Generative Feedback Loops with LLMs

This Repository contains a collection of code snippets for running Generative Feedback Loops with Weaviate.

Additional Content

• 📄 Blog Post with implementation details: https://weaviate.io/blog/generative-feedback-loops-with-LLMs
• 🎙️ Podcast: https://youtu.be/1RALju6ZJz0

Users can easily ablate:

1. Python or TypeScript
2. OpenAI or Cohere

Please see the folders

python/
javascript/

Interested in joining the Weaviate community? Join our Slack!

Additional Resources for exploring Generative Feedback Loops!

Papers

• Augmented Language Models: A Survey. Mialon et al. 2023. Link: https://arxiv.org/abs/2302.07842.
• Toolformer: Language Models Can Teach Themselves To Use Tools. Shick et al. 2023. Link: https://arxiv.org/abs/2302.04761.
• Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. Wei et al. 2022. Link: https://arxiv.org/abs/2201.11903.
• Synergizing Acting and Reasoning in Language Models. Yao et al. 2022. Link: https://arxiv.org/abs/2210.03629.
• Emergent autonomous scientific research capabilities of large language models. Boiko et al. 2023. Link: https://arxiv.org/pdf/2304.05332.pdf.
• Generative Agents: Interactive Simulacra of Human Behavior. Park et al. 2023. Link: https://arxiv.org/pdf/2304.03442.pdf.
• OpenAGI: When LLM Meets Domain Experts. Ge et al. 2023. Link: https://arxiv.org/pdf/2304.04370.pdf.
• HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face. Shen et al. 2023. Link: https://arxiv.org/pdf/2303.17580.pdf.

Summary Index

• Retrieving Texts based on Abstract Descriptions. Ravfogel et al. 2023. Link: https://arxiv.org/pdf/2305.12517.pdf