.release-please-manifest.json

@@ -1,3 +1,3 @@
 {
-  ".": "1.11.1"
+  ".": "1.12.0"
 }

CHANGELOG.md

@@ -1,5 +1,31 @@
 # Changelog
 
+## 1.12.0 (2024-02-08)
+
+Full Changelog: [v1.11.1...v1.12.0](https://github.com/openai/openai-python/compare/v1.11.1...v1.12.0)
+
+### Features
+
+* **api:** add `timestamp_granularities`, add `gpt-3.5-turbo-0125` model ([#1125](https://github.com/openai/openai-python/issues/1125)) ([1ecf8f6](https://github.com/openai/openai-python/commit/1ecf8f6b12323ed09fb6a2815c85b9533ee52a50))
+* **cli/images:** add support for `--model` arg ([#1132](https://github.com/openai/openai-python/issues/1132)) ([0d53866](https://github.com/openai/openai-python/commit/0d5386615cda7cd50d5db90de2119b84dba29519))
+
+
+### Bug Fixes
+
+* remove double brackets from timestamp_granularities param ([#1140](https://github.com/openai/openai-python/issues/1140)) ([3db0222](https://github.com/openai/openai-python/commit/3db022216a81fa86470b53ec1246669bc7b17897))
+* **types:** loosen most List params types to Iterable ([#1129](https://github.com/openai/openai-python/issues/1129)) ([bdb31a3](https://github.com/openai/openai-python/commit/bdb31a3b1db6ede4e02b3c951c4fd23f70260038))
+
+
+### Chores
+
+* **internal:** add lint command ([#1128](https://github.com/openai/openai-python/issues/1128)) ([4c021c0](https://github.com/openai/openai-python/commit/4c021c0ab0151c2ec092d860c9b60e22e658cd03))
+* **internal:** support serialising iterable types ([#1127](https://github.com/openai/openai-python/issues/1127)) ([98d4e59](https://github.com/openai/openai-python/commit/98d4e59afcf2d65d4e660d91eb9462240ef5cd63))
+
+
+### Documentation
+
+* add CONTRIBUTING.md ([#1138](https://github.com/openai/openai-python/issues/1138)) ([79c8f0e](https://github.com/openai/openai-python/commit/79c8f0e8bf5470e2e31e781e8d279331e89ddfbe))
+
 ## 1.11.1 (2024-02-04)
 
 Full Changelog: [v1.11.0...v1.11.1](https://github.com/openai/openai-python/compare/v1.11.0...v1.11.1)

CONTRIBUTING.md

@@ -0,0 +1,125 @@
+## Setting up the environment
+
+### With Rye
+
+We use [Rye](https://rye-up.com/) to manage dependencies so we highly recommend [installing it](https://rye-up.com/guide/installation/) as it will automatically provision a Python environment with the expected Python version.
+
+After installing Rye, you'll just have to run this command:
+
+```sh
+$ rye sync --all-features
+```
+
+You can then run scripts using `rye run python script.py` or by activating the virtual environment:
+
+```sh
+$ rye shell
+# or manually activate - https://docs.python.org/3/library/venv.html#how-venvs-work
+$ source .venv/bin/activate
+
+# now you can omit the `rye run` prefix
+$ python script.py
+```
+
+### Without Rye
+
+Alternatively if you don't want to install `Rye`, you can stick with the standard `pip` setup by ensuring you have the Python version specified in `.python-version`, create a virtual environment however you desire and then install dependencies using this command:
+
+```sh
+$ pip install -r requirements-dev.lock
+```
+
+## Modifying/Adding code
+
+Most of the SDK is generated code, and any modified code will be overridden on the next generation. The
+`src/openai/lib/` and `examples/` directories are exceptions and will never be overridden.
+
+## Adding and running examples
+
+All files in the `examples/` directory are not modified by the Stainless generator and can be freely edited or
+added to.
+
+```bash
+# add an example to examples/<your-example>.py
+
+#!/usr/bin/env -S rye run python
+…
+```
+
+```
+chmod +x examples/<your-example>.py
+# run the example against your api
+./examples/<your-example>.py
+```
+
+## Using the repository from source
+
+If you’d like to use the repository from source, you can either install from git or link to a cloned repository:
+
+To install via git:
+
+```bash
+pip install git+ssh://git@github.com:openai/openai-python.git
+```
+
+Alternatively, you can build from source and install the wheel file:
+
+Building this package will create two files in the `dist/` directory, a `.tar.gz` containing the source files and a `.whl` that can be used to install the package efficiently.
+
+To create a distributable version of the library, all you have to do is run this command:
+
+```bash
+rye build
+# or
+python -m build
+```
+
+Then to install:
+
+```sh
+pip install ./path-to-wheel-file.whl
+```
+
+## Running tests
+
+Most tests will require you to [setup a mock server](https://github.com/stoplightio/prism) against the OpenAPI spec to run the tests.
+
+```bash
+# you will need npm installed
+npx prism path/to/your/openapi.yml
+```
+
+```bash
+rye run pytest
+```
+
+## Linting and formatting
+
+This repository uses [ruff](https://github.com/astral-sh/ruff) and
+[black](https://github.com/psf/black) to format the code in the repository.
+
+To lint:
+
+```bash
+rye run lint
+```
+
+To format and fix all ruff issues automatically:
+
+```bash
+rye run format
+```
+
+## Publishing and releases
+
+Changes made to this repository via the automated release PR pipeline should publish to PyPI automatically. If
+the changes aren't made through the automated pipeline, you may want to make releases manually.
+
+### Publish with a GitHub workflow
+
+You can release to package managers by using [the `Publish PyPI` GitHub action](https://www.github.com/openai/openai-python/actions/workflows/publish-pypi.yml). This will require a setup organization or repository secret to be set up.
+
+### Publish manually
+
+If you need to manually release a package, you can run the `bin/publish-pypi` script with an `PYPI_TOKEN` set on
+the environment.

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "openai"
-version = "1.11.1"
+version = "1.12.0"
 description = "The official Python library for the openai API"
 readme = "README.md"
 license = "Apache-2.0"
@@ -75,6 +75,10 @@ format = { chain = [
 "format:ruff" = "ruff format"
 "format:isort" = "isort ."
 
+"lint" = { chain = [
+  "check:ruff",
+  "typecheck",
+]}
 "check:ruff" = "ruff ."
 "fix:ruff" = "ruff --fix ."
 

src/openai/_utils/__init__.py

@@ -9,6 +9,7 @@
     is_mapping as is_mapping,
     is_tuple_t as is_tuple_t,
     parse_date as parse_date,
+    is_iterable as is_iterable,
     is_sequence as is_sequence,
     coerce_float as coerce_float,
     is_mapping_t as is_mapping_t,
@@ -33,6 +34,7 @@
     is_list_type as is_list_type,
     is_union_type as is_union_type,
     extract_type_arg as extract_type_arg,
+    is_iterable_type as is_iterable_type,
     is_required_type as is_required_type,
     is_annotated_type as is_annotated_type,
     strip_annotated_type as strip_annotated_type,

src/openai/_utils/_transform.py

@@ -9,11 +9,13 @@
 from ._utils import (
     is_list,
     is_mapping,
+    is_iterable,
 )
 from ._typing import (
     is_list_type,
     is_union_type,
     extract_type_arg,
+    is_iterable_type,
     is_required_type,
     is_annotated_type,
     strip_annotated_type,
@@ -157,7 +159,12 @@ def _transform_recursive(
     if is_typeddict(stripped_type) and is_mapping(data):
         return _transform_typeddict(data, stripped_type)
 
-    if is_list_type(stripped_type) and is_list(data):
+    if (
+        # List[T]
+        (is_list_type(stripped_type) and is_list(data))
+        # Iterable[T]
+        or (is_iterable_type(stripped_type) and is_iterable(data) and not isinstance(data, str))
+    ):
         inner_type = extract_type_arg(stripped_type, 0)
         return [_transform_recursive(d, annotation=annotation, inner_type=inner_type) for d in data]
 

src/openai/_utils/_typing.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
-from typing import Any, TypeVar, cast
+from typing import Any, TypeVar, Iterable, cast
+from collections import abc as _c_abc
 from typing_extensions import Required, Annotated, get_args, get_origin
 
 from .._types import InheritsGeneric
@@ -15,6 +16,12 @@ def is_list_type(typ: type) -> bool:
     return (get_origin(typ) or typ) == list
 
 
+def is_iterable_type(typ: type) -> bool:
+    """If the given type is `typing.Iterable[T]`"""
+    origin = get_origin(typ) or typ
+    return origin == Iterable or origin == _c_abc.Iterable
+
+
 def is_union_type(typ: type) -> bool:
     return _is_union(get_origin(typ))
 

src/openai/_utils/_utils.py

@@ -164,6 +164,10 @@ def is_list(obj: object) -> TypeGuard[list[object]]:
     return isinstance(obj, list)
 
 
+def is_iterable(obj: object) -> TypeGuard[Iterable[object]]:
+    return isinstance(obj, Iterable)
+
+
 def deepcopy_minimal(item: _T) -> _T:
     """Minimal reimplementation of copy.deepcopy() that will only copy certain object types:
 

src/openai/_version.py

@@ -1,4 +1,4 @@
 # File generated from our OpenAPI spec by Stainless.
 
 __title__ = "openai"
-__version__ = "1.11.1"  # x-release-please-version
+__version__ = "1.12.0"  # x-release-please-version

src/openai/cli/_api/image.py

@@ -14,13 +14,15 @@
 
 def register(subparser: _SubParsersAction[ArgumentParser]) -> None:
     sub = subparser.add_parser("images.generate")
+    sub.add_argument("-m", "--model", type=str)
     sub.add_argument("-p", "--prompt", type=str, required=True)
     sub.add_argument("-n", "--num-images", type=int, default=1)
     sub.add_argument("-s", "--size", type=str, default="1024x1024", help="Size of the output image")
     sub.add_argument("--response-format", type=str, default="url")
     sub.set_defaults(func=CLIImage.create, args_model=CLIImageCreateArgs)
 
     sub = subparser.add_parser("images.edit")
+    sub.add_argument("-m", "--model", type=str)
     sub.add_argument("-p", "--prompt", type=str, required=True)
     sub.add_argument("-n", "--num-images", type=int, default=1)
     sub.add_argument(
@@ -42,6 +44,7 @@ def register(subparser: _SubParsersAction[ArgumentParser]) -> None:
     sub.set_defaults(func=CLIImage.edit, args_model=CLIImageEditArgs)
 
     sub = subparser.add_parser("images.create_variation")
+    sub.add_argument("-m", "--model", type=str)
     sub.add_argument("-n", "--num-images", type=int, default=1)
     sub.add_argument(
         "-I",
@@ -60,13 +63,15 @@ class CLIImageCreateArgs(BaseModel):
     num_images: int
     size: str
     response_format: str
+    model: NotGivenOr[str] = NOT_GIVEN
 
 
 class CLIImageCreateVariationArgs(BaseModel):
     image: str
     num_images: int
     size: str
     response_format: str
+    model: NotGivenOr[str] = NOT_GIVEN
 
 
 class CLIImageEditArgs(BaseModel):
@@ -76,12 +81,14 @@ class CLIImageEditArgs(BaseModel):
     response_format: str
     prompt: str
     mask: NotGivenOr[str] = NOT_GIVEN
+    model: NotGivenOr[str] = NOT_GIVEN
 
 
 class CLIImage:
     @staticmethod
     def create(args: CLIImageCreateArgs) -> None:
         image = get_client().images.generate(
+            model=args.model,
             prompt=args.prompt,
             n=args.num_images,
             # casts required because the API is typed for enums
@@ -97,6 +104,7 @@ def create_variation(args: CLIImageCreateVariationArgs) -> None:
             buffer_reader = BufferReader(file_reader.read(), desc="Upload progress")
 
         image = get_client().images.create_variation(
+            model=args.model,
             image=("image", buffer_reader),
             n=args.num_images,
             # casts required because the API is typed for enums
@@ -118,6 +126,7 @@ def edit(args: CLIImageEditArgs) -> None:
                 mask = BufferReader(file_reader.read(), desc="Mask progress")
 
         image = get_client().images.edit(
+            model=args.model,
             prompt=args.prompt,
             image=("image", buffer_reader),
             n=args.num_images,

src/openai/resources/audio/transcriptions.py

@@ -2,7 +2,7 @@
 
 from __future__ import annotations
 
-from typing import Union, Mapping, cast
+from typing import List, Union, Mapping, cast
 from typing_extensions import Literal
 
 import httpx
@@ -39,6 +39,7 @@ def create(
         prompt: str | NotGiven = NOT_GIVEN,
         response_format: Literal["json", "text", "srt", "verbose_json", "vtt"] | NotGiven = NOT_GIVEN,
         temperature: float | NotGiven = NOT_GIVEN,
+        timestamp_granularities: List[Literal["word", "segment"]] | 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,
@@ -74,6 +75,10 @@ def create(
               [log probability](https://en.wikipedia.org/wiki/Log_probability) to
               automatically increase the temperature until certain thresholds are hit.
 
+          timestamp_granularities: The timestamp granularities to populate for this transcription. Any of these
+              options: `word`, or `segment`. Note: There is no additional latency for segment
+              timestamps, but generating word timestamps incurs additional latency.
+
           extra_headers: Send extra headers
 
           extra_query: Add additional query parameters to the request
@@ -90,6 +95,7 @@ def create(
                 "prompt": prompt,
                 "response_format": response_format,
                 "temperature": temperature,
+                "timestamp_granularities": timestamp_granularities,
             }
         )
         files = extract_files(cast(Mapping[str, object], body), paths=[["file"]])
@@ -127,6 +133,7 @@ async def create(
         prompt: str | NotGiven = NOT_GIVEN,
         response_format: Literal["json", "text", "srt", "verbose_json", "vtt"] | NotGiven = NOT_GIVEN,
         temperature: float | NotGiven = NOT_GIVEN,
+        timestamp_granularities: List[Literal["word", "segment"]] | 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,
@@ -162,6 +169,10 @@ async def create(
               [log probability](https://en.wikipedia.org/wiki/Log_probability) to
               automatically increase the temperature until certain thresholds are hit.
 
+          timestamp_granularities: The timestamp granularities to populate for this transcription. Any of these
+              options: `word`, or `segment`. Note: There is no additional latency for segment
+              timestamps, but generating word timestamps incurs additional latency.
+
           extra_headers: Send extra headers
 
           extra_query: Add additional query parameters to the request
@@ -178,6 +189,7 @@ async def create(
                 "prompt": prompt,
                 "response_format": response_format,
                 "temperature": temperature,
+                "timestamp_granularities": timestamp_granularities,
             }
         )
         files = extract_files(cast(Mapping[str, object], body), paths=[["file"]])