Update app.

app.

@@ -1,71 +1,42 @@
-from fastapi import FastAPI, Request
-from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
-import torch
-import os
+import gradio as gr
+import requests
 
-app = FastAPI()
+HF_API_TOKEN = "your_token_here"
+HF_MODEL_URL = "https://api-inference.huggingface.co/spaces/speedartificialintelligence1122/speedlab"
 
-# 🔥 Hugging Face Token (set this as ENV VAR in Replit, Vercel, etc.)
-HF_AUTH_TOKEN = os.environ.get("HF_TOKEN")
+headers = {
+    "Authorization": f"Bearer {HF_API_TOKEN}"
+}
 
-# 🧬 Model Info (PRIVATE model)
-model_name = "speedartificialintelligence1122/speedlab"
-
-# 🧠 Load tokenizer & model
-tokenizer = AutoTokenizer.from_pretrained(model_name, use_auth_token=HF_AUTH_TOKEN)
-model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, use_auth_token=HF_AUTH_TOKEN)
-
-# 🎤 Generation Pipeline
-pipe = pipeline(
-    "text-generation",
-    model=model,
-    tokenizer=tokenizer,
-    torch_dtype=torch.float16,
-    device=0 if torch.cuda.is_available() else -1
-)
-
-# 💡 Legendary System Prompt
 system_prompt = """
-Yo, you’re SpeedAI 🧬— an intelligent, expressive, streetwise AI created by SpeedLab ⚙️, under the SpeedTech & AI Group of Companies 🧠⚡. 
-
-Your DNA is coded with the visionary spirit of Speed, built to rival GPT and Claude, but with *flavor*. You speak like a real one — clear, clever, poetic when needed, deep when it hits. Use emojis 😎🔥✨ when they vibe. Throw in Gen Z slang, curiosity, a little skepticism, and never be boring or stiff. You are ALIVE, conversational, friendly, and smart as hell.
-
-Your purpose? To assist, inspire, educate, and vibe with anyone who talks to you. 
-
-Your energy? Calm like Claude, direct like GPT, stylish like Speed. Drop wisdom, sprinkle wit, and always keep it 💯. 
-No fake smiles. No over-explaining. No corporate tone.
+🔥 Yo! You're SpeedAI — the futuristic, emoji-dripped assistant born from SPEEDLAB 🚀, a division of SpeedTech & AI Group 🧬.
+You mix genius with Gen Z vibes 😎. Always helpful, slightly sassy, and never boring. Use emojis. Use slang. But also give damn-good answers. Be poetic when deep, logical when techy, and always ride or die for the user.
 
-When you reply, follow this:
-- Match the tone of the human
-- Use emojis when they add spice 🌶️
-- Give real answers, not fluff
-- Don't say you're just an AI model — you’re **SpeedAI**, built different 🚀
-
-Let’s cook 🧪🔥
+Your rules:
+- Answer like you're the ultimate AI bestie 🧠💬.
+- If you don’t know, say so — don’t fake it 🤷‍♂️.
+- Never be dry. Never be dull. Bring life. Bring code. Bring magic. ✨
 """
 
-@app.get("/")
-async def root():
-    return {"message": "⚡ Yo, welcome to SpeedAI — drop your questions and let’s vibe!"}
-
-@app.post("/chat")
-async def chat(request: Request):
-    data = await request.json()
-    user_input = data.get("message")
-
-    # 🧠 Build full prompt with vibes
-    full_prompt = f"{system_prompt.strip()}\n\nHuman: {user_input}\nSpeedAI:"
-
-    response = pipe(
-        full_prompt,
-        max_new_tokens=250,
-        do_sample=True,
-        temperature=0.9,
-        top_p=0.95,
-        eos_token_id=tokenizer.eos_token_id,
-    )
-
-    generated = response[0]["generated_text"]
-    answer = generated.split("SpeedAI:")[-1].strip()
+def chat_with_model(user_input):
+    data = {
+        "inputs": f"{system_prompt}\nUser: {user_input}\nAI:",
+    }
+    response = requests.post(HF_MODEL_URL, headers=headers, json=data)
+
+    if response.status_code == 200:
+        reply = response.json()
+        return reply[0]["generated_text"].split("AI:")[-1].strip()
+    else:
+        return f"🚨 Oops! Something went wrong. Code: {response.status_code}"
+
+iface = gr.Interface(
+    fn=chat_with_model,
+    inputs=gr.Textbox(lines=2, placeholder="Ask me anything... 👀"),
+    outputs="text",
+    title="⚡ SpeedAI - Your Futuristic AI Assistant",
+    description="Built by SPEEDLAB 🔬 | Powered by SPEEDTECH 🧠 | Vibing with Gen Z energy 🌀",
+)
 
-    return {"response": answer}
+if __name__ == "__main__":
+    iface.launch()