Update app.py

app.py

@@ -7,20 +7,6 @@ import numpy as np
 from sklearn.feature_extraction.text import TfidfVectorizer
 from sklearn.metrics.pairwise import cosine_similarity
 from io import StringIO
-import easyocr
-
-# Function to extract text from image using EasyOCR
-def extract_text_from_image(image):
-    # Initialize EasyOCR reader
-    reader = easyocr.Reader(['en'])  # Specify language(s); you can add more like ['en', 'fr'] for multiple languages
-    
-    # Read text from the image
-    result = reader.readtext(image)
-    
-    # Extract and concatenate the text from the OCR result
-    text = ' '.join([item[1] for item in result])  # item[1] contains the recognized text
-    
-    return text
 
 # Function to extract text from a PDF file
 def extract_text_from_pdf(pdf_file):
@@ -80,16 +66,7 @@ def generate_math_solution(query):
         messages=[{"role": "user", "content": prompt}]
     )
     return response['choices'][0]['message']['content']
-
-# Function to answer questions based on the image or its content
-def answer_question_based_on_image(query, image_text):
-    prompt = f"The following is text extracted from an image: {image_text}\n\nQuestion: {query}\n\nAnswer the question based on the image text."
-    response = openai.ChatCompletion.create(
-        model="gpt-4o-mini",  # You can choose another model like GPT-4 Vision, if available
-        messages=[{"role": "user", "content": prompt}]
-    )
-    return response['choices'][0]['message']['content']
-    
+   
 from PIL import Image  # Required for local image files
 
 # Streamlit app starts here
@@ -404,35 +381,3 @@ if openai_api_key:
                 )
                 answer = response['choices'][0]['message']['content']
                 st.write(f"### Answer: {answer}")
-
-    elif mode == "Image Upload":
-        st.header("Image Upload and Analysis")
-
-        # Image upload feature
-        uploaded_image = st.file_uploader("Upload an image:", type=["jpg", "jpeg", "png"])
-
-        if uploaded_image:
-            # Open the image with PIL
-            image = Image.open(uploaded_image)
-
-            # Display the uploaded image
-            st.image(image, caption="Uploaded Image", use_column_width=True)
-
-            # Extract text from the image using EasyOCR
-            with st.spinner("Extracting text from the image..."):
-                image_text = extract_text_from_image(image)
-
-            # Show the extracted text
-            if image_text:
-                st.write("### Extracted Text from Image:")
-                st.write(image_text)
-            else:
-                st.write("No text was extracted from the image.")
-
-            # Allow the user to ask questions about the image
-            question = st.text_input("Ask a question about the image:")
-
-            if question:
-                with st.spinner("Getting answer..."):
-                    answer = answer_question_based_on_image(question, image_text)
-                    st.write(f"### Answer: {answer}")