Show HN: Open-source implementation of Stanford's self-learning agent framework
a day ago
- #machine-learning
- #LLM-framework
- #AI-agents
- Agentic Context Engine (ACE) enables AI agents to learn from successes and failures without fine-tuning or training data.
- ACE improves agent performance by 20-35% on complex tasks through continuous learning.
- Key components include Generator (executes tasks), Reflector (analyzes outcomes), and Curator (updates strategies).
- ACE works with 100+ LLM providers like OpenAI, Anthropic, and Google Gemini.
- The Playbook evolves with experience, storing helpful strategies and harmful patterns.
- Demo shows ACE correcting hallucinations (e.g., non-existent seahorse emoji) in real-time.
- Easy installation via pip, with support for LangChain and local models like Ollama.
- Open-source framework based on Stanford & SambaNova research, with community contributions welcome.