EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Hacker News·Aug 15·5 min read
Show HN: ThoughtDAG – An editable context graph for LLM conversations
TL;DR
ThoughtDAG is an innovative tool that allows users to create and edit a context graph for conversations with large language models (LLMs), enabling exploration of alternative interpretations without losing previous context.
✦ Why It Matters
Start using ThoughtDAG to enhance your interactions with LLMs by managing conversation context effectively.
Key Takeaways
- Utilize ThoughtDAG to visualize conversation context.
- Experiment with context changes to see varied model outputs.
- Maintain clarity on what context influences responses.
- Improve user interactions by refining conversation history.
How It Works
ThoughtDAG allows users to create a visual representation of conversation context as a graph. Each node represents a part of the conversation, and edges indicate the relationships between different context elements.
Users can edit this graph to add or remove context, which directly influences the responses generated by the LLM. This transparency helps users understand how specific context changes affect the model's output.