ThoughtDAG Creates Editable Context Graph for LLM Conversations
TL;DR. ThoughtDAG, an open-source tool, introduces a visual context graph to manage information for large language model interactions. - This local-first application allows users to visually arrange and connect context nodes, dictating what an LLM processes. - The tool offers features like branching conversations, parallel explorations, and structured information delivery to models. - Its design aims to improve LLM conversation coherence and explore complex ideas without losing context.
- ThoughtDAG is an open-source, local-first application.
- It visualizes and manages LLM conversation context using an editable graph.
- Users define what the LLM 'sees' by connecting nodes in the graph.
- Features include branching, parallel exploration, and a canvas-based interface.
- Aims to enhance LLM coherence and enable complex ideation.
Sources
- github.com — github.com
- Show HN: ThoughtDAG – An editable context graph for LLM conversations — chenxiachan.github.io