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Dockerfile

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+# Use the official Python image as a base image
+FROM python:3.9
+
+# Set the working directory in the container
+WORKDIR /app
+
+# Copy the requirements file to the container
+COPY requirements.txt .
+
+# Install any necessary dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy the rest of the application code to the container
+COPY . .
+
+# Expose the port that the FastAPI app will run on
+EXPOSE 8000
+
+# Command to run the FastAPI app using Uvicorn
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8000"]

app.py

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+import logging
+from fastapi import FastAPI, File, UploadFile, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from paddleocr import PaddleOCR
+from doctr.io import DocumentFile
+from doctr.models import ocr_predictor
+import numpy as np
+from PIL import Image
+import io
+
+# Set up logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+app = FastAPI()
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# Initialize models once at startup
+ocr_model = ocr_predictor(pretrained=True)
+paddle_ocr = PaddleOCR(lang='en', use_angle_cls=True)
+
+def ocr_with_doctr(file):
+    text_output = ''
+    try:
+        logger.info("Processing PDF with Doctr...")
+        doc = DocumentFile.from_pdf(file)
+        result = ocr_model(doc)
+        for page in result.pages:
+            for block in page.blocks:
+                for line in block.lines:
+                    text_output += " ".join([word.value for word in line.words]) + "\n"
+    except Exception as e:
+        logger.error(f"Error processing PDF: {e}")
+        raise HTTPException(status_code=500, detail=f"Error processing PDF: {e}")
+    return text_output
+
+def ocr_with_paddle(img):
+    finaltext = ''
+    try:
+        logger.info("Processing image with PaddleOCR...")
+        result = paddle_ocr.ocr(img)
+        for i in range(len(result[0])):
+            text = result[0][i][1][0]
+            finaltext += ' ' + text
+    except Exception as e:
+        logger.error(f"Error processing image: {e}")
+        raise HTTPException(status_code=500, detail=f"Error processing image: {e}")
+    return finaltext
+
+@app.post("/ocr/")
+async def perform_ocr(file: UploadFile = File(...)):
+    try:
+        logger.info(f"Received file: {file.filename}")
+        file_bytes = await file.read()
+        
+        if file.filename.endswith('.pdf'):
+            logger.info("Detected PDF file")
+            text_output = ocr_with_doctr(io.BytesIO(file_bytes))
+        else:
+            logger.info("Detected image file")
+            img = np.array(Image.open(io.BytesIO(file_bytes)))
+            text_output = ocr_with_paddle(img)
+        
+        logger.info("OCR completed successfully")
+        return {"ocr_text": text_output}
+
+    except Exception as e:
+        logger.error(f"Internal server error: {e}")
+        raise HTTPException(status_code=500, detail=f"Internal server error: {e}")
+
+@app.get("/test/")
+async def test_call():
+    return {"message": "Hi. I'm running"}

requirements.txt

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+fastapi==0.112.2
+uvicorn==0.30.6
+Pillow==10.4.0
+numpy==1.26.4
+paddleocr==2.8.1
+python-doctr==0.9.0
+setuptools==74.0.0
+requests==2.32.3
+paddleocr