diff --git a/docs/_static/llama-stack-spec.html b/docs/_static/llama-stack-spec.html
index 5407f9808..bad747c5c 100644
--- a/docs/_static/llama-stack-spec.html
+++ b/docs/_static/llama-stack-spec.html
@@ -3241,6 +3241,47 @@
}
},
"/v1/openai/v1/vector_stores/{vector_store_id}/files": {
+ "get": {
+ "responses": {
+ "200": {
+ "description": "A VectorStoreListFilesResponse containing the list of files.",
+ "content": {
+ "application/json": {
+ "schema": {
+ "$ref": "#/components/schemas/VectorStoreListFilesResponse"
+ }
+ }
+ }
+ },
+ "400": {
+ "$ref": "#/components/responses/BadRequest400"
+ },
+ "429": {
+ "$ref": "#/components/responses/TooManyRequests429"
+ },
+ "500": {
+ "$ref": "#/components/responses/InternalServerError500"
+ },
+ "default": {
+ "$ref": "#/components/responses/DefaultError"
+ }
+ },
+ "tags": [
+ "VectorIO"
+ ],
+ "description": "List files in a vector store.",
+ "parameters": [
+ {
+ "name": "vector_store_id",
+ "in": "path",
+ "description": "The ID of the vector store to list files from.",
+ "required": true,
+ "schema": {
+ "type": "string"
+ }
+ }
+ ]
+ },
"post": {
"responses": {
"200": {
@@ -3666,6 +3707,168 @@
]
}
},
+ "/v1/openai/v1/vector_stores/{vector_store_id}/files/{file_id}": {
+ "get": {
+ "responses": {
+ "200": {
+ "description": "A VectorStoreFileObject representing the file.",
+ "content": {
+ "application/json": {
+ "schema": {
+ "$ref": "#/components/schemas/VectorStoreFileObject"
+ }
+ }
+ }
+ },
+ "400": {
+ "$ref": "#/components/responses/BadRequest400"
+ },
+ "429": {
+ "$ref": "#/components/responses/TooManyRequests429"
+ },
+ "500": {
+ "$ref": "#/components/responses/InternalServerError500"
+ },
+ "default": {
+ "$ref": "#/components/responses/DefaultError"
+ }
+ },
+ "tags": [
+ "VectorIO"
+ ],
+ "description": "Retrieves a vector store file.",
+ "parameters": [
+ {
+ "name": "vector_store_id",
+ "in": "path",
+ "description": "The ID of the vector store containing the file to retrieve.",
+ "required": true,
+ "schema": {
+ "type": "string"
+ }
+ },
+ {
+ "name": "file_id",
+ "in": "path",
+ "description": "The ID of the file to retrieve.",
+ "required": true,
+ "schema": {
+ "type": "string"
+ }
+ }
+ ]
+ },
+ "post": {
+ "responses": {
+ "200": {
+ "description": "A VectorStoreFileObject representing the updated file.",
+ "content": {
+ "application/json": {
+ "schema": {
+ "$ref": "#/components/schemas/VectorStoreFileObject"
+ }
+ }
+ }
+ },
+ "400": {
+ "$ref": "#/components/responses/BadRequest400"
+ },
+ "429": {
+ "$ref": "#/components/responses/TooManyRequests429"
+ },
+ "500": {
+ "$ref": "#/components/responses/InternalServerError500"
+ },
+ "default": {
+ "$ref": "#/components/responses/DefaultError"
+ }
+ },
+ "tags": [
+ "VectorIO"
+ ],
+ "description": "Updates a vector store file.",
+ "parameters": [
+ {
+ "name": "vector_store_id",
+ "in": "path",
+ "description": "The ID of the vector store containing the file to update.",
+ "required": true,
+ "schema": {
+ "type": "string"
+ }
+ },
+ {
+ "name": "file_id",
+ "in": "path",
+ "description": "The ID of the file to update.",
+ "required": true,
+ "schema": {
+ "type": "string"
+ }
+ }
+ ],
+ "requestBody": {
+ "content": {
+ "application/json": {
+ "schema": {
+ "$ref": "#/components/schemas/OpenaiUpdateVectorStoreFileRequest"
+ }
+ }
+ },
+ "required": true
+ }
+ },
+ "delete": {
+ "responses": {
+ "200": {
+ "description": "A VectorStoreFileDeleteResponse indicating the deletion status.",
+ "content": {
+ "application/json": {
+ "schema": {
+ "$ref": "#/components/schemas/VectorStoreFileDeleteResponse"
+ }
+ }
+ }
+ },
+ "400": {
+ "$ref": "#/components/responses/BadRequest400"
+ },
+ "429": {
+ "$ref": "#/components/responses/TooManyRequests429"
+ },
+ "500": {
+ "$ref": "#/components/responses/InternalServerError500"
+ },
+ "default": {
+ "$ref": "#/components/responses/DefaultError"
+ }
+ },
+ "tags": [
+ "VectorIO"
+ ],
+ "description": "Delete a vector store file.",
+ "parameters": [
+ {
+ "name": "vector_store_id",
+ "in": "path",
+ "description": "The ID of the vector store containing the file to delete.",
+ "required": true,
+ "schema": {
+ "type": "string"
+ }
+ },
+ {
+ "name": "file_id",
+ "in": "path",
+ "description": "The ID of the file to delete.",
+ "required": true,
+ "schema": {
+ "type": "string"
+ }
+ }
+ ]
+ }
+ },
"/v1/openai/v1/embeddings": {
"post": {
"responses": {
@@ -12969,6 +13172,35 @@
],
"title": "OpenaiCreateVectorStoreRequest"
},
+ "VectorStoreFileCounts": {
+ "type": "object",
+ "properties": {
+ "completed": {
+ "type": "integer"
+ },
+ "cancelled": {
+ "type": "integer"
+ },
+ "failed": {
+ "type": "integer"
+ },
+ "in_progress": {
+ "type": "integer"
+ },
+ "total": {
+ "type": "integer"
+ }
+ },
+ "additionalProperties": false,
+ "required": [
+ "completed",
+ "cancelled",
+ "failed",
+ "in_progress",
+ "total"
+ ],
+ "title": "VectorStoreFileCounts"
+ },
"VectorStoreObject": {
"type": "object",
"properties": {
@@ -12990,10 +13222,7 @@
"default": 0
},
"file_counts": {
- "type": "object",
- "additionalProperties": {
- "type": "integer"
- }
+ "$ref": "#/components/schemas/VectorStoreFileCounts"
},
"status": {
"type": "string",
@@ -13120,6 +13349,30 @@
"title": "VectorStoreDeleteResponse",
"description": "Response from deleting a vector store."
},
+ "VectorStoreFileDeleteResponse": {
+ "type": "object",
+ "properties": {
+ "id": {
+ "type": "string"
+ },
+ "object": {
+ "type": "string",
+ "default": "vector_store.file.deleted"
+ },
+ "deleted": {
+ "type": "boolean",
+ "default": true
+ }
+ },
+ "additionalProperties": false,
+ "required": [
+ "id",
+ "object",
+ "deleted"
+ ],
+ "title": "VectorStoreFileDeleteResponse",
+ "description": "Response from deleting a vector store file."
+ },
"OpenaiEmbeddingsRequest": {
"type": "object",
"properties": {
@@ -13348,6 +13601,28 @@
"title": "OpenAIFileObject",
"description": "OpenAI File object as defined in the OpenAI Files API."
},
+ "VectorStoreListFilesResponse": {
+ "type": "object",
+ "properties": {
+ "object": {
+ "type": "string",
+ "default": "list"
+ },
+ "data": {
+ "type": "array",
+ "items": {
+ "$ref": "#/components/schemas/VectorStoreFileObject"
+ }
+ }
+ },
+ "additionalProperties": false,
+ "required": [
+ "object",
+ "data"
+ ],
+ "title": "VectorStoreListFilesResponse",
+ "description": "Response from listing vector stores."
+ },
"OpenAIModel": {
"type": "object",
"properties": {
@@ -13661,6 +13936,42 @@
"additionalProperties": false,
"title": "OpenaiUpdateVectorStoreRequest"
},
+ "OpenaiUpdateVectorStoreFileRequest": {
+ "type": "object",
+ "properties": {
+ "attributes": {
+ "type": "object",
+ "additionalProperties": {
+ "oneOf": [
+ {
+ "type": "null"
+ },
+ {
+ "type": "boolean"
+ },
+ {
+ "type": "number"
+ },
+ {
+ "type": "string"
+ },
+ {
+ "type": "array"
+ },
+ {
+ "type": "object"
+ }
+ ]
+ },
+ "description": "The updated key-value attributes to store with the file."
+ }
+ },
+ "additionalProperties": false,
+ "required": [
+ "attributes"
+ ],
+ "title": "OpenaiUpdateVectorStoreFileRequest"
+ },
"DPOAlignmentConfig": {
"type": "object",
"properties": {
diff --git a/docs/_static/llama-stack-spec.yaml b/docs/_static/llama-stack-spec.yaml
index a354e4bd0..c02decfe2 100644
--- a/docs/_static/llama-stack-spec.yaml
+++ b/docs/_static/llama-stack-spec.yaml
@@ -2264,6 +2264,36 @@ paths:
$ref: '#/components/schemas/LogEventRequest'
required: true
/v1/openai/v1/vector_stores/{vector_store_id}/files:
+ get:
+ responses:
+ '200':
+ description: >-
+ A VectorStoreListFilesResponse containing the list of files.
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/VectorStoreListFilesResponse'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ '429':
+ $ref: >-
+ #/components/responses/TooManyRequests429
+ '500':
+ $ref: >-
+ #/components/responses/InternalServerError500
+ default:
+ $ref: '#/components/responses/DefaultError'
+ tags:
+ - VectorIO
+ description: List files in a vector store.
+ parameters:
+ - name: vector_store_id
+ in: path
+ description: >-
+ The ID of the vector store to list files from.
+ required: true
+ schema:
+ type: string
post:
responses:
'200':
@@ -2572,6 +2602,121 @@ paths:
required: true
schema:
type: string
+ /v1/openai/v1/vector_stores/{vector_store_id}/files/{file_id}:
+ get:
+ responses:
+ '200':
+ description: >-
+ A VectorStoreFileObject representing the file.
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/VectorStoreFileObject'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ '429':
+ $ref: >-
+ #/components/responses/TooManyRequests429
+ '500':
+ $ref: >-
+ #/components/responses/InternalServerError500
+ default:
+ $ref: '#/components/responses/DefaultError'
+ tags:
+ - VectorIO
+ description: Retrieves a vector store file.
+ parameters:
+ - name: vector_store_id
+ in: path
+ description: >-
+ The ID of the vector store containing the file to retrieve.
+ required: true
+ schema:
+ type: string
+ - name: file_id
+ in: path
+ description: The ID of the file to retrieve.
+ required: true
+ schema:
+ type: string
+ post:
+ responses:
+ '200':
+ description: >-
+ A VectorStoreFileObject representing the updated file.
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/VectorStoreFileObject'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ '429':
+ $ref: >-
+ #/components/responses/TooManyRequests429
+ '500':
+ $ref: >-
+ #/components/responses/InternalServerError500
+ default:
+ $ref: '#/components/responses/DefaultError'
+ tags:
+ - VectorIO
+ description: Updates a vector store file.
+ parameters:
+ - name: vector_store_id
+ in: path
+ description: >-
+ The ID of the vector store containing the file to update.
+ required: true
+ schema:
+ type: string
+ - name: file_id
+ in: path
+ description: The ID of the file to update.
+ required: true
+ schema:
+ type: string
+ requestBody:
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/OpenaiUpdateVectorStoreFileRequest'
+ required: true
+ delete:
+ responses:
+ '200':
+ description: >-
+ A VectorStoreFileDeleteResponse indicating the deletion status.
+ content:
+ application/json:
+ schema:
+ $ref: '#/components/schemas/VectorStoreFileDeleteResponse'
+ '400':
+ $ref: '#/components/responses/BadRequest400'
+ '429':
+ $ref: >-
+ #/components/responses/TooManyRequests429
+ '500':
+ $ref: >-
+ #/components/responses/InternalServerError500
+ default:
+ $ref: '#/components/responses/DefaultError'
+ tags:
+ - VectorIO
+ description: Delete a vector store file.
+ parameters:
+ - name: vector_store_id
+ in: path
+ description: >-
+ The ID of the vector store containing the file to delete.
+ required: true
+ schema:
+ type: string
+ - name: file_id
+ in: path
+ description: The ID of the file to delete.
+ required: true
+ schema:
+ type: string
/v1/openai/v1/embeddings:
post:
responses:
@@ -9031,6 +9176,27 @@ components:
required:
- name
title: OpenaiCreateVectorStoreRequest
+ VectorStoreFileCounts:
+ type: object
+ properties:
+ completed:
+ type: integer
+ cancelled:
+ type: integer
+ failed:
+ type: integer
+ in_progress:
+ type: integer
+ total:
+ type: integer
+ additionalProperties: false
+ required:
+ - completed
+ - cancelled
+ - failed
+ - in_progress
+ - total
+ title: VectorStoreFileCounts
VectorStoreObject:
type: object
properties:
@@ -9047,9 +9213,7 @@ components:
type: integer
default: 0
file_counts:
- type: object
- additionalProperties:
- type: integer
+ $ref: '#/components/schemas/VectorStoreFileCounts'
status:
type: string
default: completed
@@ -9129,6 +9293,25 @@ components:
- deleted
title: VectorStoreDeleteResponse
description: Response from deleting a vector store.
+ VectorStoreFileDeleteResponse:
+ type: object
+ properties:
+ id:
+ type: string
+ object:
+ type: string
+ default: vector_store.file.deleted
+ deleted:
+ type: boolean
+ default: true
+ additionalProperties: false
+ required:
+ - id
+ - object
+ - deleted
+ title: VectorStoreFileDeleteResponse
+ description: >-
+ Response from deleting a vector store file.
OpenaiEmbeddingsRequest:
type: object
properties:
@@ -9320,6 +9503,22 @@ components:
title: OpenAIFileObject
description: >-
OpenAI File object as defined in the OpenAI Files API.
+ VectorStoreListFilesResponse:
+ type: object
+ properties:
+ object:
+ type: string
+ default: list
+ data:
+ type: array
+ items:
+ $ref: '#/components/schemas/VectorStoreFileObject'
+ additionalProperties: false
+ required:
+ - object
+ - data
+ title: VectorStoreListFilesResponse
+ description: Response from listing vector stores.
OpenAIModel:
type: object
properties:
@@ -9524,6 +9723,25 @@ components:
Set of 16 key-value pairs that can be attached to an object.
additionalProperties: false
title: OpenaiUpdateVectorStoreRequest
+ OpenaiUpdateVectorStoreFileRequest:
+ type: object
+ properties:
+ attributes:
+ type: object
+ additionalProperties:
+ oneOf:
+ - type: 'null'
+ - type: boolean
+ - type: number
+ - type: string
+ - type: array
+ - type: object
+ description: >-
+ The updated key-value attributes to store with the file.
+ additionalProperties: false
+ required:
+ - attributes
+ title: OpenaiUpdateVectorStoreFileRequest
DPOAlignmentConfig:
type: object
properties:
diff --git a/llama_stack/apis/vector_io/vector_io.py b/llama_stack/apis/vector_io/vector_io.py
index 20cc594cc..8e569bfeb 100644
--- a/llama_stack/apis/vector_io/vector_io.py
+++ b/llama_stack/apis/vector_io/vector_io.py
@@ -38,6 +38,15 @@ class QueryChunksResponse(BaseModel):
scores: list[float]
+@json_schema_type
+class VectorStoreFileCounts(BaseModel):
+ completed: int
+ cancelled: int
+ failed: int
+ in_progress: int
+ total: int
+
+
@json_schema_type
class VectorStoreObject(BaseModel):
"""OpenAI Vector Store object."""
@@ -47,7 +56,7 @@ class VectorStoreObject(BaseModel):
created_at: int
name: str | None = None
usage_bytes: int = 0
- file_counts: dict[str, int] = Field(default_factory=dict)
+ file_counts: VectorStoreFileCounts
status: str = "completed"
expires_after: dict[str, Any] | None = None
expires_at: int | None = None
@@ -183,6 +192,23 @@ class VectorStoreFileObject(BaseModel):
vector_store_id: str
+@json_schema_type
+class VectorStoreListFilesResponse(BaseModel):
+ """Response from listing vector stores."""
+
+ object: str = "list"
+ data: list[VectorStoreFileObject]
+
+
+@json_schema_type
+class VectorStoreFileDeleteResponse(BaseModel):
+ """Response from deleting a vector store file."""
+
+ id: str
+ object: str = "vector_store.file.deleted"
+ deleted: bool = True
+
+
class VectorDBStore(Protocol):
def get_vector_db(self, vector_db_id: str) -> VectorDB | None: ...
@@ -358,3 +384,59 @@ class VectorIO(Protocol):
:returns: A VectorStoreFileObject representing the attached file.
"""
...
+
+ @webmethod(route="/openai/v1/vector_stores/{vector_store_id}/files", method="GET")
+ async def openai_list_files_in_vector_store(
+ self,
+ vector_store_id: str,
+ ) -> VectorStoreListFilesResponse:
+ """List files in a vector store.
+
+ :param vector_store_id: The ID of the vector store to list files from.
+ :returns: A VectorStoreListFilesResponse containing the list of files.
+ """
+ ...
+
+ @webmethod(route="/openai/v1/vector_stores/{vector_store_id}/files/{file_id}", method="GET")
+ async def openai_retrieve_vector_store_file(
+ self,
+ vector_store_id: str,
+ file_id: str,
+ ) -> VectorStoreFileObject:
+ """Retrieves a vector store file.
+
+ :param vector_store_id: The ID of the vector store containing the file to retrieve.
+ :param file_id: The ID of the file to retrieve.
+ :returns: A VectorStoreFileObject representing the file.
+ """
+ ...
+
+ @webmethod(route="/openai/v1/vector_stores/{vector_store_id}/files/{file_id}", method="POST")
+ async def openai_update_vector_store_file(
+ self,
+ vector_store_id: str,
+ file_id: str,
+ attributes: dict[str, Any],
+ ) -> VectorStoreFileObject:
+ """Updates a vector store file.
+
+ :param vector_store_id: The ID of the vector store containing the file to update.
+ :param file_id: The ID of the file to update.
+ :param attributes: The updated key-value attributes to store with the file.
+ :returns: A VectorStoreFileObject representing the updated file.
+ """
+ ...
+
+ @webmethod(route="/openai/v1/vector_stores/{vector_store_id}/files/{file_id}", method="DELETE")
+ async def openai_delete_vector_store_file(
+ self,
+ vector_store_id: str,
+ file_id: str,
+ ) -> VectorStoreFileDeleteResponse:
+ """Delete a vector store file.
+
+ :param vector_store_id: The ID of the vector store containing the file to delete.
+ :param file_id: The ID of the file to delete.
+ :returns: A VectorStoreFileDeleteResponse indicating the deletion status.
+ """
+ ...
diff --git a/llama_stack/distribution/routers/vector_io.py b/llama_stack/distribution/routers/vector_io.py
index 3001b8666..c09b1df2e 100644
--- a/llama_stack/distribution/routers/vector_io.py
+++ b/llama_stack/distribution/routers/vector_io.py
@@ -21,7 +21,11 @@ from llama_stack.apis.vector_io import (
VectorStoreObject,
VectorStoreSearchResponsePage,
)
-from llama_stack.apis.vector_io.vector_io import VectorStoreChunkingStrategy, VectorStoreFileObject
+from llama_stack.apis.vector_io.vector_io import (
+ VectorStoreChunkingStrategy,
+ VectorStoreFileDeleteResponse,
+ VectorStoreFileObject,
+)
from llama_stack.log import get_logger
from llama_stack.providers.datatypes import HealthResponse, HealthStatus, RoutingTable
@@ -279,6 +283,58 @@ class VectorIORouter(VectorIO):
chunking_strategy=chunking_strategy,
)
+ async def openai_list_files_in_vector_store(
+ self,
+ vector_store_id: str,
+ ) -> list[VectorStoreFileObject]:
+ logger.debug(f"VectorIORouter.openai_list_files_in_vector_store: {vector_store_id}")
+ # Route based on vector store ID
+ provider = self.routing_table.get_provider_impl(vector_store_id)
+ return await provider.openai_list_files_in_vector_store(
+ vector_store_id=vector_store_id,
+ )
+
+ async def openai_retrieve_vector_store_file(
+ self,
+ vector_store_id: str,
+ file_id: str,
+ ) -> VectorStoreFileObject:
+ logger.debug(f"VectorIORouter.openai_retrieve_vector_store_file: {vector_store_id}, {file_id}")
+ # Route based on vector store ID
+ provider = self.routing_table.get_provider_impl(vector_store_id)
+ return await provider.openai_retrieve_vector_store_file(
+ vector_store_id=vector_store_id,
+ file_id=file_id,
+ )
+
+ async def openai_update_vector_store_file(
+ self,
+ vector_store_id: str,
+ file_id: str,
+ attributes: dict[str, Any],
+ ) -> VectorStoreFileObject:
+ logger.debug(f"VectorIORouter.openai_update_vector_store_file: {vector_store_id}, {file_id}")
+ # Route based on vector store ID
+ provider = self.routing_table.get_provider_impl(vector_store_id)
+ return await provider.openai_update_vector_store_file(
+ vector_store_id=vector_store_id,
+ file_id=file_id,
+ attributes=attributes,
+ )
+
+ async def openai_delete_vector_store_file(
+ self,
+ vector_store_id: str,
+ file_id: str,
+ ) -> VectorStoreFileDeleteResponse:
+ logger.debug(f"VectorIORouter.openai_delete_vector_store_file: {vector_store_id}, {file_id}")
+ # Route based on vector store ID
+ provider = self.routing_table.get_provider_impl(vector_store_id)
+ return await provider.openai_delete_vector_store_file(
+ vector_store_id=vector_store_id,
+ file_id=file_id,
+ )
+
async def health(self) -> dict[str, HealthResponse]:
health_statuses = {}
timeout = 1 # increasing the timeout to 1 second for health checks
diff --git a/llama_stack/providers/inline/vector_io/faiss/faiss.py b/llama_stack/providers/inline/vector_io/faiss/faiss.py
index 0864ba3a7..83c74bce5 100644
--- a/llama_stack/providers/inline/vector_io/faiss/faiss.py
+++ b/llama_stack/providers/inline/vector_io/faiss/faiss.py
@@ -45,6 +45,7 @@ VERSION = "v3"
VECTOR_DBS_PREFIX = f"vector_dbs:{VERSION}::"
FAISS_INDEX_PREFIX = f"faiss_index:{VERSION}::"
OPENAI_VECTOR_STORES_PREFIX = f"openai_vector_stores:{VERSION}::"
+OPENAI_VECTOR_STORES_FILES_PREFIX = f"openai_vector_stores_files:{VERSION}::"
class FaissIndex(EmbeddingIndex):
@@ -283,3 +284,28 @@ class FaissVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtocolPr
assert self.kvstore is not None
key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}"
await self.kvstore.delete(key)
+
+ async def _save_openai_vector_store_file(self, store_id: str, file_id: str, file_info: dict[str, Any]) -> None:
+ """Save vector store file metadata to kvstore."""
+ assert self.kvstore is not None
+ key = f"{OPENAI_VECTOR_STORES_FILES_PREFIX}{store_id}:{file_id}"
+ await self.kvstore.set(key=key, value=json.dumps(file_info))
+
+ async def _load_openai_vector_store_file(self, store_id: str, file_id: str) -> dict[str, Any]:
+ """Load vector store file metadata from kvstore."""
+ assert self.kvstore is not None
+ key = f"{OPENAI_VECTOR_STORES_FILES_PREFIX}{store_id}:{file_id}"
+ stored_data = await self.kvstore.get(key)
+ return json.loads(stored_data) if stored_data else {}
+
+ async def _update_openai_vector_store_file(self, store_id: str, file_id: str, file_info: dict[str, Any]) -> None:
+ """Update vector store file metadata in kvstore."""
+ assert self.kvstore is not None
+ key = f"{OPENAI_VECTOR_STORES_FILES_PREFIX}{store_id}:{file_id}"
+ await self.kvstore.set(key=key, value=json.dumps(file_info))
+
+ async def _delete_openai_vector_store_file_from_storage(self, store_id: str, file_id: str) -> None:
+ """Delete vector store file metadata from kvstore."""
+ assert self.kvstore is not None
+ key = f"{OPENAI_VECTOR_STORES_FILES_PREFIX}{store_id}:{file_id}"
+ await self.kvstore.delete(key)
diff --git a/llama_stack/providers/inline/vector_io/sqlite_vec/sqlite_vec.py b/llama_stack/providers/inline/vector_io/sqlite_vec/sqlite_vec.py
index c6712882a..50cc262e4 100644
--- a/llama_stack/providers/inline/vector_io/sqlite_vec/sqlite_vec.py
+++ b/llama_stack/providers/inline/vector_io/sqlite_vec/sqlite_vec.py
@@ -461,6 +461,14 @@ class SQLiteVecVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtoc
metadata TEXT
);
""")
+ # Create a table to persist OpenAI vector store files.
+ cur.execute("""
+ CREATE TABLE IF NOT EXISTS openai_vector_store_files (
+ store_id TEXT,
+ file_id TEXT,
+ metadata TEXT
+ );
+ """)
connection.commit()
# Load any existing vector DB registrations.
cur.execute("SELECT metadata FROM vector_dbs")
@@ -615,6 +623,90 @@ class SQLiteVecVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtoc
await asyncio.to_thread(_delete)
+ async def _save_openai_vector_store_file(self, store_id: str, file_id: str, file_info: dict[str, Any]) -> None:
+ """Save vector store file metadata to SQLite database."""
+
+ def _store():
+ connection = _create_sqlite_connection(self.config.db_path)
+ cur = connection.cursor()
+ try:
+ cur.execute(
+ "INSERT OR REPLACE INTO openai_vector_store_files (store_id, file_id, metadata) VALUES (?, ?, ?)",
+ (store_id, file_id, json.dumps(file_info)),
+ )
+ connection.commit()
+ except Exception as e:
+ logger.error(f"Error saving openai vector store file {store_id} {file_id}: {e}")
+ raise
+ finally:
+ cur.close()
+ connection.close()
+
+ try:
+ await asyncio.to_thread(_store)
+ except Exception as e:
+ logger.error(f"Error saving openai vector store file {store_id} {file_id}: {e}")
+ raise
+
+ async def _load_openai_vector_store_file(self, store_id: str, file_id: str) -> dict[str, Any]:
+ """Load vector store file metadata from SQLite database."""
+
+ def _load():
+ connection = _create_sqlite_connection(self.config.db_path)
+ cur = connection.cursor()
+ try:
+ cur.execute(
+ "SELECT metadata FROM openai_vector_store_files WHERE store_id = ? AND file_id = ?",
+ (store_id, file_id),
+ )
+ row = cur.fetchone()
+ print(f"!!! row is {row}")
+ if row is None:
+ return None
+ (metadata,) = row
+ return metadata
+ finally:
+ cur.close()
+ connection.close()
+
+ stored_data = await asyncio.to_thread(_load)
+ return json.loads(stored_data) if stored_data else {}
+
+ async def _update_openai_vector_store_file(self, store_id: str, file_id: str, file_info: dict[str, Any]) -> None:
+ """Update vector store file metadata in SQLite database."""
+
+ def _update():
+ connection = _create_sqlite_connection(self.config.db_path)
+ cur = connection.cursor()
+ try:
+ cur.execute(
+ "UPDATE openai_vector_store_files SET metadata = ? WHERE store_id = ? AND file_id = ?",
+ (json.dumps(file_info), store_id, file_id),
+ )
+ connection.commit()
+ finally:
+ cur.close()
+ connection.close()
+
+ await asyncio.to_thread(_update)
+
+ async def _delete_openai_vector_store_file_from_storage(self, store_id: str, file_id: str) -> None:
+ """Delete vector store file metadata from SQLite database."""
+
+ def _delete():
+ connection = _create_sqlite_connection(self.config.db_path)
+ cur = connection.cursor()
+ try:
+ cur.execute(
+ "DELETE FROM openai_vector_store_files WHERE store_id = ? AND file_id = ?", (store_id, file_id)
+ )
+ connection.commit()
+ finally:
+ cur.close()
+ connection.close()
+
+ await asyncio.to_thread(_delete)
+
async def insert_chunks(self, vector_db_id: str, chunks: list[Chunk], ttl_seconds: int | None = None) -> None:
if vector_db_id not in self.cache:
raise ValueError(f"Vector DB {vector_db_id} not found. Found: {list(self.cache.keys())}")
diff --git a/llama_stack/providers/remote/vector_io/chroma/chroma.py b/llama_stack/providers/remote/vector_io/chroma/chroma.py
index 12c1b5022..cb9e49409 100644
--- a/llama_stack/providers/remote/vector_io/chroma/chroma.py
+++ b/llama_stack/providers/remote/vector_io/chroma/chroma.py
@@ -24,7 +24,11 @@ from llama_stack.apis.vector_io import (
VectorStoreObject,
VectorStoreSearchResponsePage,
)
-from llama_stack.apis.vector_io.vector_io import VectorStoreChunkingStrategy, VectorStoreFileObject
+from llama_stack.apis.vector_io.vector_io import (
+ VectorStoreChunkingStrategy,
+ VectorStoreFileObject,
+ VectorStoreListFilesResponse,
+)
from llama_stack.providers.datatypes import Api, VectorDBsProtocolPrivate
from llama_stack.providers.inline.vector_io.chroma import ChromaVectorIOConfig as InlineChromaVectorIOConfig
from llama_stack.providers.utils.memory.vector_store import (
@@ -263,3 +267,31 @@ class ChromaVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
chunking_strategy: VectorStoreChunkingStrategy | None = None,
) -> VectorStoreFileObject:
raise NotImplementedError("OpenAI Vector Stores API is not supported in Chroma")
+
+ async def openai_list_files_in_vector_store(
+ self,
+ vector_store_id: str,
+ ) -> VectorStoreListFilesResponse:
+ raise NotImplementedError("OpenAI Vector Stores API is not supported in Chroma")
+
+ async def openai_retrieve_vector_store_file(
+ self,
+ vector_store_id: str,
+ file_id: str,
+ ) -> VectorStoreFileObject:
+ raise NotImplementedError("OpenAI Vector Stores API is not supported in Chroma")
+
+ async def openai_update_vector_store_file(
+ self,
+ vector_store_id: str,
+ file_id: str,
+ attributes: dict[str, Any] | None = None,
+ ) -> VectorStoreFileObject:
+ raise NotImplementedError("OpenAI Vector Stores API is not supported in Chroma")
+
+ async def openai_delete_vector_store_file(
+ self,
+ vector_store_id: str,
+ file_id: str,
+ ) -> VectorStoreFileObject:
+ raise NotImplementedError("OpenAI Vector Stores API is not supported in Chroma")
diff --git a/llama_stack/providers/remote/vector_io/milvus/milvus.py b/llama_stack/providers/remote/vector_io/milvus/milvus.py
index 31a9535db..830b80bf1 100644
--- a/llama_stack/providers/remote/vector_io/milvus/milvus.py
+++ b/llama_stack/providers/remote/vector_io/milvus/milvus.py
@@ -26,7 +26,11 @@ from llama_stack.apis.vector_io import (
VectorStoreObject,
VectorStoreSearchResponsePage,
)
-from llama_stack.apis.vector_io.vector_io import VectorStoreChunkingStrategy, VectorStoreFileObject
+from llama_stack.apis.vector_io.vector_io import (
+ VectorStoreChunkingStrategy,
+ VectorStoreFileObject,
+ VectorStoreListFilesResponse,
+)
from llama_stack.providers.datatypes import Api, VectorDBsProtocolPrivate
from llama_stack.providers.inline.vector_io.milvus import MilvusVectorIOConfig as InlineMilvusVectorIOConfig
from llama_stack.providers.utils.memory.vector_store import (
@@ -262,6 +266,34 @@ class MilvusVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
) -> VectorStoreFileObject:
raise NotImplementedError("OpenAI Vector Stores API is not supported in Milvus")
+ async def openai_list_files_in_vector_store(
+ self,
+ vector_store_id: str,
+ ) -> VectorStoreListFilesResponse:
+ raise NotImplementedError("OpenAI Vector Stores API is not supported in Milvus")
+
+ async def openai_retrieve_vector_store_file(
+ self,
+ vector_store_id: str,
+ file_id: str,
+ ) -> VectorStoreFileObject:
+ raise NotImplementedError("OpenAI Vector Stores API is not supported in Milvus")
+
+ async def openai_update_vector_store_file(
+ self,
+ vector_store_id: str,
+ file_id: str,
+ attributes: dict[str, Any] | None = None,
+ ) -> VectorStoreFileObject:
+ raise NotImplementedError("OpenAI Vector Stores API is not supported in Milvus")
+
+ async def openai_delete_vector_store_file(
+ self,
+ vector_store_id: str,
+ file_id: str,
+ ) -> VectorStoreFileObject:
+ raise NotImplementedError("OpenAI Vector Stores API is not supported in Milvus")
+
def generate_chunk_id(document_id: str, chunk_text: str) -> str:
"""Generate a unique chunk ID using a hash of document ID and chunk text."""
diff --git a/llama_stack/providers/remote/vector_io/qdrant/qdrant.py b/llama_stack/providers/remote/vector_io/qdrant/qdrant.py
index 1ebf861e2..2cf697f41 100644
--- a/llama_stack/providers/remote/vector_io/qdrant/qdrant.py
+++ b/llama_stack/providers/remote/vector_io/qdrant/qdrant.py
@@ -24,7 +24,11 @@ from llama_stack.apis.vector_io import (
VectorStoreObject,
VectorStoreSearchResponsePage,
)
-from llama_stack.apis.vector_io.vector_io import VectorStoreChunkingStrategy, VectorStoreFileObject
+from llama_stack.apis.vector_io.vector_io import (
+ VectorStoreChunkingStrategy,
+ VectorStoreFileObject,
+ VectorStoreListFilesResponse,
+)
from llama_stack.providers.datatypes import Api, VectorDBsProtocolPrivate
from llama_stack.providers.inline.vector_io.qdrant import QdrantVectorIOConfig as InlineQdrantVectorIOConfig
from llama_stack.providers.utils.memory.vector_store import (
@@ -263,3 +267,31 @@ class QdrantVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
chunking_strategy: VectorStoreChunkingStrategy | None = None,
) -> VectorStoreFileObject:
raise NotImplementedError("OpenAI Vector Stores API is not supported in Qdrant")
+
+ async def openai_list_files_in_vector_store(
+ self,
+ vector_store_id: str,
+ ) -> VectorStoreListFilesResponse:
+ raise NotImplementedError("OpenAI Vector Stores API is not supported in Qdrant")
+
+ async def openai_retrieve_vector_store_file(
+ self,
+ vector_store_id: str,
+ file_id: str,
+ ) -> VectorStoreFileObject:
+ raise NotImplementedError("OpenAI Vector Stores API is not supported in Qdrant")
+
+ async def openai_update_vector_store_file(
+ self,
+ vector_store_id: str,
+ file_id: str,
+ attributes: dict[str, Any] | None = None,
+ ) -> VectorStoreFileObject:
+ raise NotImplementedError("OpenAI Vector Stores API is not supported in Qdrant")
+
+ async def openai_delete_vector_store_file(
+ self,
+ vector_store_id: str,
+ file_id: str,
+ ) -> VectorStoreFileObject:
+ raise NotImplementedError("OpenAI Vector Stores API is not supported in Qdrant")
diff --git a/llama_stack/providers/utils/memory/openai_vector_store_mixin.py b/llama_stack/providers/utils/memory/openai_vector_store_mixin.py
index 13d2d7423..cd53c05c8 100644
--- a/llama_stack/providers/utils/memory/openai_vector_store_mixin.py
+++ b/llama_stack/providers/utils/memory/openai_vector_store_mixin.py
@@ -28,8 +28,11 @@ from llama_stack.apis.vector_io.vector_io import (
VectorStoreChunkingStrategy,
VectorStoreChunkingStrategyAuto,
VectorStoreChunkingStrategyStatic,
+ VectorStoreFileCounts,
+ VectorStoreFileDeleteResponse,
VectorStoreFileLastError,
VectorStoreFileObject,
+ VectorStoreListFilesResponse,
)
from llama_stack.providers.utils.memory.vector_store import content_from_data_and_mime_type, make_overlapped_chunks
@@ -70,6 +73,26 @@ class OpenAIVectorStoreMixin(ABC):
"""Delete vector store metadata from persistent storage."""
pass
+ @abstractmethod
+ async def _save_openai_vector_store_file(self, store_id: str, file_id: str, file_info: dict[str, Any]) -> None:
+ """Save vector store file metadata to persistent storage."""
+ pass
+
+ @abstractmethod
+ async def _load_openai_vector_store_file(self, store_id: str, file_id: str) -> dict[str, Any]:
+ """Load vector store file metadata from persistent storage."""
+ pass
+
+ @abstractmethod
+ async def _update_openai_vector_store_file(self, store_id: str, file_id: str, file_info: dict[str, Any]) -> None:
+ """Update vector store file metadata in persistent storage."""
+ pass
+
+ @abstractmethod
+ async def _delete_openai_vector_store_file_from_storage(self, store_id: str, file_id: str) -> None:
+ """Delete vector store file metadata from persistent storage."""
+ pass
+
@abstractmethod
async def register_vector_db(self, vector_db: VectorDB) -> None:
"""Register a vector database (provider-specific implementation)."""
@@ -136,18 +159,28 @@ class OpenAIVectorStoreMixin(ABC):
await self.register_vector_db(vector_db)
# Create OpenAI vector store metadata
+ status = "completed"
+ file_ids = file_ids or []
+ file_counts = VectorStoreFileCounts(
+ cancelled=0,
+ completed=len(file_ids),
+ failed=0,
+ in_progress=0,
+ total=len(file_ids),
+ )
+ # TODO: actually attach these files to the vector store...
store_info = {
"id": store_id,
"object": "vector_store",
"created_at": created_at,
"name": store_id,
"usage_bytes": 0,
- "file_counts": {},
- "status": "completed",
+ "file_counts": file_counts.model_dump(),
+ "status": status,
"expires_after": expires_after,
"expires_at": None,
"last_active_at": created_at,
- "file_ids": file_ids or [],
+ "file_ids": file_ids,
"chunking_strategy": chunking_strategy,
}
@@ -170,8 +203,8 @@ class OpenAIVectorStoreMixin(ABC):
created_at=created_at,
name=store_id,
usage_bytes=0,
- file_counts={},
- status="completed",
+ file_counts=file_counts,
+ status=status,
expires_after=expires_after,
expires_at=None,
last_active_at=created_at,
@@ -455,14 +488,20 @@ class OpenAIVectorStoreMixin(ABC):
attributes: dict[str, Any] | None = None,
chunking_strategy: VectorStoreChunkingStrategy | None = None,
) -> VectorStoreFileObject:
+ if vector_store_id not in self.openai_vector_stores:
+ raise ValueError(f"Vector store {vector_store_id} not found")
+
+ store_info = self.openai_vector_stores[vector_store_id].copy()
+
attributes = attributes or {}
chunking_strategy = chunking_strategy or VectorStoreChunkingStrategyAuto()
+ created_at = int(time.time())
vector_store_file_object = VectorStoreFileObject(
id=file_id,
attributes=attributes,
chunking_strategy=chunking_strategy,
- created_at=int(time.time()),
+ created_at=created_at,
status="in_progress",
vector_store_id=vector_store_id,
)
@@ -510,6 +549,20 @@ class OpenAIVectorStoreMixin(ABC):
vector_db_id=vector_store_id,
chunks=chunks,
)
+ vector_store_file_object.status = "completed"
+
+ # Create OpenAI vector store file metadata
+ file_info = vector_store_file_object.model_dump(exclude={"last_error"})
+
+ # Save to persistent storage (provider-specific)
+ await self._save_openai_vector_store_file(vector_store_id, file_id, file_info)
+
+ # Update in-memory cache
+ store_info["file_ids"].append(file_id)
+ store_info["file_counts"]["completed"] += 1
+ store_info["file_counts"]["total"] += 1
+ self.openai_vector_stores[vector_store_id] = store_info
+
except Exception as e:
logger.error(f"Error attaching file to vector store: {e}")
vector_store_file_object.status = "failed"
@@ -519,6 +572,84 @@ class OpenAIVectorStoreMixin(ABC):
)
return vector_store_file_object
- vector_store_file_object.status = "completed"
-
return vector_store_file_object
+
+ async def openai_list_files_in_vector_store(
+ self,
+ vector_store_id: str,
+ ) -> VectorStoreListFilesResponse:
+ """List files in a vector store."""
+
+ if vector_store_id not in self.openai_vector_stores:
+ raise ValueError(f"Vector store {vector_store_id} not found")
+
+ store_info = self.openai_vector_stores[vector_store_id]
+
+ file_objects = []
+ for file_id in store_info["file_ids"]:
+ file_info = await self._load_openai_vector_store_file(vector_store_id, file_id)
+ file_objects.append(VectorStoreFileObject(**file_info))
+
+ return VectorStoreListFilesResponse(
+ data=file_objects,
+ )
+
+ async def openai_retrieve_vector_store_file(
+ self,
+ vector_store_id: str,
+ file_id: str,
+ ) -> VectorStoreFileObject:
+ """Retrieves a vector store file."""
+ if vector_store_id not in self.openai_vector_stores:
+ raise ValueError(f"Vector store {vector_store_id} not found")
+
+ store_info = self.openai_vector_stores[vector_store_id]
+ if file_id not in store_info["file_ids"]:
+ raise ValueError(f"File {file_id} not found in vector store {vector_store_id}")
+
+ file_info = await self._load_openai_vector_store_file(vector_store_id, file_id)
+ return VectorStoreFileObject(**file_info)
+
+ async def openai_update_vector_store_file(
+ self,
+ vector_store_id: str,
+ file_id: str,
+ attributes: dict[str, Any],
+ ) -> VectorStoreFileObject:
+ """Updates a vector store file."""
+ if vector_store_id not in self.openai_vector_stores:
+ raise ValueError(f"Vector store {vector_store_id} not found")
+
+ store_info = self.openai_vector_stores[vector_store_id]
+ if file_id not in store_info["file_ids"]:
+ raise ValueError(f"File {file_id} not found in vector store {vector_store_id}")
+
+ file_info = await self._load_openai_vector_store_file(vector_store_id, file_id)
+ file_info["attributes"] = attributes
+ await self._update_openai_vector_store_file(vector_store_id, file_id, file_info)
+ return VectorStoreFileObject(**file_info)
+
+ async def openai_delete_vector_store_file(
+ self,
+ vector_store_id: str,
+ file_id: str,
+ ) -> VectorStoreFileDeleteResponse:
+ """Deletes a vector store file."""
+ if vector_store_id not in self.openai_vector_stores:
+ raise ValueError(f"Vector store {vector_store_id} not found")
+
+ store_info = self.openai_vector_stores[vector_store_id].copy()
+
+ file = await self.openai_retrieve_vector_store_file(vector_store_id, file_id)
+ await self._delete_openai_vector_store_file_from_storage(vector_store_id, file_id)
+
+ # Update in-memory cache
+ store_info["file_ids"].remove(file_id)
+ store_info["file_counts"][file.status] -= 1
+ store_info["file_counts"]["total"] -= 1
+ self.openai_vector_stores[vector_store_id] = store_info
+
+ return VectorStoreFileDeleteResponse(
+ id=file_id,
+ deleted=True,
+ )
diff --git a/tests/integration/vector_io/test_openai_vector_stores.py b/tests/integration/vector_io/test_openai_vector_stores.py
index d9c4199ed..d092c6fcd 100644
--- a/tests/integration/vector_io/test_openai_vector_stores.py
+++ b/tests/integration/vector_io/test_openai_vector_stores.py
@@ -6,8 +6,11 @@
import logging
import time
+from io import BytesIO
import pytest
+from llama_stack_client import BadRequestError, LlamaStackClient
+from openai import BadRequestError as OpenAIBadRequestError
from openai import OpenAI
from llama_stack.apis.vector_io import Chunk
@@ -73,11 +76,23 @@ def compat_client_with_empty_stores(compat_client):
logger.warning("Failed to clear vector stores")
pass
+ def clear_files():
+ try:
+ response = compat_client.files.list()
+ for file in response.data:
+ compat_client.files.delete(file_id=file.id)
+ except Exception:
+ # If the API is not available or fails, just continue
+ logger.warning("Failed to clear files")
+ pass
+
clear_vector_stores()
+ clear_files()
yield compat_client
# Clean up after the test
clear_vector_stores()
+ clear_files()
def test_openai_create_vector_store(compat_client_with_empty_stores, client_with_models):
@@ -423,3 +438,204 @@ def test_openai_vector_store_search_with_max_num_results(
assert search_response is not None
assert len(search_response.data) == 2
+
+
+def test_openai_vector_store_attach_file_response_attributes(compat_client_with_empty_stores, client_with_models):
+ """Test OpenAI vector store attach file."""
+ skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
+
+ if isinstance(compat_client_with_empty_stores, LlamaStackClient):
+ pytest.skip("Vector Store Files attach is not yet supported with LlamaStackClient")
+
+ compat_client = compat_client_with_empty_stores
+
+ # Create a vector store
+ vector_store = compat_client.vector_stores.create(name="test_store")
+
+ # Create a file
+ test_content = b"This is a test file"
+ with BytesIO(test_content) as file_buffer:
+ file_buffer.name = "openai_test.txt"
+ file = compat_client.files.create(file=file_buffer, purpose="assistants")
+
+ # Attach the file to the vector store
+ file_attach_response = compat_client.vector_stores.files.create(
+ vector_store_id=vector_store.id,
+ file_id=file.id,
+ )
+
+ assert file_attach_response
+ assert file_attach_response.object == "vector_store.file"
+ assert file_attach_response.id == file.id
+ assert file_attach_response.vector_store_id == vector_store.id
+ assert file_attach_response.status == "completed"
+ assert file_attach_response.chunking_strategy.type == "auto"
+ assert file_attach_response.created_at > 0
+ assert not file_attach_response.last_error
+
+ updated_vector_store = compat_client.vector_stores.retrieve(vector_store_id=vector_store.id)
+ assert updated_vector_store.file_counts.completed == 1
+ assert updated_vector_store.file_counts.total == 1
+ assert updated_vector_store.file_counts.cancelled == 0
+ assert updated_vector_store.file_counts.failed == 0
+ assert updated_vector_store.file_counts.in_progress == 0
+
+
+def test_openai_vector_store_list_files(compat_client_with_empty_stores, client_with_models):
+ """Test OpenAI vector store list files."""
+ skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
+
+ if isinstance(compat_client_with_empty_stores, LlamaStackClient):
+ pytest.skip("Vector Store Files list is not yet supported with LlamaStackClient")
+
+ compat_client = compat_client_with_empty_stores
+
+ # Create a vector store
+ vector_store = compat_client.vector_stores.create(name="test_store")
+
+ # Create some files and attach them to the vector store
+ file_ids = []
+ for i in range(3):
+ with BytesIO(f"This is a test file {i}".encode()) as file_buffer:
+ file_buffer.name = f"openai_test_{i}.txt"
+ file = compat_client.files.create(file=file_buffer, purpose="assistants")
+
+ compat_client.vector_stores.files.create(
+ vector_store_id=vector_store.id,
+ file_id=file.id,
+ )
+ file_ids.append(file.id)
+
+ files_list = compat_client.vector_stores.files.list(vector_store_id=vector_store.id)
+ assert files_list
+ assert files_list.object == "list"
+ assert files_list.data
+ assert len(files_list.data) == 3
+ assert file_ids == [file.id for file in files_list.data]
+ assert files_list.data[0].object == "vector_store.file"
+ assert files_list.data[0].vector_store_id == vector_store.id
+ assert files_list.data[0].status == "completed"
+ assert files_list.data[0].chunking_strategy.type == "auto"
+ assert files_list.data[0].created_at > 0
+ assert not files_list.data[0].last_error
+
+ updated_vector_store = compat_client.vector_stores.retrieve(vector_store_id=vector_store.id)
+ assert updated_vector_store.file_counts.completed == 3
+ assert updated_vector_store.file_counts.total == 3
+ assert updated_vector_store.file_counts.cancelled == 0
+ assert updated_vector_store.file_counts.failed == 0
+ assert updated_vector_store.file_counts.in_progress == 0
+
+
+def test_openai_vector_store_list_files_invalid_vector_store(compat_client_with_empty_stores, client_with_models):
+ """Test OpenAI vector store list files with invalid vector store ID."""
+ skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
+
+ if isinstance(compat_client_with_empty_stores, LlamaStackClient):
+ pytest.skip("Vector Store Files list is not yet supported with LlamaStackClient")
+
+ compat_client = compat_client_with_empty_stores
+
+ with pytest.raises((BadRequestError, OpenAIBadRequestError)):
+ compat_client.vector_stores.files.list(vector_store_id="abc123")
+
+
+def test_openai_vector_store_delete_file(compat_client_with_empty_stores, client_with_models):
+ """Test OpenAI vector store delete file."""
+ skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
+
+ if isinstance(compat_client_with_empty_stores, LlamaStackClient):
+ pytest.skip("Vector Store Files list is not yet supported with LlamaStackClient")
+
+ compat_client = compat_client_with_empty_stores
+
+ # Create a vector store
+ vector_store = compat_client.vector_stores.create(name="test_store")
+
+ # Create some files and attach them to the vector store
+ file_ids = []
+ for i in range(3):
+ with BytesIO(f"This is a test file {i}".encode()) as file_buffer:
+ file_buffer.name = f"openai_test_{i}.txt"
+ file = compat_client.files.create(file=file_buffer, purpose="assistants")
+
+ compat_client.vector_stores.files.create(
+ vector_store_id=vector_store.id,
+ file_id=file.id,
+ )
+ file_ids.append(file.id)
+
+ files_list = compat_client.vector_stores.files.list(vector_store_id=vector_store.id)
+ assert len(files_list.data) == 3
+
+ # Delete the first file
+ delete_response = compat_client.vector_stores.files.delete(vector_store_id=vector_store.id, file_id=file_ids[0])
+ assert delete_response
+ assert delete_response.id == file_ids[0]
+ assert delete_response.deleted is True
+ assert delete_response.object == "vector_store.file.deleted"
+
+ updated_vector_store = compat_client.vector_stores.retrieve(vector_store_id=vector_store.id)
+ assert updated_vector_store.file_counts.completed == 2
+ assert updated_vector_store.file_counts.total == 2
+ assert updated_vector_store.file_counts.cancelled == 0
+ assert updated_vector_store.file_counts.failed == 0
+ assert updated_vector_store.file_counts.in_progress == 0
+
+ # Delete the second file
+ delete_response = compat_client.vector_stores.files.delete(vector_store_id=vector_store.id, file_id=file_ids[1])
+ assert delete_response
+ assert delete_response.id == file_ids[1]
+
+ updated_vector_store = compat_client.vector_stores.retrieve(vector_store_id=vector_store.id)
+ assert updated_vector_store.file_counts.completed == 1
+ assert updated_vector_store.file_counts.total == 1
+ assert updated_vector_store.file_counts.cancelled == 0
+ assert updated_vector_store.file_counts.failed == 0
+ assert updated_vector_store.file_counts.in_progress == 0
+
+
+def test_openai_vector_store_update_file(compat_client_with_empty_stores, client_with_models):
+ """Test OpenAI vector store update file."""
+ skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
+
+ if isinstance(compat_client_with_empty_stores, LlamaStackClient):
+ pytest.skip("Vector Store Files update is not yet supported with LlamaStackClient")
+
+ compat_client = compat_client_with_empty_stores
+
+ # Create a vector store
+ vector_store = compat_client.vector_stores.create(name="test_store")
+
+ # Create a file
+ test_content = b"This is a test file"
+ with BytesIO(test_content) as file_buffer:
+ file_buffer.name = "openai_test.txt"
+ file = compat_client.files.create(file=file_buffer, purpose="assistants")
+
+ # Attach the file to the vector store
+ file_attach_response = compat_client.vector_stores.files.create(
+ vector_store_id=vector_store.id,
+ file_id=file.id,
+ attributes={"foo": "bar"},
+ )
+
+ assert file_attach_response.status == "completed"
+ assert file_attach_response.attributes["foo"] == "bar"
+
+ # Update the file's attributes
+ updated_response = compat_client.vector_stores.files.update(
+ vector_store_id=vector_store.id,
+ file_id=file.id,
+ attributes={"foo": "baz"},
+ )
+
+ assert updated_response.status == "completed"
+ assert updated_response.attributes["foo"] == "baz"
+
+ # Ensure we can retrieve the file and see the updated attributes
+ retrieved_file = compat_client.vector_stores.files.retrieve(
+ vector_store_id=vector_store.id,
+ file_id=file.id,
+ )
+ assert retrieved_file.attributes["foo"] == "baz"