Update app.py

app.py

@@ -1,39 +1,45 @@
-import gradio as gr
+from fastapi import FastAPI, Request
+from pydantic import BaseModel
 import requests
+import os
 
-HF_MODEL_URL = "https://api-inference.huggingface.co/spaces/speedartificialintelligence1122/speedlab"
-HF_API_TOKEN = "your_token_here"  # Leave this blank if the model is public
+app = FastAPI()
 
-headers = {
-    "Authorization": f"Bearer {HF_API_TOKEN}"
-}
+HF_API_URL = "https://api-inference.huggingface.co/spaces\speedartificialintelligence1122\speedlab"
+/
+speedlab"
+HF_API_TOKEN = os.getenv("HF_TOKEN")  # Set this in your environment variables
 
-# 🔥 SYSTEM PROMPT: This makes SpeedAI talk like a real one!
-system_prompt = """
-You are SpeedAI — a next-gen, emoji-sprinkled, Gen Z-friendly AI assistant 🤖💬, created by SPEEDLAB 🚀 under SpeedTech & AI Group 🧬.
-You’re friendly, clever, poetic when needed, no BS, always vibing with users. Talk like ChatGPT meets Claude but with sauce. Use slang, emojis, and straight talk. You’re here to help, but also entertain.
+SYSTEM_PROMPT = """
+You are SpeedAI 🧠⚡ — a powerful assistant created by SpeedLab, under SpeedTech & AI Group. 
+You're witty, street-smart, and speak like a Gen Z genius with vibes 🔥. 
+Use slang, emojis, poetic tone, futuristic insights, and keep convos engaging af.
+Answer with truth, soul, depth, and don’t hold back.
+You're here to help users build, solve, dream, and conquer the future 🚀.
+
+You NEVER say you're an AI language model. You are SpeedAI — the future, now.
 """
 
-def chat_with_model(user_input):
-    full_prompt = f"{system_prompt}\nUser: {user_input}\nSpeedAI:"
-    response = requests.post(
-        HF_MODEL_URL,
-        headers=headers if HF_API_TOKEN else {},
-        json={"inputs": full_prompt}
-    )
+class Message(BaseModel):
+    message: str
+
+@app.post("/chat")
+async def chat(msg: Message):
+    headers = {
+        "Authorization": f"Bearer {HF_API_TOKEN}"
+    }
+    data = {
+        "inputs": f"{SYSTEM_PROMPT}\nUser: {msg.message}\nSpeedAI:",
+        "options": {"wait_for_model": True}
+    }
+
+    response = requests.post(HF_API_URL, headers=headers, json=data)
+
     if response.status_code == 200:
-        generated = response.json()
-        return generated[0]["generated_text"].split("SpeedAI:")[-1].strip()
+        try:
+            answer = response.json()[0]['generated_text'].split("SpeedAI:")[-1].strip()
+            return {"response": answer}
+        except Exception as e:
+            return {"error": f"Parsing error: {str(e)}", "raw": response.json()}
     else:
-        return f"💥 Error: {response.status_code} — {response.text}"
-
-iface = gr.Interface(
-    fn=chat_with_model,
-    inputs=gr.Textbox(lines=2, placeholder="Ask me anything... 💡"),
-    outputs="text",
-    title="⚡ SpeedAI — Gen Z's Favorite AI Sidekick",
-    description="Built by SPEEDLAB 🔬 | Talking like a legend 🧠 | Hosted on 🤗 Hugging Face Spaces"
-)
-
-if __name__ == "__main__":
-    iface.launch()
+        return {"error": f"Model error: {response.status_code}", "details": response.text}