import gradio as gr # Import modules from other files from chatbot import chatbot, model_inference, EXAMPLES from live_chat import videochat # Define Gradio theme theme = gr.themes.Soft( primary_hue="blue", secondary_hue="orange", neutral_hue="gray", font=[gr.themes.GoogleFont('Libre Franklin'), gr.themes.GoogleFont('Public Sans'), 'system-ui', 'sans-serif'] ).set( body_background_fill_dark="#111111", block_background_fill_dark="#111111", block_border_width="1px", block_title_background_fill_dark="#1e1c26", input_background_fill_dark="#292733", button_secondary_background_fill_dark="#24212b", border_color_primary_dark="#343140", background_fill_secondary_dark="#111111", color_accent_soft_dark="transparent" ) with gr.Blocks() as voice: gr.Markdown("## Temproraly Not Working (Update in Progress)") # Chat interface block with gr.Blocks( fill_height=True, css=""".gradio-container .avatar-container {height: 40px width: 40px !important;} #duplicate-button {margin: auto; color: white; background: #f1a139; border-radius: 100vh; margin-top: 2px; margin-bottom: 2px;}""", ) as chat: gr.Markdown("### Chat with Image, Chat with Video, Image Generation and Normal Chat") gr.ChatInterface( fn=model_inference, chatbot=chatbot, examples=EXAMPLES, multimodal=True, cache_examples=False, additional_inputs=[ gr.Checkbox(label="Web Search", value=False), ], ) # Live chat block with gr.Blocks() as livechat: gr.Interface( fn=videochat, inputs=[gr.Image(type="pil",sources="webcam", label="Upload Image"), gr.Textbox(label="Prompt", value="what he is doing")], outputs=gr.Textbox(label="Answer") ) with gr.Blocks() as image: gr.HTML("") with gr.Blocks() as instant2: gr.HTML("") with gr.Blocks() as video: gr.Markdown("""More Models are coming""") gr.TabbedInterface([ instant2], ['Instant🎥']) # Main application block with gr.Blocks(theme=theme, title="OpenGPT 4o DEMO") as demo: gr.Markdown("# OpenGPT 4o") gr.TabbedInterface([chat, voice, livechat, image, video], ['💬 SuperChat','🗣️ Voice Chat','📸 Live Chat', '🖼️ Image Engine', '🎥 Video Engine']) demo.queue(max_size=300) demo.launch()