VertexAI is Google’s cloud platform for building, training, and deploying machine learning models.
Authentication
Authenticate with GcloudExample
UseGemini with your Agent:
from phi.agent import Agent, RunResponse
from phi.model.vertexai import Gemini
agent = Agent(
model=Gemini(id="gemini-1.5-flash"),
markdown=True
)
# Get the response in a variable
# run: RunResponse = agent.run("Share a 2 sentence horror story.")
# print(run.content)
# Print the response on the terminal
agent.print_response("Share a 2 sentence horror story.")
Params
| Parameter | Type | Default | Description |
|---|---|---|---|
id | str | "claude-3-5-sonnet-20240620" | The specific model ID used for generating responses. |
name | str | "Claude" | The name identifier for the agent. |
provider | str | "Anthropic" | The provider of the model. |
max_tokens | Optional[int] | 1024 | The maximum number of tokens to generate in the response. |
temperature | Optional[float] | - | The sampling temperature to use, between 0 and 2. Higher values like 0.8 make the output more random, while lower values like 0.2 make it more focused and deterministic. |
stop_sequences | Optional[List[str]] | - | A list of sequences where the API will stop generating further tokens. |
top_p | Optional[float] | - | Nucleus sampling parameter. The model considers the results of the tokens with top_p probability mass. |
top_k | Optional[int] | - | The number of highest probability vocabulary tokens to keep for top-k-filtering. |
request_params | Optional[Dict[str, Any]] | - | Additional parameters to include in the request. |
api_key | Optional[str] | - | The API key for authenticating requests to the service. |
client_params | Optional[Dict[str, Any]] | - | Additional parameters for client configuration. |
client | Optional[AnthropicClient] | - | A pre-configured instance of the Anthropic client. |