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| import streamlit as st | |
| import base64 | |
| import openai | |
| # Function to encode the image to base64 | |
| def encode_image(image_file): | |
| return base64.b64encode(image_file.getvalue()).decode("utf-8") | |
| # Streamlit page setup | |
| st.set_page_config(page_title="MTSS Image Accessibility Alt Text Generator", layout="centered", initial_sidebar_state="collapsed") | |
| #Add the image with a specified width | |
| image_width = 300 # Set the desired width in pixels | |
| st.image('MTSS.ai_Logo.png', width=image_width) | |
| st.title('MTSS VisionText™ | Accessibility') | |
| st.subheader(':green[_Image Alt Text Generator_]') | |
| # Retrieve the OpenAI API Key from secrets | |
| openai.api_key = st.secrets["openai_api_key"] | |
| # File uploader allows user to add their own image | |
| 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): | |
| 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) | |
| 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 | |
| ) | |
| # Button to trigger the analysis | |
| analyze_button = st.button("Analyse the Image", type="secondary") | |
| # 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 analyze_button: | |
| with st.spinner("Analyzing the image ..."): | |
| # Encode the image | |
| base64_image = encode_image(uploaded_file) | |
| # Optimized prompt for additional clarity and detail | |
| prompt_text = ( | |
| "You are a highly knowledgeable accessibility expert. " | |
| "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 markdown format. " | |
| "Create a detailed image caption in explaining in 150 words or less." | |
| ) | |
| 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 | |
| try: | |
| # Without Stream | |
| # response = openai.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 openai.chat.completions.create( | |
| model="gpt-4-vision-preview", messages=messages, | |
| max_tokens=150, 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) | |
| except Exception as e: | |
| st.error(f"An error occurred: {e}") | |
| else: | |
| # Warnings for user action required | |
| if not uploaded_file and analyze_button: | |
| st.warning("Please upload an image.") | |