AdalFlow
NormalDescription
AdalFlow: The library to build & auto-optimize LLM applications.
Key Features
- 100% open-source Agent SDK with built-in human-in-the-loop and tracing
- Unified auto-differentiative framework for zero-shot and few-shot prompt optimization (LLM-AutoDiff)
- Model-agnostic building blocks for RAG, Agents, and classical NLP tasks via config switching
- PyTorch-like API design for building and auto-optimizing LM workflows from chatbots to agents
- Sync, async, and streaming execution modes with Runner and step history tracking
Use Cases
π‘ Building RAG pipelines with automatic prompt tuning and retrieval optimization
π‘ Creating AI agents with tool-use capabilities and multi-step reasoning
π‘ Automated few-shot example selection to improve in-context learning accuracy
π‘ Prototyping and evaluating chatbot workflows across different LLM providers
Categories
Quick Start
1. Install: pip install adalflow. 2. Define tools (functions with docstrings), create an Agent with a model client, and wrap it in a Runner. 3. Call runner.call() for sync, runner.acall() for async, or runner.astream() for streaming.