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Method __init__

mllm_tools/vertex_ai.py:14–43  ·  view source on GitHub ↗

Initialize the Vertex AI wrapper. Args: model_name: Name of the model to use (e.g. "gemini-1.5-pro") temperature: Temperature for generation between 0 and 1 print_cost: Whether to print the cost of the completion verbose: Whether to pr

(
        self,
        model_name: str = "gemini-1.5-pro",
        temperature: float = 0.7,
        print_cost: bool = False,
        verbose: bool = False,
        use_langfuse: bool = False
    )

Source from the content-addressed store, hash-verified

12 """Wrapper for Vertex AI to support Gemini models."""
13
14 def __init__(
15 self,
16 model_name: str = "gemini-1.5-pro",
17 temperature: float = 0.7,
18 print_cost: bool = False,
19 verbose: bool = False,
20 use_langfuse: bool = False
21 ):
22 """Initialize the Vertex AI wrapper.
23
24 Args:
25 model_name: Name of the model to use (e.g. "gemini-1.5-pro")
26 temperature: Temperature for generation between 0 and 1
27 print_cost: Whether to print the cost of the completion
28 verbose: Whether to print verbose output
29 use_langfuse: Whether to enable Langfuse logging
30 """
31 self.model_name = model_name
32 self.temperature = temperature
33 self.print_cost = print_cost
34 self.verbose = verbose
35
36 # Initialize Vertex AI
37 project_id = os.getenv("GOOGLE_CLOUD_PROJECT")
38 location = os.getenv("GOOGLE_CLOUD_LOCATION", "us-central1")
39 if not project_id:
40 raise ValueError("No GOOGLE_CLOUD_PROJECT found in environment variables")
41
42 vertexai.init(project=project_id, location=location)
43 self.model = GenerativeModel(model_name)
44
45 def __call__(self, messages: List[Dict[str, Any]], metadata: Optional[Dict[str, Any]] = None) -> str:
46 """Process messages and return completion.

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