Vertex AI (Gemini)

pip install traceAI-vertexai
pip install vertexai

import os
os.environ["FI_API_KEY"] = "your-futureagi-api-key"
os.environ["FI_SECRET_KEY"] = "your-futureagi-secret-key"

from fi_instrumentation import register
from fi_instrumentation.fi_types import ProjectType

trace_provider = register(
    project_type=ProjectType.OBSERVE,
    project_name="vertexai_project",
    )

from traceai_vertexai import VertexAIInstrumentor

VertexAIInstrumentor().instrument(tracer_provider=trace_provider)

import vertexai
from vertexai.generative_models import FunctionDeclaration, GenerativeModel, Part, Tool

vertexai.init(
    project="project_name",
)

# Describe a function by specifying its schema (JsonSchema format)
get_current_weather_func = FunctionDeclaration(
    name="get_current_weather",
    description="Get the current weather in a given location",
    parameters={
        "type": "object",
        "properties": {
            "location": {
                "type": "string",
                "description": "The city and state, e.g. San Francisco, CA",
            },
            "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
        },
        "required": ["location"],
    },
)

# Tool is a collection of related functions
weather_tool = Tool(function_declarations=[get_current_weather_func])

# Use tools in chat
chat = GenerativeModel("gemini-1.5-flash", tools=[weather_tool]).start_chat()

if __name__ == "__main__":
    # Send a message to the model. The model will respond with a function call.
    for response in chat.send_message(
        "What is the weather like in Boston?", stream=True
    ):
        print(response)
    # Then send a function response to the model. The model will use it to answer.
    for response in chat.send_message(
        Part.from_function_response(
            name="get_current_weather",
            response={"content": {"weather": "super nice"}},
        ),
        stream=True,
    ):
        print(response)