feat(ocr payment page) - added backend routes on app

apps/Backend/src/routes/index.ts

@@ -3,14 +3,15 @@ import patientsRoutes from "./patients";
 import appointmentsRoutes from "./appointments";
 import usersRoutes from "./users";
 import staffsRoutes from "./staffs";
-import pdfExtractionRoutes from "./pdfExtraction";
 import claimsRoutes from "./claims";
+import patientDataExtractionRoutes from "./patientdataExtraction";
 import insuranceCredsRoutes from "./insuranceCreds";
 import documentsRoutes from "./documents";
 import insuranceEligibilityRoutes from "./insuranceEligibility";
 import paymentsRoutes from "./payments";
 import databaseManagementRoutes from "./database-management";
 import notificationsRoutes from "./notifications";
+import paymentOcrRoutes from "./paymentOcrExtraction";
 
 const router = Router();
 
@@ -18,7 +19,7 @@ router.use("/patients", patientsRoutes);
 router.use("/appointments", appointmentsRoutes);
 router.use("/users", usersRoutes);
 router.use("/staffs", staffsRoutes);
-router.use("/pdfExtraction", pdfExtractionRoutes);
+router.use("/patientDataExtraction", patientDataExtractionRoutes);
 router.use("/claims", claimsRoutes);
 router.use("/insuranceCreds", insuranceCredsRoutes);
 router.use("/documents", documentsRoutes);
@@ -26,5 +27,6 @@ router.use("/insuranceEligibility", insuranceEligibilityRoutes);
 router.use("/payments", paymentsRoutes);
 router.use("/database-management", databaseManagementRoutes);
 router.use("/notifications", notificationsRoutes);
+router.use("/payment-ocr", paymentOcrRoutes);
 
 export default router;

apps/Backend/src/routes/patientDataExtraction.ts

@@ -2,17 +2,17 @@ import { Router } from "express";
 import type { Request, Response } from "express";
 const router = Router();
 import  multer from "multer";
-import forwardToPdfService from "../services/pdfClient";
+import forwardToPatientDataExtractorService from "../services/patientDataExtractorService";
 
 const upload = multer({ storage: multer.memoryStorage() });
 
-router.post("/extract", upload.single("pdf"), async (req: Request, res: Response): Promise<any>=> {
+router.post("/patientdataextract", upload.single("pdf"), async (req: Request, res: Response): Promise<any>=> {
   if (!req.file) {
     return res.status(400).json({ error: "No PDF file uploaded." });
   }
 
   try {
-    const result = await forwardToPdfService(req.file);
+    const result = await forwardToPatientDataExtractorService(req.file);
     res.json(result);
   } catch (err) {
     console.error(err);

apps/Backend/src/routes/paymentOcrExtraction.ts

@@ -0,0 +1,50 @@
+import { Router, Request, Response } from "express";
+import multer from "multer";
+import { forwardToPaymentOCRService } from "../services/paymentOCRService"; 
+
+const router = Router();
+
+// keep files in memory; FastAPI accepts them as multipart bytes
+const upload = multer({ storage: multer.memoryStorage() });
+
+// POST /payment-ocr/extract  (field name: "files")
+router.post(
+  "/extract",
+  upload.array("files"), // allow multiple images
+  async (req: Request, res: Response): Promise<any> => {
+    try {
+      const files = req.files as Express.Multer.File[] | undefined;
+
+      if (!files || files.length === 0) {
+        return res
+          .status(400)
+          .json({ error: "No image files uploaded. Use field name 'files'." });
+      }
+
+      // (optional) basic client-side MIME guard
+      const allowed = new Set([
+        "image/jpeg",
+        "image/png",
+        "image/tiff",
+        "image/bmp",
+        "image/jpg",
+      ]);
+      const bad = files.filter((f) => !allowed.has(f.mimetype.toLowerCase()));
+      if (bad.length) {
+        return res.status(415).json({
+          error: `Unsupported file types: ${bad
+            .map((b) => b.originalname)
+            .join(", ")}`,
+        });
+      }
+
+      const rows = await forwardToPaymentOCRService(files);
+      return res.json({ rows });
+    } catch (err) {
+      console.error(err);
+      return res.status(500).json({ error: "Payment OCR extraction failed" });
+    }
+  }
+);
+
+export default router;

apps/Backend/src/services/patientDataExtractorService.ts

@@ -9,7 +9,7 @@ export interface ExtractedData {
   [key: string]: any; 
 }
 
-export default async function forwardToPdfService(
+export default async function forwardToPatientDataExtractorService(
   file: Express.Multer.File
 ): Promise<ExtractedData> {
   const form = new FormData();

apps/Backend/src/services/paymentOCRService.ts

@@ -0,0 +1,34 @@
+import axios from "axios";
+import FormData from "form-data";
+
+export async function forwardToPaymentOCRService(
+  files: Express.Multer.File | Express.Multer.File[]
+): Promise<any> {
+  const arr = Array.isArray(files) ? files : [files];
+
+  const form = new FormData();
+  for (const f of arr) {
+    form.append("files", f.buffer, {
+      filename: f.originalname,
+      contentType: f.mimetype, // image/jpeg, image/png, image/tiff, etc.
+      knownLength: f.size,
+    });
+  }
+
+  const url = `http://localhost:5003/extract/json`;
+
+  try {
+    const resp = await axios.post<{ rows: any }>(url, form, {
+      headers: form.getHeaders(),
+      maxBodyLength: Infinity,
+      maxContentLength: Infinity,
+      timeout: 120000, // OCR can be heavy; adjust as needed
+    });
+    return resp.data?.rows ?? [];
+  } catch (err: any) {
+    // Bubble up a useful error message
+    const status = err?.response?.status;
+    const detail = err?.response?.data?.detail || err?.message || "Unknown error";
+    throw new Error(`Payment OCR request failed${status ? ` (${status})` : ""}: ${detail}`);
+  }
+}

apps/Frontend/src/hooks/use-extractPdfData.ts

@@ -16,7 +16,7 @@ export default function useExtractPdfData() {
       const formData = new FormData();
       formData.append("pdf", pdfFile);
 
-      const res = await apiRequest("POST", "/api/pdfExtraction/extract", formData);
+      const res = await apiRequest("POST", "/api/patientDataExtraction/patientdataextract", formData);
       if (!res.ok) throw new Error("Failed to extract PDF");
       return res.json();
     },

apps/PaymentOCRService/.env.example

@@ -0,0 +1,3 @@
+GOOGLE_APPLICATION_CREDENTIALS=google-credentials.json
+HOST="0.0.0.0"
+PORT="5003"

apps/PaymentOCRService/.gitignore

@@ -0,0 +1 @@
+google_credentials.json

apps/PaymentOCRService/app/main.py

@@ -1,81 +0,0 @@
-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}")

apps/PaymentOCRService/complete_pipeline.py

@@ -2,6 +2,8 @@
 # -*- coding: utf-8 -*-
 
 """
+ALL IS GENERATED BY REPLIT: 
+
 End-to-end local pipeline (single script)
 
 - One Google Vision pass per image (DOCUMENT_TEXT_DETECTION)

apps/PaymentOCRService/complete_pipeline_adapter.py

@@ -4,10 +4,7 @@ from typing import List, Dict
 import pandas as pd
 
 # Import your existing functions directly from complete_pipeline.py
-from complete_pipeline import (
+from complete_pipeline import smart_deskew_with_lines, extract_all_clients_from_lines
-    smart_deskew_with_lines,
-    extract_all_clients_from_lines,
-)
 
 def _process_single_image_bytes(blob: bytes, display_name: str) -> List[Dict]:
     """

apps/PaymentOCRService/main.py

@@ -0,0 +1,168 @@
+from fastapi import FastAPI, UploadFile, File, HTTPException, Request
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import StreamingResponse, JSONResponse, PlainTextResponse
+from typing import List, Optional
+import io
+import os
+import asyncio
+
+from dotenv import load_dotenv
+load_dotenv()  # loads .env (GOOGLE_APPLICATION_CREDENTIALS, HOST, PORT, etc.)
+
+# Your adapter that calls the pipeline
+from complete_pipeline_adapter import process_images_to_rows,rows_to_csv_bytes
+
+# -------------------------------------------------
+# App + concurrency controls (similar to your other app)
+# -------------------------------------------------
+app = FastAPI(
+    title="Payment OCR Services API",
+    description="FastAPI wrapper around the OCR pipeline (Google Vision + deskew + line grouping + extraction).",
+    version="1.0.0",
+)
+
+# Concurrency/semaphore (optional but useful for OCR)
+MAX_CONCURRENCY = int(os.getenv("MAX_CONCURRENCY", "2"))
+semaphore = asyncio.Semaphore(MAX_CONCURRENCY)
+
+active_jobs = 0
+waiting_jobs = 0
+lock = asyncio.Lock()
+
+# CORS
+cors_origins = os.getenv("CORS_ORIGINS", "*")
+allow_origins = ["*"] if cors_origins.strip() == "*" else [o.strip() for o in cors_origins.split(",") if o.strip()]
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=allow_origins,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+ALLOWED_EXTS = {".jpg", ".jpeg", ".png", ".tif", ".tiff", ".bmp"}
+
+# -------------------------------------------------
+# Health + status
+# -------------------------------------------------
+@app.get("/health", response_class=PlainTextResponse)
+def health():
+    creds = os.environ.get("GOOGLE_APPLICATION_CREDENTIALS", "")
+    return f"OK | GOOGLE_APPLICATION_CREDENTIALS set: {bool(creds)}"
+
+@app.get("/status")
+async def get_status():
+    async with lock:
+        return {
+            "active_jobs": active_jobs,
+            "queued_jobs": waiting_jobs,
+            "max_concurrency": MAX_CONCURRENCY,
+            "status": "busy" if active_jobs > 0 or waiting_jobs > 0 else "idle",
+        }
+
+# -------------------------------------------------
+# Helpers
+# -------------------------------------------------
+def _validate_files(files: List[UploadFile]):
+    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))}"
+        )
+
+# -------------------------------------------------
+# Endpoints
+# -------------------------------------------------
+@app.post("/extract/json")
+async def extract_json(files: List[UploadFile] = File(...)):
+    _validate_files(files)
+
+    async with lock:
+        global waiting_jobs
+        waiting_jobs += 1
+
+    async with semaphore:
+        async with lock:
+            waiting_jobs -= 1
+            global active_jobs
+            active_jobs += 1
+
+        try:
+            blobs = [await f.read() for f in files]
+            names = [f.filename or "upload.bin" for f in files]
+            rows = process_images_to_rows(blobs, names)  # calls your pipeline
+            return JSONResponse(content={"rows": rows})
+        except Exception as e:
+            raise HTTPException(status_code=500, detail=f"Processing error: {e}")
+        finally:
+            async with lock:
+                active_jobs -= 1
+
+@app.post("/extract/csvtext", response_class=PlainTextResponse)
+async def extract_csvtext(files: List[UploadFile] = File(...)):
+    _validate_files(files)
+
+    async with lock:
+        global waiting_jobs
+        waiting_jobs += 1
+
+    async with semaphore:
+        async with lock:
+            waiting_jobs -= 1
+            global active_jobs
+            active_jobs += 1
+
+        try:
+            blobs = [await f.read() for f in files]
+            names = [f.filename or "upload.bin" for f in files]
+            rows = process_images_to_rows(blobs, names)
+            csv_bytes = rows_to_csv_bytes(rows)
+            return PlainTextResponse(csv_bytes.decode("utf-8"), media_type="text/csv")
+        except Exception as e:
+            raise HTTPException(status_code=500, detail=f"Processing error: {e}")
+        finally:
+            async with lock:
+                active_jobs -= 1
+
+@app.post("/extract/csv")
+async def extract_csv(files: List[UploadFile] = File(...), filename: Optional[str] = None):
+    _validate_files(files)
+
+    async with lock:
+        global waiting_jobs
+        waiting_jobs += 1
+
+    async with semaphore:
+        async with lock:
+            waiting_jobs -= 1
+            global active_jobs
+            active_jobs += 1
+
+        try:
+            blobs = [await f.read() for f in files]
+            names = [f.filename or "upload.bin" for f in files]
+            rows = process_images_to_rows(blobs, names)
+            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}")
+        finally:
+            async with lock:
+                active_jobs -= 1
+
+# -------------------------------------------------
+# Entrypoint (same pattern as your selenium app)
+# -------------------------------------------------
+if __name__ == "__main__":
+    import uvicorn
+    host = os.getenv("HOST")
+    port = int(os.getenv("PORT"))
+    reload_flag = os.getenv("RELOAD", "false").lower() == "true"
+    uvicorn.run(app, host=host, port=port, reload=reload_flag)

apps/PaymentOCRService/package.json

@@ -1,5 +1,5 @@
 {
-  "name": "pdfservice",
+  "name": "paymentocrservice",
   "private": true,
   "scripts": {
     "postinstall": "pip install -r requirements.txt",

apps/PaymentOCRService/requirements.txt

@@ -1,10 +1,26 @@
-fastapi
+annotated-types==0.7.0
-uvicorn[standard]
+anyio==4.10.0
-google-cloud-vision
+click==8.2.1
-opencv-python-headless
+colorama==0.4.6
-pytesseract
+et_xmlfile==2.0.0
-pillow
+fastapi==0.116.1
-pandas
+h11==0.16.0
-openpyxl
+idna==3.10
-numpy
+numpy==2.2.6
-python-multipart
+google-cloud-vision>=3.10.2
+opencv-python==4.12.0.88
+openpyxl==3.1.5
+pandas==2.3.2
+pydantic==2.11.7
+pydantic_core==2.33.2
+python-dateutil==2.9.0.post0
+python-dotenv==1.1.1
+pytz==2025.2
+six==1.17.0
+sniffio==1.3.1
+starlette==0.47.3
+typing-inspection==0.4.1
+typing_extensions==4.15.0
+tzdata==2025.2
+uvicorn==0.35.0
+python-multipart==0.0.20

package-lock.json

@@ -163,8 +163,17 @@
         "vite": "^6.3.5"
       }
     },
+    "apps/PatientDataExtractorService": {
+      "name": "patientdataextractorservice",
+      "hasInstallScript": true
+    },
+    "apps/PaymentOCRService": {
+      "name": "paymentocrservice",
+      "hasInstallScript": true
+    },
     "apps/PdfService": {
       "name": "pdfservice",
+      "extraneous": true,
       "hasInstallScript": true
     },
     "apps/SeleniumService": {
@@ -9983,11 +9992,19 @@
       "devOptional": true,
       "license": "MIT"
     },
+    "node_modules/patientdataextractorservice": {
+      "resolved": "apps/PatientDataExtractorService",
+      "link": true
+    },
     "node_modules/pause": {
       "version": "0.0.1",
       "resolved": "https://registry.npmjs.org/pause/-/pause-0.0.1.tgz",
       "integrity": "sha512-KG8UEiEVkR3wGEb4m5yZkVCzigAD+cVEJck2CzYZO37ZGJfctvVptVO192MwrtPhzONn6go8ylnOdMhKqi4nfg=="
     },
+    "node_modules/paymentocrservice": {
+      "resolved": "apps/PaymentOCRService",
+      "link": true
+    },
     "node_modules/pdfjs-dist": {
       "version": "3.11.174",
       "resolved": "https://registry.npmjs.org/pdfjs-dist/-/pdfjs-dist-3.11.174.tgz",
@@ -10001,10 +10018,6 @@
         "path2d-polyfill": "^2.0.1"
       }
     },
-    "node_modules/pdfservice": {
-      "resolved": "apps/PdfService",
-      "link": true
-    },
     "node_modules/perfect-debounce": {
       "version": "1.0.0",
       "resolved": "https://registry.npmjs.org/perfect-debounce/-/perfect-debounce-1.0.0.tgz",

package.json

@@ -11,8 +11,8 @@
     "db:generate": "prisma generate --schema=packages/db/prisma/schema.prisma && ts-node packages/db/scripts/patch-zod-buffer.ts",
     "db:migrate": "dotenv -e packages/db/.env -- prisma migrate dev --schema=packages/db/prisma/schema.prisma",
     "db:seed": "prisma db seed --schema=packages/db/prisma/schema.prisma",
-    "setup:env": "shx cp packages/db/prisma/.env.example packages/db/prisma/.env && shx cp apps/Frontend/.env.example apps/Frontend/.env && shx cp apps/Backend/.env.example apps/Backend/.env",
+    "setup:env": "shx cp packages/db/prisma/.env.example packages/db/prisma/.env && shx cp apps/Frontend/.env.example apps/Frontend/.env && shx cp apps/Backend/.env.example apps/Backend/.env && shx cp apps/PaymentOCRService/.env.example apps/PaymentOCRService/.env",
-    "postinstall": "cd apps/PdfService && npm run postinstall"
+    "postinstall": "npm --prefix apps/PatientDataExtractorService run postinstall && npm --prefix apps/PaymentOCRService run postinstall"
   },
   "prisma": {
     "seed": "ts-node packages/db/prisma/seed.ts"