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ADALFLOW
Auto-optimize LLM applications with task pipelines
MIT
ABOUT
Building production-grade LLM applications requires tedious manual prompt engineering, fragile chain-of-thought scaffolding, and separate frameworks for RAG, agents, and chat. AdalFlow unifies these patterns into one configurable pipeline with auto-optimization that tunes prompts and templates without hand-tuning.
INSTALL
pip install adalflowINTEGRATION GUIDE
1. Build and optimize RAG pipelines with automatic prompt tuning and retrieval configuration
2. Create multi-step agent workflows with auto-optimized task decomposition and tool selection
3. Develop production chatbots with built-in evaluation loops that improve responses over time
TAGS
agentsllmoptimizationragprompt-engineeringpython