thoughtdag

chenxiachan/thoughtdag is ranked 1,504 among these 8 peers; techjarves/Mobile-Harness is ranked 1,505.

ThoughtDAG **AI conversations that branch on an infinite canvas. ** Explore a side question, connect useful paths, and choose what the model sees next. 5 update · CLI · Harness · Desktop · How it works · How it differs · Research New in 0. 5 · ThoughtDAG × Jev **Bring relevant past conversations into the question you are asking now. ** The local index searches supported agent sessions and ThoughtDAG canvases. Topic dossiers collect decisions and open questions with links back to their sources. ** The optional **Jev decision layer

** helps identify topics and rank relevant excerpts. Your chosen language model develops the answer. ** With recall enabled, the context panel lists the dossiers and excerpts added to a request. Inspect their sources or exclude individual items before continuing. In a small relevance-selection pilot, Jev's median was **391 ms** versus **24,813 ms** for our GLM adapter. These are selection-stage timings, not end-to-end search or answer times. What the timing measures Six runs per engine over the

same 14 synthetic excerpts. Median selection latency: **391 ms** for Jev-1. These are different inference paths, not a controlled ranking of model speed. Retrieval and answer generation are excluded; this does not measure whole-product speed or accuracy gains. Without a decision model, recall falls back to rules. The **System 1 / System 2-style split** describes software roles here: quick relevance decisions, then answer and dossier generation. It is not a claim about human cognition. Set up history and

recall · Configure Jev Find past context from the command line Remember a file, a phrase or a URL, but not the session? Search local conversations and jump to the matching turn, without opening the desktop app. Run to expose read-only history tools to your agent. Retrieve the relevant turns rather than replaying a whole session. CLI guide → Inside DeepSeek Harness Switch between chat and ThoughtDAG's graph inside the harness. Choose the context on the canvas; the harness runs the

next turn. 2 or later): open **Plugins**, search for , install it, and restart Harness. A release published within the last 24 hours needs its version named, (pnpm holds back such versions by default). For the web profile, from the command line: The plugin bundles the canvas and memory layer. Plugin guide → The desktop app Read a document beside your conversation, branch from a passage, and connect the paths you want to explore together. Or download for macOS, Windows or Linux

, connect a model and open the example canvas. ▶ Watch the 33-second tour The one rule **Wires are the context. ** Connect conversation paths to use them in the next question. Disconnect a path without deleting the work. Branch from a detail, explore it separately, then connect the useful parts to a later question. The graph changes the model's input, not just the layout. **Preview what the model will receive before sending. ** Wires select the conversation paths; explicit references and enabled

recall can add material alongside them. Context guide → In action ✂️ Change the context, keep the exploration Select text in an