ai.explain_stream(findings_text, on_chunk) streams token deltas and returns
(ok, full_text). Ollama: stream=True NDJSON; Claude: stream=True SSE (parse
content_block_delta text deltas). The diagnostic dialog opens an explanation
window immediately and fills it token-by-token via a _chunk signal, then
re-renders the finished answer as Markdown — no more multi-second freeze on a
local model. Non-streaming explain() kept for the CLI. Tests for both parsers;
verified live against qwen2.5:7b.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The model guessed "Rainbow Six Siege" for appID 2694490 (Path of Exile 2). We
already know the names locally, so ground it: steam.appid_names() maps appid→name
from the scanned library, and ai.build_prompt scans the text for app IDs and
injects a resolved glossary. Only locally-known IDs are listed; no network, no
fine-tuning. Tests + verified live (2694490 = Path of Exile 2).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
New optional module (D24): explains the collected findings in plain language,
contacted ONLY on an explicit user action (never automatic).
- core/ai.py: provider chosen explicitly (no default) — ollama (local) or claude
(Anthropic Messages API via stdlib urllib; key in keyring). Grounded prompt;
HTTP error parsing; one-shot (no thinking/caching — snappy).
- core/ai_knowledge.py: curated reference KB (Xid/SMART/Proton/tunables),
exact keyword/code match ("RAG-lite", no embeddings) injected into the prompt —
lifts local models, sharpens Claude. No fine-tuning.
- config: ai_provider/ai_model/ai_endpoint + keyring-backed AI key (generalized
the token keyring helpers).
- GUI: Settings → AI assistant (provider radios, model/endpoint/key, Save/Test);
"Explain with AI" button on the diagnostic dialog (consent prompt for cloud).
- CLI: `rigdoctor ai status|test|explain`.
- Docs: D24, SPEC/MODULES/ROADMAP (Phase 7); tests for providers/grounding/parse.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
jessey