import openai import gradio as gr openai.api_key = "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" def predict(message, history): history_openai_format = [] for human, assistant in history: history_openai_format.append({"role": "user", "content": human }) history_openai_format.append({"role": "assistant", "content":assistant}) history_openai_format.append({"role": "user", "content": message}) response = openai.ChatCompletion.create( model='gpt-3.5-turbo', messages= history_openai_format, temperature=1.0, stream=True ) partial_message = "" for chunk in response: if len(chunk['choices'][0]['delta']) != 0: partial_message = partial_message + chunk['choices'][0]['delta']['content'] yield partial_message A1 = gr.ChatInterface(predict, title="TREBLE", description="An AI Powered Chatbot with Vision and Image Generation Capabilities Created By Peach State Innovation and Technology. Ask Me A Question About Anything...From Georgia and Beyond...And I'll Give You An Answer!", theme= gr.themes.Glass(primary_hue="amber", neutral_hue="lime"), retry_btn=None, clear_btn="Clear") A2 = gr.load( "huggingface/Salesforce/blip-image-captioning-large", title="Upon Further Review...", description="Upload or Take a Photo Image, I'll Describe It For You", outputs=[gr.Textbox(label="I see...")], theme= gr.themes.Glass(primary_hue="amber", neutral_hue="lime")) A3 = gr.load( "huggingface/stabilityai/stable-diffusion-xl-base-1.0", inputs=[gr.Textbox(label="Enter Your Image Description")], outputs=[gr.Image(label="Image")], title="Sailcloth", description="Bring Your Imagination Into Existence On The Digital Canvas", allow_flagging="never", examples=["A monster wandering the streets of downtown Atlanta","A robot in a Brazilian favela"]) pcp = gr.TabbedInterface([A1, A2, A3], ["Chat", "Describe", "Create"], theme= gr.themes.Glass(primary_hue="amber", neutral_hue="lime")) pcp.queue().launch()