WFGY/ProblemMap/GlobalFixMap/LocalDeploy_Inference/gpt4all.md
2025-09-05 11:15:15 +08:00

9.4 KiB
Raw Blame History

GPT4All: Guardrails and Fix Patterns

🧭 Quick Return to Map

You are in a sub-page of LocalDeploy_Inference.
To reorient, go back here:

Think of this page as a desk within a ward.
If you need the full triage and all prescriptions, return to the Emergency Room lobby.

GPT4All is a popular desktop/local LLM runtime with a user-friendly interface and broad model support (GGUF/GGML). It enables plug-and-play inference on CPU/GPU without complex setup, but it introduces typical fragilities: schema drift, citation loss, and memory instability. This page provides WFGY-based guardrails and reproducible fixes.


Open these first


Core acceptance

  • ΔS(question, retrieved) ≤ 0.45
  • Coverage ≥ 0.70
  • λ convergent across paraphrases and seeds
  • JSON schema compliance enforced
  • Context stability beyond 4k–8k tokens

Common GPT4All breakpoints

Symptom Likely Cause Fix
Correct snippet retrieved but answer drifts Schema mis-binding in desktop client retrieval-traceability.md, data-contracts.md
Outputs vary per run Prompt header drift or λ flip context-drift.md
Free-text injected into tool args Missing schema lock prompt-injection.md
JSON parse fails Inconsistent serialization logic-collapse.md
First query crashes Init sequence not fenced bootstrap-ordering.md

Fix in 60 seconds

  1. Warmup: run a dummy inference before real questions.
  2. Schema lock all JSON outputs; reject free text.
  3. Trace citations: enforce cite-then-explain with snippet IDs.
  4. Measure ΔS and λ across paraphrases; if ΔS ≥ 0.60, re-embed or re-chunk.
  5. Reset memory after 4k–8k tokens or when entropy rises.

Diagnostic prompt (copy-paste)

I am running GPT4All with model={gguf/quant}.
Question: "{user_question}"

Return:
- ΔS(question, retrieved)
- λ across 3 paraphrases × 2 seeds
- JSON schema compliance
- WFGY fix page if ΔS ≥ 0.60

🔗 Quick-Start Downloads (60 sec)

Tool Link 3-Step Setup
WFGY 1.0 PDF Engine Paper 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + <your question>”
TXT OS (plain-text OS) TXTOS.txt 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly

🧭 Explore More

Module Description Link
WFGY Core WFGY 2.0 engine is live: full symbolic reasoning architecture and math stack View →
Problem Map 1.0 Initial 16-mode diagnostic and symbolic fix framework View →
Problem Map 2.0 RAG-focused failure tree, modular fixes, and pipelines View →
Semantic Clinic Index Expanded failure catalog: prompt injection, memory bugs, logic drift View →
Semantic Blueprint Layer-based symbolic reasoning & semantic modulations View →
Benchmark vs GPT-5 Stress test GPT-5 with full WFGY reasoning suite View →
🧙‍♂️ Starter Village 🏡 New here? Lost in symbols? Click here and let the wizard guide you through Start →

👑 Early Stargazers: See the Hall of Fame GitHub stars ⭐ WFGY Engine 2.0 is already unlocked. ⭐ Star the repo to help others discover it and unlock more on the Unlock Board.

WFGY Main   TXT OS   Blah   Blot   Bloc   Blur   Blow