structured well

apps/PaymentOCRService/app/main.py

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+from fastapi import FastAPI, UploadFile, File, HTTPException
+from fastapi.responses import StreamingResponse, JSONResponse, PlainTextResponse
+from typing import List, Optional
+import io
+import os
+
+from app.pipeline_adapter import (
+    process_images_to_rows,
+    rows_to_csv_bytes,
+)
+
+app = FastAPI(
+    title="Medical Billing OCR API",
+    description="FastAPI wrapper around the complete OCR pipeline (Google Vision + deskew + line clustering + extraction).",
+    version="1.0.0",
+)
+
+ALLOWED_EXTS = {".jpg", ".jpeg", ".png", ".tif", ".tiff", ".bmp"}
+
+@app.get("/health", response_class=PlainTextResponse)
+def health():
+    # Simple sanity check (also ensures GCP creds var visibility)
+    creds = os.environ.get("GOOGLE_APPLICATION_CREDENTIALS", "")
+    return f"OK | GOOGLE_APPLICATION_CREDENTIALS set: {bool(creds)}"
+
+@app.post("/extract/json")
+async def extract_json(files: List[UploadFile] = File(...)):
+    if not files:
+        raise HTTPException(status_code=400, detail="No files provided.")
+
+    # Validate extensions early (not bulletproof, but helpful)
+    bad = [f.filename for f in files if os.path.splitext(f.filename or "")[1].lower() not in ALLOWED_EXTS]
+    if bad:
+        raise HTTPException(
+            status_code=415,
+            detail=f"Unsupported file types: {', '.join(bad)}. Allowed: {', '.join(sorted(ALLOWED_EXTS))}"
+        )
+
+    # Read blobs in-memory
+    blobs = []
+    filenames = []
+    for f in files:
+        blobs.append(await f.read())
+        filenames.append(f.filename or "upload.bin")
+
+    try:
+        rows = process_images_to_rows(blobs, filenames)
+        # rows is a list[dict] where each dict contains the columns you already emit (Patient Name, etc.)
+        return JSONResponse(content={"rows": rows})
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Processing error: {e}")
+
+@app.post("/extract/csv")
+async def extract_csv(files: List[UploadFile] = File(...), filename: Optional[str] = None):
+    if not files:
+        raise HTTPException(status_code=400, detail="No files provided.")
+
+    bad = [f.filename for f in files if os.path.splitext(f.filename or "")[1].lower() not in ALLOWED_EXTS]
+    if bad:
+        raise HTTPException(
+            status_code=415,
+            detail=f"Unsupported file types: {', '.join(bad)}. Allowed: {', '.join(sorted(ALLOWED_EXTS))}"
+        )
+
+    blobs = []
+    filenames = []
+    for f in files:
+        blobs.append(await f.read())
+        filenames.append(f.filename or "upload.bin")
+
+    try:
+        rows = process_images_to_rows(blobs, filenames)
+        csv_bytes = rows_to_csv_bytes(rows)
+        out_name = filename or "medical_billing_extract.csv"
+        return StreamingResponse(
+            io.BytesIO(csv_bytes),
+            media_type="text/csv",
+            headers={"Content-Disposition": f'attachment; filename="{out_name}"'}
+        )
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Processing error: {e}")