> ## Documentation Index
> Fetch the complete documentation index at: https://docs.iearena.org/llms.txt
> Use this file to discover all available pages before exploring further.

# Existing plugins

> Connect Harbor jobs to observability platforms.

Job plugins run in the Harbor process and react to job and trial events. Pass
them at runtime with `--plugin`; plugins are not stored in `config.json`.

<Note>
  Install a plugin in the same Python environment as Harbor. Plugin credentials
  are [Harbor process variables](/core-concepts/jobs/environment-variables), not
  agent environment variables.
</Note>

## Discover plugins

Installed packages register a short plugin name. List them with:

```bash theme={"system"}
harbor plugins list
```

Harbor provides two official plugins: `langsmith` and `atif2otel`.
`harbor plugins list` shows the plugins installed in the environment running
Harbor. A source checkout may already include both as editable workspace
packages; PyPI installations must add the desired plugin package.

You can also pass a full `module:Class` import path to `--plugin`.

## LangSmith

The [LangSmith](https://www.langchain.com/langsmith/observability) plugin syncs Harbor tasks
to a LangSmith dataset and records each job as an experiment.

```bash theme={"system"}
uv tool install "harbor[langsmith]"
```

```bash theme={"system"}
export OPENAI_API_KEY="..."
export LANGSMITH_API_KEY="..."

harbor run \
  -t hello-world/hello-world \
  -a codex -m openai/gpt-5.6-sol \
  --plugin langsmith \
  --pk dataset_name=harbor-evals \
  --pk experiment_name=codex-baseline
```

<Frame caption="Harbor experiments in LangSmith">
  <img src="https://mintcdn.com/kobe/a7qBdwTWcuB-3sC1/images/langsmith-experiments.jpeg?fit=max&auto=format&n=a7qBdwTWcuB-3sC1&q=85&s=7f6bd436aecbd8bb1bb036dce5403cc2" alt="LangSmith showing Harbor experiments with reward, latency, token, and error metrics" width="3436" height="1676" data-path="images/langsmith-experiments.jpeg" />
</Frame>

<Accordion title="LangSmith options">
  | Option            | Environment variable             |
  | ----------------- | -------------------------------- |
  | `dataset_name`    | `HARBOR_LANGSMITH_DATASET`       |
  | `experiment_name` | `HARBOR_LANGSMITH_EXPERIMENT`    |
  | `experiment_id`   | `HARBOR_LANGSMITH_EXPERIMENT_ID` |
  | `endpoint`        | `LANGSMITH_ENDPOINT`             |
  | `workspace_id`    | `LANGSMITH_WORKSPACE_ID`         |
  | `sync_dataset`    | `HARBOR_LANGSMITH_SYNC_DATASET`  |
  | `fail_fast`       | `HARBOR_LANGSMITH_FAIL_FAST`     |

  `api_key` is also accepted, but `LANGSMITH_API_KEY` is recommended for
  credentials.
</Accordion>

See the [LangSmith docs](https://docs.langchain.com/langsmith/harbor-integrations)
and [launch post](https://x.com/LangChain/status/2071972238128005278).

## ATIF to OpenTelemetry

The ATIF-to-OpenTelemetry plugin converts each
agent's [ATIF **trajectory**](/core-concepts/agents/atif) into [OpenTelemetry](https://opentelemetry.io/) spans.

It converts `agent/trajectory.json` into spans for model calls, tool calls, and
subagents.

```bash theme={"system"}
uv tool install --with harbor-atif2otel harbor
```

<Tabs>
  <Tab title="Write files">
    Export all trials after the job finishes:

    ```bash theme={"system"}
    export OPENAI_API_KEY="..."

    harbor run \
      -t hello-world/hello-world \
      -a codex -m openai/gpt-5.6-sol \
      --plugin atif2otel \
      --pk output_dir=./otel-traces \
      --pk encoding=json
    ```
  </Tab>

  <Tab title="Stream to MLflow">
    The built-in uploader exports each trial to an MLflow server when it
    finishes:

    ```bash theme={"system"}
    export OPENAI_API_KEY="..."
    export MLFLOW_TRACKING_TOKEN="..."

    harbor run \
      -t hello-world/hello-world \
      -a codex -m openai/gpt-5.6-sol \
      --plugin atif2otel \
      --pk endpoint=https://mlflow.example.com \
      --pk experiment_name=harbor-evals
    ```
  </Tab>
</Tabs>

<Accordion title="ATIF-to-OpenTelemetry options">
  | Option            | Environment variable          | Default   |
  | ----------------- | ----------------------------- | --------- |
  | `endpoint`        | `OTEL_EXPORTER_OTLP_ENDPOINT` | —         |
  | `output_dir`      | `HARBOR_OTEL_OUTPUT_DIR`      | —         |
  | `experiment_name` | `MLFLOW_EXPERIMENT_NAME`      | Job name  |
  | `token`           | `MLFLOW_TRACKING_TOKEN`       | `""`      |
  | `workspace`       | —                             | `default` |
  | `encoding`        | —                             | `json`    |
  | `mode`            | —                             | `auto`    |

  `mode=auto` streams when `endpoint` is set and writes files when `output_dir`
  is set. Set both to enable both outputs.
</Accordion>

See the [plugin source](https://github.com/harbor-framework/harbor/tree/main/packages/harbor-atif2otel).

## Use multiple plugins

`--plugin` and `--plugin-kwarg` are repeatable. Prefix each kwarg with its plugin
name when using more than one plugin:

```bash theme={"system"}
harbor run ... \
  --plugin langsmith \
  --plugin atif2otel \
  --pk langsmith.experiment_name=codex-baseline \
  --pk atif2otel.output_dir=./otel-traces
```

When running from a job config, keep plugin flags on the command line:

```bash theme={"system"}
harbor run --config config.json --plugin langsmith
```

To build another integration, see [Custom plugins](/core-concepts/plugins/custom-plugins).