Context-Engine
Verified Safeby m1rl0k
Overview
A Retrieval-Augmented Generation (RAG) stack for codebases, enabling context-aware AI agents for developers and IDEs through unified code indexing, hybrid search, and local LLM integration.
Installation
docker compose up -dEnvironment Variables
- QDRANT_URL
- COLLECTION_NAME
- EMBEDDING_MODEL
- LLAMACPP_URL
- GLM_API_KEY
- QDRANT_API_KEY
- REFRAG_DECODER
- RERANKER_ONNX_PATH
- RERANKER_TOKENIZER_PATH
- FASTMCP_HOST
- FASTMCP_INDEXER_PORT
- FASTMCP_PORT
- USE_GPU_DECODER
- MICRO_BUDGET_TOKENS
Security Notes
The project uses `subprocess` to execute Python scripts, which is safe if commands and arguments are controlled. Input validation and path sanitization (e.g., preventing directory traversal in `qdrant_index` and `upload_service`) are critical for security. The `upload_service` handles incoming tar archives, requiring robust validation to prevent malicious file uploads. `_ast.literal_eval` is used for lenient argument parsing but is generally safer than `eval`. Default CORS settings (`*`) for the upload service and `HostPath` volumes in Kubernetes deployments require careful consideration in production environments.
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