Update app.py

app.py

@@ -28,9 +28,17 @@ try:
     else:
         backend_client = Client(BACKEND_URL)
     print(f"Connected to backend at {BACKEND_URL}")
+    # Debug: List available API endpoints
+    try:
+        api_info = backend_client.view_api()
+        print(f"Available API endpoints: {list(api_info.keys()) if isinstance(api_info, dict) else 'Could not list APIs'}")
+    except:
+        pass
 except Exception as e:
     print(f"Warning: Could not connect to backend: {e}")
     print(f"Make sure BACKEND_URL and HF_TOKEN are set correctly.")
+    print(f"BACKEND_URL: {BACKEND_URL}")
+    print(f"HF_TOKEN set: {bool(HF_TOKEN)}")
     backend_client = None
 
 def add_sentences_ui(sentences_text):
@@ -41,7 +49,7 @@ def add_sentences_ui(sentences_text):
     try:
         result = backend_client.predict(
             sentences_text,
-            api_name="api_add_sentences"
+            api_name="/api_add_sentences"
         )
         if isinstance(result, dict):
             vocab_info = result.get("vocab_info", {})
@@ -62,7 +70,7 @@ def train_brain_ui(epochs, progress=gr.Progress()):
         yield "🔄 Training in progress... Please wait..."
         result = backend_client.predict(
             int(epochs),
-            api_name="api_train"
+            api_name="/api_train"
         )
         if isinstance(result, str):
             yield result
@@ -84,7 +92,7 @@ def run_stream_ui(seed_word, steps, coupling_gain, transmission_threshold):
             int(steps),
             float(coupling_gain),
             float(transmission_threshold),
-            api_name="api_run_stream"
+            api_name="/api_run_stream"
         )
         # Gradio returns tuple/list for multiple outputs
         if isinstance(result, (list, tuple)) and len(result) >= 2:
@@ -102,7 +110,7 @@ def clear_brain_ui():
         return "❌ Backend not available. Please check configuration.", "**Error:** Backend connection failed."
     
     try:
-        result = backend_client.predict(api_name="api_clear_brain")
+        result = backend_client.predict(api_name="/api_clear_brain")
         if isinstance(result, dict):
             vocab_info = result.get("vocab_info", {})
             vocab_text = f"**Current Vocabulary:** {vocab_info.get('vocab_size', 0)} words\n**Corpus:** {vocab_info.get('corpus_size', 0)} sentences\n**Trained:** {vocab_info.get('trained_size', 0)} sentences"