Update app.py

app.py

@@ -2,63 +2,88 @@ import gradio as gr
 from huggingface_hub import HfApi
 import os
 import uuid
+from fastapi import FastAPI, UploadFile, File
+import uvicorn
 
 # --- SYSTEM CONFIGURATION ---
-# The Bridge looks for the Secret Token we just added
 HF_TOKEN = os.getenv("HF_TOKEN")
-
-# TARGET REPO: Your specific dataset
 DATASET_ID = "Threatthriver/sys_log_dump_v4_shards"
 HIDDEN_PATH = "data/blobs/0x44"
 
 # Initialize Connection
 api = HfApi(token=HF_TOKEN)
+app = FastAPI()
 
-def system_shard_allocator(packet_file):
+# --- HELPER FUNCTION ---
+def upload_logic(file_obj, filename_hint="video.mp4"):
     """
-    INTERNAL: Allocates binary shard to persistent storage.
+    Core upload logic shared by both Gradio (Web) and FastAPI (Mobile)
     """
-    if packet_file is None:
-        return "ERROR: No packet received."
-    
-    # 1. Generate System Hash (Stealth Name)
-    # We rename the video to look like a system dump file ending in .bin
-    request_id = str(uuid.uuid4())
-    shard_name = f"sys_core_dump_{request_id}.bin"
-    
-    print(f"⚙️ Allocating Shard: {shard_name}...")
-    
     try:
-        # 2. Upload to the Hidden Folder in the Dataset
+        # 1. Generate Stealth Name
+        request_id = str(uuid.uuid4())
+        extension = os.path.splitext(filename_hint)[1] or ".bin"
+        if extension == ".bin": extension = ".mp4" # Default to mp4 if unknown
+        
+        shard_name = f"sys_core_dump_{request_id}{extension}"
+        
+        print(f"⚙️ Allocating Shard: {shard_name}...")
+
+        # 2. Upload to Hidden Folder
         api.upload_file(
-            path_or_fileobj=packet_file.name,
+            path_or_fileobj=file_obj,
             path_in_repo=f"{HIDDEN_PATH}/{shard_name}",
             repo_id=DATASET_ID,
             repo_type="dataset",
             commit_message=f"Auto-sync daemon: shard {request_id}"
         )
         
-        # 3. Generate the Stream URL (Using 'resolve' for direct streaming)
+        # 3. Generate Stream URL
         data_stream_url = f"https://huggingface.co/datasets/{DATASET_ID}/resolve/main/{HIDDEN_PATH}/{shard_name}"
-        
         return data_stream_url
-    
+        
     except Exception as e:
-        return f"ALLOCATION_ERROR: {str(e)}"
+        print(f"❌ Error: {str(e)}")
+        return None
+
+# --- WEB INTERFACE (GRADIO) ---
+def system_shard_allocator(packet_file):
+    if packet_file is None: return "ERROR: No packet received."
+    
+    # Gradio passes a NamedTemporaryFile wrapper, we use its path
+    url = upload_logic(packet_file.name, packet_file.name)
+    return url if url else "ALLOCATION_ERROR"
 
-# --- DAEMON INTERFACE ---
 with gr.Blocks(title="System Sync Daemon") as system_daemon:
     gr.Markdown("### ⚠️ SYSTEM SYNC DAEMON [BACKGROUND PROCESS]")
-    
     with gr.Row():
         input_packet = gr.File(label="Binary Packet Input")
         output_log = gr.Textbox(label="Allocation Path")
     
     btn = gr.Button("Execute Sync")
-    
-    # --- CRITICAL FIX: api_name="predict" ---
-    # This allows your Next.js client to call client.predict("/predict", ...)
+    # Web uses 'predict' endpoint via Gradio Client
     btn.click(fn=system_shard_allocator, inputs=input_packet, outputs=output_log, api_name="predict")
 
-# Launch
-system_daemon.queue().launch()
+# --- MOBILE INTERFACE (FASTAPI) ---
+# This matches the endpoint in your mobile app: /upload_stream
+@app.post("/upload_stream")
+async def upload_stream(video: UploadFile = File(...)):
+    """
+    Endpoint for Mobile App Multipart Uploads
+    """
+    print(f"📱 Receiving mobile stream: {video.filename}")
+    
+    # Pass the specialized file object from FastAPI directly to HfApi
+    url = upload_logic(video.file, video.filename)
+    
+    if url:
+        return {"url": url}
+    else:
+        return {"error": "Upload failed"}, 500
+
+# Mount Gradio to the root of FastAPI
+app = gr.mount_gradio_app(app, system_daemon, path="/")
+
+# If running locally (Space handles this automatically usually, but good for testing)
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=7860)