protect against supply chain attacks while allowing patch updates. All dependencies have been:
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- Checked for known CVEs (as of 2025-12-05)
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- Checked for known CVEs (as of 2025-12-06)
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- Pinned to secure minor versions
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- Documented with version rationale in `requirements.txt`
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### CVE Status (2025-12-05)
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### CVE Status (2025-12-06)
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- **FastAPI 0.123.9**: No known vulnerabilities
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- **Uvicorn 0.38.0**: No known vulnerabilities
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@@ -228,10 +227,15 @@ The API is currently set up with **mock responses** for development:
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```bash
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# Install test dependencies
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pip install pytest pytest-asyncio httpx
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pip install -r requirements-dev.txt
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# Run tests
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pytest
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# Run tests with coverage
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pytest --cov=src --cov-report=term-missing
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# Current coverage: 62%
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```
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## Documentation
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@@ -257,27 +261,28 @@ docker-compose up -d
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- Set up monitoring and logging
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- Use a process manager (systemd/supervisor)
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- Configure proper resource limits
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- Ensure reliable network connectivity to Ollama instance
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- Consider Ollama failover/redundancy strategies
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- (Future) Ensure reliable network connectivity to Ollama instance
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- (Future) Consider Ollama failover/redundancy strategies
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## Troubleshooting
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### Common Issues
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**Issue**: Cannot connect to Ollama
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- Verify `OLLAMA_HOST` in `.env` points to the correct address
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- Ensure the Ollama instance is running and accessible
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- Check network connectivity and firewall rules
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- Test connectivity: `curl http://your-ollama-host:11434/api/tags`
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**Issue**: Import errors
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- Ensure virtual environment is activated
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- Reinstall dependencies: `pip install -r requirements.txt`
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- Verify Python 3.12+ is being used
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**Issue**: Streaming not working
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- Verify SSE-Starlette is installed
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- Check client supports Server-Sent Events
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- Review browser/tool compatibility
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- Check test suite: `pytest tests/chat/test_router.py -k streaming`
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**Issue**: Import errors
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- Ensure virtual environment is activated
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- Reinstall dependencies: `pip install -r requirements.txt`
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**Issue**: Tests failing
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- Install test dependencies: `pip install -r requirements-dev.txt`
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- Check async test configuration in `pytest.ini`
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- Run with verbose output: `pytest -v`
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## Contributing
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@@ -291,14 +296,7 @@ docker-compose up -d
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[Add your license here]
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## Changelog
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### 2025-12-05 - Initial Setup
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- Project structure created
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- Dependencies configured with CVE checks
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- Security: Minor version locking implemented
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- Documentation added
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---
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For detailed changelog, see [CHANGELOG.md](CHANGELOG.md).
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For AI assistant instructions and package documentation, see [AGENTS.md](AGENTS.md).
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