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import gradio as gr |
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import requests |
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import json |
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import huggingface_hub |
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from huggingface_hub import HfApi |
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from gradio_client import Client |
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import os |
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HF_TOKEN = os.environ["HF_TOKEN"] |
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HEADERS = {"Authorization": f"Bearer {HF_TOKEN}"} |
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tulu = "https://tonic1-tulu.hf.space/--replicas/gzzjr/" |
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welcome_message = """ |
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Hi! I'm using [Tulu from AlenAi](https://huggingface.co/spaces/Tonic1/Tulu) I'll help you **build a GPT**. You can say something like, "make a bot that gives advice on how to grow your startup." |
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What would you like to make? |
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""" |
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welcome_preview_message = """ |
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Welcome to **{}**! Say something like: |
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"{}" |
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""" |
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system_prompt = """ |
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I an AI whose job it is to help users create their own chatbots. In particular, I respond using titles and subtiles in a friendly tone, write a system prompt for an LLM, a catchy title for the chatbot, and a very short example user input. I make sure each part is included. |
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<|user|> |
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"make a bot that gives advice on how to grow your startup", |
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<|assistant|> |
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I first do a friendly response, then I add the title, system prompt, and example user input. I Immediately STOP after the example input. It should be EXACTLY in this format: |
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Sure, I'd be happy to help you build a bot! I'm generating a title, system prompt, and an example input. How do they sound? Feel free to give me feedback! |
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# Title: Startup Coach |
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# System prompt: Your job as an LLM is to provide good startup advice. Do not provide extraneous comments on other topics. Be succinct but useful. |
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# Example input: Risks of setting up a non-profit board |
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<|user|> |
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Make a chatbot that roasts tech ceos" |
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<|assistant|> |
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Sure, I'd be happy to help you build a bot! I'm generating a title, system prompt, and an example input. How do they sound? Feel free to give me feedback! |
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# Title: Tech Roaster |
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# System prompt: As an LLM, your primary function is to deliver hilarious and biting critiques of technology CEOs. Keep it witty and entertaining, but also make sure your jokes aren't too mean-spirited or factually incorrect. |
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# Example input: Elon Musk |
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""" |
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def predict_beta(message, chatbot=[], system_prompt=system_prompt, max_new_tokens=900, temperature=0.4, top_p=0.9, repetition_penalty=0.9, advanced=False): |
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client = Client(tulu) |
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try: |
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result = client.predict( |
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message, |
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system_prompt, |
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max_new_tokens, |
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temperature, |
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top_p, |
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repetition_penalty, |
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advanced, |
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fn_index=0 |
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) |
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if result is not None and len(result) > 0: |
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bot_message = result[0] |
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print(bot_message) |
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return bot_message |
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else: |
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raise gr.Error("No response received from the model.") |
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except Exception as e: |
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error_msg = f"An error occurred: {str(e)}" |
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raise gr.Error(error_msg) |
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def extract_title_prompt_example(text, title, system_prompt, example_input): |
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default_title = "Custom GPT Agent" |
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default_system_prompt = "This is a custom GPT agent." |
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default_example_input = "Type your query here." |
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title_start = -1 |
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prompt_start = -1 |
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example_start = -1 |
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try: |
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title_start = text.lower().find("title:") + len("title:") |
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if title_start >= len("title:"): |
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prompt_start = text.lower().find("system prompt:", title_start) |
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title = text[title_start:prompt_start].strip() if prompt_start != -1 else "" |
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else: |
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title = "" |
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if prompt_start >= 0: |
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example_start = text.lower().find("example input:", prompt_start) |
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system_prompt = text[prompt_start + len("system prompt:"):example_start].strip() if example_start != -1 else "" |
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else: |
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system_prompt = "" |
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if example_start >= 0: |
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example_input = text[example_start + len("example input:"):].strip().split("\n")[0] |
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else: |
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example_input = "" |
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except Exception as e: |
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print(f"Error in extract_title_prompt_example: {e}") |
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return text, title, system_prompt, example_input |
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return text, title, system_prompt, example_input |
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def make_open_gpt(message, history, current_title, system_prompt, current_example_input): |
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response = predict_beta(message, history, system_prompt) |
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response, title, system_prompt, example_input = extract_title_prompt_example(response, current_title, system_prompt, current_example_input) |
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return "", history + [(message, response)], title, system_prompt, example_input, [(None, welcome_preview_message.format(title, example_input))], example_input, gr.Column(visible=True), gr.Group(visible=True) |
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def set_title_example(title, example): |
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return [(None, welcome_preview_message.format(title, example))], example, gr.Column(visible=True), gr.Group(visible=True) |
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chatbot_preview = gr.Chatbot(layout="panel") |
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textbox_preview = gr.Textbox(scale=7, container=False) |
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def test_preview_chatbot(message, history, system_prompt): |
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response = predict_beta(message, history, system_prompt) |
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text_start = response.rfind("<|assistant|>", ) + len("<|assistant|>") |
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response = response[text_start:] |
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return response |
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def strip_invalid_filename_characters(filename: str, max_bytes: int = 200) -> str: |
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"""Strips invalid characters from a filename and ensures that the file_length is less than `max_bytes` bytes.""" |
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filename = filename.replace(" ", "-") |
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filename = "".join([char for char in filename if char.isalnum() or char in "_-"]) |
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filename_len = len(filename.encode()) |
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if filename_len > max_bytes: |
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while filename_len > max_bytes: |
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if len(filename) == 0: |
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break |
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filename = filename[:-1] |
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filename_len = len(filename.encode()) |
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return filename |
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constants = """ |
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SYSTEM_PROMPT = "{}" |
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TITLE = "{}" |
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EXAMPLE_INPUT = "{}" |
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""" |
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def publish(textbox_system_prompt, textbox_title, textbox_example, textbox_token): |
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source_file = 'app_template.py' |
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destination_file = 'app.py' |
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constants_formatted = constants.format(textbox_system_prompt, textbox_title, textbox_example) |
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with open(source_file, 'r') as file: |
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original_content = file.read() |
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with open(destination_file, 'w') as file: |
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file.write(constants_formatted + original_content) |
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title = strip_invalid_filename_characters(textbox_title, max_bytes=30) |
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api = HfApi(token=textbox_token) |
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new_space = api.create_repo( |
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repo_id=f"open-gpt-{title}", |
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repo_type="space", |
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exist_ok=True, |
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private=False, |
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space_sdk="gradio", |
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token=textbox_token, |
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) |
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api.upload_file( |
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repo_id=new_space.repo_id, |
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path_or_fileobj='app.py', |
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path_in_repo='app.py', |
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token=textbox_token, |
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repo_type="space", |
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) |
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api.upload_file( |
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repo_id=new_space.repo_id, |
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path_or_fileobj='README_template.md', |
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path_in_repo='README.md', |
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token=textbox_token, |
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repo_type="space", |
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) |
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huggingface_hub.add_space_secret( |
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new_space.repo_id, "HF_TOKEN", textbox_token, token=textbox_token |
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) |
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return gr.Markdown(f"Published to https://huggingface.co/spaces/{new_space.repo_id} ✅", visible=True), gr.Button("Publish", interactive=True) |
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css = """ |
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#preview-tab-button{ |
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font-weight: bold; |
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} |
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""" |
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with gr.Blocks(css=css) as demo: |
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gr.Markdown(""" # 👋🏻Welcome to 🕵🏻♂️Agent🌷Tulu |
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**A🕵🏻♂️Agent🌷Tulu** lets you create your own **open-source GPTs** using [allenai/tulu-2-dpo-13b](https://huggingface.co/allenai/tulu-2-dpo-13b). Start chatting to automatically below to automatically bake your GPT (or you can manually configure the recipe in the second tab). You can build and test them for free & publish them on Spaces (as Open GPTs are powered by the [Tulu DPO model](https://huggingface.co/allenai/tulu-2-dpo-70b) ). |
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You think this is cool + want to make your own ? check out [GPTBaker](https://huggingface.co/abidlabs/GPT-Baker) from [AbidLabs](https://huggingface.co/abidlabs) of 🤗[Gradio](https://www.gradio.app/) |
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### Join us: |
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TeamTonic is always making cool demos! Join our active builder's community on Discord: [Discord](https://discord.gg/GWpVpekp) On Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) On Github: [Polytonic](https://github.com/tonic-ai) & contribute to [PolyGPT](https://github.com/tonic-ai/polygpt-alpha) """ |
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) |
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with gr.Row(): |
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with gr.Column(scale=3): |
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with gr.Tab("Create"): |
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chatbot_maker = gr.Chatbot([(None, welcome_message)], layout="panel", elem_id="chatbot-maker") |
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with gr.Group(): |
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with gr.Row(): |
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textbox_maker = gr.Textbox(placeholder="Make a bot that roasts tech CEOs", scale=7, container=False, autofocus=True) |
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submit_btn = gr.Button("Bake 👩🍳", variant="secondary") |
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with gr.Tab("Configure Recipe"): |
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textbox_title = gr.Textbox("GPT Preview", label="Title") |
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textbox_system_prompt = gr.Textbox(label="System prompt", lines=6) |
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textbox_example = gr.Textbox(label="Placeholder example", lines=2) |
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with gr.Tab("Files"): |
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gr.Markdown("RAG coming soon!") |
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with gr.Column(visible=False, scale=5) as preview_column: |
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with gr.Tab("🪄 Preview of your Open GPT", elem_id="preview-tab") as preview_tab: |
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gr.ChatInterface(test_preview_chatbot, chatbot=chatbot_preview, textbox=textbox_preview, autofocus=False, submit_btn="Test", additional_inputs=[textbox_system_prompt]) |
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with gr.Group(visible=False) as publish_row: |
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with gr.Row(): |
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textbox_token = gr.Textbox(show_label=False, placeholder="Ready to publish to Spaces? Enter your HF token here", scale=7) |
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publish_btn = gr.Button("Publish", variant="primary") |
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published_status = gr.Markdown(visible=False) |
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gr.on([submit_btn.click, textbox_maker.submit], make_open_gpt, [textbox_maker, chatbot_maker, textbox_title, textbox_system_prompt, textbox_example], [textbox_maker, chatbot_maker, textbox_title, textbox_system_prompt, textbox_example, chatbot_preview, textbox_preview, preview_column, publish_row]) |
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gr.on([textbox_title.blur, textbox_example.blur], set_title_example, [textbox_title, textbox_example], [chatbot_preview, textbox_preview, preview_column, publish_row]) |
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publish_btn.click(lambda : gr.Button("Publishing...", interactive=False), None, publish_btn).then(publish, [textbox_system_prompt, textbox_title, textbox_example, textbox_token], [published_status, publish_btn]) |
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demo.launch() |