Together AI

Together AI hosts open-weight models behind its native Python client. The TogetherInstrumentor captures Together and AsyncTogether chat completions, streaming output, tool calls, and token counts as OpenInference LLM spans in Arize AX.

Prerequisites

Python 3.10+
An Arize AX account (sign up)
A TOGETHER_API_KEY from the Together AI console

Launch Arize AX

Sign in to your Arize AX account.
From Space Settings, copy your Space ID and API Key. You will set them as ARIZE_SPACE_ID and ARIZE_API_KEY below.

Install

pip install arize-otel openinference-instrumentation-together together

Configure credentials

export ARIZE_SPACE_ID="<your-space-id>"
export ARIZE_API_KEY="<your-api-key>"
export ARIZE_PROJECT_NAME="together-ai-tracing-example"
export TOGETHER_API_KEY="<your-together-api-key>"

Setup tracing

# instrumentation.py
import os

from arize.otel import register
from openinference.instrumentation.together import TogetherInstrumentor

tracer_provider = register(
    space_id=os.environ["ARIZE_SPACE_ID"],
    api_key=os.environ["ARIZE_API_KEY"],
    project_name=os.environ["ARIZE_PROJECT_NAME"],
)

TogetherInstrumentor().instrument(tracer_provider=tracer_provider)
print("Arize AX tracing initialized for Together AI.")

Import instrumentation before creating a Together or AsyncTogether client.

Run Together AI

# example.py
import os

from instrumentation import tracer_provider
from together import Together

client = Together(api_key=os.environ["TOGETHER_API_KEY"])
response = client.chat.completions.create(
    model="meta-llama/Llama-3.3-70B-Instruct-Turbo",
    messages=[
        {
            "role": "user",
            "content": "Why is the ocean salty? Answer in two sentences.",
        },
    ],
)

print(response.choices[0].message.content)

Expected output

Arize AX tracing initialized for Together AI.
The ocean is salty because rivers carry dissolved minerals into it and evaporation leaves the salt behind. This process concentrates salt over millions of years.

Verify in Arize AX

Open your Arize AX space and select project together-ai-tracing-example.
You should see a new trace within ~30 seconds containing a Completions LLM span.
If no traces appear, see Troubleshooting.

Check from the skill, CLI, or SDK

Confirm spans are actually reaching your Arize AX project. Use whichever fits your workflow — the skill and CLI work for any framework; the SDK check is shown for each language.

Arize skill (agent)
AX CLI
SDK

Install the Arize Skills plugin and let your coding agent check for you:

npx skills add Arize-ai/arize-skills

Then prompt your agent:

Use the arize-trace skill to export and analyze recent traces from my project. Confirm spans are arriving, and summarize any errors or latency issues.

Export recent spans for your project — any rows mean traces are landing:

ax spans export "$ARIZE_PROJECT_NAME" --space "$ARIZE_SPACE_ID" \
  --limit 5 --stdout | jq 'length'

A non-zero count confirms spans reached Arize AX. Run ax auth login first if you have not authenticated. See the ax spans reference.

Query the project’s spans and check that at least one came back.

import os
from arize import ArizeClient

client = ArizeClient(api_key=os.environ["ARIZE_API_KEY"])
resp = client.spans.list(
    project=os.environ["ARIZE_PROJECT_NAME"],
    space=os.environ["ARIZE_SPACE_ID"],
    limit=5,
)
count = len(resp.spans)
print(
    f"{count} span(s) found" if count else "No spans yet — recheck setup"
)

// Reads ARIZE_API_KEY from the environment.
import { listSpans } from "@arizeai/ax-client";

const { data: spans } = await listSpans({
  project: process.env.ARIZE_PROJECT_NAME!,
  space: process.env.ARIZE_SPACE_ID!,
  limit: 5,
});
const count = spans.length;
console.log(
  count ? `${count} span(s) found` : "No spans yet — recheck setup",
);

client, err := arize.NewClient(
    arize.Config{APIKey: os.Getenv("ARIZE_API_KEY")},
)
if err != nil {
    log.Fatal(err)
}
resp, err := client.Spans.List(ctx, spans.ListRequest{
    Project: os.Getenv("ARIZE_PROJECT_NAME"),
    Space:   os.Getenv("ARIZE_SPACE_ID"),
    Limit:   5,
})
if err != nil {
    log.Fatal(err)
}
fmt.Printf("%d span(s) found\n", len(resp.Spans))

SDK span references: Python · TypeScript · Go.

Troubleshooting

No traces in Arize AX. Call TogetherInstrumentor().instrument(...) before creating the client.
401 from Together. Verify TOGETHER_API_KEY is set and active.
model_not_found. Replace the model with one available to your Together account.
402 credit limit exceeded. Add credit to the Together account before running the example.

OpenTelemetry

LLM Providers

Agent Frameworks

Coding Agents

Platforms

Orchestration

Evaluation

Prerequisites

Launch Arize AX

Install

Configure credentials

Setup tracing

Run Together AI

Expected output

Verify in Arize AX

Check from the skill, CLI, or SDK

Troubleshooting

Resources

OpenInference Together Instrumentor

Together AI Python SDK

​Prerequisites

​Launch Arize AX

​Install

​Configure credentials

​Setup tracing

​Run Together AI

​Expected output

​Verify in Arize AX

​Check from the skill, CLI, or SDK

​Troubleshooting

​Resources

OpenInference Together Instrumentor

Together AI Python SDK

Prerequisites

Launch Arize AX

Install

Configure credentials

Setup tracing

Run Together AI

Expected output

Verify in Arize AX

Check from the skill, CLI, or SDK

Troubleshooting

Resources