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Replace deprecated vertexai modules for google.genai #407

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Replace deprecated vertexai modules for google.genai #407

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29 changes: 21 additions & 8 deletions src/neo4j_graphrag/llm/vertexai_llm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -34,17 +34,17 @@
from neo4j_graphrag.message_history import MessageHistory
from neo4j_graphrag.tool import Tool
from neo4j_graphrag.types import LLMMessage
from google import genai
from google.genai import types

try:
from vertexai.generative_models import (
Content,
FunctionCall,
FunctionDeclaration,
GenerationResponse,
GenerativeModel,
Part,
ResponseValidationError,
Tool as VertexAITool,
ToolConfig,
)
except ImportError:
Expand Down Expand Up @@ -189,20 +189,20 @@ async def ainvoke(
except ResponseValidationError as e:
raise LLMGenerationError("Error calling VertexAILLM") from e

def _to_vertexai_function_declaration(self, tool: Tool) -> FunctionDeclaration:
return FunctionDeclaration(
def _to_vertexai_function_declaration(self, tool: Tool) -> types.FunctionDeclaration:
return types.FunctionDeclaration(
name=tool.get_name(),
description=tool.get_description(),
parameters=tool.get_parameters(exclude=["additional_properties"]),
)

def _get_llm_tools(
self, tools: Optional[Sequence[Tool]]
) -> Optional[list[VertexAITool]]:
) -> Optional[list[types.Tool]]:
if not tools:
return None
return [
VertexAITool(
types.Tool(
function_declarations=[
self._to_vertexai_function_declaration(tool) for tool in tools
]
Expand Down Expand Up @@ -254,7 +254,20 @@ async def _acall_llm(
) -> GenerationResponse:
model = self._get_model(system_instruction=system_instruction)
options = self._get_call_params(input, message_history, tools)
response = await model.generate_content_async(**options)

client = genai.Client()
response = await client.aio.models.generate_content(
model=self.model_name,
contents=types.Content(
role="user",
parts=[types.Part.from_text(text=input)],
),
config=types.GenerateContentConfig(
tools=options["tools"],
system_instruction=system_instruction,
temperature=0.0,
),
)
return response # type: ignore[no-any-return]

def _call_llm(
Expand All @@ -276,7 +289,7 @@ def _to_tool_call(self, function_call: FunctionCall) -> ToolCall:
)

def _parse_tool_response(self, response: GenerationResponse) -> ToolCallResponse:
function_calls = response.candidates[0].function_calls
function_calls = response.function_calls
return ToolCallResponse(
tool_calls=[self._to_tool_call(f) for f in function_calls],
content=None,
Expand Down
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