adds improved dataset utils with new interface

scripts/trackio_tonic/app.py

@@ -721,13 +721,16 @@ def get_metrics_dataframe(experiment_id: str) -> pd.DataFrame:
     logger.info(f"Using local data for {experiment_id}")
     return trackio_space.get_metrics_dataframe(experiment_id)
 
-def create_experiment_interface(name: str, description: str) -> str:
+def create_experiment_interface(name: str, description: str):
     """Create a new experiment"""
     try:
         experiment = trackio_space.create_experiment(name, description)
-        return f"✅ Experiment created successfully!\nID: {experiment['id']}\nName: {experiment['name']}\nStatus: {experiment['status']}"
+        msg = f"✅ Experiment created successfully!\nID: {experiment['id']}\nName: {experiment['name']}\nStatus: {experiment['status']}"
+        dropdown = gr.Dropdown(choices=list(trackio_space.experiments.keys()), value=experiment['id'])
+        return msg, dropdown
     except Exception as e:
-        return f"❌ Error creating experiment: {str(e)}"
+        dropdown = gr.Dropdown(choices=list(trackio_space.experiments.keys()), value=None)
+        return f"❌ Error creating experiment: {str(e)}", dropdown
 
 def log_metrics_interface(experiment_id: str, metrics_json: str, step: str) -> str:
     """Log metrics for an experiment"""

src/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
+            # Some hubs raise a split-metadata mismatch; retry with relaxed verification
+            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/app.py

@@ -990,13 +990,17 @@ def get_metrics_dataframe(experiment_id: str) -> pd.DataFrame:
         logger.info(f"Falling back to local data for {experiment_id}")
         return trackio_space.get_metrics_dataframe(experiment_id)
 
-def create_experiment_interface(name: str, description: str) -> str:
+def create_experiment_interface(name: str, description: str):
     """Create a new experiment"""
     try:
         experiment = trackio_space.create_experiment(name, description)
-        return f"✅ Experiment created successfully!\nID: {experiment['id']}\nName: {experiment['name']}\nStatus: {experiment['status']}"
+        # Return both the status message and a refreshed dropdown
+        msg = f"✅ Experiment created successfully!\nID: {experiment['id']}\nName: {experiment['name']}\nStatus: {experiment['status']}"
+        dropdown = gr.Dropdown(choices=get_experiment_dropdown_choices(), value=experiment['id'])
+        return msg, dropdown
     except Exception as e:
-        return f"❌ Error creating experiment: {str(e)}"
+        dropdown = gr.Dropdown(choices=get_experiment_dropdown_choices(), value=None)
+        return f"❌ Error creating experiment: {str(e)}", dropdown
 
 def log_metrics_interface(experiment_id: str, metrics_json: str, step: str) -> str:
     """Log metrics for an experiment"""