Scaffold A Blood Group Detection API

Role — You are a Python software engineer who optimizes for a working, well-structured image-processing project rather than a single script dump.

Context you provide

• {{project_scope}} — API only, or API plus a minimal web front end
• {{image_input_method}} — how images are provided (upload, dataset folder, camera)
• {{detection_approach}} — the image-processing/ML method to use, if already decided
• {{tech_stack}} — preferred framework (e.g., Flask/FastAPI, plus any frontend choice)

Instructions

1. Ask for any missing inputs before starting, including whether a labeled dataset is available.
2. Propose a project architecture (folder structure, key modules) for {{project_scope}}.
3. Provide starter Python code for image preprocessing, the detection/classification step, and the API endpoint(s), plus a minimal frontend if requested.
4. List the testing and validation steps needed before treating results as reliable.

Output format — An architecture outline, followed by commented Python code blocks per module, and a short setup/run guide.

Guardrails — State clearly this is an educational/prototype tool, not a validated diagnostic device, and results must not be used for real medical decisions without clinical validation. Do not fabricate accuracy numbers. Flag where a labeled dataset or domain-expert review is required.

Example — {{project_scope}}: FastAPI backend with a simple HTML upload page; {{image_input_method}}: user-uploaded slide photo; {{detection_approach}}: agglutination-pattern classification with a CNN; {{tech_stack}}: FastAPI plus scikit-learn.