feat: add Parallel Tool mode for Vertex AI

[devjn]

This PR intends to add parallel tool mode for Vertex AI.
That is done by adding new mode VERTEXAI_PARALLEL_TOOLS.

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Important

Adds VERTEXAI_PARALLEL_TOOLS mode for parallel tool processing in Vertex AI, with updates to model handling and response processing.

• Behavior:
  • Adds VERTEXAI_PARALLEL_TOOLS mode in mode.py.
  • Updates from_vertexai() in client_vertexai.py to support the new mode.
  • Implements handle_vertexai_parallel_tools() in process_response.py to process responses in parallel.
• Models:
  • Introduces VertexAIParallelBase in parallel.py for handling parallel responses.
  • Adds VertexAIParallelModel() in parallel.py to create instances of VertexAIParallelBase.
• Functions:
  • Modifies _create_vertexai_tool() in client_vertexai.py to handle multiple models.
  • Updates vertexai_process_response() in client_vertexai.py to support parallel tools.
• Misc:
  • Adds type checks in _create_gemini_json_schema() in client_vertexai.py.

^{This description was created by for c582618. It will automatically update as commits are pushed.}

[ellipsis-dev]

👍 Looks good to me! Reviewed everything up to c582618 in 1 minute and 12 seconds

More details

• Looked at 233 lines of code in 4 files
• Skipped 0 files when reviewing.
• Skipped posting 8 drafted comments based on config settings.

1. instructor/client_vertexai.py:39

• Draft comment:
  Remove the debug print statement or replace it with proper logging.

# print(f"Debug - Model list: {[model.__name__ for model in model_list]}")

• Reason this comment was not posted:
  Confidence changes required: 80%
  The debug print statement is not suitable for production code and should be removed or replaced with proper logging.

2. instructor/client_vertexai.py:30

• Draft comment:
  The type hint for models should be updated to only include BaseModel or list[BaseModel].

def _create_vertexai_tool(models: Union[BaseModel, list[BaseModel]]) -> gm.Tool:

• Reason this comment was not posted:
  Confidence changes required: 80%
  The function _create_vertexai_tool is designed to handle both single models and lists of models. However, the type hint for models includes Type, which is not necessary and could lead to confusion. The function should only accept BaseModel or list[BaseModel].

3. instructor/client_vertexai.py:104

• Draft comment:
  The type hint for model should be updated to only include BaseModel or list[BaseModel].

def vertexai_process_response(_kwargs: dict[str, Any], model: Union[BaseModel, list[BaseModel]]):

• Reason this comment was not posted:
  Confidence changes required: 80%
  The function vertexai_process_response is designed to handle both single models and lists of models. However, the type hint for model includes Type, which is not necessary and could lead to confusion. The function should only accept BaseModel or list[BaseModel].

4. instructor/client_vertexai.py:39

• Draft comment:
  Debug print statements should be removed or replaced with proper logging.

# print(f"Debug - Model list: {[model.__name__ for model in model_list]}")

• Reason this comment was not posted:
  Confidence changes required: 80%
  The function _create_vertexai_tool in instructor/client_vertexai.py has a debug print statement that should be removed or replaced with proper logging.

5. instructor/client_vertexai.py:13

• Draft comment:
  Function _create_gemini_json_schema should have a return type annotation for clarity and consistency.

def _create_gemini_json_schema(model: BaseModel) -> dict[str, Any]:

• Reason this comment was not posted:
  Confidence changes required: 80%
  The function _create_gemini_json_schema in instructor/client_vertexai.py lacks a return type annotation, which is important for clarity and consistency.

6. instructor/client_vertexai.py:30

• Draft comment:
  Function _create_vertexai_tool should have a return type annotation for clarity and consistency.

def _create_vertexai_tool(models: Union[BaseModel, list[BaseModel], Type]) -> gm.Tool:

• Reason this comment was not posted:
  Confidence changes required: 80%
  The function _create_vertexai_tool in instructor/client_vertexai.py lacks a return type annotation, which is important for clarity and consistency.

7. instructor/client_vertexai.py:104

• Draft comment:
  Function vertexai_process_response should have a return type annotation for clarity and consistency.

def vertexai_process_response(_kwargs: dict[str, Any], model: Union[BaseModel, list[BaseModel], Type]) -> tuple[list[gm.Content], list[gm.Tool], ToolConfig]:

• Reason this comment was not posted:
  Confidence changes required: 80%
  The function vertexai_process_response in instructor/client_vertexai.py lacks a return type annotation, which is important for clarity and consistency.

8. instructor/dsl/parallel.py:50

• Draft comment:
  Function from_response should have a return type annotation for clarity and consistency.

def from_response(

• Reason this comment was not posted:
  Confidence changes required: 80%
  The function from_response in instructor/dsl/parallel.py lacks a return type annotation, which is important for clarity and consistency.

Workflow ID: wflow_tx9ZvP1F3sMzVhxR

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[ivanleomk]

Verified that all vertex tests are passing locally and updated the docs

tests/llm/test_vertexai/test_format.py ....                                                                                              [ 14%]
tests/llm/test_vertexai/test_message_parser.py ....                                                                                      [ 28%]
tests/llm/test_vertexai/test_modes.py ......                                                                                             [ 50%]
tests/llm/test_vertexai/test_retries.py ....                                                                                             [ 64%]
tests/llm/test_vertexai/test_simple_types.py ......                                                                                      [ 85%]
tests/llm/test_vertexai/test_stream.py ....                                                                                              [100%]