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import gradio as gr
import requests
import json
from reportlab.lib.pagesizes import letter
from reportlab.pdfgen import canvas
# Hugging Face Inference API details
HF_API_URL = "https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Instruct-v0.3"
import os
HF_API_KEY = os.getenv("HF_API_KEY") # Read from environment variable
HEADERS = {"Authorization": f"Bearer {HF_API_KEY}"}
# Function to call Hugging Face API
def query_hf_api(prompt):
payload = {"inputs": prompt}
response = requests.post(HF_API_URL, headers=HEADERS, json=payload)
if response.status_code == 200:
return response.json()[0]["generated_text"]
else:
return f"Error: {response.status_code} - {response.text}"
# Debate function
def conduct_debate(topic):
# AI Assistant 1's response
prompt_1 = f"The topic of debate is: {topic}. Present your argument in favor."
response_1 = query_hf_api(prompt_1)
# AI Assistant 2's response
prompt_2 = f"The topic of debate is: {topic}. Present your argument against."
response_2 = query_hf_api(prompt_2)
# Judge's conclusion
prompt_judge = f"The debate topic was: {topic}. One argument in favor: {response_1}. One argument against: {response_2}. As a judge, analyze the arguments and provide a fair conclusion."
conclusion = query_hf_api(prompt_judge)
return response_1, response_2, conclusion
# Function to generate a PDF
def generate_pdf(topic, response_1, response_2, conclusion):
pdf_filename = "debate_result.pdf"
c = canvas.Canvas(pdf_filename, pagesize=letter)
c.drawString(100, 750, f"Debate Topic: {topic}")
c.drawString(100, 730, "Argument in Favor:")
c.drawString(100, 710, response_1[:1000]) # Limiting text for PDF readability
c.drawString(100, 690, "Argument Against:")
c.drawString(100, 670, response_2[:1000])
c.drawString(100, 650, "Judge's Conclusion:")
c.drawString(100, 630, conclusion[:1000])
c.save()
return pdf_filename
# Gradio UI
def debate_interface(topic):
response_1, response_2, conclusion = conduct_debate(topic)
pdf_file = generate_pdf(topic, response_1, response_2, conclusion)
return response_1, response_2, conclusion, pdf_file
iface = gr.Interface(
fn=debate_interface,
inputs=gr.Textbox(label="Enter Debate Topic"),
outputs=[
gr.Textbox(label="Argument in Favor"),
gr.Textbox(label="Argument Against"),
gr.Textbox(label="Judge's Conclusion"),
gr.File(label="Download Debate PDF")
],
title="AI Debate Platform",
description="Enter a debate topic and let two AI assistants argue, with a third AI model acting as a judge."
)
iface.launch()
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