traceAI-llamaindex 0.1.8

OpenTelemetry instrumentation for Llama Index

Llama Index OpenTelemetry Integration

Overview

This integration provides support for using OpenTelemetry with the Llama Index framework. It enables tracing and monitoring of applications built with Llama Index.

Installation

1. Install traceAI Llama Index

pip install traceAI-llamaindex

2. Install Llama Index

pip install llama-index

Set Environment Variables

Set up your environment variables to authenticate with FutureAGI

import os

os.environ["FI_API_KEY"] = FI_API_KEY
os.environ["FI_SECRET_KEY"] = FI_SECRET_KEY

Quickstart

Register Tracer Provider

Set up the trace provider to establish the observability pipeline. The trace provider:

from fi_instrumentation import register
from fi_instrumentation.fi_types import ProjectType

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

Configure Llama Index Instrumentation

Instrument the Llama Index client to enable telemetry collection. This step ensures that all interactions with the Llama Index SDK are tracked and monitored.

from traceai_llamaindex import LlamaIndexInstrumentor

LlamaIndexInstrumentor().instrument(tracer_provider=trace_provider)

Create Llama Index Components

Set up your Llama Index client with built-in observability.

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")

if __name__ == "__main__":
    response = agent.query("What is (121 * 3) + 42?")
    print(response)