flowllm
by FlowLLM-AI
Overview
FlowLLM is a configuration-driven framework for building LLM-powered applications, encapsulating LLM, Embedding, and vector store capabilities as HTTP/MCP services. It's designed for AI assistants, RAG applications, and complex workflow orchestration, minimizing boilerplate code.
Installation
flowllm backend=http http.port=8002Environment Variables
- FLOW_LLM_API_KEY
- FLOW_LLM_BASE_URL
- FLOW_EMBEDDING_API_KEY
- FLOW_EMBEDDING_BASE_URL
- FLOW_DASHSCOPE_API_KEY
- FLOW_TAVILY_API_KEY
- FLOW_PGVECTOR_CONNECTION_STRING
- FLOW_PGVECTOR_ASYNC_CONNECTION_STRING
- FLOW_QDRANT_HOST
- FLOW_QDRANT_PORT
- FLOW_QDRANT_API_KEY
- FLOW_ES_HOSTS
- FLOW_APP_NAME
Security Notes
The framework uses `exec()` and `eval()` internally (`parse_flow_expression`) to process `flow_content` defined in YAML configuration. While the documentation states execution in a 'restricted environment', arbitrary code execution remains a critical risk if the YAML input is not from an absolutely trusted source or if the sandbox is insufficient. Default CORS settings allow all origins, which should be restricted in production environments.
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