SDK audit update (20260629-104549)

datalab_sdk/client.py

@@ -427,6 +427,10 @@ def _build_conversion_result(self, result_data: Dict[str, Any], default_format:
             runtime=result_data.get("runtime"),
             cost_breakdown=result_data.get("cost_breakdown"),
             evaluation=result_data.get("evaluation"),
+            extraction_score_average=result_data.get("extraction_score_average"),
+            extraction_mode=result_data.get("extraction_mode"),
+            result_url=result_data.get("result_url"),
+            expires_in=result_data.get("expires_in"),
         )
 
     async def _submit_and_poll(

datalab_sdk/models.py

@@ -15,6 +15,7 @@ class ProcessingOptions:
     max_pages: Optional[int] = None
     skip_cache: bool = False
     page_range: Optional[str] = None
+    processing_location: Optional[str] = None  # Data residency region override (e.g. "us", "eu")
 
     def to_form_data(self) -> Dict[str, Any]:
         """Convert to form data format for API requests"""
@@ -54,6 +55,7 @@ class ConvertOptions(ProcessingOptions):
     include_markdown_in_chunks: bool = False  # include markdown field in chunks/JSON output
     token_efficient_markdown: bool = False  # optimize markdown for LLM token usage
     eval_rubric_id: Optional[int] = None  # run evaluation rubric after conversion
+    word_bboxes: bool = False  # predict per-word bounding boxes inlined into HTML output
 
     def to_form_data(self) -> Dict[str, Any]:
         """Convert to form data format for API requests"""
@@ -83,7 +85,8 @@ class ExtractOptions(ProcessingOptions):
     schema_id: Optional[str] = None  # ID of a saved extraction schema (e.g. sch_k8Hx9mP2nQ4v). Mutually exclusive with page_schema.
     schema_version: Optional[int] = None  # Version of the schema. Only valid with schema_id.
     checkpoint_id: Optional[str] = None  # From previous /convert with save_checkpoint=true
-    mode: str = "fast"  # fast, balanced, accurate
+    mode: str = "fast"  # Parse mode: fast, balanced, accurate
+    extraction_mode: Optional[str] = None  # Extraction mode: "turbo", "fast", or "balanced". Defaults to "balanced".
     output_format: str = "markdown"  # markdown, json, html, chunks
     save_checkpoint: bool = False
     webhook_url: Optional[str] = None
@@ -94,6 +97,9 @@ def to_form_data(self) -> Dict[str, Any]:
         # When using schema_id, suppress the empty default page_schema
         if self.schema_id and not self.page_schema:
             form_data.pop("page_schema", None)
+        # Only send extraction_mode if explicitly set
+        if self.extraction_mode is None:
+            form_data.pop("extraction_mode", None)
         return form_data
 
 
@@ -202,6 +208,10 @@ class ConversionResult:
     runtime: Optional[float] = None
     cost_breakdown: Optional[Dict[str, Any]] = None
     evaluation: Optional[Dict[str, Any]] = None  # Evaluation results when run_eval=true
+    extraction_score_average: Optional[float] = None  # Average confidence score (1-5) across extracted fields
+    extraction_mode: Optional[str] = None  # Extraction mode used: "turbo", "fast", or "balanced"
+    result_url: Optional[str] = None  # Signed URL for direct download of large result JSON
+    expires_in: Optional[int] = None  # Seconds until result_url expires
 
     def save_output(
         self, output_path: Union[str, Path], save_images: bool = True