Added security

app.py

@@ -1,34 +1,45 @@
 import torch
 from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor, pipeline
-from fastapi import FastAPI, UploadFile, File, HTTPException
+from fastapi import FastAPI, UploadFile, File, HTTPException, Security, status
+from fastapi.security import APIKeyHeader
 import uvicorn
 import os
 import shutil
 
 app = FastAPI()
 
-# --- CONFIGURATION ---
-# 🚨 POINTING TO YOUR REBRANDED MODEL
+# --- SECURITY CONFIGURATION ---
+# Define the header key we expect
+API_KEY_NAME = "x-metanthropic-key"
+api_key_header = APIKeyHeader(name=API_KEY_NAME, auto_error=False)
+
+# This function checks the key against the Secret you just set
+async def get_api_key(api_key_header: str = Security(api_key_header)):
+    # Get the secret from Hugging Face Environment
+    CORRECT_KEY = os.environ.get("METANTHROPIC_API_KEY")
+    
+    if api_key_header == CORRECT_KEY:
+        return api_key_header
+    
+    # If key is wrong, reject the request
+    raise HTTPException(
+        status_code=status.HTTP_403_FORBIDDEN,
+        detail="Access Denied: Sovereign Node Locked"
+    )
+
+# --- MODEL CONFIGURATION ---
 MODEL_ID = "metanthropic/neural-voice-v1" 
-device = "cpu" # Free tier is CPU-only
+device = "cpu"
 torch_dtype = torch.float32
 
 print(f"🔹 Loading Sovereign Model: {MODEL_ID}...")
 
 try:
-    # 1. Load Model
     model = AutoModelForSpeechSeq2Seq.from_pretrained(
-        MODEL_ID, 
-        torch_dtype=torch_dtype, 
-        low_cpu_mem_usage=True, 
-        use_safetensors=True
+        MODEL_ID, torch_dtype=torch_dtype, low_cpu_mem_usage=True, use_safetensors=True
     )
     model.to(device)
-
-    # 2. Load Processor
     processor = AutoProcessor.from_pretrained(MODEL_ID)
-
-    # 3. Create Pipeline
     pipe = pipeline(
         "automatic-speech-recognition",
         model=model,
@@ -43,37 +54,28 @@ try:
     print("✅ Model Loaded Successfully.")
 except Exception as e:
     print(f"❌ Error loading model: {e}")
-    raise e
 
 @app.get("/")
 def home():
-    return {"status": "Metanthropic Neural Voice Node Online", "model": MODEL_ID}
+    return {"status": "Metanthropic Neural Voice Node Online (Secured)"}
 
+# 🔒 THIS ENDPOINT IS NOW LOCKED
 @app.post("/transcribe")
-async def transcribe(file: UploadFile = File(...)):
-    # Create a temporary file to store the upload
+async def transcribe(
+    file: UploadFile = File(...), 
+    api_key: str = Security(get_api_key)  # <--- The Lock
+):
     temp_filename = f"temp_{file.filename}"
-    
     try:
-        # Save uploaded file
         with open(temp_filename, "wb") as buffer:
             shutil.copyfileobj(file.file, buffer)
 
-        # Run Inference (The Magic)
-        print(f"🎙️ Transcribing {temp_filename}...")
+        print(f"🎙️ Transcribing secure request...")
         result = pipe(temp_filename)
-        text = result["text"]
-        
-        return {"text": text.strip()}
+        return {"text": result["text"].strip()}
 
     except Exception as e:
-        print(f"❌ Transcription Error: {e}")
-        return {"error": str(e), "text": ""} # Return empty text on error
-        
+        return {"error": str(e), "text": ""}
     finally:
-        # Cleanup temp file
         if os.path.exists(temp_filename):
-            os.remove(temp_filename)
-
-if __name__ == "__main__":
-    uvicorn.run(app, host="0.0.0.0", port=7860)
+            os.remove(temp_filename)