Fix authentication error and add setup instructions

SETUP_INSTRUCTIONS.md

@@ -0,0 +1,24 @@
+# Setup Instructions
+
+## Required Steps:
+
+1. **Accept the pyannote model conditions**:
+   - Visit https://huggingface.co/pyannote/speaker-diarization-3.1
+   - Click "Agree and access repository" to accept the conditions
+
+2. **Create a Hugging Face token**:
+   - Go to https://huggingface.co/settings/tokens
+   - Create a new token with "read" permissions
+   - Copy the token
+
+3. **Add the token to your Space secrets**:
+   - Go to your Space settings: https://huggingface.co/spaces/marcosremar2/speaker-diarization-pyannote/settings
+   - Scroll to "Repository secrets" section
+   - Add a new secret:
+     - Name: `HF_TOKEN`
+     - Value: Your Hugging Face token
+   - Click "Save"
+
+4. **Restart the Space** after adding the token
+
+The Space should now work correctly!

app.py

@@ -7,21 +7,30 @@ import os
 
 # Login to Hugging Face if token is available
 hf_token = os.environ.get("HF_TOKEN")
-if hf_token:
-    login(token=hf_token)
+if not hf_token:
+    raise ValueError("HF_TOKEN environment variable is required. Please set it in the Space settings.")
 
-# Initialize the pipeline
-pipeline = Pipeline.from_pretrained(
-    "pyannote/speaker-diarization-3.1",
-    use_auth_token=hf_token
-)
+login(token=hf_token)
 
-# Send pipeline to GPU if available
-if torch.cuda.is_available():
-    pipeline.to(torch.device("cuda"))
+# Initialize the pipeline
+try:
+    pipeline = Pipeline.from_pretrained(
+        "pyannote/speaker-diarization-3.1",
+        use_auth_token=hf_token
+    )
+    
+    # Send pipeline to GPU if available
+    if torch.cuda.is_available():
+        pipeline.to(torch.device("cuda"))
+except Exception as e:
+    print(f"Error loading pipeline: {e}")
+    pipeline = None
 
 def diarize_audio(audio_file):
     """Process audio file and return diarization results"""
+    if pipeline is None:
+        return "Pipeline not loaded. Please ensure HF_TOKEN is set and you have access to pyannote/speaker-diarization-3.1"
+    
     try:
         # Apply pretrained pipeline
         diarization = pipeline(audio_file)