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LLM Tracing
Tracing FeaturesEnvironment

Environment

The environment feature allows you to specify which environment your traces are coming from. This is useful for separating traces from different environments in "development", "staging", or "production".

Configure Environment

You can configure the environment with the CONFIDENT_TRACE_ENVIRONMENT environment variable.

export CONFIDENT_TRACE_ENVIRONMENT="staging"

Alternatively, you can set the environment directly in code:

import openai
from deepeval.tracing import observe, trace_manager
 
trace_manager.configure(environment="production")
 
@observe()
def llm_app(query: str):
    return openai.ChatCompletion.create(
        model="gpt-4o",
        messages=[
            {"role": "user", "content": query}
        ]
    ).choices[0].message["content"]
 
 
llm_app("Write me a poem.")

The environment can be either "production", "staging", or "development", and helps you identify where your traces are coming from.

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AttributesInput/Output