Local LLMs & agentsProject record · Sep 2026

Local LLM Inference & Agents

ZhengMind architecture study

A provider-neutral task-control architecture studied alongside the later ZhengMindYAGNI implementation.

PythonFastAPISQLiteJinja2Task graphsScoped tokensAudit trails
Why it sits here. Retain as an architectural study connected to YAGNI; separate authorship and mock integrations rule out using it as Donald built-work proof.
04 / Follow a thought through the machine.STUDY IN SPACE

01 / IMPLEMENTATION & CONTRIBUTION

What the work involves

An architectural study of the ZhengMind prototype credited to yq77zs73/Zheng Shen. It is separate from Donald’s independently attributed ZhengMindYAGNI implementation.

Technical depth

Task trees, dependency-aware claims, scoped API tokens, prompt snapshots, sanitized audit events, proposal/SCM seams, and explicit parent integration express a sophisticated agent-governance model.

The project family

ZhengMind

02 / RESULTS

What came out of it

The reference prototype explores task trees, dependency-aware claims, prompt snapshots, and auditable state changes. Its external database, GitHub-write, and LLM adapters remain unconnected.

03 / SUPPORTING EVIDENCE

Follow the source

Implementation notes, project records, and supporting artifacts.

Source context & project scope

Not a production deployment; real external adapters and LLM execution are not established.

Some domain concepts are future plans rather than implemented runtime support.

Historical test counts in README were not rerun.

Explicit local/mock boundary, canonical work model, implemented MVP surfaces, and future concepts.

SOURCE · 2026-09-17

Task-tree service and claiming implementation.

SOURCE · 2026-09-17

Work/task naming contract and compatibility limits.

SOURCE · 2026-09-17

Concrete documented relationship between this predecessor and the simplification study.

SOURCE · 2026-09-17

Clean upstream history under yq77zs73/Zheng Shen; no Donald identity equivalence established.

SOURCE · 2026-09-17
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