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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/gzzjr/"
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 = """
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.
<|user|>
"make a bot that gives advice on how to grow your startup",
<|assistant|>
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:
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
<|user|>
Make a chatbot that roasts tech ceos"
<|assistant|>
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 predict_beta(message, chatbot=[], system_prompt=system_prompt, max_new_tokens=1200, temperature=0.4, top_p=0.9, repetition_penalty=0.5, advanced=True):
client = Client(tulu)
try:
result = client.predict(
message,
system_prompt,
max_new_tokens,
temperature,
top_p,
repetition_penalty,
advanced,
fn_index=0
)
if result is not None and len(result) > 0:
bot_message = result[0]
print(bot_message)
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):
# Default values if the expected format is not found
default_title = "Custom GPT Agent"
default_system_prompt = "This is a custom GPT agent."
default_example_input = "Type your query here."
# Initialize variables
title_start = -1
prompt_start = -1
example_start = -1
try:
title_start = text.lower().find("title:") + len("title:")
if title_start >= len("title:"):
prompt_start = text.lower().find("system prompt:", title_start)
title = text[title_start:prompt_start].strip() if prompt_start != -1 else ""
else:
title = ""
if prompt_start >= 0:
example_start = text.lower().find("example input:", prompt_start)
system_prompt = text[prompt_start + len("system prompt:"):example_start].strip() if example_start != -1 else ""
else:
system_prompt = ""
if example_start >= 0:
example_input = text[example_start + len("example input:"):].strip().split("\n")[0]
else:
example_input = ""
except Exception as e:
print(f"Error in extract_title_prompt_example: {e}")
# Return the original values if there's an error
return text, title, system_prompt, example_input
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() |