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Update app.py
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app.py
CHANGED
@@ -1800,18 +1800,19 @@ if AddAFileForContext:
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def main():
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#st.markdown("### OpenAI GPT-4o Model")
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st.markdown("##### GPT-4o Omni Model: Text, Audio, Image, & Video")
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option = st.selectbox("Select an option", ("Text", "Image", "Audio", "Video"))
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if option == "Text":
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text_input = st.text_input("Enter your text:")
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if (text_input > ''):
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textResponse = process_text(text_input)
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elif option == "Image":
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text = "Help me understand what is in this picture and list ten facts as markdown outline with appropriate emojis that describes what you see."
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text_input = st.text_input(label="Enter text prompt to use with Image context.", value=text)
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image_input = st.file_uploader("Upload an image", type=["png"])
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elif option == "Audio":
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text = "You are generating a transcript summary. Create a summary of the provided transcription. Respond in Markdown."
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@@ -1824,7 +1825,6 @@ def main():
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process_audio(audio_input, text_input)
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elif option == "Audio old":
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#text = "Transcribe and answer questions as a helpful audio music and speech assistant. "
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text = "You are generating a transcript summary. Create a summary of the provided transcription. Respond in Markdown."
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text_input = st.text_input(label="Enter text prompt to use with Audio context.", value=text)
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@@ -1851,7 +1851,6 @@ def main():
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video_input = st.file_uploader("Upload a video file", type=["mp4"])
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process_audio_and_video(video_input)
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# Enter the GPT-4o omni model in streamlit chatbot
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current_messages=[]
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for message in st.session_state.messages:
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current_messages.append(message)
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st.markdown(message["content"])
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# 🎵 Wav Audio files - Transcription History in Wav
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audio_files = glob.glob("*.wav")
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audio_files = [file for file in audio_files if len(os.path.splitext(file)[0]) >= 10] # exclude files with short names
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@@ -1881,9 +1878,6 @@ video_files_mp3 = glob.glob("*.mp3")
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video_files_mp3 = [file for file in video_files_mp3 if len(os.path.splitext(file)[0]) >= 10] # exclude files with short names
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video_files_mp3.sort(key=lambda x: (os.path.splitext(x)[1], x), reverse=True) # sort by file type and file name in descending order
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main()
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# Delete All button for each file type
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@@ -1962,10 +1956,6 @@ for file in video_files_mp3:
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os.remove(file)
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st.rerun()
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# ChatBot Entry
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if prompt := st.chat_input("GPT-4o Multimodal ChatBot - What can I help you with?"):
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st.session_state.messages.append({"role": "user", "content": prompt})
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response = process_text2(text_input=prompt)
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st.session_state.messages.append({"role": "assistant", "content": response})
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# Image and Video Galleries
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num_columns_images=st.slider(key="num_columns_images", label="Choose Number of Image Columns", min_value=1, max_value=15, value=3)
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display_images_and_wikipedia_summaries(num_columns_images) # Image Jump Grid
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num_columns_video=st.slider(key="num_columns_video", label="Choose Number of Video Columns", min_value=1, max_value=15, value=3)
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display_videos_and_links(num_columns_video) # Video Jump Grid
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# Optional UI's
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showExtendedTextInterface=False
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if showExtendedTextInterface:
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num_columns_text=st.slider(key="num_columns_text", label="Choose Number of Text Columns", min_value=1, max_value=15, value=4)
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display_buttons_with_scores(num_columns_text) # Feedback Jump Grid
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st.markdown(personality_factors)
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#if __name__ == "__main__":
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def main():
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st.markdown("##### GPT-4o Omni Model: Text, Audio, Image, & Video")
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option = st.selectbox("Select an option", ("Text", "Image", "Audio", "Video"))
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if option == "Text":
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text_input = st.text_input("Enter your text:")
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if (text_input > ''):
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textResponse = process_text(text_input)
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elif option == "Image":
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text = "Help me understand what is in this picture and list ten facts as markdown outline with appropriate emojis that describes what you see."
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text_input = st.text_input(label="Enter text prompt to use with Image context.", value=text)
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image_input = st.file_uploader("Upload an image", type=["png"])
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if (image_input is not None):
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image_response = process_image(image_input, text_input)
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elif option == "Audio":
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text = "You are generating a transcript summary. Create a summary of the provided transcription. Respond in Markdown."
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process_audio(audio_input, text_input)
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elif option == "Audio old":
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text = "You are generating a transcript summary. Create a summary of the provided transcription. Respond in Markdown."
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text_input = st.text_input(label="Enter text prompt to use with Audio context.", value=text)
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video_input = st.file_uploader("Upload a video file", type=["mp4"])
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process_audio_and_video(video_input)
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# Enter the GPT-4o omni model in streamlit chatbot
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current_messages=[]
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for message in st.session_state.messages:
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current_messages.append(message)
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st.markdown(message["content"])
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# 🎵 Wav Audio files - Transcription History in Wav
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audio_files = glob.glob("*.wav")
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audio_files = [file for file in audio_files if len(os.path.splitext(file)[0]) >= 10] # exclude files with short names
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video_files_mp3 = [file for file in video_files_mp3 if len(os.path.splitext(file)[0]) >= 10] # exclude files with short names
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video_files_mp3.sort(key=lambda x: (os.path.splitext(x)[1], x), reverse=True) # sort by file type and file name in descending order
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main()
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# Delete All button for each file type
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os.remove(file)
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st.rerun()
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# ChatBot Entry
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if prompt := st.chat_input("GPT-4o Multimodal ChatBot - What can I help you with?"):
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st.session_state.messages.append({"role": "user", "content": prompt})
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response = process_text2(text_input=prompt)
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st.session_state.messages.append({"role": "assistant", "content": response})
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# Image and Video Galleries
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num_columns_images=st.slider(key="num_columns_images", label="Choose Number of Image Columns", min_value=1, max_value=15, value=3)
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display_images_and_wikipedia_summaries(num_columns_images) # Image Jump Grid
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num_columns_video=st.slider(key="num_columns_video", label="Choose Number of Video Columns", min_value=1, max_value=15, value=3)
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display_videos_and_links(num_columns_video) # Video Jump Grid
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# Optional UI's
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showExtendedTextInterface=False
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if showExtendedTextInterface:
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num_columns_text=st.slider(key="num_columns_text", label="Choose Number of Text Columns", min_value=1, max_value=15, value=4)
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display_buttons_with_scores(num_columns_text) # Feedback Jump Grid
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st.markdown(personality_factors)
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