OpenInference Integration

from judgeval import Tracer
from openinference.instrumentation.openai import OpenAIInstrumentor
from openai import OpenAI

Tracer.init(project_name="openinference_project")
Tracer.registerOTELInstrumentation(OpenAIInstrumentor())

client = OpenAI()

def analyze_sentiment(text: str) -> str:
    response = client.chat.completions.create(
        model="gpt-5.2",
        messages=[
            {"role": "system", "content": "You are a sentiment analysis expert."},
            {"role": "user", "content": f"Analyze the sentiment of: {text}"}
        ]
    )
    return response.choices[0].message.content

def extract_entities(text: str) -> str:
    response = client.chat.completions.create(
        model="gpt-5.2",
        messages=[
            {"role": "system", "content": "You are an entity extraction expert."},
            {"role": "user", "content": f"Extract entities from: {text}"}
        ]
    )
    return response.choices[0].message.content

def summarize_text(text: str) -> str:
    response = client.chat.completions.create(
        model="gpt-5.2",
        messages=[
            {"role": "system", "content": "You are a summarization expert."},
            {"role": "user", "content": f"Summarize: {text}"}
        ]
    )
    return response.choices[0].message.content

@Tracer.observe(span_type="function")  
def main():
    text = "Apple Inc. announced today that their new iPhone will be released next month. The market reacted positively to this news."

    sentiment = analyze_sentiment(text)
    entities = extract_entities(text)
    summary = summarize_text(text)

    print(f"Sentiment: {sentiment}")
    print(f"Entities: {entities}")
    print(f"Summary: {summary}")

if __name__ == "__main__":
    main()