LLM Observability with LangSmith and OpenLLMetry

LangSmith is an all-in-one developer platform for every step of the LLM-powered application lifecycle. LangSmith supports ingesting traces using OpenTelemetry / OpenLLMetry format. For more details, see LangSmith’s OpenTelemetry documentation.

To Log Traces to Langsmith

Signup for LangSmith and create an API Key. Then setup your environment variables:

TRACELOOP_BASE_URL=https://api.smith.langchain.com/otel
TRACELOOP_HEADERS="x-api-key=<LANGSMITH_API_KEY>"

You can then log traces with OpenLLMetry to LangSmith, here is an example:

from openai import OpenAI
from traceloop.sdk import Traceloop

client = OpenAI()
Traceloop.init()

completion = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {
            "role": "user",
            "content": "Write a haiku about recursion in programming."
        }
    ]
)

print(completion.choices[0].message)

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LLM Observability with LangSmith and OpenLLMetry

To Log Traces to Langsmith

​To Log Traces to Langsmith

To Log Traces to Langsmith