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1. Installation

Install the traceAI and other necessary packages. 
pip install traceAI-instructor instructor

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2. Set Environment Variables

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

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

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4. Instrument your Project

Use the Instructor Instrumentor to instrument your project. 
from traceai_instructor import InstructorInstrumentor

InstructorInstrumentor().instrument(tracer_provider=trace_provider)

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5. Run your Instructor application.

Run your Instructor application as you normally would. Our Instrumentor will automatically trace and send the telemetry data to our platform. 
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))