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Diff/aledon8-openleukemia-ai-service-claude ↔ aledon8-openleukemia-github-copilot-instructions

Comparison

A · CLAUDE.md · Aledon8/OpenLeukemiaB · Copilot instructions · Aledon8/OpenLeukemia
What each file covers, counted
DimensionSharedOnly in AOnly in BOverlap
Sections0340%
Commands32433%
Section tags31160%

What each file covers

Sections

0 shared · 3 only in A · 4 only in B
  • − AI Service Instructions
  • − Commands
  • − Rules
  • + GitHub Copilot Instructions
  • + Always Follow
  • + Stack And Commands
  • + Workflow

Commands

3 shared · 2 only in A · 4 only in B
  • − python -m uvicorn app.main:app --reload
  • − mypy app
  • + npm run lint:frontend
  • + npm run typecheck:frontend
  • + npm test --workspace frontend
  • + npm --workspace frontend run build
  •   python -m ruff check .
  •   python -m pytest
  •   python -m mypy app

Section tags

3 shared · 1 only in A · 1 only in B
  • − do-not
  • + code-style
  •   test
  •   lint-format
  •   agent-behaviour

Line diff

+23 added−18 removed7 unchanged23.3% identical
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 · .github/copilot-instructions.md
@@ +1 @@
1# GitHub Copilot Instructions
2 
3OpenLeukemia is a patient-centered leukemia data platform. It organizes medical data, tracks changes over time, extracts structured information from documents, and explains validated model outputs in plain language.
4 
5## Always Follow
6 
7- Preserve explicit consent, privacy-by-default behavior, and patient ownership of data.
8- Registration is not blanket consent.
9- AI output may summarize, extract, and explain; it must not diagnose, recommend treatment, or make urgent clinical judgments.
10- Treat LLM extraction as candidate data until validated or confirmed.
11- Prefer minimal, focused changes that match nearby code.
12- Do not introduce dependencies, API changes, schema changes, or consent-flow changes without clear need.
13- Add or update tests when behavior changes.
14- Run or recommend the relevant check after changes.
15 
16## Stack And Commands
 
 
 
 
 
17 
18- Frontend: React 19, TypeScript, Vite, Vitest, ESLint.
19- Platform: Supabase Auth, Postgres, Storage, RLS, Edge Functions.
20- AI service: Python 3.12, FastAPI, Pydantic, Uvicorn.
21- Frontend checks: `npm run lint:frontend`, `npm run typecheck:frontend`, `npm test --workspace frontend`, `npm --workspace frontend run build`.
22- AI-service checks from `ai-service/`: `python -m ruff check .`, `python -m pytest`, `python -m mypy app`.
23 
24## Workflow
25 
26- Read nearby files before editing and follow the existing pattern.
27- For multi-file or risky changes, identify touched files and verification steps before implementation.
28- Use artifacts as primary evidence: errors, logs, screenshots, issues, plans, and referenced files.
29- Verify work with tests, build, lint, typecheck, or visual comparison when practical.
 
30 
@@ −1 +1 @@
1−# AI Service Instructions
1+# GitHub Copilot Instructions
22  
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.
3+OpenLeukemia is a patient-centered leukemia data platform. It organizes medical data, tracks changes over time, extracts structured information from documents, and explains validated model outputs in plain language.
44  
5−## Commands
5+## Always Follow
66  
7−Run from `ai-service/`:
7+- Preserve explicit consent, privacy-by-default behavior, and patient ownership of data.
8+- Registration is not blanket consent.
9+- AI output may summarize, extract, and explain; it must not diagnose, recommend treatment, or make urgent clinical judgments.
10+- Treat LLM extraction as candidate data until validated or confirmed.
11+- Prefer minimal, focused changes that match nearby code.
12+- Do not introduce dependencies, API changes, schema changes, or consent-flow changes without clear need.
13+- Add or update tests when behavior changes.
14+- Run or recommend the relevant check after changes.
815  
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−```
16+## Stack And Commands
1517  
16−## Rules
18+- Frontend: React 19, TypeScript, Vite, Vitest, ESLint.
19+- Platform: Supabase Auth, Postgres, Storage, RLS, Edge Functions.
20+- AI service: Python 3.12, FastAPI, Pydantic, Uvicorn.
21+- Frontend checks: `npm run lint:frontend`, `npm run typecheck:frontend`, `npm test --workspace frontend`, `npm --workspace frontend run build`.
22+- AI-service checks from `ai-service/`: `python -m ruff check .`, `python -m pytest`, `python -m mypy app`.
1723  
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.
24+## Workflow
25+ 
26+- Read nearby files before editing and follow the existing pattern.
27+- For multi-file or risky changes, identify touched files and verification steps before implementation.
28+- Use artifacts as primary evidence: errors, logs, screenshots, issues, plans, and referenced files.
29+- Verify work with tests, build, lint, typecheck, or visual comparison when practical.
2530  
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