Example: OpenAI OpenTelemetrySDK Instrumentation

from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from dotenv import load_dotenv
import os
from openai import OpenAI

# Load environment variables from .env file
load_dotenv()

# Setup tracer provider
provider = TracerProvider()
trace.set_tracer_provider(provider)

TFY_API_KEY = os.environ.get("TFY_API_KEY")
# OTLP exporter (HTTP)
otlp_exporter = OTLPSpanExporter(
    endpoint="{enter_your_api_endpoint}/v1/traces",
    headers={
        "Authorization": f"Bearer {TFY_API_KEY}",
        "TFY-Tracing-Project": "<enter_your_tracing_project_fqn>",
    }
)

# Span processor using batch (recommended for production)
span_processor = BatchSpanProcessor(otlp_exporter)
provider.add_span_processor(span_processor)

# Get tracer
tracer = trace.get_tracer(__name__)

# Initialize OpenAI client
client = OpenAI()

def generate_ai_response(input_text):
    with tracer.start_as_current_span("OpenAI-Trace") as span:
        # Set up the chat messages
        input_prompt = [
            {"role": "user", "content": input_text}
        ]
        
        # Add relevant attributes to the span
        span.set_attribute("input.value", input_text)
        span.set_attribute("model.name", "gpt-4")
        span.set_attribute("temperature", 0.7)
        span.set_attribute("gen_ai.prompt.0.role", "user")
        span.set_attribute("gen_ai.prompt.0.content", input_text)

        # Make the API call
        response = client.chat.completions.create(
            messages=input_prompt,
            model="gpt-4",
            temperature=0.7,
        )

        # Add response attributes to the span
        output_content = response.choices[0].message.content
        span.set_attribute("output.value", output_content)
        span.set_attribute("gen_ai.completion.0.role", "assistant")
        span.set_attribute("gen_ai.completion.0.content", output_content)

        return output_content

# Example usage
if __name__ == "__main__":
    input_text = "Explain the concept of AI in 50 words"
    response = generate_ai_response(input_text)
    print(response)