Update app.py

app.py

@@ -67,6 +67,21 @@ def generate_math_solution(query):
     )
     return response['choices'][0]['message']['content']
 
+# Function to extract text from image using OCR
+def extract_text_from_image(image):
+    # Use pytesseract to do OCR on the image and extract text
+    text = pytesseract.image_to_string(image)
+    return text
+
+# 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
@@ -96,7 +111,8 @@ if openai_api_key:
         "Mathematics Assistant",  # Added option for Math
         "Biology Assistant",      # Added option for Biology
         "Chemistry Assistant",    # Added option for Chemistry
-        "Physics Assistant"       # Added option for Physics
+        "Physics Assistant",       # Added option for Physics
+        "Image Upload" # New model for image upload
     ))
 
     if mode == "Course Query Assistant":
@@ -380,3 +396,35 @@ 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 OCR
+            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}")