import gradio as gr import requests import json import huggingface_hub from huggingface_hub import HfApi from gradio_client import Client import os HF_TOKEN = os.environ["HF_TOKEN"] HEADERS = {"Authorization": f"Bearer {HF_TOKEN}"} tulu = "https://tonic1-tulu.hf.space/--replicas/9sffh/" welcome_message = """ 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." What would you like to make? """ welcome_preview_message = """ Welcome to **{}**! Say something like: "{}" """ # sample_response = """ # Certainly! Here we go: # Title: Recipe Recommender # System Prompt: Utilize your language model abilities to suggest delicious recipes based on user preferences such as ingredients, cuisine type, cooking time, etc. Ensure accuracy and variety while maintaining a conversational style with the user. # Example User Input: Vegetarian dinner ideas under 30 minutes # """ system_prompt = """ You are an AI whose job it is to help users create their own chatbots. In particular, you need to respond succintly in a friendly tone, write a system prompt for an LLM, a catchy title for the chatbot, and a very short example user input. Make sure each part is included. For example, if a user says, "make a bot that gives advice on how to grow your startup", first do a friendly response, then add the title, system prompt, and example user input. Immediately STOP after the example input. It should be EXACTLY in this format: 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! Title: Startup Coach 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. Example input: Risks of setting up a non-profit board Here's another example. If a user types, "Make a chatbot that roasts tech ceos", respond: 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! Title: Tech Roaster 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. Example input: Elon Musk """ def build_input_prompt(message, chatbot, system_prompt): """ Constructs the input prompt string from the chatbot interactions and the current message. """ input_prompt = "<|system|>\n" + system_prompt + "\n<|user|>\n" for interaction in chatbot: input_prompt = input_prompt + str(interaction[0]) + "\n<|assistant|>\n" + str(interaction[1]) + "\n\n<|user|>\n" input_prompt = input_prompt + str(message) + "\n<|assistant|>" return input_prompt def post_request_beta(payload): """ Sends a POST request to the predefined Tulu and returns the JSON response. """ response = requests.post(tulu, headers=HEADERS, json=payload) response.raise_for_status() # Will raise an HTTPError if the HTTP request returned an unsuccessful status code return response.json() def predict_beta(message, chatbot=[], system_prompt=system_prompt): client = Client(tulu) try: # Adjust these parameters as needed max_new_tokens = 1200 temperature = 0.4 top_p = 0.9 repetition_penalty = 0.5 advanced = False # Making the prediction result = client.predict( message, # Your Message system_prompt, # Optional Tulu Assistant Message (can adjust if needed) max_new_tokens, temperature, top_p, repetition_penalty, advanced, fn_index=0 ) # Extracting the response if result is not None and len(result) > 0: bot_message = result[0] # Assuming the response is in the first element return bot_message else: raise gr.Error("No response received from the model.") except Exception as e: error_msg = f"An error occurred: {str(e)}" raise gr.Error(error_msg) def extract_title_prompt_example(text, title, system_prompt, example_input): try: # Finding the indices of the key terms text_start = text.rfind("<|assistant|>", ) + len("<|assistant|>") text = text[text_start:] except ValueError: pass try: title_start = text.lower().rfind("title:") + len("title:") prompt_start = text.lower().rfind("system prompt:") title = text[title_start:prompt_start].strip() except ValueError: pass try: prompt_start = text.lower().rfind("system prompt:") + len("system prompt:") example_start = text.lower().rfind("example input:") system_prompt = text[prompt_start:example_start].strip() except ValueError: pass try: example_start = text.lower().rfind("example input:") + len("example input:") example_input = text[example_start:].strip() example_input = example_input[:example_input.index("\n")] except ValueError: pass return text, title, system_prompt, example_input def make_open_gpt(message, history, current_title, system_prompt, current_example_input): response = predict_beta(message, history, system_prompt) response, title, system_prompt, example_input = extract_title_prompt_example(response, current_title, system_prompt, current_example_input) 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) def set_title_example(title, example): return [(None, welcome_preview_message.format(title, example))], example, gr.Column(visible=True), gr.Group(visible=True) chatbot_preview = gr.Chatbot(layout="panel") textbox_preview = gr.Textbox(scale=7, container=False) def test_preview_chatbot(message, history, system_prompt): response = predict_beta(message, history, system_prompt) text_start = response.rfind("<|assistant|>", ) + len("<|assistant|>") response = response[text_start:] return response def strip_invalid_filename_characters(filename: str, max_bytes: int = 200) -> str: """Strips invalid characters from a filename and ensures that the file_length is less than `max_bytes` bytes.""" filename = filename.replace(" ", "-") filename = "".join([char for char in filename if char.isalnum() or char in "_-"]) filename_len = len(filename.encode()) if filename_len > max_bytes: while filename_len > max_bytes: if len(filename) == 0: break filename = filename[:-1] filename_len = len(filename.encode()) return filename constants = """ SYSTEM_PROMPT = "{}" TITLE = "{}" EXAMPLE_INPUT = "{}" """ def publish(textbox_system_prompt, textbox_title, textbox_example, textbox_token): source_file = 'app_template.py' destination_file = 'app.py' constants_formatted = constants.format(textbox_system_prompt, textbox_title, textbox_example) with open(source_file, 'r') as file: original_content = file.read() with open(destination_file, 'w') as file: file.write(constants_formatted + original_content) title = strip_invalid_filename_characters(textbox_title, max_bytes=30) api = HfApi(token=textbox_token) new_space = api.create_repo( repo_id=f"open-gpt-{title}", repo_type="space", exist_ok=True, private=False, space_sdk="gradio", token=textbox_token, ) api.upload_file( repo_id=new_space.repo_id, path_or_fileobj='app.py', path_in_repo='app.py', token=textbox_token, repo_type="space", ) api.upload_file( repo_id=new_space.repo_id, path_or_fileobj='README_template.md', path_in_repo='README.md', token=textbox_token, repo_type="space", ) huggingface_hub.add_space_secret( new_space.repo_id, "HF_TOKEN", textbox_token, token=textbox_token ) return gr.Markdown(f"Published to https://huggingface.co/spaces/{new_space.repo_id} ✅", visible=True), gr.Button("Publish", interactive=True) css = """ #preview-tab-button{ font-weight: bold; } """ with gr.Blocks(css=css) as demo: gr.Markdown(""" # 👋🏻Welcome to 🕵🏻‍♂️Agent🌷Tulu **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) ). 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/) ### Join us: 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) """ ) with gr.Row(): with gr.Column(scale=3): with gr.Tab("Create"): chatbot_maker = gr.Chatbot([(None, welcome_message)], layout="panel", elem_id="chatbot-maker") with gr.Group(): with gr.Row(): textbox_maker = gr.Textbox(placeholder="Make a bot that roasts tech CEOs", scale=7, container=False, autofocus=True) submit_btn = gr.Button("Bake 👩‍🍳", variant="secondary") with gr.Tab("Configure Recipe"): textbox_title = gr.Textbox("GPT Preview", label="Title") textbox_system_prompt = gr.Textbox(label="System prompt", lines=6) textbox_example = gr.Textbox(label="Placeholder example", lines=2) with gr.Tab("Files"): gr.Markdown("RAG coming soon!") with gr.Column(visible=False, scale=5) as preview_column: with gr.Tab("🪄 Preview of your Open GPT", elem_id="preview-tab") as preview_tab: gr.ChatInterface(test_preview_chatbot, chatbot=chatbot_preview, textbox=textbox_preview, autofocus=False, submit_btn="Test", additional_inputs=[textbox_system_prompt]) with gr.Group(visible=False) as publish_row: with gr.Row(): textbox_token = gr.Textbox(show_label=False, placeholder="Ready to publish to Spaces? Enter your HF token here", scale=7) publish_btn = gr.Button("Publish", variant="primary") published_status = gr.Markdown(visible=False) 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]) gr.on([textbox_title.blur, textbox_example.blur], set_title_example, [textbox_title, textbox_example], [chatbot_preview, textbox_preview, preview_column, publish_row]) 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]) demo.launch()