The problem I kept hitting
Every time I went deep on a topic with ChatGPT, one tangent would
poison the whole thread. You ask a follow-up question, and suddenly
your entire conversation context is contaminated with an irrelevant
detour. The LLM loses the plot.
The standard workaround? Open a new chat. Paste context manually.
Repeat. That's not a solution, that's giving up.
I wanted branches — real ones. Not tabs. Not separate threads you
manage yourself. Branches that inherit the right context automatically
and stay isolated from each other.
So I built ContextTree.
What it does
ContextTree is a node-based visual canvas for LLM conversations.
Every message is a node. Branching is a first-class action, not a
workaround.
The core invariant: a child node only inherits its direct parent
lineage — never siblings, never cousins. No cross-contamination.
But the feature that surprised me most during development is what
each node carries independently:
- Its own LLM model (GPT-4o on one branch, Gemini Flash on another)
- Its own custom system prompt (scoped to that node and its children)
- Its own advanced settings: temperature, max output tokens, history mode, last K messages, context budget in tokens, external context chunk count
This means on one canvas you can have a general assistant node, fork
into a strict legal-persona branch with a lawyer system prompt and
tight context budget, then fork again into a summarizer with low
temperature. Three personalities, zero interference, one visual graph.
The hardest design decision: context inheritance
The honest rule in the codebase:
A child node never reads parent live state — no shared LangGraph
state, no reads of the parent's current summary after the fork
moment. Each node evolves independently.However, ancestry-scoped vector search lets a child retrieve
relevant snippets from any ancestor's history, capped at the
fork point. Branches inherit knowledge, not state.
This distinction took a while to nail. "Knowledge not state" is the
mental model that made the architecture clean. If you want hard
isolation, set SIMILAR_CONTEXT_LIMIT=0 per node.
What I'm still figuring out
- Prompt stack order — should users be able to reorder layers?
- Is per-node system prompt enough, or do people want per-node RAG sources pinned differently?
- The multi-LLM branching UX — is it obvious enough what's happening?
Try it
Demo:CONTEXTTREE
Video walkthrough: https://youtu.be/AqmICcc26VI
Built solo. Early stage. Brutal feedback welcome — especially from
anyone who's built multi-agent or prompt engineering tooling.
