85 lines
2.5 KiB
Markdown
85 lines
2.5 KiB
Markdown
# Model Orchestration V0
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status: draft_orchestration_boundary
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date: 2026-06-20
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## Purpose
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Orchestration decides which small set of models should participate in a cognitive-processing run.
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M0-M1 only defines the decision fields and call limits. It does not implement a selector.
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## Roles
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- `routing_model`: classifies input and controls next-step routing.
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- `depth_model`: performs vertical deep processing.
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- `primary_model`: main explanatory model for a run.
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- `support_model`: fills a known blind spot of the primary model.
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- `contrast_model`: challenges or reframes the primary model.
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- `calibration_model`: checks evidence, action boundary, or overclaim risk.
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- `translation_model`: rewrites internal output for reader use.
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- `synthesis_model`: integrates outputs into a coherent judgment.
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## Startup Defaults
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`qpi`:
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- default role: `routing_model`;
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- should run before deep processing when problem framing is unclear;
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- should stop at routing and misframing diagnosis.
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`intellectual_archaeology`:
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- default role: `depth_model`;
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- can become `primary_model` for complex, high-value, reusable, or repeatedly failing issues;
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- should run after intake/QPI justifies deeper work.
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## Single-Run Call Budget
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A normal run may include at most:
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- one primary model;
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- two or three support or contrast models;
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- one calibration lens;
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- one reader translation layer.
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Do not call every related model. A model must add explanatory value, reduce a blind spot, or change the action boundary.
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## Main Model Selection Signals
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Primary model choice should consider:
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- problem type match;
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- explanatory gain;
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- intended output;
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- model maturity;
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- processing cost.
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Do not use simple keyword matching as the final selection method.
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## Support Model Entry Conditions
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A support model may enter only when:
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- the primary model has a known blind spot;
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- the primary model may over-explain;
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- the issue needs comparison, contrast, or calibration.
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## Guardrails
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- QPI is not the product output.
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- Intellectual Archaeology is not default for light tasks.
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- No full selector in M0-M1.
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- No flat scoring across a large model universe.
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- No expansion beyond the two startup models without owner instruction.
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## Future 100-Model Direction
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If the project later grows toward many models, orchestration should use a layered path:
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```text
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input -> domain/problem family -> 5-8 candidates -> 1 primary -> 2-3 support/contrast -> calibration -> synthesis -> translation
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```
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This future direction is only a design hook. It is not part of v0.1 implementation.
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