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improve(vertex_ai.py): Switch to simpler dict type.

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David Manouchehri 2024-04-22 17:00:37 +00:00
parent 6b730214dd
commit aa5ee6a626
1 changed files with 23 additions and 114 deletions
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137
litellm/llms/vertex_ai.py
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@ -21,6 +21,29 @@ class VertexAIError(Exception):
self.message self.message
) # Call the base class constructor with the parameters it needs ) # Call the base class constructor with the parameters it needs
class ExtendedGenerationConfig(dict):
"""Extended parameters for the generation."""
def __init__(
self,
*,
temperature: Optional[float] = None,
top_p: Optional[float] = None,
top_k: Optional[int] = None,
candidate_count: Optional[int] = None,
max_output_tokens: Optional[int] = None,
stop_sequences: Optional[List[str]] = None,
response_mime_type: Optional[str] = None,
):
super().__init__(
temperature=temperature,
top_p=top_p,
top_k=top_k,
candidate_count=candidate_count,
max_output_tokens=max_output_tokens,
stop_sequences=stop_sequences,
response_mime_type=response_mime_type,
)
class VertexAIConfig: class VertexAIConfig:
""" """
@ -363,42 +386,6 @@ def completion(
from google.cloud.aiplatform_v1beta1.types import content as gapic_content_types # type: ignore from google.cloud.aiplatform_v1beta1.types import content as gapic_content_types # type: ignore
import google.auth # type: ignore import google.auth # type: ignore
class ExtendedGenerationConfig(GenerationConfig):
"""Extended parameters for the generation."""
def __init__(
self,
*,
temperature: Optional[float] = None,
top_p: Optional[float] = None,
top_k: Optional[int] = None,
candidate_count: Optional[int] = None,
max_output_tokens: Optional[int] = None,
stop_sequences: Optional[List[str]] = None,
response_mime_type: Optional[str] = None,
):
args_spec = inspect.getfullargspec(gapic_content_types.GenerationConfig)
if "response_mime_type" in args_spec.args:
self._raw_generation_config = gapic_content_types.GenerationConfig(
temperature=temperature,
top_p=top_p,
top_k=top_k,
candidate_count=candidate_count,
max_output_tokens=max_output_tokens,
stop_sequences=stop_sequences,
response_mime_type=response_mime_type,
)
else:
self._raw_generation_config = gapic_content_types.GenerationConfig(
temperature=temperature,
top_p=top_p,
top_k=top_k,
candidate_count=candidate_count,
max_output_tokens=max_output_tokens,
stop_sequences=stop_sequences,
)
## Load credentials with the correct quota project ref: https://github.com/googleapis/python-aiplatform/issues/2557#issuecomment-1709284744 ## Load credentials with the correct quota project ref: https://github.com/googleapis/python-aiplatform/issues/2557#issuecomment-1709284744
print_verbose( print_verbose(
f"VERTEX AI: vertex_project={vertex_project}; vertex_location={vertex_location}" f"VERTEX AI: vertex_project={vertex_project}; vertex_location={vertex_location}"
@ -811,45 +798,6 @@ async def async_completion(
Add support for acompletion calls for gemini-pro Add support for acompletion calls for gemini-pro
""" """
try: try:
from vertexai.preview.generative_models import GenerationConfig
from google.cloud.aiplatform_v1beta1.types import content as gapic_content_types # type: ignore
class ExtendedGenerationConfig(GenerationConfig):
"""Extended parameters for the generation."""
def __init__(
self,
*,
temperature: Optional[float] = None,
top_p: Optional[float] = None,
top_k: Optional[int] = None,
candidate_count: Optional[int] = None,
max_output_tokens: Optional[int] = None,
stop_sequences: Optional[List[str]] = None,
response_mime_type: Optional[str] = None,
):
args_spec = inspect.getfullargspec(gapic_content_types.GenerationConfig)
if "response_mime_type" in args_spec.args:
self._raw_generation_config = gapic_content_types.GenerationConfig(
temperature=temperature,
top_p=top_p,
top_k=top_k,
candidate_count=candidate_count,
max_output_tokens=max_output_tokens,
stop_sequences=stop_sequences,
response_mime_type=response_mime_type,
)
else:
self._raw_generation_config = gapic_content_types.GenerationConfig(
temperature=temperature,
top_p=top_p,
top_k=top_k,
candidate_count=candidate_count,
max_output_tokens=max_output_tokens,
stop_sequences=stop_sequences,
)
if mode == "vision": if mode == "vision":
print_verbose("\nMaking VertexAI Gemini Pro Vision Call") print_verbose("\nMaking VertexAI Gemini Pro Vision Call")
print_verbose(f"\nProcessing input messages = {messages}") print_verbose(f"\nProcessing input messages = {messages}")
@ -1056,45 +1004,6 @@ async def async_streaming(
""" """
Add support for async streaming calls for gemini-pro Add support for async streaming calls for gemini-pro
""" """
from vertexai.preview.generative_models import GenerationConfig
from google.cloud.aiplatform_v1beta1.types import content as gapic_content_types # type: ignore
class ExtendedGenerationConfig(GenerationConfig):
"""Extended parameters for the generation."""
def __init__(
self,
*,
temperature: Optional[float] = None,
top_p: Optional[float] = None,
top_k: Optional[int] = None,
candidate_count: Optional[int] = None,
max_output_tokens: Optional[int] = None,
stop_sequences: Optional[List[str]] = None,
response_mime_type: Optional[str] = None,
):
args_spec = inspect.getfullargspec(gapic_content_types.GenerationConfig)
if "response_mime_type" in args_spec.args:
self._raw_generation_config = gapic_content_types.GenerationConfig(
temperature=temperature,
top_p=top_p,
top_k=top_k,
candidate_count=candidate_count,
max_output_tokens=max_output_tokens,
stop_sequences=stop_sequences,
response_mime_type=response_mime_type,
)
else:
self._raw_generation_config = gapic_content_types.GenerationConfig(
temperature=temperature,
top_p=top_p,
top_k=top_k,
candidate_count=candidate_count,
max_output_tokens=max_output_tokens,
stop_sequences=stop_sequences,
)
if mode == "vision": if mode == "vision":
stream = optional_params.pop("stream") stream = optional_params.pop("stream")
tools = optional_params.pop("tools", None) tools = optional_params.pop("tools", None)