more fixes

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

@@ -2623,17 +2623,7 @@
                 ],
                 "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": {
@@ -12154,19 +12144,6 @@
                             ]
                         },
                         "description": "Set of key-value pairs that can be attached to the vector store"
-                    },
-                    "embedding_model": {
-                        "type": "string",
-                        "description": "(Optional) The embedding model to use for this vector store"
-                    },
-                    "embedding_dimension": {
-                        "type": "integer",
-                        "default": 384,
-                        "description": "(Optional) The dimension of the embedding vectors (default: 384)"
-                    },
-                    "provider_id": {
-                        "type": "string",
-                        "description": "(Optional) The ID of the provider to use for this vector store"
                     }
                 },
                 "additionalProperties": false,
@@ -12344,6 +12321,10 @@
             "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": {
@@ -12384,6 +12365,7 @@
                 },
                 "additionalProperties": false,
                 "required": [
+                    "vector_store_id",
                     "file_ids"
                 ],
                 "title": "OpenAICreateVectorStoreFileBatchRequestWithExtraBody",

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

@@ -1932,14 +1932,7 @@ 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:
@@ -9205,19 +9198,6 @@ components:
               - type: object
           description: >-
             Set of key-value pairs that can be attached to the vector store
-        embedding_model:
-          type: string
-          description: >-
-            (Optional) The embedding model to use for this vector store
-        embedding_dimension:
-          type: integer
-          default: 384
-          description: >-
-            (Optional) The dimension of the embedding vectors (default: 384)
-        provider_id:
-          type: string
-          description: >-
-            (Optional) The ID of the provider to use for this vector store
       additionalProperties: false
       title: >-
         OpenAICreateVectorStoreRequestWithExtraBody
@@ -9346,6 +9326,10 @@ 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:
@@ -9371,6 +9355,7 @@ components:
             auto
       additionalProperties: false
       required:
+        - vector_store_id
         - file_ids
       title: >-
         OpenAICreateVectorStoreFileBatchRequestWithExtraBody

docs/static/llama-stack-spec.html

@@ -3357,17 +3357,7 @@
                 ],
                 "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": {
@@ -12680,19 +12670,6 @@
                             ]
                         },
                         "description": "Set of key-value pairs that can be attached to the vector store"
-                    },
-                    "embedding_model": {
-                        "type": "string",
-                        "description": "(Optional) The embedding model to use for this vector store"
-                    },
-                    "embedding_dimension": {
-                        "type": "integer",
-                        "default": 384,
-                        "description": "(Optional) The dimension of the embedding vectors (default: 384)"
-                    },
-                    "provider_id": {
-                        "type": "string",
-                        "description": "(Optional) The ID of the provider to use for this vector store"
                     }
                 },
                 "additionalProperties": false,
@@ -12870,6 +12847,10 @@
             "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": {
@@ -12910,6 +12891,7 @@
                 },
                 "additionalProperties": false,
                 "required": [
+                    "vector_store_id",
                     "file_ids"
                 ],
                 "title": "OpenAICreateVectorStoreFileBatchRequestWithExtraBody",

docs/static/llama-stack-spec.yaml

@@ -2553,14 +2553,7 @@ 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:
@@ -9670,19 +9663,6 @@ components:
               - type: object
           description: >-
             Set of key-value pairs that can be attached to the vector store
-        embedding_model:
-          type: string
-          description: >-
-            (Optional) The embedding model to use for this vector store
-        embedding_dimension:
-          type: integer
-          default: 384
-          description: >-
-            (Optional) The dimension of the embedding vectors (default: 384)
-        provider_id:
-          type: string
-          description: >-
-            (Optional) The ID of the provider to use for this vector store
       additionalProperties: false
       title: >-
         OpenAICreateVectorStoreRequestWithExtraBody
@@ -9811,6 +9791,10 @@ 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:
@@ -9836,6 +9820,7 @@ components:
             auto
       additionalProperties: false
       required:
+        - vector_store_id
         - file_ids
       title: >-
         OpenAICreateVectorStoreFileBatchRequestWithExtraBody

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

@@ -3357,17 +3357,7 @@
                 ],
                 "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": {
@@ -14689,19 +14679,6 @@
                             ]
                         },
                         "description": "Set of key-value pairs that can be attached to the vector store"
-                    },
-                    "embedding_model": {
-                        "type": "string",
-                        "description": "(Optional) The embedding model to use for this vector store"
-                    },
-                    "embedding_dimension": {
-                        "type": "integer",
-                        "default": 384,
-                        "description": "(Optional) The dimension of the embedding vectors (default: 384)"
-                    },
-                    "provider_id": {
-                        "type": "string",
-                        "description": "(Optional) The ID of the provider to use for this vector store"
                     }
                 },
                 "additionalProperties": false,
@@ -14879,6 +14856,10 @@
             "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": {
@@ -14919,6 +14900,7 @@
                 },
                 "additionalProperties": false,
                 "required": [
+                    "vector_store_id",
                     "file_ids"
                 ],
                 "title": "OpenAICreateVectorStoreFileBatchRequestWithExtraBody",

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

@@ -2556,14 +2556,7 @@ 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:
@@ -11115,19 +11108,6 @@ components:
               - type: object
           description: >-
             Set of key-value pairs that can be attached to the vector store
-        embedding_model:
-          type: string
-          description: >-
-            (Optional) The embedding model to use for this vector store
-        embedding_dimension:
-          type: integer
-          default: 384
-          description: >-
-            (Optional) The dimension of the embedding vectors (default: 384)
-        provider_id:
-          type: string
-          description: >-
-            (Optional) The ID of the provider to use for this vector store
       additionalProperties: false
       title: >-
         OpenAICreateVectorStoreRequestWithExtraBody
@@ -11256,6 +11236,10 @@ 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:
@@ -11281,6 +11265,7 @@ components:
             auto
       additionalProperties: false
       required:
+        - vector_store_id
         - file_ids
       title: >-
         OpenAICreateVectorStoreFileBatchRequestWithExtraBody

llama_stack/apis/vector_io/vector_io.py

@@ -491,11 +491,13 @@ 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
@@ -847,13 +849,11 @@ 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/routers/vector_io.py

@@ -383,17 +383,13 @@ 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: {vector_store_id}, {len(params.file_ids)} files"
+            f"VectorIORouter.openai_create_vector_store_file_batch: {params.vector_store_id}, {len(params.file_ids)} files"
-        )
-        provider = await self.routing_table.get_provider_impl(vector_store_id)
-        return await provider.openai_create_vector_store_file_batch(
-            vector_store_id=vector_store_id,
-            params=params,
         )
+        provider = await self.routing_table.get_provider_impl(params.vector_store_id)
+        return await provider.openai_create_vector_store_file_batch(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)