Update app.py

app.py

@@ -1,111 +1,54 @@
 import streamlit as st
 import base64
-# from openai import OpenAI
 import openai
 
-
 # Function to encode the image to base64
 def encode_image(image_file):
     return base64.b64encode(image_file.getvalue()).decode("utf-8")
 
-st.set_page_config(page_title="MTSS Image Accessibility Alt Text Generator", layout="centered", initial_sidebar_state="collapsed")
 # Streamlit page setup
+st.set_page_config(page_title="MTSS Image Accessibility Alt Text Generator", layout="centered", initial_sidebar_state="collapsed")
 st.title("MTSS Snapshot: Accessibility Image Textifier: `Alt Text`")
 
-# Retrieve the OpenAI API key from Streamlit secrets
-openai_api_key = st.secrets["openai_api_key"]
-
-# Initialize the OpenAI client with the API key
-# client = OpenAI(api_key=openai_api_key)
-client = openai.api_key(api_key=openai_api_key)
-# openai.api_key = openai_api_key
+# Retrieve the OpenAI API key from Streamlit secrets and set it
+openai.api_key = st.secrets["openai_api_key"]
 
-# File uploader allows user to add their own image
+# File uploader for images
 uploaded_file = st.file_uploader("Upload an image", type=["jpg", "png", "jpeg"])
 
 if uploaded_file:
-    # Display the uploaded image
-    with st.expander("Image", expanded = True):
+    with st.expander("Image", expanded=True):
         st.image(uploaded_file, caption=uploaded_file.name, use_column_width=True)
 
-# Toggle for showing additional details input
-show_details = st.toggle("Add details about the image", value=False)
+# Toggle for additional details input
+show_details = st.checkbox("Add details about the image")
 
 if show_details:
-    # Text input for additional details about the image, shown only if toggle is True
-    additional_details = st.text_area(
-        "Add any additional details or context about the image here:",
-        disabled=not show_details
-    )
+    additional_details = st.text_area("Add any additional details or context about the image here:")
 
 # Button to trigger the analysis
-analyze_button = st.button("Analyse the Scientific Image", type="secondary")
+analyze_button = st.button("Analyse the Scientific Image")
 
-# Check if an image has been uploaded, if the API key is available, and if the button has been pressed
-if uploaded_file is not None and api_key and analyze_button:
-
-    with st.spinner("Analysing the image ..."):
-        # Encode the image
+if uploaded_file and openai.api_key and analyze_button:
+    with st.spinner("Analysing the image..."):
         base64_image = encode_image(uploaded_file)
-    
-        # Optimized prompt for additional clarity and detail
-        prompt_text = (
-            "You are a highly knowledgeable accessibility specialist. "
-            "Your task is to examine the following image in detail. "
-            "Provide a comprehensive, factual, and accurate explanation of what the image depicts. "
-            "Highlight key elements and their significance, and present your analysis in clear, well-structured format. "
-            "Assume the reader has a basic understanding of scientific concepts."
-            "Create a detailed image caption using 150 words or less."
-        )
-    
+        prompt_text = "You are a highly knowledgeable accessibility specialist. [Your detailed prompt here]"
+
         if show_details and additional_details:
-            prompt_text += (
-                f"\n\nAdditional Context Provided by the User:\n{additional_details}"
-            )
-    
-        # Create the payload for the completion request
-        messages = [
-            {
-                "role": "user",
-                "content": [
-                    {"type": "text", "text": prompt_text},
-                    {
-                        "type": "image_url",
-                        "image_url": f"data:image/jpeg;base64,{base64_image}",
-                    },
-                ],
-            }
-        ]
-    
-        # Make the request to the OpenAI API
+            prompt_text += f"\n\nAdditional Context Provided by the User:\n{additional_details}"
+
+        # Define the messages payload
+        messages = [{
+            "role": "user",
+            "content": [{"type": "text", "text": prompt_text}, {"type": "image_url", "image_url": f"data:image/jpeg;base64,{base64_image}"}]
+        }]
+
         try:
-            # Without Stream
-            
-            # response = client.chat.completions.create(
-            #     model="gpt-4-vision-preview", messages=messages, max_tokens=500, stream=False
-            # )
-    
-            # Stream the response
-            full_response = ""
-            message_placeholder = st.empty()
-            for completion in client.chat.completions.create(
-                model="gpt-4-vision-preview", messages=messages, 
-                max_tokens=1200, stream=True
-            ):
-                # Check if there is content to display
-                if completion.choices[0].delta.content is not None:
-                    full_response += completion.choices[0].delta.content
-                    message_placeholder.markdown(full_response + "▌")
-            # Final update to placeholder after the stream ends
-            message_placeholder.markdown(full_response)
-    
-            # Display the response in the app
-            # st.write(response.choices[0].message.content)
+            # Make the request to OpenAI and handle streaming if required
+            response = openai.ChatCompletion.create(model="gpt-4-vision-preview", messages=messages, max_tokens=1200)
+            st.write(response.choices[0].message.content)
         except Exception as e:
             st.error(f"An error occurred: {e}")
 else:
-    # Warnings for user action required
-    if not uploaded_file and analyze_button:
+    if not uploaded_file:
         st.warning("Please upload an image.")
-    if not api_key:
-        st.warning("Please enter your OpenAI API key.")