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app.py

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+
+import gradio as gr
+import json
+from transformers import pipeline
+from gtts import gTTS
+import os
+
+# Load all personas
+def load_personas():
+    personas = []
+    for i in range(1, 7):
+        with open(f'personas/persona_{i}.json', 'r') as f:
+            personas.append(json.load(f))
+    return personas
+
+personas = load_personas()
+
+# Use GPT-2 for demo purposes
+bot = pipeline("text-generation", model="gpt2")
+
+# Debate function
+def start_debate(topic):
+    history = f"Debate Topic: {topic}\n"
+    outputs = []
+
+    for idx, persona in enumerate(personas):
+        prompt = f"{persona['prompt_style']}\n{history}\n{persona['name']}:"
+        response = bot(prompt, max_length=100, do_sample=True)[0]['generated_text']
+        response_text = response[len(prompt):].strip().split("\n")[0]
+
+        # Update history
+        history += f"{persona['name']}: {response_text}\n"
+
+        # Generate TTS using gTTS (placeholder for 11 Labs)
+        tts = gTTS(response_text, lang='en')
+        audio_file = f"temp_{idx}.mp3"
+        tts.save(audio_file)
+
+        outputs.append((f"{persona['name']}: {response_text}", audio_file))
+
+    return outputs
+
+# Gradio Interface
+def debate_interface(topic):
+    results = start_debate(topic)
+    texts = [r[0] for r in results]
+    audios = [r[1] for r in results]
+    return texts, audios
+
+text_output = [gr.Textbox(label=f"Turn {i+1}") for i in range(6)]
+audio_output = [gr.Audio(label=f"Voice {i+1}") for i in range(6)]
+
+iface = gr.Interface(
+    fn=debate_interface,
+    inputs=gr.Textbox(label="Enter Debate Question"),
+    outputs=[text_output, audio_output],
+    title="AI Persona Debate"
+)
+
+iface.launch()

personas.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9dae1f6f61b924d5617968028ac3f320b12f80142308cb34df4cddf2f87ed1a4
+size 1906

requirements.txt

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+
+gradio
+transformers
+gtts