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import gradio as gr
import json
from datetime import datetime
from theme import TufteInspired
import glob
import os
import uuid
from pathlib import Path
from huggingface_hub import InferenceClient
from openai import OpenAI
from huggingface_hub import get_token
from huggingface_hub import CommitScheduler, hf_hub_download, login
from prompts import detailed_genre_description_prompt, basic_prompt
import random
# TODOs
# 1. Add a login button
# 2. Prompt library expand
# 3. log user if logged in
client = OpenAI(
base_url="https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-70B-Instruct/v1",
api_key=get_token(),
)
def generate_prompt():
if random.choice([True, False]):
return detailed_genre_description_prompt()
else:
return basic_prompt()
def generate_blurb():
max_tokens = random.randint(100, 1000)
prompt = generate_prompt()
print(prompt)
chat_completion = client.chat.completions.create(
model="tgi",
messages=[
{"role": "user", "content": prompt},
],
stream=True,
max_tokens=max_tokens,
)
full_text = ""
for message in chat_completion:
full_text += message.choices[0].delta.content
yield full_text
# Function to log blurb and vote
def log_blurb_and_vote(blurb, vote):
log_entry = {"timestamp": datetime.now().isoformat(), "blurb": blurb, "vote": vote}
with open("blurb_log.jsonl", "a") as f:
f.write(json.dumps(log_entry) + "\n")
gr.Info("Thank you for voting!")
return f"Logged: {vote}"
# Create custom theme
tufte_theme = TufteInspired()
# Create Gradio interface
with gr.Blocks(theme=tufte_theme) as demo:
gr.Markdown("<h1 style='text-align: center;'>Would you read this book?</h1>")
gr.Markdown(
"""<p style='text-align: center;'>Looking for your next summer read?
Would you read a book based on this LLM generated blurb? <br> Your vote will be added to <a href="https://example.com">this</a> Hugging Face dataset</p>"""
+ """"""
)
# gr.LoginButton(size="sm")
user_name = gr.Textbox(label="User Name", placeholder="Enter your name")
with gr.Row():
generate_btn = gr.Button("Create a book", variant="primary")
blurb_output = gr.Markdown(label="Book blurb")
with gr.Row(visible=False) as voting_row:
upvote_btn = gr.Button("👍 would read")
downvote_btn = gr.Button("👎 wouldn't read")
vote_output = gr.Textbox(label="Vote Status", interactive=False, visible=False)
def show_voting_buttons(blurb):
return blurb, gr.Row(visible=True)
generate_btn.click(generate_blurb, outputs=blurb_output).then(
show_voting_buttons, inputs=blurb_output, outputs=[blurb_output, voting_row]
)
upvote_btn.click(
lambda x: log_blurb_and_vote(x, "upvote"),
inputs=blurb_output,
outputs=vote_output,
)
downvote_btn.click(
lambda x: log_blurb_and_vote(x, "downvote"),
inputs=blurb_output,
outputs=vote_output,
)
if __name__ == "__main__":
demo.launch()
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