Observability for together.ai with Splunk

Step 1

Install the Traceloop SDK and initialize it. It will automatically log all calls to models served from together.ai, with prompts and completions as separate spans.

from together import Together
from traceloop.sdk import Traceloop
from traceloop.sdk.decorators import workflow

Traceloop.init(app_name="joke_generation_service")

client = Together(api_key=os.environ.get("TOGETHER_API_KEY"))

@workflow(name="joke_creation")
def create_joke():
    response = client.chat.completions.create(
        model="mistralai/Mixtral-8x7B-Instruct-v0.1",
        messages=[{"role": "user", "content": "Tell me a joke about OpenTelemetry."}],
    )

    return response.choices[0].message.content

Step 2

Configure your collector to collect traces and send them to Splunk Observability Cloud; point OpenLLMetry to send traces to your Splunk collector

# In your Splunk collector configuration
receivers:
  otlp:
    protocols:
      grpc:
        endpoint: "0.0.0.0:4317"
      http:
        endpoint: "0.0.0.0:4318"
exporters:
  # Traces
  sapm:
    access_token: "${SPLUNK_ACCESS_TOKEN}"
    endpoint: "https://ingest.${SPLUNK_REALM}.signalfx.com/v2/trace"
    sending_queue:
      num_consumers: 32
 pipelines:
  traces:
    receivers: [jaeger, otlp, sapm, zipkin]
    processors:
    - memory_limiter
    - batch
    #- resource/add_environment
    exporters: [sapm]
        
# In the environment of your application
TRACELOOP_BASE_URL=http://splunk-otel-collector:4318

Docs

Observability for together.ai with Splunk

Step 1

Step 2

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