Fix pytype (#39)

* Squashed commit of the following:

commit de62d09
Author: Mark Daoust <[email protected]>
Date:   Tue Jun 6 17:26:10 2023 -0700

    Revert discuss types (tests failing with 3.9).

commit 7e2ccd8
Author: Mark Daoust <[email protected]>
Date:   Fri Jun 2 13:59:38 2023 -0700

    format

commit 70cc6d5
Author: Mark Daoust <[email protected]>
Date:   Fri Jun 2 13:47:20 2023 -0700

    Add future annotations for py3.9

commit d74f436
Author: Mark Daoust <[email protected]>
Date:   Fri Jun 2 13:30:54 2023 -0700

    Update Unions

commit 4d2e710
Author: Mark Daoust <[email protected]>
Date:   Fri Jun 2 13:23:37 2023 -0700

    Update Unions

commit 3d93a3e
Author: Mark Daoust <[email protected]>
Date:   Thu Jun 1 15:49:15 2023 -0700

    Pytype passes with python 3.10

    + modernize some annotations

* Debug: revert to Union for non-lazy annotations

* format

Author: MarkDaoust

google/generativeai/__init__.py

@@ -65,6 +65,7 @@
 ```
 
 """
+from __future__ import annotations
 
 from google.generativeai import types
 from google.generativeai import version

google/generativeai/client.py

@@ -12,6 +12,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+from __future__ import annotations
 
 import os
 from typing import cast, Optional, Union
@@ -35,17 +36,17 @@
 
 def configure(
     *,
-    api_key: Optional[str] = None,
-    credentials: Union[ga_credentials.Credentials, dict, None] = None,
+    api_key: str | None = None,
+    credentials: ga_credentials.Credentials | dict | None = None,
     # The user can pass a string to choose `rest` or `grpc` or 'grpc_asyncio'.
     # See `_transport_registry` in `DiscussServiceClientMeta`.
     # Since the transport classes align with the client classes it wouldn't make
     # sense to accept a `Transport` object here even though the client classes can.
     # We could accept a dict since all the `Transport` classes take the same args,
     # but that seems rare. Users that need it can just switch to the low level API.
-    transport: Union[str, None] = None,
-    client_options: Union[client_options_lib.ClientOptions, dict, None] = None,
-    client_info: Optional[gapic_v1.client_info.ClientInfo] = None,
+    transport: str | None = None,
+    client_options: client_options_lib.ClientOptions | dict | None = None,
+    client_info: gapic_v1.client_info.ClientInfo | None = None,
 ):
     """Captures default client configuration.
 

google/generativeai/discuss.py

@@ -12,6 +12,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+from __future__ import annotations
 
 import dataclasses
 import sys
@@ -150,9 +151,9 @@ def _make_examples(examples: discuss_types.ExamplesOptions) -> List[glm.Example]
 def _make_message_prompt_dict(
     prompt: discuss_types.MessagePromptOptions = None,
     *,
-    context: Optional[str] = None,
-    examples: Optional[discuss_types.ExamplesOptions] = None,
-    messages: Optional[discuss_types.MessagesOptions] = None,
+    context: str | None = None,
+    examples: discuss_types.ExamplesOptions | None = None,
+    messages: discuss_types.MessagesOptions | None = None,
 ) -> glm.MessagePrompt:
     if prompt is None:
         prompt = dict(
@@ -196,9 +197,9 @@ def _make_message_prompt_dict(
 def _make_message_prompt(
     prompt: discuss_types.MessagePromptOptions = None,
     *,
-    context: Optional[str] = None,
-    examples: Optional[discuss_types.ExamplesOptions] = None,
-    messages: Optional[discuss_types.MessagesOptions] = None,
+    context: str | None = None,
+    examples: discuss_types.ExamplesOptions | None = None,
+    messages: discuss_types.MessagesOptions | None = None,
 ) -> glm.MessagePrompt:
     prompt = _make_message_prompt_dict(
         prompt=prompt, context=context, examples=examples, messages=messages
@@ -208,15 +209,15 @@ def _make_message_prompt(
 
 def _make_generate_message_request(
     *,
-    model: Optional[model_types.ModelNameOptions],
-    context: Optional[str] = None,
-    examples: Optional[discuss_types.ExamplesOptions] = None,
-    messages: Optional[discuss_types.MessagesOptions] = None,
-    temperature: Optional[float] = None,
-    candidate_count: Optional[int] = None,
-    top_p: Optional[float] = None,
-    top_k: Optional[float] = None,
-    prompt: Optional[discuss_types.MessagePromptOptions] = None,
+    model: model_types.ModelNameOptions | None,
+    context: str | None = None,
+    examples: discuss_types.ExamplesOptions | None = None,
+    messages: discuss_types.MessagesOptions | None = None,
+    temperature: float | None = None,
+    candidate_count: int | None = None,
+    top_p: float | None = None,
+    top_k: float | None = None,
+    prompt: discuss_types.MessagePromptOptions | None = None,
 ) -> glm.GenerateMessageRequest:
     model = model_types.make_model_name(model)
 
@@ -247,16 +248,16 @@ def inner(f):
 
 def chat(
     *,
-    model: Optional[model_types.ModelNameOptions] = "models/chat-bison-001",
-    context: Optional[str] = None,
-    examples: Optional[discuss_types.ExamplesOptions] = None,
-    messages: Optional[discuss_types.MessagesOptions] = None,
-    temperature: Optional[float] = None,
-    candidate_count: Optional[int] = None,
-    top_p: Optional[float] = None,
-    top_k: Optional[float] = None,
-    prompt: Optional[discuss_types.MessagePromptOptions] = None,
-    client: Optional[glm.DiscussServiceClient] = None,
+    model: model_types.ModelNameOptions | None = "models/chat-bison-001",
+    context: str | None = None,
+    examples: discuss_types.ExamplesOptions | None = None,
+    messages: discuss_types.MessagesOptions | None = None,
+    temperature: float | None = None,
+    candidate_count: int | None = None,
+    top_p: float | None = None,
+    top_k: float | None = None,
+    prompt: discuss_types.MessagePromptOptions | None = None,
+    client: glm.DiscussServiceClient | None = None,
 ) -> discuss_types.ChatResponse:
     """Calls the API and returns a `types.ChatResponse` containing the response.
 
@@ -345,16 +346,16 @@ def chat(
 @set_doc(chat.__doc__)
 async def chat_async(
     *,
-    model: Optional[model_types.ModelNameOptions] = None,
-    context: Optional[str] = None,
-    examples: Optional[discuss_types.ExamplesOptions] = None,
-    messages: Optional[discuss_types.MessagesOptions] = None,
-    temperature: Optional[float] = None,
-    candidate_count: Optional[int] = None,
-    top_p: Optional[float] = None,
-    top_k: Optional[float] = None,
-    prompt: Optional[discuss_types.MessagePromptOptions] = None,
-    client: Optional[glm.DiscussServiceAsyncClient] = None,
+    model: model_types.ModelNameOptions | None = None,
+    context: str | None = None,
+    examples: discuss_types.ExamplesOptions | None = None,
+    messages: discuss_types.MessagesOptions | None = None,
+    temperature: float | None = None,
+    candidate_count: int | None = None,
+    top_p: float | None = None,
+    top_k: float | None = None,
+    prompt: discuss_types.MessagePromptOptions | None = None,
+    client: glm.DiscussServiceAsyncClient | None = None,
 ) -> discuss_types.ChatResponse:
     request = _make_generate_message_request(
         model=model,
@@ -380,7 +381,7 @@ async def chat_async(
 @set_doc(discuss_types.ChatResponse.__doc__)
 @dataclasses.dataclass(**DATACLASS_KWARGS, init=False)
 class ChatResponse(discuss_types.ChatResponse):
-    _client: Optional[glm.DiscussServiceClient] = dataclasses.field(
+    _client: glm.DiscussServiceClient | None = dataclasses.field(
         default=lambda: None, repr=False
     )
 
@@ -390,7 +391,7 @@ def __init__(self, **kwargs):
 
     @property
     @set_doc(discuss_types.ChatResponse.last.__doc__)
-    def last(self) -> Optional[str]:
+    def last(self) -> str | None:
         if self.messages[-1]:
             return self.messages[-1]["content"]
         else:
@@ -445,7 +446,7 @@ async def reply_async(
 def _build_chat_response(
     request: glm.GenerateMessageRequest,
     response: glm.GenerateMessageResponse,
-    client: Union[glm.DiscussServiceClient, glm.DiscussServiceAsyncClient],
+    client: glm.DiscussServiceClient | glm.DiscussServiceAsyncClient,
 ) -> ChatResponse:
     request = type(request).to_dict(request)
     prompt = request.pop("prompt")
@@ -473,7 +474,7 @@ def _build_chat_response(
 
 def _generate_response(
     request: glm.GenerateMessageRequest,
-    client: Optional[glm.DiscussServiceClient] = None,
+    client: glm.DiscussServiceClient | None = None,
 ) -> ChatResponse:
     if client is None:
         client = get_default_discuss_client()
@@ -485,7 +486,7 @@ def _generate_response(
 
 async def _generate_response_async(
     request: glm.GenerateMessageRequest,
-    client: Optional[glm.DiscussServiceAsyncClient] = None,
+    client: glm.DiscussServiceAsyncClient | None = None,
 ) -> ChatResponse:
     if client is None:
         client = get_default_discuss_async_client()
@@ -498,11 +499,11 @@ async def _generate_response_async(
 def count_message_tokens(
     *,
     prompt: discuss_types.MessagePromptOptions = None,
-    context: Optional[str] = None,
-    examples: Optional[discuss_types.ExamplesOptions] = None,
-    messages: Optional[discuss_types.MessagesOptions] = None,
+    context: str | None = None,
+    examples: discuss_types.ExamplesOptions | None = None,
+    messages: discuss_types.MessagesOptions | None = None,
     model: model_types.ModelNameOptions = DEFAULT_DISCUSS_MODEL,
-    client: Optional[glm.DiscussServiceAsyncClient] = None,
+    client: glm.DiscussServiceAsyncClient | None = None,
 ):
     model = model_types.make_model_name(model)
     prompt = _make_message_prompt(

google/generativeai/docstring_utils.py

@@ -12,6 +12,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+from __future__ import annotations
 
 
 def strip_oneof(docstring):

google/generativeai/models.py

@@ -12,6 +12,8 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+from __future__ import annotations
+
 import re
 from typing import Optional, List
 
@@ -37,9 +39,9 @@ def __init__(
         self,
         *,
         page_size: int,
-        page_token: Optional[str],
+        page_token: str | None,
         models: List[model_types.Model],
-        client: Optional[glm.ModelServiceClient],
+        client: glm.ModelServiceClient | None,
     ):
         self._page_size = page_size
         self._page_token = page_token
@@ -73,7 +75,7 @@ def _list_models(page_size, page_token, client):
 
 
 def list_models(
-    *, page_size: Optional[int] = None, client: Optional[glm.ModelServiceClient] = None
+    *, page_size: int | None = None, client: glm.ModelServiceClient | None = None
 ) -> model_types.ModelsIterable:
     """Lists available models.
 

google/generativeai/notebook/__init__.py

@@ -25,7 +25,7 @@ def load_ipython_extension(ipython):
     # Since we're in an interactive environment, make the tables prettier.
     try:
         # pylint: disable-next=g-import-not-at-top
-        from google import colab
+        from google import colab  # type: ignore
 
         colab.data_table.enable_dataframe_formatter()
     except ImportError:

google/generativeai/notebook/flag_def.py

@@ -35,7 +35,7 @@
 import argparse
 import dataclasses
 import enum
-from typing import Any, Callable, Sequence, Union, Tuple
+from typing import Any, Callable, Sequence, Tuple, Union
 
 from google.generativeai.notebook.lib import llmfn_inputs_source
 from google.generativeai.notebook.lib import llmfn_outputs
@@ -49,10 +49,10 @@
 _DESTTYPES = Union[
     _PARSETYPES,
     enum.Enum,
-    Tuple[str, Callable[[str, str], Any]],  # For --compare_fn
-    Sequence[str],  # For --ground_truth
-    llmfn_inputs_source.LLMFnInputsSource,  # For --inputs
-    llmfn_outputs.LLMFnOutputsSink,  # For --outputs
+    Tuple[str, Callable[[str, str], Any]],
+    Sequence[str],  # For --compare_fn
+    llmfn_inputs_source.LLMFnInputsSource,  # For --ground_truth
+    llmfn_outputs.LLMFnOutputsSink,  # For --inputs  # For --outputs
 ]
 
 # The signature of a function that converts a command line argument from the

google/generativeai/notebook/lib/llm_function.py

@@ -17,7 +17,16 @@
 
 import abc
 import dataclasses
-from typing import AbstractSet, Any, Callable, Iterable, Mapping, Optional, Sequence
+from typing import (
+    AbstractSet,
+    Any,
+    Callable,
+    Iterable,
+    Mapping,
+    Optional,
+    Sequence,
+    Union,
+)
 
 from google.generativeai.notebook.lib import llmfn_input_utils
 from google.generativeai.notebook.lib import llmfn_output_row
@@ -117,7 +126,7 @@ def _generate_prompts(
 
 class LLMFunction(
     Callable[
-        [Optional[llmfn_input_utils.LLMFunctionInputs]],
+        [Union[llmfn_input_utils.LLMFunctionInputs, None]],
         llmfn_outputs.LLMFnOutputs,
     ],
     metaclass=abc.ABCMeta,

google/generativeai/notebook/lib/llm_function_test.py

@@ -15,7 +15,7 @@
 """Unittest for llm_function."""
 from __future__ import annotations
 
-from typing import Any, Callable, Optional, Mapping, Sequence
+from typing import Any, Callable, Mapping, Sequence
 
 from absl.testing import absltest
 from google.generativeai.notebook.lib import llm_function
@@ -61,7 +61,7 @@ class LLMFunctionBasicTest(absltest.TestCase):
 
     def _test_is_callable(
         self,
-        llm_fn: Callable[[Optional[Sequence[tuple[str, str]]]], LLMFnOutputs],
+        llm_fn: Callable[[Sequence[tuple[str, str]] | None], LLMFnOutputs],
     ) -> LLMFnOutputs:
         return llm_fn(None)
 

google/generativeai/notebook/lib/llmfn_input_utils.py

@@ -24,10 +24,7 @@
 
 _ColumnOrderValuesList = Mapping[str, Sequence[str]]
 
-LLMFunctionInputs = Union[
-    _ColumnOrderValuesList,
-    llmfn_inputs_source.LLMFnInputsSource,
-]
+LLMFunctionInputs = Union[_ColumnOrderValuesList, llmfn_inputs_source.LLMFnInputsSource]
 
 
 def _is_column_order_values_list(inputs: Any) -> bool: