Create app.py

app.py

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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()