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Diff/aledon8-openleukemia-cursor-rules-ai-service ↔ aledon8-openleukemia-ml-inference-claude

Comparison

A · Cursor rules · Aledon8/OpenLeukemiaB · CLAUDE.md · Aledon8/OpenLeukemia
What each file covers, counted
DimensionSharedOnly in AOnly in BOverlap
Sections0110%
Commands0300%
Section tags0310%

What each file covers

Sections

0 shared · 1 only in A · 1 only in B
  • − AI Service Rules
  • + ML Inference Memory

Commands

0 shared · 3 only in A · 0 only in B
  • − python -m mypy app
  • − python -m ruff check .
  • − python -m pytest

Section tags

0 shared · 3 only in A · 1 only in B
  • − test
  • − lint-format
  • − do-not
  • + performance

Line diff

+6 added−13 removed3 unchanged18.8% identical
Aledon8/OpenLeukemia · .cursor/rules/ai-service.mdc
@@ −1 @@
1---
2description: Python FastAPI AI-service rules
3globs:
4 - "ai-service/**/*.py"
5alwaysApply: false
6---
7 
8# AI Service Rules
9 
10- Keep FastAPI route handlers thin; put reusable behavior in `app/domains`.
11- Use explicit Pydantic request and response models.
12- Preserve strict typing and keep `python -m mypy app` clean.
13- Use `response_model` for route outputs.
14- Treat extraction and model outputs as explainable signals or candidate data, not clinical decisions.
15- Run `python -m ruff check .` and relevant `python -m pytest` tests for Python changes.
16 
Aledon8/OpenLeukemia · ml/inference/CLAUDE.md
@@ +1 @@
1# ML Inference Memory
 
 
 
 
 
2 
3Apply this inside `ml/inference/`.
4 
5- Keep inference interfaces typed, deterministic, and easy to validate.
6- Return explainable scores or signals with limitations, not clinical conclusions.
7- Preserve compatibility with `ai-service/` consumers when inference code is promoted.
8- Validate feature order, units, and missing-value behavior explicitly.
 
 
9 
@@ −1 +1 @@
1−---
2−description: Python FastAPI AI-service rules
3−globs:
4− - "ai-service/**/*.py"
5−alwaysApply: false
6−---
1+# ML Inference Memory
72  
8−# AI Service Rules
3+Apply this inside `ml/inference/`.
94  
10−- Keep FastAPI route handlers thin; put reusable behavior in `app/domains`.
11−- Use explicit Pydantic request and response models.
12−- Preserve strict typing and keep `python -m mypy app` clean.
13−- Use `response_model` for route outputs.
14−- Treat extraction and model outputs as explainable signals or candidate data, not clinical decisions.
15−- Run `python -m ruff check .` and relevant `python -m pytest` tests for Python changes.
5+- Keep inference interfaces typed, deterministic, and easy to validate.
6+- Return explainable scores or signals with limitations, not clinical conclusions.
7+- Preserve compatibility with `ai-service/` consumers when inference code is promoted.
8+- Validate feature order, units, and missing-value behavior explicitly.
169  
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