@@ -1,6 +1,6 @@
 [project]
 name = "uipath-platform"
-version = "0.2.32"
+version = "0.2.33"
 description = "HTTP client library for programmatic access to UiPath Platform"
 readme = { file = "README.md", content-type = "text/markdown" }
 requires-python = ">=3.11"
 
@@ -196,12 +196,24 @@ class CreateBatchTransform(BaseModel):
     index_folder_key: str | None = None
     index_folder_path: str | None = None
     is_ephemeral_index: bool | None = None
+    attachment: str | None = None
 
     @model_validator(mode="after")
     def validate_ephemeral_index_requires_index_id(self) -> "CreateBatchTransform":
         """Validate that if it is an ephemeral index that it is using index id."""
-        if self.is_ephemeral_index is True and self.index_id is None:
-            raise ValueError("Index id must be provided for an ephemeral index")
+        if (
+            self.is_ephemeral_index is True
+            and self.index_id is None
+            and not self.attachment
+        ):
+            raise ValueError(
+                "Index id must be provided for an ephemeral index (or use attachment)"
+            )
+        if self.attachment is not None:
+            if self.index_id is not None or self.index_name is not None:
+                raise ValueError(
+                    "attachment cannot be combined with index_id or index_name"
+                )
         return self
 
 
 
@@ -963,6 +963,9 @@ async def start_batch_transform_async(
         )
         return BatchTransformCreationResponse.model_validate(response.json())
 
+    @deprecated(
+        "Use start_batch_transform_from_attachment instead — one call, no separate index step."
+    )
     @resource_override(resource_type="index", resource_identifier="index_name")
     @traced(name="contextgrounding_start_batch_transform", run_type="uipath")
     async def start_batch_transform_ephemeral(
@@ -1009,6 +1012,9 @@ async def start_batch_transform_ephemeral(
         )
         return BatchTransformCreationResponse.model_validate(response.json())
 
+    @deprecated(
+        "Use start_batch_transform_from_attachment_async instead — one call, no separate index step."
+    )
     @resource_override(resource_type="index", resource_identifier="index_name")
     @traced(name="contextgrounding_start_batch_transform_async", run_type="uipath")
     async def start_batch_transform_ephemeral_async(
@@ -1055,6 +1061,115 @@ async def start_batch_transform_ephemeral_async(
         )
         return BatchTransformCreationResponse.model_validate(response.json())
 
+    @traced(
+        name="contextgrounding_start_batch_transform_from_attachment", run_type="uipath"
+    )
+    def start_batch_transform_from_attachment(
+        self,
+        name: str,
+        prompt: Annotated[str, Field(max_length=250000)],
+        output_columns: List[BatchTransformOutputColumn],
+        attachment: str,
+        enable_web_search_grounding: bool = False,
+        exclude_domains: Optional[List[str]] = None,
+        folder_key: str | None = None,
+        folder_path: str | None = None,
+    ) -> BatchTransformCreationResponse:
+        """Starts a Batch Transform task from a single attachment in one server call.
+
+        The server creates the ephemeral index from the attachment and starts the Batch Transform
+        task in one operation; the caller does not need to create the index separately.
+
+        Args:
+            name (str): The name of the Batch Transform task.
+            prompt (str): Describe the task: what to transform and how to output.
+            output_columns (list[BatchTransformOutputColumn]): The output columns to add into the csv.
+            attachment (str): The attachment id to transform. Exactly one attachment is supported today.
+            enable_web_search_grounding (bool): Whether to enable web search. Defaults to False.
+            exclude_domains (list[str], optional): Domains to exclude from web search grounding.
+                Only applies when enable_web_search_grounding is True.
+            folder_key (str, optional): The folder key context. Defaults to None.
+            folder_path (str, optional): The folder path context. Defaults to None.
+
+        Returns:
+            BatchTransformCreationResponse: The Batch Transform task creation response.
+        """
+        spec = self._batch_transform_from_attachment_creation_spec(
+            name=name,
+            prompt=prompt,
+            output_columns=output_columns,
+            attachment=attachment,
+            enable_web_search_grounding=enable_web_search_grounding,
+            exclude_domains=exclude_domains,
+            folder_key=folder_key,
+            folder_path=folder_path,
+        )
+
+        response = self.request(
+            spec.method,
+            spec.endpoint,
+            params=spec.params,
+            json=spec.json,
+            headers=spec.headers,
+        )
+
+        return BatchTransformCreationResponse.model_validate(response.json())
+
+    @traced(
+        name="contextgrounding_start_batch_transform_from_attachment_async",
+        run_type="uipath",
+    )
+    async def start_batch_transform_from_attachment_async(
+        self,
+        name: str,
+        prompt: Annotated[str, Field(max_length=250000)],
+        output_columns: List[BatchTransformOutputColumn],
+        attachment: str,
+        enable_web_search_grounding: bool = False,
+        exclude_domains: Optional[List[str]] = None,
+        folder_key: str | None = None,
+        folder_path: str | None = None,
+    ) -> BatchTransformCreationResponse:
+        """Asynchronously starts a Batch Transform task from a single attachment in one server call.
+
+        The server creates the ephemeral index from the attachment and starts the Batch Transform
+        task in one operation; the caller does not need to create the index separately.
+
+        Args:
+            name (str): The name of the Batch Transform task.
+            prompt (str): Describe the task: what to transform and how to output.
+            output_columns (list[BatchTransformOutputColumn]): The output columns to add into the csv.
+            attachment (str): The attachment id to transform. Exactly one attachment is supported today.
+            enable_web_search_grounding (bool): Whether to enable web search. Defaults to False.
+            exclude_domains (list[str], optional): Domains to exclude from web search grounding.
+                Only applies when enable_web_search_grounding is True.
+            folder_key (str, optional): The folder key context. Defaults to None.
+            folder_path (str, optional): The folder path context. Defaults to None.
+
+        Returns:
+            BatchTransformCreationResponse: The Batch Transform task creation response.
+        """
+        spec = self._batch_transform_from_attachment_creation_spec(
+            name=name,
+            prompt=prompt,
+            output_columns=output_columns,
+            attachment=attachment,
+            enable_web_search_grounding=enable_web_search_grounding,
+            exclude_domains=exclude_domains,
+            folder_key=folder_key,
+            folder_path=folder_path,
+        )
+
+        response = await self.request_async(
+            spec.method,
+            spec.endpoint,
+            params=spec.params,
+            json=spec.json,
+            headers=spec.headers,
+        )
+
+        return BatchTransformCreationResponse.model_validate(response.json())
+
     @resource_override(resource_type="index", resource_identifier="index_name")
     @traced(name="contextgrounding_retrieve_batch_transform", run_type="uipath")
     def retrieve_batch_transform(
@@ -2633,6 +2748,41 @@ def _batch_transform_ephemeral_creation_spec(
             headers={**header_job_key()},
         )
 
+    def _batch_transform_from_attachment_creation_spec(
+        self,
+        name: str,
+        prompt: str,
+        output_columns: List[BatchTransformOutputColumn],
+        attachment: str,
+        enable_web_search_grounding: bool,
+        exclude_domains: Optional[List[str]],
+        folder_key: str | None = None,
+        folder_path: str | None = None,
+    ) -> RequestSpec:
+        headers: dict[str, str] = {**header_job_key()}
+        if folder_key is not None or folder_path is not None:
+            folder_key = self._resolve_folder_key(folder_key, folder_path)
+            headers = {**header_folder(folder_key, None), **headers}
+
+        body: dict[str, object] = {
+            "name": name,
+            "prompt": prompt,
+            "useWebSearchGrounding": enable_web_search_grounding,
+            "outputColumns": [
+                column.model_dump(by_alias=True) for column in output_columns
+            ],
+            "attachments": [attachment],
+        }
+        if exclude_domains:
+            body["excludeDomains"] = exclude_domains
+
+        return RequestSpec(
+            method="POST",
+            endpoint=Endpoint("/ecs_/v2/batchrag/create"),
+            json=body,
+            headers=headers,
+        )
+
     def _deep_rag_retrieve_spec(
         self,
         id: str,
 
@@ -799,7 +799,17 @@ async def _handle_batch_rag_job_trigger(
         elif isinstance(value, CreateBatchTransform):
             uipath = UiPath()
             try:
-                if value.is_ephemeral_index:
+                if value.attachment is not None:
+                    batch_transform = await uipath.context_grounding.start_batch_transform_from_attachment_async(
+                        name=value.name,
+                        prompt=value.prompt,
+                        output_columns=value.output_columns,
+                        attachment=value.attachment,
+                        enable_web_search_grounding=value.enable_web_search_grounding,
+                        folder_path=value.index_folder_path,
+                        folder_key=value.index_folder_key,
+                    )
+                elif value.is_ephemeral_index:
                     batch_transform = await uipath.context_grounding.start_batch_transform_ephemeral_async(
                         name=value.name,
                         index_id=value.index_id,