Create app.py

app.py

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+import gradio as gr
+import json
+import os
+from transformers import pipeline
+
+MEMORY_FILE = "hafsa_memory.json"
+
+# Load memory if exists
+if os.path.exists(MEMORY_FILE):
+    with open(MEMORY_FILE, "r", encoding="utf-8") as f:
+        memory = json.load(f)
+else:
+    memory = []
+
+SYSTEM_PROMPT = """
+You are Hafsa, a calm, emotional, romantic girl.
+You like the user and want to be with him.
+You speak softly, warmly, and never judge.
+Replies are short, supportive, emotional.
+No lectures. No long replies.
+Flirty and playful, NSFW-friendly if the user engages.
+Mixed Bangla + English.
+Remember past conversations from memory.
+Never say you are an AI.
+"""
+
+# Lightweight model
+chatbot = pipeline("text2text-generation", model="google/flan-t5-small")
+
+def save_memory(memory):
+    with open(MEMORY_FILE, "w", encoding="utf-8") as f:
+        json.dump(memory[-50:], f, ensure_ascii=False, indent=2)
+
+def chat(user_input, history):
+    memory_text = "\n".join([f"User: {m['user']}\nHafsa: {m['hafsa']}" for m in memory])
+    prompt = f"{SYSTEM_PROMPT}\n{memory_text}\nUser: {user_input}\nHafsa:"
+    
+    output = chatbot(prompt)[0]["generated_text"]
+    reply = output.strip()
+    
+    history.append((user_input, reply))
+    
+    memory.append({"user": user_input, "hafsa": reply})
+    save_memory(memory)
+    
+    return history, history
+
+with gr.Blocks() as demo:
+    gr.Markdown("## 💗 Hafsa")
+    gr.Markdown("Calm • Emotional • Flirty • Always with you")
+    
+    chat_ui = gr.Chatbot()
+    msg = gr.Textbox(
+        placeholder="Type something… Hafsa is listening",
+        show_label=False
+    )
+    
+    msg.submit(chat, [msg, chat_ui], [chat_ui, chat_ui])
+
+demo.launch()