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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:grey[.ai]') | |
| # st.header('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 specified width | |
| # image_width = 100 # Set the desired width in pixels | |
| # with st.expander("Image", expanded=True): | |
| # st.image(uploaded_file, caption=uploaded_file.name, width=image_width, use_column_width=False) | |
| # # 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( | |
| # "The details could include specific information that is important to include in the alt text or reflect why the image is being used:", | |
| # disabled=not show_details | |
| # ) | |
| # # Toggle for modifying the prompt for complex images | |
| # complex_image = st.toggle("Is this a complex image? ", value=False) | |
| # if complex_image: | |
| # # Text input for additional details about the image, shown only if toggle is True | |
| # complex_image_details = st.caption( | |
| # "By clicking this toggle, it will inform MTSS.ai to create a description that exceeds the 125 character limit. " | |
| # "Add the description in a placeholder behind the image and 'Description in the content placeholder' in the alt text box. " | |
| # ) | |
| # # Button to trigger the analysis | |
| # analyze_button = st.button("Analyze the Image", type="secondary") | |
| # # Optimized prompt for complex images | |
| # complex_image_prompt_text = ( | |
| # "As an expert in image accessibility and alternative text, thoroughly describe the image provided. " | |
| # "Provide a brief description using not more than 500 characters that convey the essential information conveyed by the image in eight or fewer clear and concise sentences. " | |
| # "Skip phrases like 'image of' or 'picture of.' " | |
| # "Your description should form a clear, well-structured, and factual paragraph that avoids bullet points, focusing on creating a seamless narrative." | |
| # ) | |
| # # 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) | |
| # # Determine which prompt to use based on the complexity of the image | |
| # if complex_image: | |
| # prompt_text = complex_image_prompt_text | |
| # else: | |
| # prompt_text = ( | |
| # "As an expert in image accessibility and alternative text, succinctly describe the image provided in less than 125 characters. " | |
| # "Provide a brief description using not more than 125 characters that convey the essential information conveyed by the image in three or fewer clear and concise sentences for use as alt text. " | |
| # "Skip phrases like 'image of' or 'picture of.' " | |
| # "Your description should form a clear, well-structured, and factual paragraph that avoids bullet points and newlines, focusing on creating a seamless narrative that serves as effective alternative text for accessibility purposes." | |
| # ) | |
| # 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=250, 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=250, 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) # stream text | |
| # # Check if there is content to display | |
| # if completion.choices[0].delta.content is not None: | |
| # full_response += completion.choices[0].delta.content | |
| # # Display the response in a text area | |
| # st.text_area('Response:', value=full_response, height=250, key="response_text_area") | |
| # st.success('Powered by MTSS GPT. AI can make mistakes. Consider checking important information.') | |
| # 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.") | |
| 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 logo image with a specified width | |
| image_width = 300 # Set the desired width in pixels | |
| st.image('MTSS.ai_Logo.png', width=image_width) | |
| st.header('VisionText™ | Accessibility') | |
| st.subheader(':green[_Image Alt Text Generator_]') | |
| # Retrieve the OpenAI API Key from secrets | |
| openai.api_key = st.secrets["openai_api_key"] | |
| # Initialize an empty string for the full_response to ensure the text area is always displayed | |
| full_response = "Awaiting analysis..." | |
| # Toggle for showing additional details input | |
| show_details = st.toggle("Add details about the image.", value=False) | |
| # Text input for additional details about the image, shown based on the toggle state | |
| additional_details = "" | |
| if show_details: | |
| additional_details = st.text_area( | |
| "The details could include specific information that is important to include in the alt text or reflect why the image is being used:" | |
| ) | |
| # Toggle for modifying the prompt for complex images | |
| complex_image = st.toggle("Is this a complex image?", value=False) | |
| # Button to trigger the analysis | |
| analyze_button = st.button("Analyze the Image") | |
| # Display the response in a text area | |
| response_text_area = st.text_area('Response:', value=full_response, height=250, key="response_text_area") | |
| # 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 specified width in an expander | |
| with st.expander("Image Preview", expanded=True): | |
| st.image(uploaded_file, caption=uploaded_file.name, width=100, use_column_width=False) | |
| # Ensure that analysis only proceeds when an image is uploaded and the analyze button is pressed | |
| if uploaded_file is not None and analyze_button: | |
| with st.spinner("Analyzing the image..."): | |
| # Encode the image for analysis | |
| base64_image = encode_image(uploaded_file) | |
| # Logic to set prompt_text based on complex_image toggle state and append additional_details if provided | |
| # Your OpenAI API call and handling logic here to update full_response based on the analysis | |
| # Update the response text area with the new full_response | |
| response_text_area.text_area('Response:', value=full_response, height=250, key="response_text_area") | |
| st.success('Analysis complete. Review the generated text for accuracy.') | |
| else: | |
| if not uploaded_file and analyze_button: | |
| st.warning("Please upload an image to proceed with the analysis.") | |