Fix typos (#437)

* update_time defined twice hence removing once.

* removed redundant parentheses from some test cases

* removed multi-step list initialization

* Removed unused import

* Revert "Removed unused import"

This reverts commit d1e6012.

* fix black issue

* fix typos

google/generativeai/answer.py

@@ -82,7 +82,7 @@ def to_answer_style(x: AnswerStyleOptions) -> AnswerStyle:
 def _make_grounding_passages(source: GroundingPassagesOptions) -> protos.GroundingPassages:
  """
  Converts the `source` into a `protos.GroundingPassage`. A `GroundingPassages` contains a list of
- `protos.GroundingPassage` objects, which each contain a `protos.Contant` and a string `id`.
+ `protos.GroundingPassage` objects, which each contain a `protos.Content` and a string `id`.
 
  Args:
  source: `Content` or a `GroundingPassagesOptions` that will be converted to protos.GroundingPassages.
@@ -191,7 +191,7 @@ def _make_generate_answer_request(
  single question to answer. For multi-turn queries, this is a repeated field that contains
  conversation history and the last `Content` in the list containing the question.
  inline_passages: Grounding passages (a list of `Content`-like objects or `(id, content)` pairs,
- or a `protos.GroundingPassages`) to send inline with the request. Exclusive with `semantic_retreiver`,
+ or a `protos.GroundingPassages`) to send inline with the request. Exclusive with `semantic_retriever`,
  one must be set, but not both.
  semantic_retriever: A Corpus, Document, or `protos.SemanticRetrieverConfig` to use for grounding. Exclusive with
  `inline_passages`, one must be set, but not both.
@@ -267,7 +267,7 @@ def generate_answer(
  >>> my_corpus = retriever.get_corpus('my_corpus')
  >>> genai.generate_answer(
  ... content=question,
- ... semantic_retreiver=my_corpus
+ ... semantic_retriever=my_corpus
  ... )
 
 
@@ -276,7 +276,7 @@ def generate_answer(
  contents: The question to be answered by the model, grounded in the
  provided source.
  inline_passages: Grounding passages (a list of `Content`-like objects or (id, content) pairs,
- or a `protos.GroundingPassages`) to send inline with the request. Exclusive with `semantic_retreiver`,
+ or a `protos.GroundingPassages`) to send inline with the request. Exclusive with `semantic_retriever`,
  one must be set, but not both.
  semantic_retriever: A Corpus, Document, or `protos.SemanticRetrieverConfig` to use for grounding. Exclusive with
  `inline_passages`, one must be set, but not both.
@@ -330,7 +330,7 @@ async def generate_answer_async(
  contents: The question to be answered by the model, grounded in the
  provided source.
  inline_passages: Grounding passages (a list of `Content`-like objects or (id, content) pairs,
- or a `protos.GroundingPassages`) to send inline with the request. Exclusive with `semantic_retreiver`,
+ or a `protos.GroundingPassages`) to send inline with the request. Exclusive with `semantic_retriever`,
  one must be set, but not both.
  semantic_retriever: A Corpus, Document, or `protos.SemanticRetrieverConfig` to use for grounding. Exclusive with
  `inline_passages`, one must be set, but not both.

google/generativeai/generative_models.py

@@ -139,7 +139,7 @@ def _prepare_request(
  """Creates a `protos.GenerateContentRequest` from raw inputs."""
  if hasattr(self, "_cached_content") and any([self._system_instruction, tools, tool_config]):
  raise ValueError(
- "`tools`, `tool_config`, `system_instruction` cannot be set on a model instantinated with `cached_content` as its context."
+ "`tools`, `tool_config`, `system_instruction` cannot be set on a model instantiated with `cached_content` as its context."
  )
 
  tools_lib = self._get_tools_lib(tools)

google/generativeai/models.py

@@ -397,7 +397,7 @@ def update_tuned_model(
  client: glm.ModelServiceClient | None = None,
  request_options: helper_types.RequestOptionsType | None = None,
 ) -> model_types.TunedModel:
- """Calls the API to puch updates to a specified tuned model where only certain attributes are updatable."""
+ """Calls the API to push updates to a specified tuned model where only certain attributes are updatable."""
 
  if request_options is None:
  request_options = {}

google/generativeai/notebook/flag_def.py

@@ -160,7 +160,7 @@ def _has_non_default_value(
 
  Args:
  namespace: The Namespace that is populated by ArgumentParser.
- dest: The attribute in the Namespacde to be populated.
+ dest: The attribute in the Namespace to be populated.
  has_default: "None" is a valid default value so we use an additional
  `has_default` boolean to indicate that `default_value` is present.
  default_value: The default value to use when `has_default` is True.

google/generativeai/notebook/lib/llmfn_post_process_cmds.py

@@ -29,7 +29,7 @@
 def _convert_view_to_output_row(
  row: llmfn_output_row.LLMFnOutputRowView,
 ) -> llmfn_output_row.LLMFnOutputRow:
- """Convenience method to conert a LLMFnOutputRowView to LLMFnOutputRow.
+ """Convenience method to convert a LLMFnOutputRowView to LLMFnOutputRow.
 
  If `row` is already a LLMFnOutputRow, return as-is for efficiency.
  This could potentially break encapsulation as it could let code to modify

google/generativeai/types/retriever_types.py

@@ -1235,7 +1235,7 @@ def batch_update_chunks(
  Update multiple chunks within the same document.
 
  Args:
- chunks: Data structure specifying which `Chunk`s to update and what the required updats are.
+ chunks: Data structure specifying which `Chunk`s to update and what the required updates are.
  request_options: Options for the request.
 
  Return: