undo vector_store_id in params

docs/static/deprecated-llama-stack-spec.html

@@ -2623,7 +2623,17 @@
                 ],
                 "summary": "Create a vector store file batch.",
                 "description": "Create a vector store file batch.\nGenerate an OpenAI-compatible vector store file batch for the given vector store.",
-                "parameters": [],
+                "parameters": [
+                    {
+                        "name": "vector_store_id",
+                        "in": "path",
+                        "description": "The ID of the vector store to create the file batch for.",
+                        "required": true,
+                        "schema": {
+                            "type": "string"
+                        }
+                    }
+                ],
                 "requestBody": {
                     "content": {
                         "application/json": {
@@ -12321,10 +12331,6 @@
             "OpenAICreateVectorStoreFileBatchRequestWithExtraBody": {
                 "type": "object",
                 "properties": {
-                    "vector_store_id": {
-                        "type": "string",
-                        "description": "The ID of the vector store to create the file batch for"
-                    },
                     "file_ids": {
                         "type": "array",
                         "items": {
@@ -12365,7 +12371,6 @@
                 },
                 "additionalProperties": false,
                 "required": [
-                    "vector_store_id",
                     "file_ids"
                 ],
                 "title": "OpenAICreateVectorStoreFileBatchRequestWithExtraBody",

docs/static/deprecated-llama-stack-spec.yaml

@@ -1932,7 +1932,14 @@ paths:
 
         Generate an OpenAI-compatible vector store file batch for the given vector
         store.
-      parameters: []
+      parameters:
+        - name: vector_store_id
+          in: path
+          description: >-
+            The ID of the vector store to create the file batch for.
+          required: true
+          schema:
+            type: string
       requestBody:
         content:
           application/json:
@@ -9326,10 +9333,6 @@ components:
     "OpenAICreateVectorStoreFileBatchRequestWithExtraBody":
       type: object
       properties:
-        vector_store_id:
-          type: string
-          description: >-
-            The ID of the vector store to create the file batch for
         file_ids:
           type: array
           items:
@@ -9355,7 +9358,6 @@ components:
             auto
       additionalProperties: false
       required:
-        - vector_store_id
         - file_ids
       title: >-
         OpenAICreateVectorStoreFileBatchRequestWithExtraBody

docs/static/llama-stack-spec.html

@@ -3357,7 +3357,17 @@
                 ],
                 "summary": "Create a vector store file batch.",
                 "description": "Create a vector store file batch.\nGenerate an OpenAI-compatible vector store file batch for the given vector store.",
-                "parameters": [],
+                "parameters": [
+                    {
+                        "name": "vector_store_id",
+                        "in": "path",
+                        "description": "The ID of the vector store to create the file batch for.",
+                        "required": true,
+                        "schema": {
+                            "type": "string"
+                        }
+                    }
+                ],
                 "requestBody": {
                     "content": {
                         "application/json": {
@@ -12847,10 +12857,6 @@
             "OpenAICreateVectorStoreFileBatchRequestWithExtraBody": {
                 "type": "object",
                 "properties": {
-                    "vector_store_id": {
-                        "type": "string",
-                        "description": "The ID of the vector store to create the file batch for"
-                    },
                     "file_ids": {
                         "type": "array",
                         "items": {
@@ -12891,7 +12897,6 @@
                 },
                 "additionalProperties": false,
                 "required": [
-                    "vector_store_id",
                     "file_ids"
                 ],
                 "title": "OpenAICreateVectorStoreFileBatchRequestWithExtraBody",

docs/static/llama-stack-spec.yaml

@@ -2553,7 +2553,14 @@ paths:
 
         Generate an OpenAI-compatible vector store file batch for the given vector
         store.
-      parameters: []
+      parameters:
+        - name: vector_store_id
+          in: path
+          description: >-
+            The ID of the vector store to create the file batch for.
+          required: true
+          schema:
+            type: string
       requestBody:
         content:
           application/json:
@@ -9791,10 +9798,6 @@ components:
     "OpenAICreateVectorStoreFileBatchRequestWithExtraBody":
       type: object
       properties:
-        vector_store_id:
-          type: string
-          description: >-
-            The ID of the vector store to create the file batch for
         file_ids:
           type: array
           items:
@@ -9820,7 +9823,6 @@ components:
             auto
       additionalProperties: false
       required:
-        - vector_store_id
         - file_ids
       title: >-
         OpenAICreateVectorStoreFileBatchRequestWithExtraBody

docs/static/stainless-llama-stack-spec.html

@@ -3357,7 +3357,17 @@
                 ],
                 "summary": "Create a vector store file batch.",
                 "description": "Create a vector store file batch.\nGenerate an OpenAI-compatible vector store file batch for the given vector store.",
-                "parameters": [],
+                "parameters": [
+                    {
+                        "name": "vector_store_id",
+                        "in": "path",
+                        "description": "The ID of the vector store to create the file batch for.",
+                        "required": true,
+                        "schema": {
+                            "type": "string"
+                        }
+                    }
+                ],
                 "requestBody": {
                     "content": {
                         "application/json": {
@@ -14856,10 +14866,6 @@
             "OpenAICreateVectorStoreFileBatchRequestWithExtraBody": {
                 "type": "object",
                 "properties": {
-                    "vector_store_id": {
-                        "type": "string",
-                        "description": "The ID of the vector store to create the file batch for"
-                    },
                     "file_ids": {
                         "type": "array",
                         "items": {
@@ -14900,7 +14906,6 @@
                 },
                 "additionalProperties": false,
                 "required": [
-                    "vector_store_id",
                     "file_ids"
                 ],
                 "title": "OpenAICreateVectorStoreFileBatchRequestWithExtraBody",

docs/static/stainless-llama-stack-spec.yaml

@@ -2556,7 +2556,14 @@ paths:
 
         Generate an OpenAI-compatible vector store file batch for the given vector
         store.
-      parameters: []
+      parameters:
+        - name: vector_store_id
+          in: path
+          description: >-
+            The ID of the vector store to create the file batch for.
+          required: true
+          schema:
+            type: string
       requestBody:
         content:
           application/json:
@@ -11236,10 +11243,6 @@ components:
     "OpenAICreateVectorStoreFileBatchRequestWithExtraBody":
       type: object
       properties:
-        vector_store_id:
-          type: string
-          description: >-
-            The ID of the vector store to create the file batch for
         file_ids:
           type: array
           items:
@@ -11265,7 +11268,6 @@ components:
             auto
       additionalProperties: false
       required:
-        - vector_store_id
         - file_ids
       title: >-
         OpenAICreateVectorStoreFileBatchRequestWithExtraBody

llama_stack/apis/vector_io/vector_io.py

@@ -491,13 +491,11 @@ class OpenAICreateVectorStoreRequestWithExtraBody(BaseModel, extra="allow"):
 class OpenAICreateVectorStoreFileBatchRequestWithExtraBody(BaseModel, extra="allow"):
     """Request to create a vector store file batch with extra_body support.
 
-    :param vector_store_id: The ID of the vector store to create the file batch for
     :param file_ids: A list of File IDs that the vector store should use
     :param attributes: (Optional) Key-value attributes to store with the files
     :param chunking_strategy: (Optional) The chunking strategy used to chunk the file(s). Defaults to auto
     """
 
-    vector_store_id: str
     file_ids: list[str]
     attributes: dict[str, Any] | None = None
     chunking_strategy: VectorStoreChunkingStrategy | None = None
@@ -849,11 +847,13 @@ class VectorIO(Protocol):
     )
     async def openai_create_vector_store_file_batch(
         self,
+        vector_store_id: str,
         params: Annotated[OpenAICreateVectorStoreFileBatchRequestWithExtraBody, Body(...)],
     ) -> VectorStoreFileBatchObject:
         """Create a vector store file batch.
 
         Generate an OpenAI-compatible vector store file batch for the given vector store.
+        :param vector_store_id: The ID of the vector store to create the file batch for.
         :returns: A VectorStoreFileBatchObject representing the created file batch.
         """
         ...

llama_stack/core/library_client.py

@@ -513,6 +513,14 @@ class AsyncLlamaStackAsLibraryClient(AsyncLlamaStackClient):
         # Strip NOT_GIVENs to use the defaults in signature
         body = {k: v for k, v in body.items() if v is not NOT_GIVEN}
 
+        # Check if there's an unwrapped body parameter among multiple parameters
+        # (e.g., path param + body param like: vector_store_id: str, params: Annotated[Model, Body(...)])
+        unwrapped_body_param = None
+        for param in params_list:
+            if is_unwrapped_body_param(param.annotation):
+                unwrapped_body_param = param
+                break
+
         # Convert parameters to Pydantic models where needed
         converted_body = {}
         for param_name, param in sig.parameters.items():
@@ -522,5 +530,11 @@ class AsyncLlamaStackAsLibraryClient(AsyncLlamaStackClient):
                     converted_body[param_name] = value
                 else:
                     converted_body[param_name] = convert_to_pydantic(param.annotation, value)
+            elif unwrapped_body_param and param.name == unwrapped_body_param.name:
+                # This is the unwrapped body param - construct it from remaining body keys
+                base_type = get_args(param.annotation)[0]
+                # Extract only the keys that aren't already used by other params
+                remaining_keys = {k: v for k, v in body.items() if k not in converted_body}
+                converted_body[param.name] = base_type(**remaining_keys)
 
         return converted_body

llama_stack/core/routers/vector_io.py

@@ -383,13 +383,14 @@ class VectorIORouter(VectorIO):
 
     async def openai_create_vector_store_file_batch(
         self,
+        vector_store_id: str,
         params: Annotated[OpenAICreateVectorStoreFileBatchRequestWithExtraBody, Body(...)],
     ) -> VectorStoreFileBatchObject:
         logger.debug(
-            f"VectorIORouter.openai_create_vector_store_file_batch: {params.vector_store_id}, {len(params.file_ids)} files"
+            f"VectorIORouter.openai_create_vector_store_file_batch: {vector_store_id}, {len(params.file_ids)} files"
         )
-        provider = await self.routing_table.get_provider_impl(params.vector_store_id)
+        provider = await self.routing_table.get_provider_impl(vector_store_id)
-        return await provider.openai_create_vector_store_file_batch(params)
+        return await provider.openai_create_vector_store_file_batch(vector_store_id, params)
 
     async def openai_retrieve_vector_store_file_batch(
         self,

llama_stack/providers/utils/memory/openai_vector_store_mixin.py

@@ -978,10 +978,10 @@ class OpenAIVectorStoreMixin(ABC):
 
     async def openai_create_vector_store_file_batch(
         self,
+        vector_store_id: str,
         params: Annotated[OpenAICreateVectorStoreFileBatchRequestWithExtraBody, Body(...)],
     ) -> VectorStoreFileBatchObject:
         """Create a vector store file batch."""
-        vector_store_id = params.vector_store_id
         if vector_store_id not in self.openai_vector_stores:
             raise VectorStoreNotFoundError(vector_store_id)
 

tests/unit/providers/vector_io/test_vector_io_openai_vector_stores.py

@@ -327,7 +327,7 @@ async def test_create_vector_store_file_batch(vector_io_adapter):
     vector_io_adapter._process_file_batch_async = AsyncMock()
 
     batch = await vector_io_adapter.openai_create_vector_store_file_batch(
-        params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(vector_store_id=store_id, file_ids=file_ids)
+        vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=file_ids)
     )
 
     assert batch.vector_store_id == store_id
@@ -354,7 +354,7 @@ async def test_retrieve_vector_store_file_batch(vector_io_adapter):
 
     # Create batch first
     created_batch = await vector_io_adapter.openai_create_vector_store_file_batch(
-        params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(vector_store_id=store_id, file_ids=file_ids)
+        vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=file_ids)
     )
 
     # Retrieve batch
@@ -387,7 +387,7 @@ async def test_cancel_vector_store_file_batch(vector_io_adapter):
 
     # Create batch
     batch = await vector_io_adapter.openai_create_vector_store_file_batch(
-        params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(vector_store_id=store_id, file_ids=file_ids)
+        vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=file_ids)
     )
 
     # Cancel batch
@@ -432,7 +432,7 @@ async def test_list_files_in_vector_store_file_batch(vector_io_adapter):
 
     # Create batch
     batch = await vector_io_adapter.openai_create_vector_store_file_batch(
-        params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(vector_store_id=store_id, file_ids=file_ids)
+        vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=file_ids)
     )
 
     # List files
@@ -451,9 +451,8 @@ async def test_file_batch_validation_errors(vector_io_adapter):
     # Test nonexistent vector store
     with pytest.raises(VectorStoreNotFoundError):
         await vector_io_adapter.openai_create_vector_store_file_batch(
-            params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(
+            vector_store_id="nonexistent",
-                vector_store_id="nonexistent", file_ids=["file_1"]
+            params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=["file_1"]),
-            ),
         )
 
     # Setup store for remaining tests
@@ -470,7 +469,7 @@ async def test_file_batch_validation_errors(vector_io_adapter):
     # Test wrong vector store for batch
     vector_io_adapter.openai_attach_file_to_vector_store = AsyncMock()
     batch = await vector_io_adapter.openai_create_vector_store_file_batch(
-        params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(vector_store_id=store_id, file_ids=["file_1"])
+        vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=["file_1"])
     )
 
     # Create wrong_store so it exists but the batch doesn't belong to it
@@ -517,7 +516,7 @@ async def test_file_batch_pagination(vector_io_adapter):
 
     # Create batch
     batch = await vector_io_adapter.openai_create_vector_store_file_batch(
-        params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(vector_store_id=store_id, file_ids=file_ids)
+        vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=file_ids)
     )
 
     # Test pagination with limit
@@ -589,7 +588,7 @@ async def test_file_batch_status_filtering(vector_io_adapter):
 
     # Create batch
     batch = await vector_io_adapter.openai_create_vector_store_file_batch(
-        params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(vector_store_id=store_id, file_ids=file_ids)
+        vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=file_ids)
     )
 
     # Test filtering by completed status
@@ -631,7 +630,7 @@ async def test_cancel_completed_batch_fails(vector_io_adapter):
 
     # Create batch
     batch = await vector_io_adapter.openai_create_vector_store_file_batch(
-        params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(vector_store_id=store_id, file_ids=file_ids)
+        vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=file_ids)
     )
 
     # Manually update status to completed
@@ -665,7 +664,7 @@ async def test_file_batch_persistence_across_restarts(vector_io_adapter):
 
     # Create batch
     batch = await vector_io_adapter.openai_create_vector_store_file_batch(
-        params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(vector_store_id=store_id, file_ids=file_ids)
+        vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=file_ids)
     )
     batch_id = batch.id
 
@@ -720,7 +719,7 @@ async def test_cancelled_batch_persists_in_storage(vector_io_adapter):
 
     # Create batch
     batch = await vector_io_adapter.openai_create_vector_store_file_batch(
-        params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(vector_store_id=store_id, file_ids=file_ids)
+        vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=file_ids)
     )
     batch_id = batch.id
 
@@ -767,10 +766,10 @@ async def test_only_in_progress_batches_resumed(vector_io_adapter):
 
     # Create multiple batches
     batch1 = await vector_io_adapter.openai_create_vector_store_file_batch(
-        params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(vector_store_id=store_id, file_ids=["file_1"])
+        vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=["file_1"])
     )
     batch2 = await vector_io_adapter.openai_create_vector_store_file_batch(
-        params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(vector_store_id=store_id, file_ids=["file_2"])
+        vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=["file_2"])
     )
 
     # Complete one batch (should persist with completed status)
@@ -783,7 +782,7 @@ async def test_only_in_progress_batches_resumed(vector_io_adapter):
 
     # Create a third batch that stays in progress
     batch3 = await vector_io_adapter.openai_create_vector_store_file_batch(
-        params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(vector_store_id=store_id, file_ids=["file_3"])
+        vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=["file_3"])
     )
 
     # Simulate restart - clear memory and reload from persistence
@@ -944,7 +943,7 @@ async def test_max_concurrent_files_per_batch(vector_io_adapter):
     file_ids = [f"file_{i}" for i in range(8)]  # 8 files, but limit should be 5
 
     batch = await vector_io_adapter.openai_create_vector_store_file_batch(
-        params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(vector_store_id=store_id, file_ids=file_ids)
+        vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=file_ids)
     )
 
     # Give time for the semaphore logic to start processing files