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Update app.py
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app.py
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@@ -1,11 +1,20 @@
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import gradio as gr
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import os
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import requests
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import json
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SYSTEM_PROMPT = "As an LLM, your job is to generate detailed prompts that start with generate the image, for image generation models based on user input. Be descriptive and specific, but also make sure your prompts are clear and concise."
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TITLE = "Image Prompter"
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EXAMPLE_INPUT = "A Reflective cat between stars."
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zephyr_7b_beta = "https://api-inference.huggingface.co/models/HuggingFaceH4/zephyr-7b-beta/"
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@@ -56,11 +65,14 @@ def predict_beta(message, chatbot=[], system_prompt=""):
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error_msg = f"Failed to decode response as JSON: {str(e)}"
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raise gr.Error(error_msg)
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def
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response = predict_beta(message,
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text_start = response.rfind("", ) + len("")
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response = response[text_start:]
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welcome_preview_message = f"""
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Expand your imagination and broaden your horizons with LLM. Welcome to **{TITLE}**!:\nThis is a chatbot that can generate detailed prompts for image generation models based on simple and short user input.\nSay something like:
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"{EXAMPLE_INPUT}"
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"""
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chatbot_preview.
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import gradio as gr
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import os
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import requests
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SYSTEM_PROMPT = "As an LLM, your job is to generate detailed prompts that start with generate the image, for image generation models based on user input. Be descriptive and specific, but also make sure your prompts are clear and concise."
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TITLE = "Image Prompter"
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EXAMPLE_INPUT = "A Reflective cat between stars."
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import gradio as gr
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import os
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import requests
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# Include the HTML code for displaying the image
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html_temp = """
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<div style="position: absolute; top: 0; right: 0;">
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<img src='https://huggingface.co/spaces/NerdN/open-gpt-Image-Prompter/blob/main/_45a03b4d-ea0f-4b81-873d-ff6b10461d52.jpg' alt='Your Image' style='width:100px;height:100px;'>
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</div>
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"""
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zephyr_7b_beta = "https://api-inference.huggingface.co/models/HuggingFaceH4/zephyr-7b-beta/"
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error_msg = f"Failed to decode response as JSON: {str(e)}"
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raise gr.Error(error_msg)
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def test_preview_chatbot(message, history):
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response = predict_beta(message, history, SYSTEM_PROMPT)
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text_start = response.rfind("", ) + len("")
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response = response[text_start:]
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# Include the image HTML code in the response
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response_with_image = f"{html_temp}\n{response}"
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return response_with_image
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welcome_preview_message = f"""
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Expand your imagination and broaden your horizons with LLM. Welcome to **{TITLE}**!:\nThis is a chatbot that can generate detailed prompts for image generation models based on simple and short user input.\nSay something like:
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"{EXAMPLE_INPUT}"
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"""
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# Use the modified test_preview_chatbot function
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chatbot_preview = gr.Chatbot(layout="panel", value=[(None, welcome_preview_message)])
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textbox_preview = gr.Textbox(scale=7, container=False, value=EXAMPLE_INPUT)
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# Use the modified test_preview_chatbot function
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demo = gr.ChatInterface(test_preview_chatbot, chatbot=chatbot_preview, textbox=textbox_preview)
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demo.launch(share=True)
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