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Update app.py
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app.py
CHANGED
@@ -1,154 +1,186 @@
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import os
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from flask import Flask, render_template, request, jsonify
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import google.generativeai as genai
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from PIL import Image
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from dotenv import load_dotenv
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import time
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#
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file
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})
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app.run(host='0.0.0.0', port=int(os.environ.get('PORT', 7860)))
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import os
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from flask import Flask, render_template, request, jsonify
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import google.generativeai as genai
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from PIL import Image
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from dotenv import load_dotenv
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import time
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import traceback
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import sys
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# Load environment variables
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load_dotenv()
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# Configure Gemini API with key from environment variable
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api_key = os.getenv("GEMINI_API_KEY", "AIzaSyB0IOx76FydAk4wabMz1juzzHF5oBiHW64")
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if api_key == "AIzaSyB0IOx76FydAk4wabMz1juzzHF5oBiHW64":
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print("WARNING: Using hardcoded API key. Set GEMINI_API_KEY environment variable instead.")
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try:
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genai.configure(api_key=api_key)
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print("Successfully configured Gemini API with provided key")
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except Exception as e:
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print(f"Error configuring Gemini API: {str(e)}")
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print(traceback.format_exc())
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# Initialize Flask app
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app = Flask(__name__)
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def extract_text_with_gemini(image_path):
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"""Extract text from image using Gemini Vision model"""
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max_retries = 3
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retry_delay = 2
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for attempt in range(max_retries):
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try:
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print(f"Attempt {attempt + 1} to extract text using Gemini...")
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# Initialize Gemini Pro Vision model
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model = genai.GenerativeModel('gemini-1.0-pro-vision') # Fallback to a stable model
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# Load the image
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with Image.open(image_path) as img:
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print(f"Image loaded from {image_path} (Size: {img.size}, Format: {img.format})")
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# Create prompt for text extraction
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prompt = "Extract all the text from this image. Return only the extracted text, nothing else."
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# Generate response with image
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print("Sending request to Gemini API for text extraction...")
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response = model.generate_content([prompt, img])
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# Validate response
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if not response or not hasattr(response, 'text') or not response.text:
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raise ValueError("Received empty response from Gemini API")
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extracted_text = response.text.strip()
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print(f"Successfully extracted text (length: {len(extracted_text)})")
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return extracted_text
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except Exception as e:
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print(f"Attempt {attempt + 1} failed: {str(e)}")
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print(traceback.format_exc())
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if attempt < max_retries - 1:
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print(f"Retrying in {retry_delay} seconds...")
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time.sleep(retry_delay)
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continue
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return "Could not extract text from the image. Please try with a clearer image."
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def translate_text(text):
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"""Translate text from English to Hindi using Gemini"""
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max_retries = 3
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retry_delay = 2
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# Check if there's text to translate
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if not text or text.strip() == "":
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return "No text to translate."
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for attempt in range(max_retries):
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try:
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print(f"Attempt {attempt + 1} to translate text using Gemini...")
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# Initialize Gemini model
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model = genai.GenerativeModel('gemini-1.0-pro') # Fallback to a stable model
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# Create prompt for translation
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prompt = f"""
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Translate the following English text to Hindi.
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Keep proper names, titles, and organization names unchanged.
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Text to translate: {text}
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"""
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# Generate response
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print("Sending request to Gemini API for translation...")
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response = model.generate_content(prompt)
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# Validate response
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if not response or not hasattr(response, 'text') or not response.text:
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raise ValueError("Received empty response from Gemini API")
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translated_text = response.text.strip()
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print(f"Successfully translated text (length: {len(translated_text)})")
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return translated_text
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except Exception as e:
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print(f"Translation attempt {attempt + 1} failed: {str(e)}")
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print(traceback.format_exc())
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if attempt < max_retries - 1:
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print(f"Retrying in {retry_delay} seconds...")
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time.sleep(retry_delay)
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continue
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return "Translation failed. Please try again later."
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@app.route('/')
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def home():
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return render_template('index.html')
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@app.route('/upload', methods=['POST'])
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def upload_file():
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print("Received upload request")
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if 'file' not in request.files:
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print("No file part in the request")
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return jsonify({'error': 'No file uploaded'}), 400
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file = request.files['file']
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if file.filename == '':
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print("No file selected")
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return jsonify({'error': 'No file selected'}), 400
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# Check file extension
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allowed_extensions = {'png', 'jpg', 'jpeg', 'gif', 'bmp'}
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if '.' not in file.filename or file.filename.rsplit('.', 1)[1].lower() not in allowed_extensions:
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print(f"Invalid file format: {file.filename}")
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return jsonify({'error': 'Invalid file format. Please upload an image (PNG, JPG, JPEG, GIF, BMP).'}), 400
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temp_path = None
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try:
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# Create temp directory if it doesn't exist
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temp_dir = "temp"
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if not os.path.exists(temp_dir):
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os.makedirs(temp_dir)
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print(f"Created temp directory: {temp_dir}")
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# Save the uploaded file temporarily with a unique name
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temp_path = os.path.join(temp_dir, f"temp_image_{int(time.time())}.png")
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file.save(temp_path)
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print(f"Saved uploaded file to {temp_path}")
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# Extract text using Gemini
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print("Starting text extraction...")
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extracted_text = extract_text_with_gemini(temp_path)
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print(f"Text extraction result: {extracted_text[:100]}...")
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# Translate text
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print("Starting text translation...")
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translated_text = translate_text(extracted_text)
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print(f"Translation result: {translated_text[:100]}...")
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return jsonify({
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'original_text': extracted_text,
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'translated_text': translated_text
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})
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except Exception as e:
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error_msg = f"Error processing image: {str(e)}"
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print(error_msg)
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print(traceback.format_exc())
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return jsonify({
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'error': 'An error occurred while processing your image. Please try again.'
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}), 500
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finally:
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# Clean up temporary file if it exists
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try:
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if temp_path and os.path.exists(temp_path):
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os.remove(temp_path)
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print(f"Removed temporary file: {temp_path}")
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except Exception as e:
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print(f"Failed to remove temporary file: {str(e)}")
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if __name__ == '__main__':
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# Ensure the template folder exists
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if not os.path.exists('templates'):
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os.makedirs('templates')
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print("Created 'templates' directory. Please place your HTML files here.")
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# For Hugging Face Spaces, we need to listen on 0.0.0.0 and port 7860
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print(f"Starting Flask app on port {os.environ.get('PORT', 7860)}")
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app.run(host='0.0.0.0', port=int(os.environ.get('PORT', 7860)))
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