> ## Documentation Index > Fetch the complete documentation index at: https://arize-ax.mintlify.site/docs/llms.txt > Use this file to discover all available pages before exploring further. # Together AI > Trace Together AI chat completions with OpenInference and send inference spans to Arize AX. [Together AI](https://www.together.ai/) hosts open-weight models behind its native Python client. The [`TogetherInstrumentor`](https://github.com/Arize-ai/openinference/tree/main/python/instrumentation/openinference-instrumentation-together) 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](https://arize.com/sign-up/)) * A `TOGETHER_API_KEY` from the [Together AI console](https://api.together.ai/settings/api-keys) ## Launch Arize AX 1. Sign in to your [Arize AX account](https://app.arize.com/). 2. From **Space Settings**, copy your **Space ID** and **API Key**. You will set them as `ARIZE_SPACE_ID` and `ARIZE_API_KEY` below. ## Install ```bash theme={null} pip install arize-otel openinference-instrumentation-together together ``` ## Configure credentials ```bash theme={null} export ARIZE_SPACE_ID="" export ARIZE_API_KEY="" export ARIZE_PROJECT_NAME="together-ai-tracing-example" export TOGETHER_API_KEY="" ``` ## Setup tracing ```python theme={null} # 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 ```python theme={null} # 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 ```text wrap theme={null} 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 1. Open your Arize AX space and select project **`together-ai-tracing-example`**. 2. You should see a new trace within \~30 seconds containing a `Completions` LLM span. 3. If no traces appear, see [Troubleshooting](#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. Install the [Arize Skills](https://github.com/Arize-ai/arize-skills) plugin and let your coding agent check for you: ```bash theme={null} 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: ```bash theme={null} 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](/docs/api-clients/cli/spans). Query the project's spans and check that at least one came back. ```python Python theme={null} 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" ) ``` ```typescript TypeScript theme={null} // 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", ); ``` ```go Go theme={null} 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](/docs/api-clients/python/version-8/client-resources/spans) · [TypeScript](/docs/api-clients/typescript/version-1/client-resources/spans) · [Go](/docs/api-clients/go/version-2/client-resources/spans). ## 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. ## Resources