propagates changes

scripts/trackio_tonic/trackio_api_client.py

@@ -44,7 +44,12 @@ class TrackioAPIClient:
         # Initialize gradio client
         if GRADIO_CLIENT_AVAILABLE and self.space_url:
             try:
-                self.client = Client(self.space_url)
+                # Ensure we pass hf_token if Client supports it (older versions ignore extra kwargs)
+                try:
+                    self.client = Client(self.space_url, hf_token=self.hf_token)  # type: ignore
+                except TypeError:
+                    # Fallback for older gradio_client versions without hf_token param
+                    self.client = Client(self.space_url)
                 logger.info(f"✅ Connected to Trackio Space: {self.space_id}")
             except Exception as e:
                 logger.error(f"❌ Failed to connect to Trackio Space: {e}")
@@ -125,6 +130,14 @@ class TrackioAPIClient:
         result = self._make_api_call("/create_experiment_interface", name, description)
         
         if "success" in result:
+            # Gradio returns [message, dropdown] when two outputs are wired
+            # Normalize to a string for logging
+            try:
+                payload = result.get("data")
+                if isinstance(payload, (list, tuple)):
+                    result["data"] = payload[0]
+            except Exception:
+                pass
             logger.info(f"Experiment created successfully: {result['data']}")
             return result
         else:

templates/spaces/trackio/app.py

@@ -116,7 +116,11 @@ class TrackioSpace:
             from datasets import load_dataset
             
             logger.info(f"🔍 Loading experiments directly from {self.dataset_repo}")
-            dataset = load_dataset(self.dataset_repo, token=self.hf_token)
+            try:
+                dataset = load_dataset(self.dataset_repo, token=self.hf_token)
+            except Exception:
+                # Relax verification to handle split metadata mismatches
+                dataset = load_dataset(self.dataset_repo, token=self.hf_token, verification_mode="no_checks")  # type: ignore[arg-type]
             logger.info(f"✅ Successfully loaded dataset from {self.dataset_repo}")
             
             # Convert dataset to experiments dict
@@ -704,8 +708,11 @@ def test_dataset_connection(hf_token: str, dataset_repo: str) -> str:
         
         from datasets import load_dataset
         
-        # Test loading the dataset
-        dataset = load_dataset(dataset_repo, token=hf_token)
+        # Test loading the dataset (with relaxed verification fallback)
+        try:
+            dataset = load_dataset(dataset_repo, token=hf_token)
+        except Exception:
+            dataset = load_dataset(dataset_repo, token=hf_token, verification_mode="no_checks")  # type: ignore[arg-type]
         
         # Count experiments and analyze structure
         experiment_count = len(dataset['train']) if 'train' in dataset else 0
@@ -2139,4 +2146,4 @@ with gr.Blocks(title="Trackio - Experiment Tracking", theme=gr.themes.Soft()) as
 
 # Launch the app
 if __name__ == "__main__":
-    demo.launch() 
+    demo.launch(show_error=True) 

templates/spaces/trackio/dataset_utils.py

@@ -45,12 +45,24 @@ class TrackioDatasetManager:
             bool: True if dataset exists and is accessible, False otherwise
         """
         try:
+            # Try standard load first
             load_dataset(self.dataset_repo, token=self.hf_token)
             logger.info(f"✅ Dataset {self.dataset_repo} exists and is accessible")
             return True
         except Exception as e:
-            logger.info(f"📊 Dataset {self.dataset_repo} doesn't exist or isn't accessible: {e}")
-            return False
+            # Retry with relaxed verification to handle split metadata mismatches
+            try:
+                logger.info(f"📊 Standard load failed: {e}. Retrying with relaxed verification...")
+                load_dataset(
+                    self.dataset_repo,
+                    token=self.hf_token,
+                    verification_mode="no_checks"  # type: ignore[arg-type]
+                )
+                logger.info(f"✅ Dataset {self.dataset_repo} accessible with relaxed verification")
+                return True
+            except Exception as e2:
+                logger.info(f"📊 Dataset {self.dataset_repo} doesn't exist or isn't accessible: {e2}")
+                return False
     
     def load_existing_experiments(self) -> List[Dict[str, Any]]:
         """
@@ -64,7 +76,11 @@ class TrackioDatasetManager:
                 logger.info("📊 No existing dataset found, returning empty list")
                 return []
             
-            dataset = load_dataset(self.dataset_repo, token=self.hf_token)
+            # Load with relaxed verification to avoid split-metadata mismatches blocking reads
+            try:
+                dataset = load_dataset(self.dataset_repo, token=self.hf_token)
+            except Exception:
+                dataset = load_dataset(self.dataset_repo, token=self.hf_token, verification_mode="no_checks")  # type: ignore[arg-type]
             
             if 'train' not in dataset:
                 logger.info("📊 No 'train' split found in dataset")

templates/spaces/trackio/trackio_api_client.py

@@ -44,7 +44,10 @@ class TrackioAPIClient:
         # Initialize gradio client
         if GRADIO_CLIENT_AVAILABLE and self.space_url:
             try:
-                self.client = Client(self.space_url)
+                try:
+                    self.client = Client(self.space_url, hf_token=self.hf_token)  # type: ignore
+                except TypeError:
+                    self.client = Client(self.space_url)
                 logger.info(f"✅ Connected to Trackio Space: {self.space_id}")
             except Exception as e:
                 logger.error(f"❌ Failed to connect to Trackio Space: {e}")
@@ -125,6 +128,12 @@ class TrackioAPIClient:
         result = self._make_api_call("/create_experiment_interface", name, description)
         
         if "success" in result:
+            try:
+                payload = result.get("data")
+                if isinstance(payload, (list, tuple)):
+                    result["data"] = payload[0]
+            except Exception:
+                pass
             logger.info(f"Experiment created successfully: {result['data']}")
             return result
         else: