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1. Installation

Install the traceAI and Llama Index packages. 
pip install traceAI-llamaindex
pip install llama-index

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2. Set Environment Variables

Set up your environment variables to authenticate with FutureAGI. 
import os

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

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3. Initialize Trace Provider

Set up the trace provider to create a new project in FutureAGI, establish telemetry data pipelines . 
from fi_instrumentation import register
from fi_instrumentation.fi_types import ProjectType

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

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4. Instrument your Project

Initialize the Llama Index instrumentor to enable automatic tracing. This step ensures that all interactions with the Llama Index are tracked and monitored. 
from traceai_llamaindex import LlamaIndexInstrumentor

LlamaIndexInstrumentor().instrument(tracer_provider=trace_provider)

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5. Create Llama Index Components

Set up your Llama Index components as you normally would. Our Instrumentor will automatically trace and send the telemetry data to our platform. 
from llama_index.agent.openai import OpenAIAgent
from llama_index.core import Settings
from llama_index.core.tools import FunctionTool
from llama_index.llms.openai import OpenAI

def multiply(a: int, b: int) -> int:
    """Multiply two integers and return the result."""
    return a * b

def add(a: int, b: int) -> int:
    """Add two integers and return the result."""
    return a + b

multiply_tool = FunctionTool.from_defaults(fn=multiply)
add_tool = FunctionTool.from_defaults(fn=add)
agent = OpenAIAgent.from_tools([multiply_tool, add_tool])
Settings.llm = OpenAI(model="gpt-3.5-turbo")

response = agent.query("What is (121 * 3) + 42?")

print(response)