From 62edb111bdb560821e9bdea212356855cfc43a2b Mon Sep 17 00:00:00 2001 From: Jeroen Schweitzer Date: Sat, 6 Dec 2025 11:07:19 +0100 Subject: [PATCH] Clean up documentation to reflect current implementation MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 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 --- AGENTS.md | 119 ++++++++++++++++++++++++++++++++------------------- CHANGELOG.md | 2 +- README.md | 114 ++++++++++++++++++++++++------------------------ 3 files changed, 131 insertions(+), 104 deletions(-) diff --git a/AGENTS.md b/AGENTS.md index 75f2bb7..d134b7a 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -4,12 +4,18 @@ This document contains instructions and documentation references for AI assistan ## Project Overview -This project implements an OpenAI-compatible API endpoint using FastAPI, with streaming support for LLM responses. The architecture consists of: +This project implements an OpenAI-compatible API endpoint using FastAPI, with streaming support. Currently returns mock responses - infrastructure prepared for future Ollama/PydanticAI integration. + +**Current State**: Production-ready mock API with OpenAI-compatible format +**Future Integration**: Ollama and PydanticAI (client code ready, not connected) + +### Components - **FastAPI**: Web framework for the API layer -- **PydanticAI**: Agent framework for LLM integration -- **Ollama**: LLM backend running on a networked container -- **Stream Coordinator**: Manages streaming responses in OpenAI-compatible format +- **SSE-Starlette**: Server-Sent Events for streaming responses +- **Pydantic**: Request/response validation +- **PydanticAI**: Dependency installed, ready for future LLM integration +- **Ollama**: Async client implemented, ready for future connection ## Documentation References @@ -40,7 +46,8 @@ This project implements an OpenAI-compatible API endpoint using FastAPI, with st #### PydanticAI - **Official Documentation**: https://ai.pydantic.dev/ - **Version**: 1.27.0 (Dec 2025) -- **Key Topics**: +- **Status**: Dependency installed, ready for future integration +- **Key Topics** (for future implementation): - Agent creation and configuration - LLM provider integration (Ollama support) - Structured outputs with Pydantic @@ -53,7 +60,7 @@ This project implements an OpenAI-compatible API endpoint using FastAPI, with st #### Pydantic - **Official Documentation**: https://docs.pydantic.dev/latest/ -- **Version**: 2.10+ (Required for PydanticAI) +- **Version**: 2.11+ (Required for PydanticAI, currently using >=2.11,<2.13) - **Key Topics**: - Data validation and serialization - Field types and validators @@ -83,25 +90,31 @@ This project implements an OpenAI-compatible API endpoint using FastAPI, with st #### Ollama API - **Official Documentation**: https://github.com/ollama/ollama/blob/main/docs/api.md -- **Key Topics**: +- **Status**: Async client implemented in `src/ollama/client.py`, ready for future integration +- **Key Topics** (for future implementation): - REST API endpoints - Streaming responses - Model management - Generate and chat endpoints - Model configuration +- **Current Model Target**: mistral-nemo:latest ### OpenAI API Compatibility #### OpenAI API Reference - **Official Documentation**: https://platform.openai.com/docs/api-reference -- **Key Endpoints to Implement**: - - `/v1/chat/completions` - Chat completion with streaming - - `/v1/models` - List available models - - `/v1/completions` - Text completion (legacy) -- **Key Features**: - - Streaming with Server-Sent Events - - Message format compatibility - - Response structure compatibility +- **Implemented Endpoints**: + - ✅ `/v1/chat/completions` - Chat completion with streaming (mock responses) + - ✅ `/v1/models` - List available models (mock listing) +- **Future Endpoints**: + - 🚧 `/v1/completions` - Text completion (legacy) + - 🚧 `/v1/embeddings` - Text embeddings +- **Implemented Features**: + - ✅ Streaming with Server-Sent Events + - ✅ Message format compatibility + - ✅ Response structure compatibility + - ✅ OpenAI error format + - ✅ Request validation with Pydantic ## FastAPI Best Practices @@ -270,55 +283,68 @@ app = create_application() ## Development Guidelines -### Code Structure -- Use async/await for ALL I/O operations (database, HTTP, file access) -- Use sync (def) for blocking SDKs or CPU-intensive work -- Implement proper error handling and logging -- Follow dependency injection for validation and shared resources -- Use Pydantic models for ALL request/response validation -- Keep business logic in service modules, not routers +### Code Structure (Current Implementation) +- ✅ Use async/await for ALL I/O operations (database, HTTP, file access) +- ✅ Use sync (def) for blocking SDKs or CPU-intensive work +- ✅ Implement proper error handling and logging +- ✅ Follow dependency injection for validation and shared resources +- ✅ Use Pydantic models for ALL request/response validation +- ✅ Keep business logic in service modules, not routers +- ✅ Domain-based project structure (not file-type based) ### Security Considerations -- Validate all inputs using Pydantic models -- Implement rate limiting for API endpoints -- Use environment variables for sensitive configuration -- Keep dependencies updated (check for CVEs regularly) +- ✅ Validate all inputs using Pydantic models +- ✅ Use environment variables for sensitive configuration +- ✅ Keep dependencies updated (all CVE-checked as of 2025-12-06) +- ✅ Minor version locking for supply chain protection +- 🚧 Implement rate limiting for API endpoints (future) +- 🚧 Add authentication/API keys (future) -### Testing -- Write integration tests for API endpoints -- Test streaming functionality thoroughly -- Mock Ollama responses for unit tests -- Validate OpenAI API compatibility +### Testing (Current Coverage: 62%) +- ✅ Integration tests for API endpoints +- ✅ Streaming functionality with 20s timeout protection +- ✅ Async test support with pytest-asyncio +- ✅ Validate OpenAI API compatibility +- ✅ Mock responses for all endpoints +- 🚧 Future: Mock Ollama responses when integrated ### Configuration -- Use `.env` files for local development -- Document all environment variables in README -- Provide sensible defaults where possible -- Support container-based configuration +- ✅ Use `.env` files for local development +- ✅ Document all environment variables in README +- ✅ Provide sensible defaults where possible +- ✅ BaseSettings from pydantic-settings +- 🚧 Support container-based configuration (future) ## Common Patterns -### Streaming Response Pattern +### Streaming Response Pattern (✅ Implemented) + +See `src/chat/router.py` for the current implementation: + ```python from sse_starlette.sse import EventSourceResponse from fastapi import FastAPI async def event_generator(): - # Stream events from Ollama/PydanticAI - yield {"data": "chunk1"} - yield {"data": "chunk2"} + # Currently yields mock lorem ipsum chunks + # Future: Stream from Ollama/PydanticAI + yield {"data": chunk.model_dump_json()} + yield {"data": "[DONE]"} -@app.get("/stream") +@app.post("/stream") async def stream(): return EventSourceResponse(event_generator()) ``` -### PydanticAI Agent Pattern +### PydanticAI Agent Pattern (🚧 Future Reference) + +For future integration when connecting to Ollama: + ```python from pydantic_ai import Agent agent = Agent( - 'ollama:llama2', # Or other Ollama model + 'ollama:mistral-nemo', # Target model # Configuration here ) @@ -326,13 +352,16 @@ agent = Agent( result = await agent.run('Your prompt') ``` -### OpenAI-Compatible Response Format +### OpenAI-Compatible Response Format (✅ Implemented) + +Current implementation in `src/chat/schemas.py`: + ```python { "id": "chatcmpl-123", "object": "chat.completion.chunk", "created": 1234567890, - "model": "model-name", + "model": "mistral-nemo:latest", "choices": [{ "index": 0, "delta": {"content": "response"}, @@ -349,4 +378,4 @@ This document should be updated when: - Breaking API changes occur - Security vulnerabilities are discovered -Last updated: 2025-12-05 +Last updated: 2025-12-06 diff --git a/CHANGELOG.md b/CHANGELOG.md index 6a5c789..b076d3a 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -33,7 +33,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 - Project initialization - Python 3.12.11 environment - FastAPI 0.123.9 web framework -- PydanticAI 1.27.0 for LLM integration +- PydanticAI 1.27.0 dependency (ready for future integration) - Mock chat completions (lorem ipsum responses) - Mock model listing (mistral-nemo:latest) - Testing infrastructure (pytest, coverage, ruff, mypy) diff --git a/README.md b/README.md index ac51b34..81763f5 100644 --- a/README.md +++ b/README.md @@ -1,43 +1,36 @@ -# OpenAI-Compatible API with Ollama Backend +# OpenAI-Compatible API -A FastAPI-based service that provides an OpenAI-compatible API endpoint, powered by PydanticAI and Ollama for LLM inference. +A FastAPI-based service that provides OpenAI-compatible API endpoints with streaming support. Currently returns mock responses - ready for future Ollama/PydanticAI integration. -## Architecture +## Current Status -``` -┌─────────────┐ ┌──────────────────┐ ┌─────────────┐ -│ Client │─────▶│ FastAPI Server │─────▶│ Ollama │ -│ │◀─────│ (Stream Coord.) │◀─────│ Container │ -└─────────────┘ └──────────────────┘ └─────────────┘ - │ - ▼ - ┌──────────┐ - │Pydantic │ - │ AI │ - └──────────┘ -``` +**✅ Production-ready mock API** with OpenAI-compatible format +**🚧 Ollama/PydanticAI integration** prepared but not connected -### Components +## Components - **FastAPI**: High-performance web framework providing the API layer -- **Stream Coordinator**: Manages streaming responses in OpenAI-compatible format -- **PydanticAI**: Agent framework handling LLM integration and structured outputs -- **Ollama**: External LLM backend (networked, managed separately) - **SSE-Starlette**: Server-Sent Events for streaming responses +- **Pydantic**: Type-safe request/response handling and validation +- **Ollama Client**: Async HTTP client prepared for future integration +- **PydanticAI**: Ready for LLM integration (not yet connected) ## Features -- OpenAI-compatible API endpoints -- Streaming responses with Server-Sent Events -- PydanticAI integration for robust LLM interactions -- Networked Ollama support -- Type-safe request/response handling with Pydantic -- Async/await throughout for optimal performance +- ✅ OpenAI-compatible API endpoints (`/v1/chat/completions`, `/v1/models`) +- ✅ Streaming responses with Server-Sent Events (SSE) +- ✅ Type-safe request/response handling with Pydantic +- ✅ Async/await throughout for optimal performance +- ✅ Comprehensive test suite (62% coverage) +- ✅ Domain-based architecture following FastAPI best practices +- 🚧 Ollama integration (client ready, not connected) +- 🚧 PydanticAI integration (dependency installed, not connected) ## Requirements - Python 3.12+ (Python 3.12.11 recommended for security) -- Network access to an existing Ollama instance (managed externally) +- No external dependencies required for mock API +- (Future: Network access to Ollama instance for LLM integration) ## Installation @@ -61,32 +54,32 @@ source venv/bin/activate # On Windows: venv\Scripts\activate pip install -r requirements.txt ``` -### 4. Configure environment variables +### 4. Configure environment variables (Optional) -Create a `.env` file in the project root: +Create a `.env` file in the project root for custom configuration: ```env -# Ollama Configuration (point to your existing Ollama instance) -OLLAMA_HOST=http://your-ollama-host:11434 -OLLAMA_MODEL=llama2 - # API Configuration API_HOST=0.0.0.0 API_PORT=8000 -API_RELOAD=true # Logging -LOG_LEVEL=info +LOG_LEVEL=INFO + +# Future Ollama Configuration (not yet integrated) +# OLLAMA_HOST=http://localhost:11434 +# OLLAMA_DEFAULT_MODEL=mistral-nemo:latest +# OLLAMA_TIMEOUT=120 ``` -**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. +**Note**: The API works with defaults. Environment variables are optional for customization. Ollama configuration is prepared but not currently used. ## Usage ### Start the development server ```bash -uvicorn main:app --reload +uvicorn src.main:app --reload ``` The API will be available at `http://localhost:8000` @@ -95,11 +88,13 @@ The API will be available at `http://localhost:8000` #### Chat Completions (OpenAI-compatible) +Returns mock lorem ipsum responses: + ```bash curl http://localhost:8000/v1/chat/completions \ -H "Content-Type: application/json" \ -d '{ - "model": "llama2", + "model": "mistral-nemo:latest", "messages": [ {"role": "user", "content": "Hello, how are you?"} ], @@ -109,10 +104,14 @@ curl http://localhost:8000/v1/chat/completions \ #### List Models +Returns mock model listing: + ```bash curl http://localhost:8000/v1/models ``` +Response: `{"object": "list", "data": [{"id": "mistral-nemo:latest", ...}]}` + ### Interactive API Documentation - Swagger UI: `http://localhost:8000/docs` @@ -124,11 +123,11 @@ curl http://localhost:8000/v1/models This project uses minor version locking (`>=X.Y,