Environments

from langfuse.decorators import langfuse_context, observe
 
# Either set the environment variable or configure the decorator. The latter takes precedence.
os.environ["LANGFUSE_TRACING_ENVIRONMENT"] = "production"
 
# Configure the decorator
langfuse_context.configure(environment="production")
 
@observe()
def fn():
    pass
 
fn()

from langfuse import Langfuse
 
# Either set the environment variable or the constructor parameter. The latter takes precedence.
os.environ["LANGFUSE_TRACING_ENVIRONMENT"] = "production"
 
# Configure the client
langfuse = Langfuse(environment="production")
 
trace = langfuse.trace(
  name="Rap Battle",
)

import { Langfuse } from "langfuse";
 
const langfuse = new Langfuse({
  environment: "production",
});

from opentelemetry import trace
from opentelemetry.trace import Status, StatusCode
 
tracer = trace.get_tracer(__name__)
 
with tracer.start_as_current_span("my-operation") as span:
    # Set environment using Langfuse-specific attribute
    span.set_attribute("langfuse.environment", "staging")
 
    # Or using OpenTelemetry convention
    span.set_attribute("deployment.environment.name", "staging")

from langfuse.openai import openai
 
# Either set the environment variable or configure the openai import. The latter takes precedence.
os.environ["LANGFUSE_TRACING_ENVIRONMENT"] = "production"
 
# Configure the openai import
openai.langfuse_environment = "production"
 
completion = openai.chat.completions.create(
  name="test-chat",
  model="gpt-3.5-turbo",
  messages=[
    {"role": "system", "content": "You are a calculator."},
    {"role": "user", "content": "1 + 1 = "}],
)

import OpenAI from "openai";
import { observeOpenAI } from "langfuse";
 
const openai = observeOpenAI(new OpenAI(), {
  clientInitParams: {
    environment: "production",
  },
});

from langfuse.callback import CallbackHandler
 
# Either set the environment variable or the constructor parameter. The latter takes precedence.
os.environ["LANGFUSE_TRACING_ENVIRONMENT"] = "production"
handler = CallbackHandler(
  environment="production"
)

import { CallbackHandler } from "langfuse-langchain";
 
const handler = new CallbackHandler({
  environment: "production",
});

import { registerOTel } from "@vercel/otel";
import { LangfuseExporter } from "langfuse-vercel";
 
export function register() {
  registerOTel({
    serviceName: "langfuse-vercel-ai-nextjs-example",
    traceExporter: new LangfuseExporter({ environment: "production" }),
  });
}

import os
from langfuse.llama_index import LlamaIndexInstrumentor
 
# Either set the environment variable or the constructor parameter. The latter takes precedence.
os.environ["LANGFUSE_TRACING_ENVIRONMENT"] = "production"
instrumentor = LlamaIndexInstrumentor(environment="production")