two version of R2R are here HEAD master

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diff --git a/.venv/lib/python3.12/site-packages/openai/resources/vector_stores/file_batches.py b/.venv/lib/python3.12/site-packages/openai/resources/vector_stores/file_batches.py
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+# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
+
+from __future__ import annotations
+
+import asyncio
+from typing import Dict, List, Iterable, Optional
+from typing_extensions import Union, Literal
+from concurrent.futures import Future, ThreadPoolExecutor, as_completed
+
+import httpx
+import sniffio
+
+from ... import _legacy_response
+from ...types import FileChunkingStrategyParam
+from ..._types import NOT_GIVEN, Body, Query, Headers, NotGiven, FileTypes
+from ..._utils import (
+    is_given,
+    maybe_transform,
+    async_maybe_transform,
+)
+from ..._compat import cached_property
+from ..._resource import SyncAPIResource, AsyncAPIResource
+from ..._response import to_streamed_response_wrapper, async_to_streamed_response_wrapper
+from ...pagination import SyncCursorPage, AsyncCursorPage
+from ..._base_client import AsyncPaginator, make_request_options
+from ...types.file_object import FileObject
+from ...types.vector_stores import file_batch_create_params, file_batch_list_files_params
+from ...types.file_chunking_strategy_param import FileChunkingStrategyParam
+from ...types.vector_stores.vector_store_file import VectorStoreFile
+from ...types.vector_stores.vector_store_file_batch import VectorStoreFileBatch
+
+__all__ = ["FileBatches", "AsyncFileBatches"]
+
+
+class FileBatches(SyncAPIResource):
+    @cached_property
+    def with_raw_response(self) -> FileBatchesWithRawResponse:
+        """
+        This property can be used as a prefix for any HTTP method call to return
+        the raw response object instead of the parsed content.
+
+        For more information, see https://www.github.com/openai/openai-python#accessing-raw-response-data-eg-headers
+        """
+        return FileBatchesWithRawResponse(self)
+
+    @cached_property
+    def with_streaming_response(self) -> FileBatchesWithStreamingResponse:
+        """
+        An alternative to `.with_raw_response` that doesn't eagerly read the response body.
+
+        For more information, see https://www.github.com/openai/openai-python#with_streaming_response
+        """
+        return FileBatchesWithStreamingResponse(self)
+
+    def create(
+        self,
+        vector_store_id: str,
+        *,
+        file_ids: List[str],
+        attributes: Optional[Dict[str, Union[str, float, bool]]] | NotGiven = NOT_GIVEN,
+        chunking_strategy: FileChunkingStrategyParam | NotGiven = NOT_GIVEN,
+        # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
+        # The extra values given here take precedence over values defined on the client or passed to this method.
+        extra_headers: Headers | None = None,
+        extra_query: Query | None = None,
+        extra_body: Body | None = None,
+        timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> VectorStoreFileBatch:
+        """
+        Create a vector store file batch.
+
+        Args:
+          file_ids: A list of [File](https://platform.openai.com/docs/api-reference/files) IDs that
+              the vector store should use. Useful for tools like `file_search` that can access
+              files.
+
+          attributes: Set of 16 key-value pairs that can be attached to an object. This can be useful
+              for storing additional information about the object in a structured format, and
+              querying for objects via API or the dashboard. Keys are strings with a maximum
+              length of 64 characters. Values are strings with a maximum length of 512
+              characters, booleans, or numbers.
+
+          chunking_strategy: The chunking strategy used to chunk the file(s). If not set, will use the `auto`
+              strategy. Only applicable if `file_ids` is non-empty.
+
+          extra_headers: Send extra headers
+
+          extra_query: Add additional query parameters to the request
+
+          extra_body: Add additional JSON properties to the request
+
+          timeout: Override the client-level default timeout for this request, in seconds
+        """
+        if not vector_store_id:
+            raise ValueError(f"Expected a non-empty value for `vector_store_id` but received {vector_store_id!r}")
+        extra_headers = {"OpenAI-Beta": "assistants=v2", **(extra_headers or {})}
+        return self._post(
+            f"/vector_stores/{vector_store_id}/file_batches",
+            body=maybe_transform(
+                {
+                    "file_ids": file_ids,
+                    "attributes": attributes,
+                    "chunking_strategy": chunking_strategy,
+                },
+                file_batch_create_params.FileBatchCreateParams,
+            ),
+            options=make_request_options(
+                extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
+            ),
+            cast_to=VectorStoreFileBatch,
+        )
+
+    def retrieve(
+        self,
+        batch_id: str,
+        *,
+        vector_store_id: str,
+        # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
+        # The extra values given here take precedence over values defined on the client or passed to this method.
+        extra_headers: Headers | None = None,
+        extra_query: Query | None = None,
+        extra_body: Body | None = None,
+        timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> VectorStoreFileBatch:
+        """
+        Retrieves a vector store file batch.
+
+        Args:
+          extra_headers: Send extra headers
+
+          extra_query: Add additional query parameters to the request
+
+          extra_body: Add additional JSON properties to the request
+
+          timeout: Override the client-level default timeout for this request, in seconds
+        """
+        if not vector_store_id:
+            raise ValueError(f"Expected a non-empty value for `vector_store_id` but received {vector_store_id!r}")
+        if not batch_id:
+            raise ValueError(f"Expected a non-empty value for `batch_id` but received {batch_id!r}")
+        extra_headers = {"OpenAI-Beta": "assistants=v2", **(extra_headers or {})}
+        return self._get(
+            f"/vector_stores/{vector_store_id}/file_batches/{batch_id}",
+            options=make_request_options(
+                extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
+            ),
+            cast_to=VectorStoreFileBatch,
+        )
+
+    def cancel(
+        self,
+        batch_id: str,
+        *,
+        vector_store_id: str,
+        # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
+        # The extra values given here take precedence over values defined on the client or passed to this method.
+        extra_headers: Headers | None = None,
+        extra_query: Query | None = None,
+        extra_body: Body | None = None,
+        timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> VectorStoreFileBatch:
+        """Cancel a vector store file batch.
+
+        This attempts to cancel the processing of
+        files in this batch as soon as possible.
+
+        Args:
+          extra_headers: Send extra headers
+
+          extra_query: Add additional query parameters to the request
+
+          extra_body: Add additional JSON properties to the request
+
+          timeout: Override the client-level default timeout for this request, in seconds
+        """
+        if not vector_store_id:
+            raise ValueError(f"Expected a non-empty value for `vector_store_id` but received {vector_store_id!r}")
+        if not batch_id:
+            raise ValueError(f"Expected a non-empty value for `batch_id` but received {batch_id!r}")
+        extra_headers = {"OpenAI-Beta": "assistants=v2", **(extra_headers or {})}
+        return self._post(
+            f"/vector_stores/{vector_store_id}/file_batches/{batch_id}/cancel",
+            options=make_request_options(
+                extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
+            ),
+            cast_to=VectorStoreFileBatch,
+        )
+
+    def create_and_poll(
+        self,
+        vector_store_id: str,
+        *,
+        file_ids: List[str],
+        poll_interval_ms: int | NotGiven = NOT_GIVEN,
+        chunking_strategy: FileChunkingStrategyParam | NotGiven = NOT_GIVEN,
+    ) -> VectorStoreFileBatch:
+        """Create a vector store batch and poll until all files have been processed."""
+        batch = self.create(
+            vector_store_id=vector_store_id,
+            file_ids=file_ids,
+            chunking_strategy=chunking_strategy,
+        )
+        # TODO: don't poll unless necessary??
+        return self.poll(
+            batch.id,
+            vector_store_id=vector_store_id,
+            poll_interval_ms=poll_interval_ms,
+        )
+
+    def list_files(
+        self,
+        batch_id: str,
+        *,
+        vector_store_id: str,
+        after: str | NotGiven = NOT_GIVEN,
+        before: str | NotGiven = NOT_GIVEN,
+        filter: Literal["in_progress", "completed", "failed", "cancelled"] | NotGiven = NOT_GIVEN,
+        limit: int | NotGiven = NOT_GIVEN,
+        order: Literal["asc", "desc"] | NotGiven = NOT_GIVEN,
+        # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
+        # The extra values given here take precedence over values defined on the client or passed to this method.
+        extra_headers: Headers | None = None,
+        extra_query: Query | None = None,
+        extra_body: Body | None = None,
+        timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> SyncCursorPage[VectorStoreFile]:
+        """
+        Returns a list of vector store files in a batch.
+
+        Args:
+          after: A cursor for use in pagination. `after` is an object ID that defines your place
+              in the list. For instance, if you make a list request and receive 100 objects,
+              ending with obj_foo, your subsequent call can include after=obj_foo in order to
+              fetch the next page of the list.
+
+          before: A cursor for use in pagination. `before` is an object ID that defines your place
+              in the list. For instance, if you make a list request and receive 100 objects,
+              starting with obj_foo, your subsequent call can include before=obj_foo in order
+              to fetch the previous page of the list.
+
+          filter: Filter by file status. One of `in_progress`, `completed`, `failed`, `cancelled`.
+
+          limit: A limit on the number of objects to be returned. Limit can range between 1 and
+              100, and the default is 20.
+
+          order: Sort order by the `created_at` timestamp of the objects. `asc` for ascending
+              order and `desc` for descending order.
+
+          extra_headers: Send extra headers
+
+          extra_query: Add additional query parameters to the request
+
+          extra_body: Add additional JSON properties to the request
+
+          timeout: Override the client-level default timeout for this request, in seconds
+        """
+        if not vector_store_id:
+            raise ValueError(f"Expected a non-empty value for `vector_store_id` but received {vector_store_id!r}")
+        if not batch_id:
+            raise ValueError(f"Expected a non-empty value for `batch_id` but received {batch_id!r}")
+        extra_headers = {"OpenAI-Beta": "assistants=v2", **(extra_headers or {})}
+        return self._get_api_list(
+            f"/vector_stores/{vector_store_id}/file_batches/{batch_id}/files",
+            page=SyncCursorPage[VectorStoreFile],
+            options=make_request_options(
+                extra_headers=extra_headers,
+                extra_query=extra_query,
+                extra_body=extra_body,
+                timeout=timeout,
+                query=maybe_transform(
+                    {
+                        "after": after,
+                        "before": before,
+                        "filter": filter,
+                        "limit": limit,
+                        "order": order,
+                    },
+                    file_batch_list_files_params.FileBatchListFilesParams,
+                ),
+            ),
+            model=VectorStoreFile,
+        )
+
+    def poll(
+        self,
+        batch_id: str,
+        *,
+        vector_store_id: str,
+        poll_interval_ms: int | NotGiven = NOT_GIVEN,
+    ) -> VectorStoreFileBatch:
+        """Wait for the given file batch to be processed.
+
+        Note: this will return even if one of the files failed to process, you need to
+        check batch.file_counts.failed_count to handle this case.
+        """
+        headers: dict[str, str] = {"X-Stainless-Poll-Helper": "true"}
+        if is_given(poll_interval_ms):
+            headers["X-Stainless-Custom-Poll-Interval"] = str(poll_interval_ms)
+
+        while True:
+            response = self.with_raw_response.retrieve(
+                batch_id,
+                vector_store_id=vector_store_id,
+                extra_headers=headers,
+            )
+
+            batch = response.parse()
+            if batch.file_counts.in_progress > 0:
+                if not is_given(poll_interval_ms):
+                    from_header = response.headers.get("openai-poll-after-ms")
+                    if from_header is not None:
+                        poll_interval_ms = int(from_header)
+                    else:
+                        poll_interval_ms = 1000
+
+                self._sleep(poll_interval_ms / 1000)
+                continue
+
+            return batch
+
+    def upload_and_poll(
+        self,
+        vector_store_id: str,
+        *,
+        files: Iterable[FileTypes],
+        max_concurrency: int = 5,
+        file_ids: List[str] = [],
+        poll_interval_ms: int | NotGiven = NOT_GIVEN,
+        chunking_strategy: FileChunkingStrategyParam | NotGiven = NOT_GIVEN,
+    ) -> VectorStoreFileBatch:
+        """Uploads the given files concurrently and then creates a vector store file batch.
+
+        If you've already uploaded certain files that you want to include in this batch
+        then you can pass their IDs through the `file_ids` argument.
+
+        By default, if any file upload fails then an exception will be eagerly raised.
+
+        The number of concurrency uploads is configurable using the `max_concurrency`
+        parameter.
+
+        Note: this method only supports `asyncio` or `trio` as the backing async
+        runtime.
+        """
+        results: list[FileObject] = []
+
+        with ThreadPoolExecutor(max_workers=max_concurrency) as executor:
+            futures: list[Future[FileObject]] = [
+                executor.submit(
+                    self._client.files.create,
+                    file=file,
+                    purpose="assistants",
+                )
+                for file in files
+            ]
+
+        for future in as_completed(futures):
+            exc = future.exception()
+            if exc:
+                raise exc
+
+            results.append(future.result())
+
+        batch = self.create_and_poll(
+            vector_store_id=vector_store_id,
+            file_ids=[*file_ids, *(f.id for f in results)],
+            poll_interval_ms=poll_interval_ms,
+            chunking_strategy=chunking_strategy,
+        )
+        return batch
+
+
+class AsyncFileBatches(AsyncAPIResource):
+    @cached_property
+    def with_raw_response(self) -> AsyncFileBatchesWithRawResponse:
+        """
+        This property can be used as a prefix for any HTTP method call to return
+        the raw response object instead of the parsed content.
+
+        For more information, see https://www.github.com/openai/openai-python#accessing-raw-response-data-eg-headers
+        """
+        return AsyncFileBatchesWithRawResponse(self)
+
+    @cached_property
+    def with_streaming_response(self) -> AsyncFileBatchesWithStreamingResponse:
+        """
+        An alternative to `.with_raw_response` that doesn't eagerly read the response body.
+
+        For more information, see https://www.github.com/openai/openai-python#with_streaming_response
+        """
+        return AsyncFileBatchesWithStreamingResponse(self)
+
+    async def create(
+        self,
+        vector_store_id: str,
+        *,
+        file_ids: List[str],
+        attributes: Optional[Dict[str, Union[str, float, bool]]] | NotGiven = NOT_GIVEN,
+        chunking_strategy: FileChunkingStrategyParam | NotGiven = NOT_GIVEN,
+        # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
+        # The extra values given here take precedence over values defined on the client or passed to this method.
+        extra_headers: Headers | None = None,
+        extra_query: Query | None = None,
+        extra_body: Body | None = None,
+        timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> VectorStoreFileBatch:
+        """
+        Create a vector store file batch.
+
+        Args:
+          file_ids: A list of [File](https://platform.openai.com/docs/api-reference/files) IDs that
+              the vector store should use. Useful for tools like `file_search` that can access
+              files.
+
+          attributes: Set of 16 key-value pairs that can be attached to an object. This can be useful
+              for storing additional information about the object in a structured format, and
+              querying for objects via API or the dashboard. Keys are strings with a maximum
+              length of 64 characters. Values are strings with a maximum length of 512
+              characters, booleans, or numbers.
+
+          chunking_strategy: The chunking strategy used to chunk the file(s). If not set, will use the `auto`
+              strategy. Only applicable if `file_ids` is non-empty.
+
+          extra_headers: Send extra headers
+
+          extra_query: Add additional query parameters to the request
+
+          extra_body: Add additional JSON properties to the request
+
+          timeout: Override the client-level default timeout for this request, in seconds
+        """
+        if not vector_store_id:
+            raise ValueError(f"Expected a non-empty value for `vector_store_id` but received {vector_store_id!r}")
+        extra_headers = {"OpenAI-Beta": "assistants=v2", **(extra_headers or {})}
+        return await self._post(
+            f"/vector_stores/{vector_store_id}/file_batches",
+            body=await async_maybe_transform(
+                {
+                    "file_ids": file_ids,
+                    "attributes": attributes,
+                    "chunking_strategy": chunking_strategy,
+                },
+                file_batch_create_params.FileBatchCreateParams,
+            ),
+            options=make_request_options(
+                extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
+            ),
+            cast_to=VectorStoreFileBatch,
+        )
+
+    async def retrieve(
+        self,
+        batch_id: str,
+        *,
+        vector_store_id: str,
+        # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
+        # The extra values given here take precedence over values defined on the client or passed to this method.
+        extra_headers: Headers | None = None,
+        extra_query: Query | None = None,
+        extra_body: Body | None = None,
+        timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> VectorStoreFileBatch:
+        """
+        Retrieves a vector store file batch.
+
+        Args:
+          extra_headers: Send extra headers
+
+          extra_query: Add additional query parameters to the request
+
+          extra_body: Add additional JSON properties to the request
+
+          timeout: Override the client-level default timeout for this request, in seconds
+        """
+        if not vector_store_id:
+            raise ValueError(f"Expected a non-empty value for `vector_store_id` but received {vector_store_id!r}")
+        if not batch_id:
+            raise ValueError(f"Expected a non-empty value for `batch_id` but received {batch_id!r}")
+        extra_headers = {"OpenAI-Beta": "assistants=v2", **(extra_headers or {})}
+        return await self._get(
+            f"/vector_stores/{vector_store_id}/file_batches/{batch_id}",
+            options=make_request_options(
+                extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
+            ),
+            cast_to=VectorStoreFileBatch,
+        )
+
+    async def cancel(
+        self,
+        batch_id: str,
+        *,
+        vector_store_id: str,
+        # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
+        # The extra values given here take precedence over values defined on the client or passed to this method.
+        extra_headers: Headers | None = None,
+        extra_query: Query | None = None,
+        extra_body: Body | None = None,
+        timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> VectorStoreFileBatch:
+        """Cancel a vector store file batch.
+
+        This attempts to cancel the processing of
+        files in this batch as soon as possible.
+
+        Args:
+          extra_headers: Send extra headers
+
+          extra_query: Add additional query parameters to the request
+
+          extra_body: Add additional JSON properties to the request
+
+          timeout: Override the client-level default timeout for this request, in seconds
+        """
+        if not vector_store_id:
+            raise ValueError(f"Expected a non-empty value for `vector_store_id` but received {vector_store_id!r}")
+        if not batch_id:
+            raise ValueError(f"Expected a non-empty value for `batch_id` but received {batch_id!r}")
+        extra_headers = {"OpenAI-Beta": "assistants=v2", **(extra_headers or {})}
+        return await self._post(
+            f"/vector_stores/{vector_store_id}/file_batches/{batch_id}/cancel",
+            options=make_request_options(
+                extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
+            ),
+            cast_to=VectorStoreFileBatch,
+        )
+
+    async def create_and_poll(
+        self,
+        vector_store_id: str,
+        *,
+        file_ids: List[str],
+        poll_interval_ms: int | NotGiven = NOT_GIVEN,
+        chunking_strategy: FileChunkingStrategyParam | NotGiven = NOT_GIVEN,
+    ) -> VectorStoreFileBatch:
+        """Create a vector store batch and poll until all files have been processed."""
+        batch = await self.create(
+            vector_store_id=vector_store_id,
+            file_ids=file_ids,
+            chunking_strategy=chunking_strategy,
+        )
+        # TODO: don't poll unless necessary??
+        return await self.poll(
+            batch.id,
+            vector_store_id=vector_store_id,
+            poll_interval_ms=poll_interval_ms,
+        )
+
+    def list_files(
+        self,
+        batch_id: str,
+        *,
+        vector_store_id: str,
+        after: str | NotGiven = NOT_GIVEN,
+        before: str | NotGiven = NOT_GIVEN,
+        filter: Literal["in_progress", "completed", "failed", "cancelled"] | NotGiven = NOT_GIVEN,
+        limit: int | NotGiven = NOT_GIVEN,
+        order: Literal["asc", "desc"] | NotGiven = NOT_GIVEN,
+        # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
+        # The extra values given here take precedence over values defined on the client or passed to this method.
+        extra_headers: Headers | None = None,
+        extra_query: Query | None = None,
+        extra_body: Body | None = None,
+        timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> AsyncPaginator[VectorStoreFile, AsyncCursorPage[VectorStoreFile]]:
+        """
+        Returns a list of vector store files in a batch.
+
+        Args:
+          after: A cursor for use in pagination. `after` is an object ID that defines your place
+              in the list. For instance, if you make a list request and receive 100 objects,
+              ending with obj_foo, your subsequent call can include after=obj_foo in order to
+              fetch the next page of the list.
+
+          before: A cursor for use in pagination. `before` is an object ID that defines your place
+              in the list. For instance, if you make a list request and receive 100 objects,
+              starting with obj_foo, your subsequent call can include before=obj_foo in order
+              to fetch the previous page of the list.
+
+          filter: Filter by file status. One of `in_progress`, `completed`, `failed`, `cancelled`.
+
+          limit: A limit on the number of objects to be returned. Limit can range between 1 and
+              100, and the default is 20.
+
+          order: Sort order by the `created_at` timestamp of the objects. `asc` for ascending
+              order and `desc` for descending order.
+
+          extra_headers: Send extra headers
+
+          extra_query: Add additional query parameters to the request
+
+          extra_body: Add additional JSON properties to the request
+
+          timeout: Override the client-level default timeout for this request, in seconds
+        """
+        if not vector_store_id:
+            raise ValueError(f"Expected a non-empty value for `vector_store_id` but received {vector_store_id!r}")
+        if not batch_id:
+            raise ValueError(f"Expected a non-empty value for `batch_id` but received {batch_id!r}")
+        extra_headers = {"OpenAI-Beta": "assistants=v2", **(extra_headers or {})}
+        return self._get_api_list(
+            f"/vector_stores/{vector_store_id}/file_batches/{batch_id}/files",
+            page=AsyncCursorPage[VectorStoreFile],
+            options=make_request_options(
+                extra_headers=extra_headers,
+                extra_query=extra_query,
+                extra_body=extra_body,
+                timeout=timeout,
+                query=maybe_transform(
+                    {
+                        "after": after,
+                        "before": before,
+                        "filter": filter,
+                        "limit": limit,
+                        "order": order,
+                    },
+                    file_batch_list_files_params.FileBatchListFilesParams,
+                ),
+            ),
+            model=VectorStoreFile,
+        )
+
+    async def poll(
+        self,
+        batch_id: str,
+        *,
+        vector_store_id: str,
+        poll_interval_ms: int | NotGiven = NOT_GIVEN,
+    ) -> VectorStoreFileBatch:
+        """Wait for the given file batch to be processed.
+
+        Note: this will return even if one of the files failed to process, you need to
+        check batch.file_counts.failed_count to handle this case.
+        """
+        headers: dict[str, str] = {"X-Stainless-Poll-Helper": "true"}
+        if is_given(poll_interval_ms):
+            headers["X-Stainless-Custom-Poll-Interval"] = str(poll_interval_ms)
+
+        while True:
+            response = await self.with_raw_response.retrieve(
+                batch_id,
+                vector_store_id=vector_store_id,
+                extra_headers=headers,
+            )
+
+            batch = response.parse()
+            if batch.file_counts.in_progress > 0:
+                if not is_given(poll_interval_ms):
+                    from_header = response.headers.get("openai-poll-after-ms")
+                    if from_header is not None:
+                        poll_interval_ms = int(from_header)
+                    else:
+                        poll_interval_ms = 1000
+
+                await self._sleep(poll_interval_ms / 1000)
+                continue
+
+            return batch
+
+    async def upload_and_poll(
+        self,
+        vector_store_id: str,
+        *,
+        files: Iterable[FileTypes],
+        max_concurrency: int = 5,
+        file_ids: List[str] = [],
+        poll_interval_ms: int | NotGiven = NOT_GIVEN,
+        chunking_strategy: FileChunkingStrategyParam | NotGiven = NOT_GIVEN,
+    ) -> VectorStoreFileBatch:
+        """Uploads the given files concurrently and then creates a vector store file batch.
+
+        If you've already uploaded certain files that you want to include in this batch
+        then you can pass their IDs through the `file_ids` argument.
+
+        By default, if any file upload fails then an exception will be eagerly raised.
+
+        The number of concurrency uploads is configurable using the `max_concurrency`
+        parameter.
+
+        Note: this method only supports `asyncio` or `trio` as the backing async
+        runtime.
+        """
+        uploaded_files: list[FileObject] = []
+
+        async_library = sniffio.current_async_library()
+
+        if async_library == "asyncio":
+
+            async def asyncio_upload_file(semaphore: asyncio.Semaphore, file: FileTypes) -> None:
+                async with semaphore:
+                    file_obj = await self._client.files.create(
+                        file=file,
+                        purpose="assistants",
+                    )
+                    uploaded_files.append(file_obj)
+
+            semaphore = asyncio.Semaphore(max_concurrency)
+
+            tasks = [asyncio_upload_file(semaphore, file) for file in files]
+
+            await asyncio.gather(*tasks)
+        elif async_library == "trio":
+            # We only import if the library is being used.
+            # We support Python 3.7 so are using an older version of trio that does not have type information
+            import trio  # type: ignore # pyright: ignore[reportMissingTypeStubs]
+
+            async def trio_upload_file(limiter: trio.CapacityLimiter, file: FileTypes) -> None:
+                async with limiter:
+                    file_obj = await self._client.files.create(
+                        file=file,
+                        purpose="assistants",
+                    )
+                    uploaded_files.append(file_obj)
+
+            limiter = trio.CapacityLimiter(max_concurrency)
+
+            async with trio.open_nursery() as nursery:
+                for file in files:
+                    nursery.start_soon(trio_upload_file, limiter, file)  # pyright: ignore [reportUnknownMemberType]
+        else:
+            raise RuntimeError(
+                f"Async runtime {async_library} is not supported yet. Only asyncio or trio is supported",
+            )
+
+        batch = await self.create_and_poll(
+            vector_store_id=vector_store_id,
+            file_ids=[*file_ids, *(f.id for f in uploaded_files)],
+            poll_interval_ms=poll_interval_ms,
+            chunking_strategy=chunking_strategy,
+        )
+        return batch
+
+
+class FileBatchesWithRawResponse:
+    def __init__(self, file_batches: FileBatches) -> None:
+        self._file_batches = file_batches
+
+        self.create = _legacy_response.to_raw_response_wrapper(
+            file_batches.create,
+        )
+        self.retrieve = _legacy_response.to_raw_response_wrapper(
+            file_batches.retrieve,
+        )
+        self.cancel = _legacy_response.to_raw_response_wrapper(
+            file_batches.cancel,
+        )
+        self.list_files = _legacy_response.to_raw_response_wrapper(
+            file_batches.list_files,
+        )
+
+
+class AsyncFileBatchesWithRawResponse:
+    def __init__(self, file_batches: AsyncFileBatches) -> None:
+        self._file_batches = file_batches
+
+        self.create = _legacy_response.async_to_raw_response_wrapper(
+            file_batches.create,
+        )
+        self.retrieve = _legacy_response.async_to_raw_response_wrapper(
+            file_batches.retrieve,
+        )
+        self.cancel = _legacy_response.async_to_raw_response_wrapper(
+            file_batches.cancel,
+        )
+        self.list_files = _legacy_response.async_to_raw_response_wrapper(
+            file_batches.list_files,
+        )
+
+
+class FileBatchesWithStreamingResponse:
+    def __init__(self, file_batches: FileBatches) -> None:
+        self._file_batches = file_batches
+
+        self.create = to_streamed_response_wrapper(
+            file_batches.create,
+        )
+        self.retrieve = to_streamed_response_wrapper(
+            file_batches.retrieve,
+        )
+        self.cancel = to_streamed_response_wrapper(
+            file_batches.cancel,
+        )
+        self.list_files = to_streamed_response_wrapper(
+            file_batches.list_files,
+        )
+
+
+class AsyncFileBatchesWithStreamingResponse:
+    def __init__(self, file_batches: AsyncFileBatches) -> None:
+        self._file_batches = file_batches
+
+        self.create = async_to_streamed_response_wrapper(
+            file_batches.create,
+        )
+        self.retrieve = async_to_streamed_response_wrapper(
+            file_batches.retrieve,
+        )
+        self.cancel = async_to_streamed_response_wrapper(
+            file_batches.cancel,
+        )
+        self.list_files = async_to_streamed_response_wrapper(
+            file_batches.list_files,
+        )