| Dimension | Shared | Only in A | Only in B | Overlap |
|---|---|---|---|---|
| Sections | 0 | 3 | 1 | 0% |
| Commands | 0 | 5 | 0 | 0% |
| Section tags | 1 | 3 | 0 | 25% |
What each file covers
Sections
0 shared · 3 only in A · 1 only in B- − AI Service Instructions
- − Commands
- − Rules
- + ML Rules
Commands
0 shared · 5 only in A · 0 only in B- − python -m uvicorn app.main:app --reload
- − python -m ruff check .
- − python -m pytest
- − python -m mypy app
- − mypy app
Section tags
1 shared · 3 only in A · 0 only in B- − test
- − lint-format
- − agent-behaviour
- do-not
Line diff
Aledon8/OpenLeukemia · ai-service/CLAUDE.md
@@ −1 @@
1# AI Service Instructions
2
3This directory contains the FastAPI service for Python-native workloads: ML inference, document extraction, OCR or parsing workflows, model-facing APIs, and compute-heavy jobs.
4
5## Commands
6
7Run from `ai-service/`:
8
9```sh
10python -m uvicorn app.main:app --reload
11python -m ruff check .
12python -m pytest
13python -m mypy app
14```
15
16## Rules
17
18- Keep route handlers thin and focused on HTTP concerns.
19- Put reusable behavior in `app/domains/` services and schemas.
20- Use explicit Pydantic request and response models.
21- Preserve strict typing and keep `mypy app` clean.
22- Treat extraction results as candidate data until validated or confirmed.
23- Keep generated explanations non-diagnostic and patient-safe.
24- For endpoint changes, define the request/response contract and tests before broad implementation.
25
Aledon8/OpenLeukemia · .cursor/rules/ml.mdc
@@ +1 @@
1---
2description: ML workspace rules
3globs:
4 - "ml/**/*"
5alwaysApply: false
6---
7
8# ML Rules
9
10- Keep structured ML workflows separate from LLM explanation workflows.
11- Use measurable criteria: split, metric, threshold, calibration, and known failure modes.
12- Do not commit patient-identifying or sensitive medical data.
13- Model outputs support signals and trends, not diagnosis or treatment guidance.
14- Document label assumptions, cohort limitations, and evaluation caveats near relevant code or reports.
15
@@ −1 +1 @@
1−# AI Service Instructions
1+---
2+description: ML workspace rules
3+globs:
4+ - "ml/**/*"
5+alwaysApply: false
6+---
27
3−This directory contains the FastAPI service for Python-native workloads: ML inference, document extraction, OCR or parsing workflows, model-facing APIs, and compute-heavy jobs.
8+# ML Rules
49
5−## Commands
6−
7−Run from `ai-service/`:
8−
9−```sh
10−python -m uvicorn app.main:app --reload
11−python -m ruff check .
12−python -m pytest
13−python -m mypy app
14−```
15−
16−## Rules
17−
18−- Keep route handlers thin and focused on HTTP concerns.
19−- Put reusable behavior in `app/domains/` services and schemas.
20−- Use explicit Pydantic request and response models.
21−- Preserve strict typing and keep `mypy app` clean.
22−- Treat extraction results as candidate data until validated or confirmed.
23−- Keep generated explanations non-diagnostic and patient-safe.
24−- For endpoint changes, define the request/response contract and tests before broad implementation.
10+- Keep structured ML workflows separate from LLM explanation workflows.
11+- Use measurable criteria: split, metric, threshold, calibration, and known failure modes.
12+- Do not commit patient-identifying or sensitive medical data.
13+- Model outputs support signals and trends, not diagnosis or treatment guidance.
14+- Document label assumptions, cohort limitations, and evaluation caveats near relevant code or reports.
2515
