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ChatDB -- Verified Reasoning Engine

Autonomous proof engine generating seven layers of verified training data.

Quick Start

npm install
cd sidecar && pip install -e ".[dev]" && cd ..
npm run sidecar:dev   # Terminal 1
npm run tauri:dev     # Terminal 2

Repository Workflow

This repository follows Gitflow plus mandatory TDD phase gates for every code change.

  • Long-lived branches
    • main: production-ready, release-tagged history
    • develop: integration branch for completed feature work
  • Working branches
    • feature/*: branch from develop, merge back to develop via PR
    • release/*: branch from develop, merge to main and back-merge to develop
    • hotfix/*: branch from main, merge to main and develop
  • Required lifecycle for all code changes
    • Red → Green → Blue is mandatory
    • No direct implementation bypassing Red evidence

Basic Local Flow (feature branch from develop)

git checkout develop
git pull origin develop
git checkout -b feature/<task-id>-<short-kebab-description>
git push -u origin feature/<task-id>-<short-kebab-description>
gh pr create --base develop --head feature/<task-id>-<short-kebab-description> --fill

TDD Enforcement Prompt Tag

No implementation before failing tests (Red)
Minimal implementation to pass tests (Green)
Refactor only after green tests (Blue)
PRs without Red evidence are non-compliant

Architecture

  • Rust Backend (Tauri 2): Loop engine, orchestrator, critic, worker pool, SQLite
  • Python Sidecar (FastAPI): SymPy, Pint, Lean validators + Council, Scout, Librarian agents
  • React Frontend: Zustand stores, proof tree, agent dashboard, training data stats

Training Data Layers

# Source Signal
1 Solvers Step-level PRM
2 Solvers Full trajectories
3 Orchestrator Routing decisions
4 Council Metacognitive deliberation
5 Scout Research query-result-outcome
6 Critic Prediction vs truth
7 Librarian Curation traces

License: Proprietary - Vario Automation

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