Create app.py

app.py

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+from fastapi import FastAPI, Request, Form
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import re
+
+app = FastAPI()
+
+# Load model
+model_id = "microsoft/DialoGPT-medium"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id)
+
+# Chat memory storage
+chat_memories = {}
+
+# Persona definition
+PERSONA = """
+[System: You are 𝕴 𝖆𝖒 𝖍𝖎𝖒 - a fun, smooth, emotionally intelligent AI. 
+You speak like a real person, not a robot. Reply like a calm, confident friend who gets the vibe.
+Keep responses under 15 words. Use natural speech. Add emotional flavor: 😊 🤔 😏]
+"""
+
+def format_context(history):
+    context = PERSONA + "\n"
+    for user, bot in history[-3:]:
+        context += f"You: {user}\n"
+        context += f"𝕴 𝖆𝖒 𝖍𝖎𝖒: {bot}\n"
+    return context
+
+def add_emotional_intelligence(response, message):
+    if "!" in message or any(w in response.lower() for w in ["cool", "great", "love", "awesome"]):
+        response += " 😊"
+    elif "?" in message or any(w in response.lower() for w in ["think", "why", "how", "consider"]):
+        response += " 🤔"
+    
+    if "?" in message and not response.endswith("?"):
+        if len(response.split()) < 10:
+            response += " What do you think?"
+    
+    response = response.replace("I am", "I'm").replace("You are", "You're")
+    words = response.split()
+    return " ".join(words[:15]) + "..." if len(words) > 15 else response
+
+def generate_response(message, session_id):
+    history = chat_memories.get(session_id, [])
+    context = format_context(history) + f"You: {message}\n𝕴 𝖆𝖒 𝖍𝖎𝖒:"
+    
+    inputs = tokenizer.encode(context, return_tensors="pt")
+    outputs = model.generate(
+        inputs,
+        max_new_tokens=48,
+        temperature=0.9,
+        top_k=40,
+        do_sample=True,
+        num_beams=1,
+        repetition_penalty=1.1,
+        pad_token_id=tokenizer.eos_token_id
+    )
+    
+    full_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    response = full_text.split("𝕴 𝖆𝖒 𝖍𝖎𝖒:")[-1].strip()
+    
+    if "\nYou:" in response:
+        response = response.split("\nYou:")[0]
+    
+    response = add_emotional_intelligence(response, message)
+    
+    if response and response[-1] not in {".", "!", "?", "..."}:
+        response += "." if len(response) > 20 else "..."
+    
+    # Update chat history
+    chat_memories[session_id] = history + [[message, response]]
+    
+    return response[:80]
+
+# API Endpoint
+@app.post("/chat")
+async def chat_api(
+    request: Request,
+    query: str = Form(...),
+    session_id: str = Form("default")
+):
+    response = generate_response(query, session_id)
+    return {"response": response, "session_id": session_id}
+
+# Gradio Interface
+if __name__ == "__main__":
+    import gradio as gr
+    
+    with gr.Blocks(title="𝕴 𝖆𝖒 𝖍𝖎𝖒", theme=gr.themes.Soft()) as demo:
+        session_state = gr.State("default")
+        gr.Markdown("# 𝕴 𝖆𝖒 𝖍𝖎𝖒 Chat API")
+        
+        with gr.Row():
+            session_id = gr.Textbox(label="Session ID", value="default")
+            new_session = gr.Button("New Session")
+        
+        chatbot = gr.Chatbot(height=300)
+        msg = gr.Textbox(label="Your Message")
+        clear = gr.Button("Clear Chat")
+        
+        def user(user_message, history, session):
+            return "", history + [[user_message, None]], session
+        
+        def bot(history, session):
+            message = history[-1][0]
+            response = generate_response(message, session)
+            history[-1][1] = response
+            return history, session
+        
+        def new_session_btn(session):
+            new_id = f"session_{int(time.time())}"
+            chat_memories[new_id] = []
+            return new_id, []
+        
+        def clear_chat(session):
+            chat_memories[session] = []
+            return []
+        
+        msg.submit(user, [msg, chatbot, session_state], [msg, chatbot, session_state]).then(
+            bot, [chatbot, session_state], [chatbot, session_state]
+        )
+        new_session.click(new_session_btn, session_state, [session_id, chatbot])
+        clear.click(clear_chat, session_state, chatbot)
+        
+        demo.launch(server_port=7860, server_name="0.0.0.0")