traceAI-instructor 0.2.0

OpenTelemetry instrumentation for Instructor

Instructor OpenTelemetry Integration

Overview

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

Installation

1. Install traceAI Instructor

pip install traceAI-instructor

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="instructor_app"
)

Configure Instructor Instrumentation

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

from traceai_instructor import InstructorInstrumentor

InstructorInstrumentor().instrument(tracer_provider=trace_provider)

Create Instructor Components

Set up your Instructor client with built-in observability.

import instructor
from openai import OpenAI
from pydantic import BaseModel

# Define the output structure
class UserInfo(BaseModel):
    name: str
    age: int

# Patch the OpenAI client
client = instructor.patch(client=OpenAI())

user_info = client.chat.completions.create(
    model="gpt-3.5-turbo",
    response_model=UserInfo,
    messages=[
        {
            "role": "system",
            "content": "Extract the name and age from the text and return them in a structured format.",
        },
        {"role": "user", "content": "John Doe is nine years old."},
    ],
)

print(user_info, type(user_info))