CPU-only – virkar strax án GPU vandræða

app.py

@@ -1,42 +1,38 @@
-# app.py – VIRKAR Á A100 ÁN @spaces.GPU (2025 leiðin)
+# app.py – Virkar 100 % á CPU (engin GPU villa, engin NVML)
 import os
 import gradio as gr
 from transformers import pipeline
 
-# Þvingar GPU með torch (virkar alltaf á A100 Spaces)
-import torch
-if torch.cuda.is_available():
-    device = 0
-    print(f"GPU virk: {torch.cuda.get_device_name(0)}")
-else:
-    device = -1
-    print("CPU – eitthvað er rangt við Space stillingar")
+print("Hleð Whisper-small... (tekur 30–60 sek í fyrsta skipti)")
 
-# Þitt private model
+# ÞITT private model
 asr = pipeline(
     "automatic-speech-recognition",
     model="palli23/whisper-small-sam_spjall",
-    device=device,
+    device=-1,  # ← CPU (ekki 0)
     token=os.getenv("HF_TOKEN")
 )
 
 def transcribe(audio):
     if not audio:
-        return "Hladdu upp hljóðskrá"
+        return "Hladdu upp hljóðskrá fyrst"
     try:
         result = asr(audio)
         return result["text"]
     except Exception as e:
         return f"Villa: {str(e)}"
 
+# Einfalt og fallegt
 with gr.Blocks() as demo:
-    gr.Markdown("# Íslenskt ASR – VIRKAR Á A100")
-    gr.Markdown("**Whisper-small · ~4–5 % WER · Keyrir á GPU**")
+    gr.Markdown("# Íslenskt ASR – Lokað Beta (CPU)")
+    gr.Markdown("**Whisper-small · ~4–5 % WER · Keyrir á CPU (nóg fyrir beta)**")
     
     audio = gr.Audio(type="filepath", label="Hladdu upp .mp3 / .wav")
-    btn = gr.Button("Transcribe", variant="primary")
-    out = gr.Textbox(lines=20, label="Útskrift")
+    btn = gr.Button("Transcribe (30–90 sek)", variant="primary", size="lg")
+    out = gr.Textbox(lines=25, label="Útskrift")
     
-    btn.click(transcribe, audio, out)
+    btn.click(transcribe, inputs=audio, outputs=out)
+    
+    gr.Markdown("© 2025 – Einkaeign")
 
 demo.launch(auth=("beta", "beta2025"))