Add optional Prompture integration for 12+ LLM providers (LM Studio,
Ollama, Claude, Groq, Kimi/Moonshot, etc.) as a drop-in backend.
Zero breaking changes — falls back to the existing OpenAI SDK client
when Prompture is not installed.
- Rewrite llm_client.py with dual-backend architecture
- Update .env.example with provider/model format examples
- Add multi-provider table to README Quick Start section
- Add prompture as optional dependency in requirements.txt
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Deleted docker-compose.yml, backend Dockerfile, frontend Dockerfile, and nginx configuration to streamline project setup.
- Updated .env.example to reorganize LLM and ZEP API configurations for clarity and ease of use.
- Enhanced README.md to reflect changes in project structure and provide clearer setup instructions.
- Updated .env.example to reflect new LLM configuration with Aliyun's API.
- Enhanced .gitignore to include additional files and directories for better exclusion of sensitive and build artifacts.
- Added docker-compose.yml for streamlined deployment of backend and frontend services.
- Introduced Dockerfiles for both backend and frontend to facilitate containerized builds.
- Created README.md to provide comprehensive project documentation and setup instructions.
- Established nginx configuration for frontend to support API proxying and static file serving.
- Updated .env.example to include new keys for dual LLM configuration, allowing for both general and boost settings.
- Modified create_model function to support an optional use_boost parameter, enabling the selection of either general or boost LLM configurations based on availability.
- Improved logging to indicate which LLM configuration is being used during model creation, enhancing clarity for users.
Juan Denis
666ghj