change order of args for gr headers

src/hf_eda_mcp/tools/analysis.py

@@ -32,10 +32,10 @@ MAX_UNIQUE_VALUES_TO_SHOW = 20
 
 def analyze_dataset_features(
     dataset_id: str,
-    hf_api_token: gr.Header,
     split: str = "train",
     sample_size: int = DEFAULT_ANALYSIS_SAMPLE_SIZE,
     config_name: Optional[str] = None,
+    hf_api_token: gr.Header = "",
 ) -> Dict[str, Any]:
     """
     Perform basic exploratory analysis on dataset features.
@@ -50,6 +50,7 @@ def analyze_dataset_features(
         split: Dataset split to analyze (default: 'train')
         sample_size: Number of samples to use for analysis (default: 1000, max: 50000)
         config_name: Optional configuration name for multi-config datasets
+        hf_api_token: Header parsed by Gradio when hf_api_token is provided in MCP configuration headers
 
     Returns:
         Dictionary containing comprehensive feature analysis:

src/hf_eda_mcp/tools/metadata.py

@@ -22,7 +22,7 @@ from hf_eda_mcp.error_handling import format_error_response, log_error_with_cont
 logger = logging.getLogger(__name__)
 
 
-def get_dataset_metadata(dataset_id: str, hf_api_token: gr.Header, config_name: Optional[str] = None) -> Dict[str, Any]:
+def get_dataset_metadata(dataset_id: str, config_name: Optional[str] = None, hf_api_token: gr.Header = "") -> Dict[str, Any]:
     """
     Retrieve comprehensive metadata for a HuggingFace dataset.
     
@@ -32,8 +32,8 @@ def get_dataset_metadata(dataset_id: str, hf_api_token: gr.Header, config_name:
     
     Args:
         dataset_id: HuggingFace dataset identifier (e.g., 'squad', 'glue', 'imdb')
-        hf_api_token: Header parsed by Gradio when hf_api_token is provided in MCP configuration headers
         config_name: Optional configuration name for multi-config datasets
+        hf_api_token: Header parsed by Gradio when hf_api_token is provided in MCP configuration headers
         
     Returns:
         Dictionary containing comprehensive dataset metadata:

src/hf_eda_mcp/tools/sampling.py

@@ -30,11 +30,11 @@ VALID_SPLITS = {"train", "validation", "test", "dev", "val"}
 
 def get_dataset_sample(
     dataset_id: str,
-    hf_api_token: gr.Header,
     split: str = "train",
     num_samples: int = DEFAULT_SAMPLE_SIZE,
     config_name: Optional[str] = None,
     streaming: bool = True,
+    hf_api_token: gr.Header = "",
 ) -> Dict[str, Any]:
     """
     Retrieve a sample of rows from a HuggingFace dataset.
@@ -49,6 +49,7 @@ def get_dataset_sample(
         num_samples: Number of samples to retrieve (default: 10, max: 10000)
         config_name: Optional configuration name for multi-config datasets
         streaming: Whether to use streaming mode for efficient loading (default: True)
+        hf_api_token: Header parsed by Gradio when hf_api_token is provided in MCP configuration headers
 
     Returns:
         Dictionary containing sampled data and metadata: