56bf30cfd8
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lakehouse/auditor 1 blocking issue: todo!() macro call in tests/real-world/scrum_master_pipeline.ts
Setup for the corpus-tightening experiment sweep (J 2026-04-26 — "now
is the only cheap window before the corpus gets large and refactoring
costs go up").
Override params on /v1/mode/execute (additive — old callers unaffected):
force_matrix_corpus — Pass 2: try alternate corpora per call
force_relevance_threshold — Pass 2: sweep filter strictness
force_temperature — Pass 3: variance test
New native mode `staffing_inference_lakehouse` (Pass 4):
- Same composer architecture as codereview_lakehouse
- Staffing framing: coordinator producing fillable|contingent|
unfillable verdict + ranked candidate list with playbook citations
- matrix_corpus = workers_500k_v8
- Validates that modes-as-prompt-molders generalizes beyond code
- Framing explicitly says "do NOT fabricate workers" — the staffing
analog of the lakehouse mode's symbol-grounding requirement
Three sweep harnesses:
scripts/mode_pass2_corpus_sweep.ts — 4 corpora × 4 thresholds × 5 files
scripts/mode_pass3_variance.ts — 3 files × 3 temps × 5 reps
scripts/mode_pass4_staffing.ts — 5 fill requests through staffing mode
Each appends per-call rows to data/_kb/mode_experiments.jsonl which
mode_compare.ts already aggregates with grounding column.
Pass 1 (10 files × 5 modes broad sweep) currently running via the
existing scripts/mode_experiment.ts — gateway restart deferred until
it completes so the new override knobs aren't enabled mid-experiment.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
63 lines
2.3 KiB
TOML
63 lines
2.3 KiB
TOML
# Mode router config — task_class → mode mapping
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#
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# `preferred_mode` is the first choice for a task class; `fallback_modes`
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# get tried in order if the preferred one isn't available (LLM Team can
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# return Unknown mode for some, OR the matrix has stronger signal for a
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# fallback). `default_model` seeds the mode runner's model field if the
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# caller doesn't override.
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#
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# Modes are dispatched against LLM Team UI (localhost:5000/api/run) for
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# now; future Rust-native runners will short-circuit before the proxy.
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# See crates/gateway/src/v1/mode.rs for the dispatch path.
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[[task_class]]
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name = "scrum_review"
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# `codereview_lakehouse` is the codebase-specific enrichment runner —
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# bundles defined/imported symbols, pathway-memory bug fingerprints,
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# and relevance-filtered matrix chunks into ONE precise prompt so the
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# model gets it right the first call. The generic `codereview` mode
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# from LLM Team is still the network fallback if execute fails.
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preferred_mode = "codereview_lakehouse"
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fallback_modes = ["codereview", "consensus", "ladder"]
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default_model = "qwen3-coder:480b"
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matrix_corpus = "distilled_procedural_v20260423102847"
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[[task_class]]
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name = "contract_analysis"
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preferred_mode = "deep_analysis"
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fallback_modes = ["research", "extract"]
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default_model = "kimi-k2:1t"
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matrix_corpus = "chicago_permits_v1"
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[[task_class]]
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name = "staffing_inference"
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# Staffing-domain native enrichment runner — Pass 4 (2026-04-26).
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# Same composer architecture as codereview_lakehouse but with staffing
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# framing + workers corpus. Validates that the modes-as-prompt-molders
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# pattern generalizes beyond code review.
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preferred_mode = "staffing_inference_lakehouse"
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fallback_modes = ["ladder", "consensus", "pipeline"]
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default_model = "openai/gpt-oss-120b:free"
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matrix_corpus = "workers_500k_v8"
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[[task_class]]
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name = "fact_extract"
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preferred_mode = "extract"
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fallback_modes = ["distill"]
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default_model = "qwen2.5"
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matrix_corpus = "kb_team_runs_v1"
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[[task_class]]
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name = "doc_drift_check"
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preferred_mode = "drift"
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fallback_modes = ["validator"]
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default_model = "gpt-oss:120b"
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matrix_corpus = "distilled_factual_v20260423095819"
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# Fallback when task_class isn't in the table — useful for ad-hoc calls
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# during development that don't yet have a mapped mode.
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[default]
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preferred_mode = "pipeline"
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fallback_modes = ["consensus", "ladder"]
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default_model = "qwen3.5:latest"
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