Datadog

export OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317

import os
from openai import OpenAI

from langtrace_python_sdk import langtrace
from langtrace_python_sdk.utils.with_root_span import with_langtrace_root_span

from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import \
    OTLPSpanExporter

# Set up the OTLP exporter with the endpoint from your collector
otlp_exporter = OTLPSpanExporter(
    # This should match your collector's OTLP gRPC endpoint
    endpoint=os.environ.get("OTEL_EXPORTER_OTLP_ENDPOINT"),
    insecure=True  # Set to False if using HTTPS
)

# set up langtrace
langtrace.init(custom_remote_exporter=otlp_exporter)

# rest of your code
@with_langtrace_root_span() # This optional annotation is used to create a parent root span for the entire application
def app():
    client = OpenAI(
        api_key="<YOUR_OPENAI_API_KEY>")
    response = client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[
            {
                "role": "system",
                "content": "How many states of matter are there?"
            }
        ],
    )
    print(response.choices[0].message.content)


app()

receivers:
  otlp:
    protocols:
      http:
        endpoint: "localhost:4318"
      grpc:
        endpoint: "localhost:4317"

processors:
  batch:

exporters:
  datadog:
    api:
      site: "datadoghq.com"
      key: "<DATADOG_API_KEY>"

service:
  pipelines:
    traces:
      receivers: [otlp]
      processors: [batch]
      exporters: [datadog]
    metrics:
      receivers: [otlp]
      processors: [batch]
      exporters: [datadog]
    logs:
      receivers: [otlp]
      processors: [batch]
      exporters: [datadog]

python main.py

otelcol-contrib --config otel-collector-config.yaml