diff --git a/README.md b/README.md index b52f314231f34333daac3c6e72a25a741f9be740..8eae61de8e2fc4ffabcdeba501fb26f527f76843 100644 --- a/README.md +++ b/README.md @@ -1,10 +1,7 @@ --- license: mit pretty_name: Generated Docs for HF -viewer: false --- This repo contains all the docs published on https://huggingface.co/docs. -The docs are generated with https://github.com/huggingface/doc-builder. - - \ No newline at end of file +The docs are generated with https://github.com/huggingface/doc-builder. \ No newline at end of file diff --git a/accelerate/_versions.yml b/accelerate/_versions.yml index 54f2f3720ad118079ceed5e3bcfb24c686ff93cd..91ca062e53043ab98b323370b03642c4aaaa417a 100644 --- a/accelerate/_versions.yml +++ b/accelerate/_versions.yml @@ -1,46 +1,4 @@ - version: main -- version: v1.15.0 -- version: v1.14.0 -- version: v1.13.0 -- version: v1.12.0 -- version: v1.11.0 -- version: v1.10.1 -- version: v1.10.0 -- version: v1.9.0 -- version: v1.8.1 -- version: v1.8.0 -- version: 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file mode 100644 index 2602eba8056f529941701534d6feb67099a4a41a..0000000000000000000000000000000000000000 --- a/trackio/main/en/_toctree.yml +++ /dev/null @@ -1,58 +0,0 @@ -- sections: - - local: index - title: Trackio - - local: installation - title: Installation - - local: quickstart - title: Quickstart - - local: migration - title: Migrating to Trackio - title: Getting started -- sections: - - local: track - title: Track - - local: sweeps - title: Hyperparameter Sweeps - - local: traces - title: Traces - - local: artifacts - title: Artifacts - - local: registry - title: Registry - - local: launch - title: Launch the Dashboard - - local: self_hosted_server - title: Self-host the Server - - local: deploy_embed - title: Deploy and Embed Dashboards - - local: manage - title: Manage Projects - - local: python_api - title: Python API for Managing Runs - - local: cli_commands - title: CLI Commands - - local: logbooks - title: Logbooks - - local: storage_schema - title: Storage Schema and Direct Queries - - local: api_mcp_server - title: API and MCP Server - - local: alerts - title: Alerts - - local: ml_agents - title: ML Agents - - local: environment_variables - title: Environment Variables - title: How-to guides -- sections: - - local: transformers_integration - title: Running with Transformers - - local: trl_integration - title: Running with TRL - - local: rapidfireai_integration - title: Running with RapidFire AI - title: Integration -- sections: - - local: api - title: API Reference - title: API diff --git a/trackio/main/en/alerts.md b/trackio/main/en/alerts.md deleted file mode 100644 index 57c93add2912c8bfedcc0bd59e5cddfa04267283..0000000000000000000000000000000000000000 --- a/trackio/main/en/alerts.md +++ /dev/null @@ -1,309 +0,0 @@ -# Alerts - -Trackio alerts let you flag important events during a run. When an alert fires, it is: - -1. **Printed to the terminal** with a color-coded severity label -2. **Stored in the database** so it can be queried later via the CLI, Python API, or HTTP endpoint -3. **Displayed in the dashboard** via a floating alert panel and the Reports page -4. **Sent to a webhook** (optional) — with native formatting for Slack and Discord - -## Firing an Alert - -Use `alert()` anywhere after calling [init()](/docs/trackio/main/en/api#trackio.init): - -```python -import trackio - -trackio.init(project="my-project") - -# ... inside your training loop ... -if val_loss > 2.0: - trackio.alert( - title="Validation loss spike", - text=f"val_loss={val_loss:.4f} exceeded threshold 2.0", - level=trackio.AlertLevel.ERROR, - ) -``` - -### Parameters - -| Parameter | Type | Default | Description | -|---|---|---|---| -| `title` | `str` | *(required)* | A short title for the alert. | -| `text` | `str \| None` | `None` | An optional longer description with details. | -| `level` | `AlertLevel` | `AlertLevel.WARN` | Severity: `INFO`, `WARN`, or `ERROR`. | -| `webhook_url` | `str \| None` | `None` | Override the global webhook URL for this alert only. | - -### Alert Levels - -```python -from trackio import AlertLevel - -AlertLevel.INFO # Informational — nothing is wrong -AlertLevel.WARN # Warning — something may need attention -AlertLevel.ERROR # Error — something is definitely wrong -``` - -## Terminal Output - -Every alert is printed to the terminal immediately, with a color-coded label: - -``` -[TRACKIO WARN] Validation loss spike: val_loss=2.3412 exceeded threshold 2.0 (step 42) -``` - -- **INFO** is printed in blue -- **WARN** is printed in yellow -- **ERROR** is printed in red - -This means alerts work out of the box with no setup — if you can see your training logs, you can see your alerts. - -## Dashboard - -Alerts appear in two places in the Trackio dashboard: - -1. **Alert panel** — A floating panel in the bottom-right corner of every dashboard page. It shows all alerts (across all projects) that arrived since the dashboard was launched, with the latest alert at the bottom. You can filter by severity level and expand/collapse the panel. The panel flashes when new alerts arrive. - -2. **Reports page** — The Reports page includes a full alerts table below the reports section. You can filter alerts by run (via the sidebar dropdown) and by severity level (via the sidebar checkbox group). - -To launch the dashboard: - -```bash -trackio show --project "my-project" -``` - -## Querying Alerts - -### CLI - -```bash -# List all alerts for a project -trackio get alerts --project "my-project" - -# Filter by run -trackio get alerts --project "my-project" --run "brave-sunset-0" - -# Filter by level -trackio get alerts --project "my-project" --level error - -# Only alerts after a specific timestamp (useful for polling) -trackio get alerts --project "my-project" --since "2025-06-01T00:00:00" - -# JSON output for programmatic consumption -trackio get alerts --project "my-project" --json -``` - -### Inspecting Metrics Around an Alert - -When an alert fires, you often want to see what all the metrics looked like at that point. Use `trackio get snapshot` to get every metric at/around the alert's step or timestamp: - -```bash -# An alert fired at step 200 — get all metrics in a ±5 step window -trackio get snapshot --project "my-project" --run "brave-sunset-0" --around 200 --window 5 --json - -# Or inspect a single metric around the alert's timestamp -trackio get metric --project "my-project" --run "brave-sunset-0" --metric "loss" --at-time "2025-06-01T12:05:30" --window 60 --json -``` - -See the [CLI Commands](cli_commands) page for the full list of filtering options. - -### Python API - -```python -import trackio - -api = trackio.Api() - -# All alerts in a project -alerts = api.alerts("my-project") - -# Filter by run and level -alerts = api.alerts("my-project", run="brave-sunset-0", level="error") - -# Only new alerts since a timestamp -alerts = api.alerts("my-project", since="2025-06-01T12:00:00") - -# From a Run object -runs = api.runs("my-project") -run_alerts = runs[0].alerts(level="warn") -``` - -### HTTP API - -If the Trackio dashboard is running (locally or on a Space), you can query alerts via the `/get_alerts` endpoint: - -```python -import httpx2 - -alerts = httpx2.post( - "http://127.0.0.1:7860/api/get_alerts", - json={ - "project": "my-project", - "run": None, - "level": "error", - "since": "2025-06-01T00:00:00", - }, -).json()["data"] -``` - -## Webhooks - -Webhooks let you push alerts to external services like Slack, Discord, or any HTTP endpoint. - -### Setting a Global Webhook - -You can set a webhook URL that applies to every alert in a run: - -**Option 1: In `trackio.init()`** - -```python -trackio.init( - project="my-project", - webhook_url="https://hooks.slack.com/services/T.../B.../xxx", -) -``` - -**Option 2: Environment variable** - -```bash -export TRACKIO_WEBHOOK_URL="https://hooks.slack.com/services/T.../B.../xxx" -``` - -```python -# No webhook_url needed — picks up the env var automatically -trackio.init(project="my-project") -``` - -The env variable is convenient when you want the same webhook for all projects without changing code. - -### Sending Only Higher-Severity Alerts to Webhooks - -If you only want webhooks for important alerts, set `webhook_min_level` in `trackio.init()`: - -```python -trackio.init( - project="my-project", - webhook_url="https://hooks.slack.com/services/T.../B.../xxx", - webhook_min_level=trackio.AlertLevel.WARN, -) -``` - -With `webhook_min_level=AlertLevel.WARN`: -- `INFO` alerts are still printed/stored/shown in UI, but not sent to webhook -- `WARN` and `ERROR` alerts are sent to webhook - -You can also configure this globally with an environment variable: - -```bash -export TRACKIO_WEBHOOK_MIN_LEVEL="warn" -``` - -### Overriding Per-Alert - -Pass `webhook_url` directly to `trackio.alert()` to override the global setting for a single alert, or to send a specific alert to a different channel: - -```python -trackio.alert( - title="Checkpoint saved", - text="Saved model at step 5000", - level=trackio.AlertLevel.INFO, - webhook_url="https://discord.com/api/webhooks/123456/abcdef", -) -``` - -### Webhook Payloads - -Trackio auto-detects the service from the URL and formats the payload accordingly. - -**Generic webhooks** receive a JSON POST body: - -```json -{ - "level": "warn", - "title": "Validation loss spike", - "text": "val_loss=2.34 exceeded threshold 2.0", - "project": "my-project", - "run": "brave-sunset-0", - "step": 42, - "timestamp": "2025-06-15T14:30:00+00:00" -} -``` - -**Slack** and **Discord** receive rich formatted messages (see sections below). - -Webhooks are sent in a background thread so `trackio.alert()` never blocks your training loop. - ---- - -## Slack - -### Creating a Slack Webhook - -1. Go to [https://api.slack.com/apps](https://api.slack.com/apps) and click **Create New App** → **From scratch**. -2. Give the app a name (e.g., "Trackio Alerts") and select your workspace. -3. In the left sidebar, click **Incoming Webhooks** and toggle it **On**. -4. Click **Add New Webhook to Workspace**, select the channel you want alerts in, and click **Allow**. -5. Copy the webhook URL. It looks like: - ``` - https://hooks.slack.com/services/TXXXXX/BXXXXX/XXXXXXXXXX - ``` - -### Using it with Trackio - -```python -trackio.init( - project="my-project", - webhook_url="https://hooks.slack.com/services/T.../B.../xxx", -) - -trackio.alert( - title="Training complete", - text="Final val_accuracy: 0.94", - level=trackio.AlertLevel.INFO, -) -``` - -### What it looks like - -Trackio sends Slack [Block Kit](https://api.slack.com/block-kit) messages with: -- A bold header with an emoji and severity level (e.g., "⚠️ **[WARN] Loss spike**") -- An optional description section with your `text` -- A context footer showing the project name, run name, and step number - ---- - -## Discord - -### Creating a Discord Webhook - -1. Open **Server Settings** → **Integrations** → **Webhooks**. -2. Click **New Webhook**. -3. Give it a name (e.g., "Trackio Alerts"), select the channel, and click **Copy Webhook URL**. -4. The URL looks like: - ``` - https://discord.com/api/webhooks/123456789/ABCDEFghijklmnop - ``` - -### Using it with Trackio - -```python -trackio.init( - project="my-project", - webhook_url="https://discord.com/api/webhooks/123456789/ABCDEFghijklmnop", -) - -trackio.alert( - title="GPU temperature critical", - text="GPU 0 reached 95°C", - level=trackio.AlertLevel.ERROR, -) -``` - -### What it looks like - -Trackio sends Discord [Embed](https://discord.com/developers/docs/resources/message#embed-object) messages with: -- A color-coded sidebar (blue for INFO, yellow for WARN, red for ERROR) -- A title with emoji and severity level -- A description with your `text` -- A footer with the project name, run name, and step number - diff --git a/trackio/main/en/api.md b/trackio/main/en/api.md deleted file mode 100644 index ac026df08ea45cba46616df31e148f0413d9d8df..0000000000000000000000000000000000000000 --- a/trackio/main/en/api.md +++ /dev/null @@ -1,1133 +0,0 @@ -# API Reference - -## Run[[trackio.Run]] - -#### trackio.Run[[trackio.Run]] - -```python -trackio.Run(url: str | None, project: str, client: typing.Optional[typing.Any], name: str | None = None, run_id: str | None = None, group: str | None = None, config: dict | None = None, space_id: str | None = None, bucket_id: str | None = None, server_base_url: str | None = None, write_token: str | None = None, existing_runs: list[str] | None = None, initial_last_step: int | None = None, auto_log_gpu: bool = False, gpu_log_interval: float = 10.0, auto_log_cpu: bool = False, cpu_log_interval: float = 10.0, webhook_url: str | None = None, webhook_min_level: trackio.alerts.AlertLevel | str | None = None, capture_console: bool = False) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/run.py#L46) - -#### link_artifact[[trackio.Run.link_artifact]] - -```python -link_artifact(artifact: Artifact, target_path: str, aliases: list[str] | None = None, bucket_id: str | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/run.py#L1683) - -**Parameters:** - -artifact (`Artifact`) : The artifact version to link. Must be an `Artifact` that has been logged or fetched. To link a specific existing version, fetch it first with `use_artifact("my-model:v3")` and link the result. An artifact that was never logged is logged to this run's project first. - -target_path (`str`) : The collection to link into, as `"registry-/"`, e.g. `"registry-models/my-model"`. The registry must already exist (see `trackio.Api().create_registry`). The collection is created on first link and adopts the artifact's type; later links must match it. - -aliases (`list[str]`, *optional*) : Aliases to place on the linked version, e.g. `["staging"]`. An alias points at one version per collection, so assigning an alias that another version holds moves it. `latest` is managed automatically and always follows the newest linked version; passing it here is a no-op. - -bucket_id (`str`, *optional*) : Hugging Face bucket holding the registry, e.g. `"my-org/models-registry"`. Required to link from a run that logs to a Space or a self-hosted server. Omit for a local registry; defaults to `TRACKIO_REGISTRY_BUCKET_ID` when that is set. - -**Returns:** - -The linked artifact at its registry location. Its `name` is the -collection, its `project` is the registry's project, and its -`version` and `aliases` are the collection's. Its content -(`manifest`, `manifest_digest`, `size`, `metadata`) is the -source version's, and the `source_project`, `source_name`, -`source_version`, and `source_qualified_name` properties point -back at it. `download()` fetches the source version's files. When -the source was fetched from a Space or self-hosted server, this -works on the linked artifact returned by this call; resolving that -registry location in a later process is not supported yet. - -Link an artifact version into a registry collection. - -A link is a pointer to the source version: no files are copied. The -link gets the next version number in the collection (`v0`, `v1`, -...), independent of the source artifact's own version numbers. -Linking a version that is already in the collection does not create -a new one: you get the existing version back, and the `aliases` you -pass still move. - -A local registry records the link alongside the run's data, so it is -only available to runs on this machine. Pass `bucket_id` to publish -into a bucket-backed registry instead — that is also how a run that -logs to a Space or a self-hosted server publishes, since the bucket is -reachable from both sides. - -#### use_artifact[[trackio.Run.use_artifact]] - -```python -use_artifact(artifact_or_name: trackio.artifact.Artifact | str, type: str | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/run.py#L1502) - -Resolve an artifact and record this run as a consumer of it. - -The spec is either a project artifact (`"name"`, `"name:vN"`, -`"name:alias"`) or a registry location -(`"registry-/[:vN|:alias]"`), which resolves -through the collection's links to the source version it points at. - -## init[[trackio.init]] - -#### trackio.init[[trackio.init]] - -```python -trackio.init(project: str, name: str | None = None, group: str | None = None, space_id: str | None = None, server_url: str | None = None, dataset_id: str | None = None, bucket_id: str | None = None, config: dict | None = None, resume: str = 'never', settings: typing.Any = None, private: bool | None = None, embed: bool = True, auto_log_gpu: bool | None = None, gpu_log_interval: float = 10.0, auto_log_cpu: bool | None = None, cpu_log_interval: float = 10.0, webhook_url: str | None = None, webhook_min_level: trackio.alerts.AlertLevel | str | None = None, capture_console: bool | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/__init__.py#L300) - -**Parameters:** - -project (*str*) : The name of the project (can be an existing project to continue tracking or a new project to start tracking from scratch). - -name (*str*, *optional*) : The name of the run (if not provided, a default name will be generated). - -group (*str*, *optional*) : The name of the group which this run belongs to in order to help organize related runs together. You can toggle the entire group's visibility in the dashboard. - -space_id (*str*, *optional*) : If provided, the project will be logged to a Hugging Face Space instead of a local directory. Should be a complete Space name like *"username/reponame"* or *"orgname/reponame"*, or just *"reponame"* in which case the Space will be created in the currently-logged-in Hugging Face user's namespace. If the Space does not exist, it will be created. If the Space already exists, the project will be logged to it. Can also be set via the *TRACKIO_SPACE_ID* environment variable. You cannot log to a Space that has been **frozen** (converted to the static SDK); use `trackio.sync(..., sdk="static")` only after you are done logging. Takes precedence over *server_url* and *TRACKIO_SERVER_URL* when more than one is set. - -server_url (*str*, *optional*) : Base URL of a self-hosted Trackio server (`http://` or `https://`), or the write-access URL from `trackio.show()` which may include a `write_token` query parameter. The client sends that token on each request (`X-Trackio-Write-Token`); you can also set `TRACKIO_WRITE_TOKEN` instead of embedding the token in the URL. When set, metrics are sent to that server over HTTP instead of creating or syncing to a Hugging Face Space. Can also be set via the `TRACKIO_SERVER_URL` environment variable. Ignored when `space_id` or `TRACKIO_SPACE_ID` is set. - -dataset_id (*str*, *optional*) : Deprecated: persisting trackio data to a Hugging Face Dataset will be removed in a future version of trackio. Use *bucket_id* (a Hugging Face Bucket) instead. - -bucket_id (*str*, *optional*) : The ID of the Hugging Face Bucket to use for metric persistence. By default, when a *space_id* is provided and *bucket_id* is not explicitly set, a bucket is auto-generated from the space_id. Buckets provide S3-like storage without git overhead - the SQLite database is stored directly via *hf-mount* in the Space. Specify a Bucket with name like *"username/bucketname"* or just *"bucketname"*. - -config (*dict*, *optional*) : A dictionary of configuration options. Provided for compatibility with *wandb.init()*. - -resume (*str*, *optional*, defaults to *"never"*) : Controls how to handle resuming a run. Can be one of: - *"must"*: Must resume the run with the given name, raises error if run doesn't exist - *"allow"*: Resume the run if it exists, otherwise create a new run - *"never"*: Never resume a run, always create a new one - -private (*bool*, *optional*) : Whether to make the Space private. If None (default), the repo will be public unless the organization's default is private. This value is ignored if the repo already exists. - -settings (*Any*, *optional*) : Not used. Provided for compatibility with *wandb.init()*. - -embed (*bool*, *optional*, defaults to *True*) : If running inside a Jupyter/Colab notebook, whether the dashboard should automatically be embedded in the cell when trackio.init() is called. For local runs, this launches a local Trackio dashboard and embeds it. For Space runs, this embeds the Space URL. In Colab, the local dashboard will be accessible via a public share URL when *share=True*. - -auto_log_gpu (*bool* or *None*, *optional*, defaults to *None*) : Controls automatic GPU metrics logging. If *None* (default), GPU logging is automatically enabled when *nvidia-ml-py* is installed and an NVIDIA GPU or Apple M series is detected. Set to *True* to force enable or *False* to disable. - -gpu_log_interval (*float*, *optional*, defaults to *10.0*) : The interval in seconds between automatic GPU metric logs. Only used when *auto_log_gpu=True*. - -auto_log_cpu (*bool* or *None*, *optional*, defaults to *None*) : Controls automatic CPU and RAM metrics logging (utilization, memory, disk I/O, network I/O, and sensors). If *None* (default), CPU logging is automatically enabled when *psutil* is installed. Set to *True* to force enable or *False* to disable. - -cpu_log_interval (*float*, *optional*, defaults to *10.0*) : The interval in seconds between automatic CPU metric logs. Only used when CPU auto-logging is enabled. - -webhook_url (*str*, *optional*) : A webhook URL to POST alert payloads to when *trackio.alert()* is called. Supports Slack and Discord webhook URLs natively (payloads are formatted automatically). Can also be set via the *TRACKIO_WEBHOOK_URL* environment variable. Individual alerts can override this URL by passing *webhook_url* to *trackio.alert()*. - -webhook_min_level (*AlertLevel* or *str*, *optional*) : Minimum alert level that should trigger webhook delivery. For example, *AlertLevel.WARN* sends only *WARN* and *ERROR* alerts to the webhook destination. Can also be set via *TRACKIO_WEBHOOK_MIN_LEVEL*. - -capture_console (*bool* or *None*, *optional*, defaults to *None*) : Whether to capture everything the script writes to stdout and stderr (including *print()* and *logging* output) and store it with the run. The output is shown in the run's page of the dashboard, where it can also be downloaded. If *None* (default), console capture is enabled only when the *TRACKIO_CAPTURE_CONSOLE* environment variable is set to *1* or *true*. - -**Returns:** `*Run*` - -A [*Run*] object that can be used to log metrics and finish the run. - -Creates a new Trackio project and returns a [*Run*] object. - -## log[[trackio.log]] - -#### trackio.log[[trackio.log]] - -```python -trackio.log(metrics: dict, step: int | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/__init__.py#L752) - -**Parameters:** - -metrics (`dict`) : A dictionary of metrics to log. - -step (`int`, *optional*) : The step number. If not provided, the step will be incremented automatically. - -Logs metrics to the current run. - -## log_gpu[[trackio.log_gpu]] - -#### trackio.log_gpu[[trackio.log_gpu]] - -```python -trackio.log_gpu(run: trackio.run.Run | None = None, device: int | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/__init__.py#L860) - -**Parameters:** - -run : Optional Run instance. If None, uses current run from context. - -device : CUDA device index to collect metrics from (NVIDIA GPUs only). If None, collects from all GPUs visible to this process. This parameter is ignored for Apple GPUs. - -**Returns:** `dict` - -The GPU metrics that were logged. - -Log GPU metrics to the current or specified run as system metrics. -Automatically detects whether an NVIDIA or Apple GPU is available and calls -the appropriate logging method. - -Example: -```python -import trackio - -run = trackio.init(project="my-project") -trackio.log({"loss": 0.5}) -trackio.log_gpu() -trackio.log_gpu(device=0) -``` - -## log_system[[trackio.log_system]] - -#### trackio.log_system[[trackio.log_system]] - -```python -trackio.log_system(metrics: dict) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/__init__.py#L772) - -**Parameters:** - -metrics (`dict`) : A dictionary of system metrics to log. - -Logs system metrics (GPU, etc.) to the current run using timestamps instead of steps. - -## log_artifact[[trackio.log_artifact]] - -#### trackio.log_artifact[[trackio.log_artifact]] - -```python -trackio.log_artifact(artifact_or_path: trackio.artifact.Artifact | str | pathlib.Path, name: str | None = None, type: str | None = None, aliases: list[str] | None = None, overwrite: bool = False) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/__init__.py#L786) - -**Parameters:** - -artifact_or_path (`Artifact`, `str`, or `Path`) : The artifact to log (must have at least one file added via `add_file` or `add_dir`), or a path to a file or directory to log as a new artifact. - -name (`str`, *optional*) : Artifact name when logging a path. Defaults to `run--`. Must not be passed with an `Artifact`. - -type (`str`, *optional*) : Artifact type when logging a path (e.g. `"model"`, `"dataset"`). Defaults to `"unspecified"`. Must not be passed with an `Artifact`. - -aliases (`list[str]`, *optional*) : Aliases to rotate onto the resulting version, alongside `latest` (assigned automatically whenever a new version is created). Your aliases rotate onto the version even when identical content is de-duplicated. - -overwrite (`bool`, *optional*) : If `True`, removes every other version of this artifact after the new content is logged. Blobs still used by other artifacts are preserved, and version numbers continue increasing. Defaults to `False`. - -**Returns:** - -The logged `Artifact` instance, hydrated with `version`, `aliases`, -`size`, `manifest`, and `project` set. - -Logs an artifact as an output of the current run. - -## use_artifact[[trackio.use_artifact]] - -#### trackio.use_artifact[[trackio.use_artifact]] - -```python -trackio.use_artifact(artifact_or_name: trackio.artifact.Artifact | str, type: str | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/__init__.py#L835) - -**Parameters:** - -artifact_or_name (`Artifact` or `str`) : An already-logged `Artifact`, or an artifact name. A bare name (`"my-model"`) resolves to `:latest`; you can also pin a version (`"my-model:v3"`) or resolve an alias (`"my-model:prod"`). - -type (`str`, *optional*) : If given, checked against the stored artifact type, raising if it does not match. - -**Returns:** - -The fetched `Artifact`, hydrated and ready to `download()`. - -Fetches an artifact and records it as an input to the current run. - -## finish[[trackio.finish]] - -#### trackio.finish[[trackio.finish]] - -```python -trackio.finish() -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/__init__.py#L930) - -Finishes the current run. - -## show[[trackio.show]] - -#### trackio.show[[trackio.show]] - -```python -trackio.show(project: str | None = None, dashboard: str | None = None, theme: typing.Any = None, mcp_server: bool | None = None, footer: bool = True, color_palette: list[str] | None = None, open_browser: bool = True, block_thread: bool | None = None, host: str | None = None, share: bool | None = None, server_port: int | None = None, frontend_dir: str | pathlib.Path | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/__init__.py#L1182) - -**Parameters:** - -project (`str`, *optional*) : The name of the project whose runs to show. If not provided, all projects will be shown and the user can select one. - -dashboard (`str`, *optional*) : Set to `"registry"` to show the standalone registry dashboard. The default is the project dashboard. - -theme (`Any`, *optional*) : Ignored. Kept for backward compatibility; Trackio no longer uses Gradio themes. - -mcp_server (`bool`, *optional*) : If `True`, the dashboard exposes an MCP server at `/mcp` when the optional `trackio[mcp]` dependency is installed. If `None` (default), the `GRADIO_MCP_SERVER` environment variable is used (e.g. on Spaces). - -footer (`bool`, *optional*, defaults to `True`) : Whether to include `footer=false` in the write-token URL when `False`. This can also be controlled via the `footer` query parameter in the URL. - -color_palette (`list[str]`, *optional*) : A list of hex color codes to use for plot lines. If not provided, the `TRACKIO_COLOR_PALETTE` environment variable will be used (comma-separated hex codes), or if that is not set, the default color palette will be used. Example: `['#FF0000', '#00FF00', '#0000FF']` - -open_browser (`bool`, *optional*, defaults to `True`) : If `True` and not in a notebook, a new browser tab will be opened with the dashboard. If `False`, the browser will not be opened. - -block_thread (`bool`, *optional*) : If `True`, the main thread will be blocked until the dashboard is closed. If `None` (default behavior), then the main thread will not be blocked if the dashboard is launched in a notebook, otherwise the main thread will be blocked. - -host (`str`, *optional*) : The host to bind the server to. If not provided, defaults to `'127.0.0.1'` (localhost only). Set to `'0.0.0.0'` to allow remote access. - -share (`bool`, *optional*) : If `True`, creates a temporary public URL (Gradio-compatible tunnel). On Colab or hosted notebooks, defaults to `True` unless overridden. - -server_port (`int`, *optional*) : Port to bind. If not set, scans from `GRADIO_SERVER_PORT` (default 7860). - -frontend_dir (`str | Path`, *optional*) : Directory containing a custom static frontend. Must contain `index.html`. If not provided, Trackio checks `TRACKIO_FRONTEND_DIR`, then the persistent Trackio config, then the bundled frontend. If an explicit `frontend_dir` points to a missing or empty directory, Trackio copies in the starter template and serves that directory. - -**Returns:** `app` - -The dashboard handle (`.close()` stops the server). -`url`: The local URL of the dashboard. -`share_url`: The public share URL, if any. -`full_url`: The full URL including the write token (share URL when sharing, else local). - -Launches the Trackio dashboard. - -## sync[[trackio.sync]] - -#### trackio.sync[[trackio.sync]] - -```python -trackio.sync(project: str, space_id: str | None = None, private: bool | None = None, force: bool = False, run_in_background: bool = False, sdk: str = 'gradio', dataset_id: str | None = None, bucket_id: str | None = None, frontend_dir: str | pathlib.Path | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/deploy.py#L1072) - -**Parameters:** - -project (*str*) : The name of the project to upload. - -space_id (*str*, *optional*) : The ID of the Space to upload to (e.g., *"username/space_id"*). If not provided, checks project metadata first, then generates a random space_id. - -private (*bool*, *optional*) : Whether to make the Space private. If None (default), the repo will be public unless the organization's default is private. This value is ignored if the repo already exists. Not supported with `sdk="static"` because static Trackio dashboards read snapshot data directly from the browser. - -force (*bool*, *optional*, defaults to *False*) : If *True*, overwrite the existing database without prompting for confirmation. If *False*, prompt the user before overwriting an existing database. - -run_in_background (*bool*, *optional*, defaults to *False*) : If *True*, the Space creation and database upload will be run in a background thread. If *False*, all the steps will be run synchronously. - -sdk (*str*, *optional*, defaults to *"gradio"*) : The type of Space to deploy. *"gradio"* deploys a Gradio Space with a live server. *"static"* freezes the Space: deploys a static Space that reads from an HF Bucket (no server needed). - -dataset_id (*str*, *optional*) : Deprecated: persisting trackio data to a Hugging Face Dataset will be removed in a future version of trackio. Use *bucket_id* (a Hugging Face Bucket) instead. - -bucket_id (*str*, *optional*) : The ID of the HF Bucket to sync to. By default, a bucket is auto-generated from the space_id. - -**Returns:** `*str*` - -The Space ID of the synced project. - -Syncs a local Trackio project's database to a Hugging Face Space. -If the Space does not exist, it will be created. Local data is never deleted. - -**Freezing:** Passing `sdk="static"` deploys a static Space backed by an HF Bucket -(read-only dashboard, no Gradio server). You can sync the same project again later to -refresh that static Space. If you want a one-time snapshot of an existing Gradio Space, -use `freeze()` instead. - -## freeze[[trackio.freeze]] - -#### trackio.freeze[[trackio.freeze]] - -```python -trackio.freeze(space_id: str, project: str, new_space_id: str | None = None, private: bool | None = None, bucket_id: str | None = None, frontend_dir: str | pathlib.Path | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/deploy.py#L1227) - -**Parameters:** - -space_id (`str`) : The ID of the source Gradio Space (e.g., `"username/my-space"` or a short repo name with the logged-in namespace inferred, like `init()`). Must be a Gradio Space with a bucket mounted at `/data`. - -project (`str`) : The name of the project whose data to include in the frozen Space. - -new_space_id (`str`, *optional*) : The ID for the new static Space. If not provided, defaults to `"{space_id}_static"`. - -private (`bool`, *optional*) : Not supported. Frozen static dashboards read snapshot data directly from the browser, so the destination snapshot must be public. - -bucket_id (`str`, *optional*) : The ID of the HF Bucket for the new static Space's data storage. If not provided, one is auto-generated from the new Space ID. - -**Returns:** `str` - -The Space ID of the newly created static Space. - -Creates a new static Hugging Face Space containing a read-only snapshot of -the data for the specified project from the source Gradio Space. The data is -read from the bucket attached to the source Space at freeze time. The original -Space is not modified, and the new static Space does not automatically reflect -metrics uploaded to the original Gradio Space after the freeze completes. - -## delete_project[[trackio.delete_project]] - -#### trackio.delete_project[[trackio.delete_project]] - -```python -trackio.delete_project(project: str, force: bool = False) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/__init__.py#L976) - -**Parameters:** - -project (`str`) : The name of the project to delete. - -force (`bool`, *optional*, defaults to `False`) : If `True`, deletes the project without prompting for confirmation. If `False`, prompts the user to confirm before deleting. - -**Returns:** `bool` - -`True` if the project was deleted, `False` otherwise. - -Deletes a project by removing its local SQLite database. - -## import_csv[[trackio.import_csv]] - -#### trackio.import_csv[[trackio.import_csv]] - -```python -trackio.import_csv(csv_path: str | pathlib.Path, project: str, name: str | None = None, space_id: str | None = None, dataset_id: str | None = None, private: bool | None = None, force: bool = False) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/imports.py#L9) - -**Parameters:** - -csv_path (`str` or `Path`) : The str or Path to the CSV file to import. - -project (`str`) : The name of the project to import the CSV file into. Must not be an existing project. - -name (`str`, *optional*) : The name of the Run to import the CSV file into. If not provided, a default name will be generated. - -name (`str`, *optional*) : The name of the run (if not provided, a default name will be generated). - -space_id (`str`, *optional*) : If provided, the project will be logged to a Hugging Face Space instead of a local directory. Should be a complete Space name like `"username/reponame"` or `"orgname/reponame"`, or just `"reponame"` in which case the Space will be created in the currently-logged-in Hugging Face user's namespace. If the Space does not exist, it will be created. If the Space already exists, the project will be logged to it. - -dataset_id (`str`, *optional*) : Deprecated: persisting trackio data to a Hugging Face Dataset will be removed in a future version of trackio. Use `bucket_id` (a Hugging Face Bucket) instead. - -private (`bool`, *optional*) : Whether to make the Space private. If None (default), the repo will be public unless the organization's default is private. This value is ignored if the repo already exists. - -Imports a CSV file into a Trackio project. The CSV file must contain a `"step"` -column, may optionally contain a `"timestamp"` column, and any other columns will be -treated as metrics. It should also include a header row with the column names. - -TODO: call init() and return a Run object so that the user can continue to log metrics to it. - -## import_tf_events[[trackio.import_tf_events]] - -#### trackio.import_tf_events[[trackio.import_tf_events]] - -```python -trackio.import_tf_events(log_dir: str | pathlib.Path, project: str, name: str | None = None, space_id: str | None = None, dataset_id: str | None = None, private: bool | None = None, force: bool = False) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/imports.py#L163) - -**Parameters:** - -log_dir (`str` or `Path`) : The str or Path to the directory containing TensorFlow Events files. - -project (`str`) : The name of the project to import the TensorFlow Events files into. Must not be an existing project. - -name (`str`, *optional*) : The name prefix for runs (if not provided, will use directory names). Each subdirectory will create a separate run. - -space_id (`str`, *optional*) : If provided, the project will be logged to a Hugging Face Space instead of a local directory. Should be a complete Space name like `"username/reponame"` or `"orgname/reponame"`, or just `"reponame"` in which case the Space will be created in the currently-logged-in Hugging Face user's namespace. If the Space does not exist, it will be created. If the Space already exists, the project will be logged to it. - -dataset_id (`str`, *optional*) : Deprecated: persisting trackio data to a Hugging Face Dataset will be removed in a future version of trackio. Use `bucket_id` (a Hugging Face Bucket) instead. - -private (`bool`, *optional*) : Whether to make the Space private. If None (default), the repo will be public unless the organization's default is private. This value is ignored if the repo already exists. - -Imports TensorFlow Events files from a directory into a Trackio project. Each -subdirectory in the log directory will be imported as a separate run. - -## save[[trackio.save]] - -#### trackio.save[[trackio.save]] - -```python -trackio.save(glob_str: str | pathlib.Path, project: str | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/__init__.py#L1031) - -**Parameters:** - -glob_str (`str` or `Path`) : The file path or glob pattern to save. Can be a single file or a pattern matching multiple files (e.g., `"*.py"`, `"models/**/*.pth"`). - -project (`str`, *optional*) : The name of the project to save files to. If not provided, uses the current project from `trackio.init()`. If no project is initialized, raises an error. - -**Returns:** `str` - -The path where the file(s) were saved (project's files directory). - -Saves files to a project (not linked to a specific run). If Trackio is running -locally, the file(s) will be copied to the project's files directory. If Trackio is -running in a Space, the file(s) will be uploaded to the Space's files directory. - -Example: -```python -import trackio - -trackio.init(project="my-project") -trackio.save("config.yaml") -trackio.save("models/*.pth") -``` - -## Artifact[[trackio.Artifact]] - -#### trackio.Artifact[[trackio.Artifact]] - -```python -trackio.Artifact(name: str, type: str, description: str | None = None, metadata: dict | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/artifact.py#L114) - -**Parameters:** - -name (`str`) : Artifact name, unique within the project. Must match `^[A-Za-z0-9._-]+$` (letters, digits, dot, underscore, hyphen). - -type (`str`) : Free-form category such as `"model"` or `"dataset"`, used to group artifacts. - -description (`str`, *optional*) : Human-readable description of the artifact. - -metadata (`dict`, *optional*) : Arbitrary JSON-serializable metadata stored alongside the version. - -A versioned, named bundle of files and references attached to a project. - -Construct an `Artifact`, add files to it with `add_file` / `add_dir` -(bytes staged into content-addressed storage) or `add_reference` (an -external URI recorded without copying any bytes), then persist it with -`trackio.log_artifact`. Logging freezes the artifact and populates its -read-only `version`, `aliases`, `size`, and `manifest`. - -#### add_dir[[trackio.Artifact.add_dir]] - -```python -add_dir(local_dir: str | pathlib.Path, name: str | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/artifact.py#L316) - -**Parameters:** - -local_dir (`str` or `Path`) : Path to an existing directory whose files are added. - -name (`str`, *optional*) : Logical path prefix for the added files. Defaults to no prefix, so files keep their paths relative to `local_dir`. - -Stage every regular file under a directory, recursively. - -Symlinks are skipped. - -#### add_file[[trackio.Artifact.add_file]] - -```python -add_file(local_path: str | pathlib.Path, name: str | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/artifact.py#L296) - -**Parameters:** - -local_path (`str` or `Path`) : Path to an existing regular file to add. - -name (`str`, *optional*) : Logical path the file is stored under inside the artifact. Defaults to the file's basename. - -Stage a single file for inclusion in the artifact. - -#### add_reference[[trackio.Artifact.add_reference]] - -```python -add_reference(uri: str, name: str | None = None, checksum: bool = True, max_objects: int | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/artifact.py#L346) - -**Parameters:** - -uri (`str`) : Location of the referenced data, percent-encoded (build local URIs with `pathlib.Path.as_uri()`). `file://`, `http(s)://`, and `hf://` are resolved and fetched natively; any other scheme (`s3://`, `gs://`, Azure blob URLs, ...) requires a custom `ReferenceHandler` registered via `trackio.register_reference_handler` — see the artifacts documentation for complete examples — and raises otherwise. - -name (`str`, *optional*) : Logical path the reference is stored under. Defaults to the last segment of `uri`; for an expanded prefix (ending with /) it is the prefix under which each object's relative path is nested. - -checksum (`bool`, *optional*, defaults to `True`) : When `True`, probes the source to derive its size and a checksum (and to expand a directory/prefix): `file://` is stream-hashed to a sha256, `hf://` uses its LFS sha256 or git blob id, and `http(s)://` uses the server `ETag`. This may read the filesystem or make network requests. When no checksum can be obtained for a *remote* source (e.g. no ETag), the URI itself is used as the `digest` and a warning is emitted. A local `file://` path that does not exist instead raises. Pass `checksum=False` to skip remote probing entirely. - -max_objects (`int`, *optional*) : Cap on how many objects a directory/prefix expands into (default 10,000); exceeding it raises. - -Stage a reference to external data, without copying any bytes. - -Unlike `add_file`/`add_dir`, a reference records the data's URI (plus, -when available, a size and checksum) *without staging the bytes into -the content-addressed store*. This is how you version and track -lineage over large or already-durably-stored datasets that must not be -duplicated. - -A URI that denotes a directory (`file://`, `hf://`, or a prefix -expanded by a custom handler) is expanded into one entry per object, -capped by `max_objects`. Reference bytes are never uploaded to a Space -or bucket. - -The URI is stored verbatim in the artifact manifest, and manifests may -be synced to a shared Hugging Face Dataset — so a signed URI triggers a -warning for security reasons; please prefer the object's canonical -unsigned URI (e.g. `s3://bucket/key`). - -#### download[[trackio.Artifact.download]] - -```python -download(root: str | pathlib.Path | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/artifact.py#L497) - -**Parameters:** - -root (`str` or `Path`, *optional*) : Directory to write the files into. Defaults to `./.trackio/artifact-downloads//_v/`, keyed by project so same-named artifacts from different projects never collide, and by the resolved version so a moving alias like `latest` never leaves behind stale files from a previous version. - -**Returns:** - -The absolute path to the download directory, as a string. - -Materialize the artifact's files into a local directory. - -Files are copied from Trackio's content-addressed cache (and fetched -from the remote when missing locally), so repeated calls are cheap and -idempotent. - -Reference entries added via `add_reference` are fetched here too: the -object at each reference URI is downloaded into the directory (via the -bundled `httpx2` for `http(s)://`, `huggingface_hub` for `hf://`, and -the registered custom `ReferenceHandler` for any other scheme). Each -object is written atomically and calls are idempotent. Because reference digests -are opaque (a provider ETag or the URI itself), a present file is assumed -current and is not re-verified against the source, and a source whose -re-probed checksum no longer matches the recorded one is downloaded -anyway with a warning. Downloading can transfer a large amount of data; -to work with the URIs without downloading, read them from the `references` -property or `get_entry_uri` instead. A missing source, an unreachable -server, or a scheme with no registered handler raises. - -#### get_entry_uri[[trackio.Artifact.get_entry_uri]] - -```python -get_entry_uri(name: str) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/artifact.py#L758) - -Return the URI recorded for the reference entry at logical path -`name`, or None if there is no reference entry with that name. - -#### link[[trackio.Artifact.link]] - -```python -link(target_path: str, aliases: list[str] | None = None, bucket_id: str | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/artifact.py#L572) - -**Parameters:** - -target_path (`str`) : The collection to link into, as `"registry-/"`. The registry must already exist. - -aliases (`list[str]`, *optional*) : Aliases to place on the linked version. `latest` is managed automatically; passing it is a no-op. - -bucket_id (`str`, *optional*) : Bucket holding the registry, e.g. `"my-org/models-registry"`. Omit for a local registry; defaults to `TRACKIO_REGISTRY_BUCKET_ID` when that is set. - -**Returns:** - -The linked artifact at its registry location. - -Link this artifact version into a registry collection. - -A link is a pointer to this version: no files are copied. See -`Run.link_artifact` for the full semantics (collection versioning, -aliases, and the returned linked artifact). - -The artifact must already be logged or fetched; unlike -`Run.link_artifact`, this does not log a draft artifact for you, and -the link records no publishing run. An artifact fetched from a Space or -a self-hosted server can only be linked into a bucket-backed registry, -since a local registry is not reachable from where its bytes live. - -#### unlink[[trackio.Artifact.unlink]] - -```python -unlink() -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/artifact.py#L617) - -Remove this registry link. - -Call this on the linked artifact returned by `link` or -`Run.link_artifact`, not on a source artifact version. The source -artifact and its files are untouched; only the collection membership -is removed. Aliases pointing at the link go with it, and the -collection version number is never reused. If the version held -`latest`, that alias moves to the highest remaining version. - -#### wait[[trackio.Artifact.wait]] - -```python -wait(timeout: int | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/artifact.py#L286) - -No-op: trackio logs artifacts synchronously, so the artifact is -already committed by the time `log_artifact` returns. - -## Registry[[trackio.Registry]] - -#### trackio.Registry[[trackio.Registry]] - -```python -trackio.Registry(name: str, bucket_id: str | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/registry.py#L51) - -**Parameters:** - -name (`str`) : Registry name, e.g. `"models"`. Must match `^[A-Za-z0-9_-]+$` (letters, digits, underscore, hyphen). - -bucket_id (`str`, *optional*) : Hugging Face bucket holding the registry, e.g. `"my-org/models-registry"`. Omit for a local registry. Defaults to `TRACKIO_REGISTRY_BUCKET_ID` when that is set. - -A handle on one artifact registry. - -A registry is a shared catalog of artifact versions, organized into -collections. You publish into it with `Run.link_artifact` and promote -versions by moving aliases such as `"staging"` or `"production"`. See -the Registry guide for the full picture. - -You do not construct a `Registry` yourself. Create a registry with -`trackio.Api().create_registry(name)` or fetch an existing one with -`trackio.Api().registry(name)`; both return this handle. - -Example: -```python -import trackio - -registry = trackio.Api().create_registry("models") -registry.create_collection( - "my-model", artifact_type="model", description="My favorite model" -) - -run = trackio.init(project="my-experiments") -artifact = trackio.log_artifact("model.pt", name="resnet", type="model") -run.link_artifact(artifact, "registry-models/my-model", aliases=["staging"]) -trackio.finish() - -registry.collection("my-model").links -``` - -#### collection[[trackio.Registry.collection]] - -```python -collection(name: str) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/registry.py#L145) - -Describe one collection. - -Returns None if the registry or the collection does not exist. - -#### collections[[trackio.Registry.collections]] - -```python -collections() -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/registry.py#L163) - -List the registry's collections, links included. - -Returns an empty list if the registry does not exist. - -#### create_collection[[trackio.Registry.create_collection]] - -```python -create_collection(name: str, artifact_type: str, description: str | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/registry.py#L113) - -**Parameters:** - -name (`str`) : Collection name, unique within the registry. Must match `^[A-Za-z0-9._-]+$`. - -artifact_type (`str`) : The artifact type the collection accepts, e.g. `"model"` or `"dataset"`. The type is fixed at creation; linking an artifact of a different type raises. - -description (`str`, *optional*) : Human-readable description of the collection. - -**Returns:** - -The [Collection](/docs/trackio/main/en/api#trackio.Collection). - -Create a collection in this registry. - -Collections are also created automatically on first link, so this -is mainly useful to set a description up front. If the collection -already exists, it is returned as-is and a non-None `description` -is applied. - -#### events[[trackio.Registry.events]] - -```python -events() -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/registry.py#L172) - -Return the registry's audit log, oldest event first. - -Each event has an `id`, a `ts` timestamp, a `kind` (`"create"`, -`"link"`, `"promote"`, `"update"`, or `"unlink"`), and a `payload` -describing the mutation. A `create` payload without a `collection` -key records the creation of the registry itself. - -## Collection[[trackio.Collection]] - -#### trackio.Collection[[trackio.Collection]] - -```python -trackio.Collection(name: str, type: str, description: str | None, created_at: str, num_links: int, latest_version: int | None, links: list[dict]) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/registry.py#L20) - -A read-only snapshot of one registry collection. - -Returned by `Registry.create_collection`, `Registry.collection`, and -`Registry.collections`. - -## Image[[trackio.TrackioImage]] - -#### trackio.TrackioImage[[trackio.TrackioImage]] - -```python -trackio.TrackioImage(value: str | pathlib.Path | numpy.ndarray | PIL.Image.Image, caption: str | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/media/image.py#L13) - -**Parameters:** - -value (`str`, `Path`, `numpy.ndarray`, or `PIL.Image`, *optional*) : A path to an image, a PIL Image, or a numpy array of shape (height, width, channels). If numpy array, should be of type `np.uint8` with RGB values in the range `[0, 255]`. - -caption (`str`, *optional*) : A string caption for the image. - -Initializes an Image object. - -Example: -```python -import trackio -import numpy as np -from PIL import Image - -# Create an image from numpy array -image_data = np.random.randint(0, 255, (64, 64, 3), dtype=np.uint8) -image = trackio.Image(image_data, caption="Random image") -trackio.log({"my_image": image}) - -# Create an image from PIL Image -pil_image = Image.new('RGB', (100, 100), color='red') -image = trackio.Image(pil_image, caption="Red square") -trackio.log({"red_image": image}) - -# Create an image from file path -image = trackio.Image("path/to/image.jpg", caption="Photo from file") -trackio.log({"file_image": image}) -``` - -## Video[[trackio.TrackioVideo]] - -#### trackio.TrackioVideo[[trackio.TrackioVideo]] - -```python -trackio.TrackioVideo(value: str | pathlib.Path | numpy.ndarray, caption: str | None = None, fps: int | None = None, format: typing.Optional[typing.Literal['gif', 'mp4', 'webm']] = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/media/video.py#L17) - -**Parameters:** - -value (`str`, `Path`, or `numpy.ndarray`, *optional*) : A path to a video file, or a numpy array. If numpy array, should be of type `np.uint8` with RGB values in the range `[0, 255]`. It is expected to have shape of either (frames, channels, height, width) or (batch, frames, channels, height, width). For the latter, the videos will be tiled into a grid. - -caption (`str`, *optional*) : A string caption for the video. - -fps (`int`, *optional*) : Frames per second for the video. Only used when value is an ndarray. Default is `24`. - -format (`Literal["gif", "mp4", "webm"]`, *optional*) : Video format ("gif", "mp4", or "webm"). Only used when value is an ndarray. Default is "gif". - -Initializes a Video object. - -Example: -```python -import trackio -import numpy as np - -# Create a simple video from numpy array -frames = np.random.randint(0, 255, (10, 3, 64, 64), dtype=np.uint8) -video = trackio.Video(frames, caption="Random video", fps=30) - -# Create a batch of videos -batch_frames = np.random.randint(0, 255, (3, 10, 3, 64, 64), dtype=np.uint8) -batch_video = trackio.Video(batch_frames, caption="Batch of videos", fps=15) - -# Create video from file path -video = trackio.Video("path/to/video.mp4", caption="Video from file") -``` - -#### write_video[[trackio.TrackioVideo.write_video]] - -```python -write_video(file_path: str | pathlib.Path, video: ndarray, fps: float, codec: typing.Literal['h264', 'vp9', 'gif']) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/media/video.py#L93) - -RGB uint8 only, shape (F, H, W, 3). - -## Audio[[trackio.TrackioAudio]] - -#### trackio.TrackioAudio[[trackio.TrackioAudio]] - -```python -trackio.TrackioAudio(value: str | pathlib.Path | numpy.ndarray, caption: str | None = None, sample_rate: int | None = None, format: typing.Optional[typing.Literal['wav', 'mp3']] = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/media/audio.py#L19) - -**Parameters:** - -value (`str`, `Path`, or `numpy.ndarray`, *optional*) : A path to an audio file, or a numpy array. The array should be shaped `(samples,)` for mono or `(samples, 2)` for stereo. Float arrays will be peak-normalized and converted to 16-bit PCM; integer arrays will be converted to 16-bit PCM as needed. - -caption (`str`, *optional*) : A string caption for the audio. - -sample_rate (`int`, *optional*) : Sample rate in Hz. Required when `value` is a numpy array. - -format (`Literal["wav", "mp3"]`, *optional*) : Audio format used when `value` is a numpy array. Default is "wav". - -Initializes an Audio object. - -Example: -```python -import trackio -import numpy as np - -# Generate a 1-second 440 Hz sine wave (mono) -sr = 16000 -t = np.linspace(0, 1, sr, endpoint=False) -wave = 0.2 * np.sin(2 * np.pi * 440 * t) -audio = trackio.Audio(wave, caption="A4 sine", sample_rate=sr, format="wav") -trackio.log({"tone": audio}) - -# Stereo from numpy array (shape: samples, 2) -stereo = np.stack([wave, wave], axis=1) -audio = trackio.Audio(stereo, caption="Stereo", sample_rate=sr, format="mp3") -trackio.log({"stereo": audio}) - -# From an existing file -audio = trackio.Audio("path/to/audio.wav", caption="From file") -trackio.log({"file_audio": audio}) -``` - -#### ensure_int16_pcm[[trackio.TrackioAudio.ensure_int16_pcm]] - -```python -ensure_int16_pcm(data: ndarray) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/media/audio.py#L90) - -Convert input audio array to contiguous int16 PCM. -Peak normalization is applied to floating inputs. - -## Object3D[[trackio.TrackioObject3D]] - -#### trackio.TrackioObject3D[[trackio.TrackioObject3D]] - -```python -trackio.TrackioObject3D(path_or_array: str | pathlib.Path | numpy.ndarray, caption: str | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/media/object3d.py#L207) - -## Html[[trackio.TrackioHtml]] - -#### trackio.TrackioHtml[[trackio.TrackioHtml]] - -```python -trackio.TrackioHtml(data: typing.Any, inject: bool = True, data_is_not_path: bool = False, caption: str | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/media/html.py#L17) - -**Parameters:** - -data (`str`, `Path`, file-like, Plotly figure, or Matplotlib figure) : Raw HTML, a path to an `.html` file, a file-like object, or a Plotly or Matplotlib figure. - -inject (`bool`, *optional*) : Wrap HTML fragments in a styled document. Default is `True`. - -data_is_not_path (`bool`, *optional*) : Accepted for `wandb.Html` compatibility but ignored. - -caption (`str`, *optional*) : A string caption for the HTML. - -Initializes an Html object. - -Example: -```python -import trackio - -trackio.init(project="my-project") - -# Raw HTML -trackio.log({"report": trackio.Html("

Results

")}) - -# Plotly figure -import plotly.express as px - -fig = px.line(x=[1, 2, 3], y=[4, 5, 6]) -trackio.log({"plot": trackio.Html(fig)}) - -# Matplotlib figure -import matplotlib.pyplot as plt - -plt.plot([1, 2, 3, 4]) -trackio.log({"chart": trackio.Html(plt)}) -``` - -## Table[[trackio.Table]] - -#### trackio.Table[[trackio.Table]] - -```python -trackio.Table(columns: list[str] | None = None, data: list[list[typing.Any]] | None = None, dataframe: typing.Optional[typing.Any] = None, rows: list[list[typing.Any]] | None = None, optional: bool | list[bool] = True, allow_mixed_types: bool = False, log_mode: typing.Optional[typing.Literal['IMMUTABLE', 'MUTABLE', 'INCREMENTAL']] = 'IMMUTABLE') -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/table.py#L9) - -**Parameters:** - -columns (`list[str]`, *optional*) : Names of the columns in the table. Optional if `data` is provided. Not expected if `dataframe` is provided. Currently ignored. - -data (`list[list[Any]]`, *optional*) : 2D row-oriented array of values. Each value can be a number, a string (treated as Markdown and truncated if too long), or a `Trackio.Image` or list of `Trackio.Image` objects. - -dataframe (`pandas.DataFrame`, *optional*) : DataFrame used to create the table. When set, `data` and `columns` arguments are ignored. - -rows (`list[list[Any]]`, *optional*) : Currently ignored. - -optional (`bool` or `list[bool]`, *optional*, defaults to `True`) : Currently ignored. - -allow_mixed_types (`bool`, *optional*, defaults to `False`) : Currently ignored. - -log_mode : (`Literal["IMMUTABLE", "MUTABLE", "INCREMENTAL"]` or `None`, *optional*, defaults to `"IMMUTABLE"`): Currently ignored. - -Initializes a Table object. - -Tables can be used to log tabular data including images, numbers, and text. - -#### to_display_format[[trackio.Table.to_display_format]] - -```python -to_display_format(table_data: list[dict]) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/table.py#L124) - -**Parameters:** - -table_data (`list[dict]`) : List of dictionaries representing table rows (from stored `_value`). - -**Returns:** `list[dict]` - -Table data with images converted to markdown syntax and long -text truncated. - -Converts stored table data to display format for UI rendering. - -Note: -This does not use the `self.data` attribute, but instead uses the -`table_data` parameter, which is what the UI receives. - -## Trace[[trackio.Trace]] - -#### trackio.Trace[[trackio.Trace]] - -```python -trackio.Trace(messages: list[dict[str, Any]], metadata: dict | None = None, spans: list[dict[str, Any]] | None = None) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/trace.py#L8) - -**Parameters:** - -messages (`list[dict[str, Any]]`) : OpenAI-style messages, e.g. `{"role": "user", "content": "..."}`. Assistant messages may include `tool_calls`, and tool results may include `tool_call_id`; when no `spans` are provided, the dashboard pairs those into tool operations. - -metadata (`dict`, *optional*) : Trace-level metadata, e.g. `session_id` or `environment`. The keys `status`, `duration_ms`, `latency_ms`, and `cost_usd` are used by the dashboard as trace-level fallbacks when spans do not supply them. - -spans (`list[dict[str, Any]]`, *optional*) : Execution spans describing what produced the response. Each span is a dictionary keyed by `id`, `name`, and `kind` (`"span"`, `"generation"`, or `"tool"`), plus optional `parent_id`, `start_time`, `end_time`, `duration_ms`, `status`, `error`, `input`, `output`, `model`, `usage`, `cost_usd`, and `metadata`. - -Initializes a Trace object. - -Traces capture a conversational or agent-style request: OpenAI-style messages, -optional metadata, and optional execution spans. Spans are dictionaries that -describe model generations, tool calls, or other operations. Nested Trackio -media objects inside messages, metadata, or spans are persisted and serialized -alongside the trace. - -## Histogram[[trackio.Histogram]] - -#### trackio.Histogram[[trackio.Histogram]] - -```python -trackio.Histogram(sequence: typing.Union[numpy.ndarray, typing.Sequence[float], typing.Sequence[int], NoneType] = None, np_histogram: tuple | None = None, num_bins: int = 64) -``` - -[Source](https://github.com/gradio-app/trackio/blob/main/trackio/histogram.py#L6) - -**Parameters:** - -sequence (`np.ndarray` or `Sequence[float]` or `Sequence[int]`, *optional*) : Sequence of values to create the histogram from. - -np_histogram (`tuple`, *optional*) : Pre-computed NumPy histogram as a `(hist, bins)` tuple. - -num_bins (`int`, *optional*, defaults to `64`) : Number of bins for the histogram (maximum `512`). - -Histogram data type for Trackio, compatible with wandb.Histogram. - -Example: -```python -import trackio -import numpy as np - -# Create histogram from sequence -data = np.random.randn(1000) -trackio.log({"distribution": trackio.Histogram(data)}) - -# Create histogram from numpy histogram -hist, bins = np.histogram(data, bins=30) -trackio.log({"distribution": trackio.Histogram(np_histogram=(hist, bins))}) - -# Specify custom number of bins -trackio.log({"distribution": trackio.Histogram(data, num_bins=50)}) -``` - diff --git a/trackio/main/en/api_mcp_server.md b/trackio/main/en/api_mcp_server.md deleted file mode 100644 index 30b128b3b0a342f573b43c2ff111cb253acca48d..0000000000000000000000000000000000000000 --- a/trackio/main/en/api_mcp_server.md +++ /dev/null @@ -1,158 +0,0 @@ -# Trackio as an API and MCP Server - -The Trackio dashboard can be configured to run as both an HTTP API server and an MCP (Model Context Protocol) server, allowing external tools and applications to programmatically interact with your experiment tracking data, or for you to be able to "chat with your experiment data" in natural language using ChatGPT, Claude, Deepseek, or various LLMs that support MCPs. This makes Trackio an ideal choice for LLM agents running autonomous ML experiments, as they can seamlessly log metrics and query experiment results. - -## Setup - -Install the optional MCP dependency, then enable the MCP server when launching the Trackio dashboard. You can do this a few different ways: - -```bash -pip install "trackio[mcp]" -``` - -### Option 1: CLI Command -```bash -trackio show --mcp-server -``` - -### Option 2: Python Function -```python -import trackio -trackio.show(mcp_server=True) -``` - -### Option 3: Environment Variable -```bash -export GRADIO_MCP_SERVER=True -trackio show -``` - -When MCP server mode is enabled, Trackio: -- Mounts a streamable-HTTP MCP server alongside the dashboard -- Exposes read-only project/run/metric inspection tools to MCP clients -- Exposes a small set of mutation tools (delete/rename/sync) gated by a write token - -## API Usage - -Trackio exposes each MCP tool as a plain HTTP endpoint at `POST /api/{tool_name}`. The body is JSON; pass arguments as `{"kwargs": {...}}`, `{"args": [...]}`, or simply as a flat `{"name": value}` object. - -```python -import httpx2 - -base = "http://127.0.0.1:7860" - -projects = httpx2.post(f"{base}/api/get_all_projects").json()["data"] -print("Projects:", projects) - -runs = httpx2.post( - f"{base}/api/get_runs_for_project", - json={"project": "my-project"}, -).json()["data"] -print("Runs:", runs) - -values = httpx2.post( - f"{base}/api/get_metric_values", - json={"project": "my-project", "run": "run-1", "metric_name": "loss"}, -).json()["data"] -print("Loss values:", values) -``` - -```javascript -const base = "http://127.0.0.1:7860"; - -async function call(name, payload = {}) { - const res = await fetch(`${base}/api/${name}`, { - method: "POST", - headers: { "Content-Type": "application/json" }, - body: JSON.stringify(payload), - }); - return (await res.json()).data; -} - -console.log("Projects:", await call("get_all_projects")); -console.log("Runs:", await call("get_runs_for_project", { project: "my-project" })); -console.log("Loss:", await call("get_metric_values", { - project: "my-project", - run: "run-1", - metric_name: "loss", -})); -``` - -```bash -# Get all projects -curl -s -X POST http://127.0.0.1:7860/api/get_all_projects \ - -H "Content-Type: application/json" -d '{}' - -# Get runs for a project -curl -s -X POST http://127.0.0.1:7860/api/get_runs_for_project \ - -H "Content-Type: application/json" \ - -d '{"project": "my-project"}' - -# Get values for a metric -curl -s -X POST http://127.0.0.1:7860/api/get_metric_values \ - -H "Content-Type: application/json" \ - -d '{"project": "my-project", "run": "run-1", "metric_name": "loss"}' -``` - -## MCP Usage - -When running as an MCP server, Trackio exposes its tools at a single streamable-HTTP endpoint that MCP-compatible clients (Claude Desktop, Claude Code, etc.) can connect to. - -### MCP Server URL - -The MCP server is available at: -```txt -http://127.0.0.1:7860/mcp/ -``` - -When deployed to a Hugging Face Space, the URL is `https://.hf.space/mcp/`. - -### Available MCP Tools - -Read tools: - -1. **get_all_projects** – List all Trackio projects on this server. -2. **get_runs_for_project** – List runs for a given project. -3. **get_metrics_for_run** – List metric names recorded for a run. -4. **get_metric_values** – Fetch metric values for a run, optionally around a step or time. -5. **get_project_summary** – Summary metadata for a project. -6. **get_run_summary** – Summary metadata for a run. -7. **get_system_metrics_for_run** – List system metric names recorded for a run. -8. **get_system_logs** – Fetch system metric logs for a run. -9. **get_snapshot** – Fetch a single snapshot around a step or timestamp. -10. **get_logs** – Fetch metric logs for a run. -11. **get_alerts** – Fetch alerts for a project, optionally filtered by run or level. -12. **get_settings** – Return dashboard settings and asset configuration. - -Mutation tools (require write access — see below): - -13. **delete_run** – Delete a run. -14. **rename_run** – Rename a run. -15. **trigger_sync** – Trigger an export/sync pass to Hugging Face. - -### Write Access for Mutation Tools - -Mutation tools are gated: - -- **Local dashboard:** pass the `write_token` argument. The token is printed in the terminal when you run `trackio show` (it's also embedded as `?write_token=...` in the dashboard URL printed at startup). For example: - ```json - {"project": "my-project", "run": "run-1", "write_token": ""} - ``` -- **Hugging Face Spaces:** pass an `hf_token` argument with write access to the Space's repo. The local `write_token` is not used in this case. - -Read tools never require a token. - -### MCP Client Configuration - -To add Trackio to clients that support streamable-HTTP MCP servers, use a config like: - -```json -{ - "mcpServers": { - "trackio": { - "url": "http://127.0.0.1:7860/mcp/" - } - } -} -``` - diff --git a/trackio/main/en/artifacts.md b/trackio/main/en/artifacts.md deleted file mode 100644 index 2580a2047db2ac34bb769f870d94f8bc578f0b43..0000000000000000000000000000000000000000 --- a/trackio/main/en/artifacts.md +++ /dev/null @@ -1,390 +0,0 @@ -# Artifacts - -## Introduction - -An **artifact** is a versioned, named bundle of files attached to a project — a trained model, a dataset, a set of evaluation outputs. Logging files as artifacts (rather than leaving them on disk) gives you: - -- **Versioning** — each time you log under the same name, Trackio records a new version (`v0`, `v1`, ...). Identical content is de-duplicated, so re-logging unchanged files reuses the existing version. -- **Aliases** — moving pointers such as `latest` (assigned automatically) or your own (`prod`, `best`) that always resolve to a single version. -- **Lineage** — artifacts are linked to the runs that produced and consumed them, so you can trace which run created a model and which runs used it. - -Artifacts work fully offline against local storage, and sync to a Hugging Face Space (or self-hosted server) when one is configured, exactly like metrics. - -## Logging an artifact - -The quickest way is to log a file or directory directly. This creates a new artifact, adds the path, and records it as an output of the current run: - -```python -import trackio - -trackio.init(project="my_project") - -# ... training ... - -trackio.log_artifact("checkpoints/model.safetensors", type="model") -``` - -When you pass a path, the artifact `name` defaults to `run--` and `type` defaults to `"unspecified"`. Pass `name` and `type` to set them explicitly: - -```python -trackio.log_artifact("checkpoints/", name="my-model", type="model") -``` - -### Artifact types - -Artifact `type` is a free-form category string. Trackio does not enforce a fixed list of types, but common conventions are: - -| Type | Use it for | -| --- | --- | -| `"model"` | Model checkpoints, adapter weights, tokenizers, model configs | -| `"dataset"` | Training, validation, test, or generated datasets | -| `"evaluation"` | Evaluation outputs, predictions, benchmark results, score files | -| `"report"` | Figures, plots, tables, notebooks, or human-readable analysis bundles | -| `"unspecified"` | The default when no type is provided | - -Use stable type names within a project so you can filter artifacts consistently and use `trackio.use_artifact(..., type="...")` to assert that a run is consuming the expected kind of artifact. - -### Building an artifact explicitly - -For finer control — multiple files, custom logical paths, a description, or metadata — construct an [Artifact](/docs/trackio/main/en/api#trackio.Artifact), add files to it, then log it: - -```python -artifact = trackio.Artifact( - name="my-model", - type="model", - description="Fine-tuned on the v2 dataset", - metadata={"base_model": "bert-base", "epochs": 3}, -) -artifact.add_file("checkpoints/model.safetensors") -artifact.add_file("checkpoints/config.json") -artifact.add_dir("tokenizer/") - -logged = trackio.log_artifact(artifact) -``` - -After logging, the artifact is frozen and its `version`, `aliases`, `size`, and `manifest` are populated: - -```python -print(logged.version) # "v0" -print(logged.aliases) # ("latest",) -``` - -### Versions and aliases - -Each log under an existing name creates the next integer version and moves the `latest` alias onto it. Assign your own aliases with `aliases=`: - -```python -trackio.log_artifact(artifact, aliases=["prod", "best"]) -``` - -Aliases are moving pointers: logging a new version with the same alias re-points it. Version specifiers (`v0`, `v1`, ...) are reserved and cannot be used as aliases. - -If you log content identical to an existing version, Trackio reuses that version instead of creating a new one. Any explicit `aliases` you pass still rotate onto it, but `latest` is left where it is — re-logging identical (or older) content never moves it backward. - -## Using an artifact - -[use_artifact()](/docs/trackio/main/en/api#trackio.use_artifact) fetches an artifact and records it as an **input** to the current run, which is what builds lineage between a consuming run and the artifact it used: - -```python -trackio.init(project="my_project") - -artifact = trackio.use_artifact("my-model") # resolves to :latest -artifact = trackio.use_artifact("my-model:v2") # pin a version -artifact = trackio.use_artifact("my-model:prod") # resolve an alias -``` - -Pass `type` to assert the artifact's type, raising if it doesn't match: - -```python -artifact = trackio.use_artifact("my-model", type="model") -``` - -### Downloading files - -`use_artifact` returns an [Artifact](/docs/trackio/main/en/api#trackio.Artifact) whose files you materialize with `download()`: - -```python -artifact = trackio.use_artifact("my-model:latest") -path = artifact.download() -# files are now under ./.trackio/artifact-downloads/my_project/my-model_v2/ -``` - -By default, files are written to `./.trackio/artifact-downloads//_v/`, keyed by project so same-named artifacts from different projects never collide; pass `root` to choose another directory. `download()` is idempotent — files already present are skipped — and when the run is backed by a Space, any file missing locally is fetched from the remote. - -## Referencing external data - -Some data is too large to copy, or already lives in durable storage you don't want duplicated. `add_reference` records such data by **URI** in the manifest *without staging any bytes* into Trackio's storage, so you still get versioning, de-duplication, aliases, and lineage over data that never moves: - -```python -artifact = trackio.Artifact(name="training-set", type="dataset") -artifact.add_reference("file:///mnt/nvme/datasets/corpus.parquet") -artifact.add_reference("file:///mnt/nvme/datasets/shards/") # a directory — expands to one entry per file -artifact.add_reference("https://example.com/data/eval.json") -artifact.add_reference("hf://datasets/username/my-dataset/train.parquet") -trackio.log_artifact(artifact) -``` - -Built-in schemes are `file://`, `http(s)://`, and `hf://` — all served by Trackio's existing dependencies. Any other scheme (`s3://`, `gs://`, Azure blob URLs, ...) is supported by registering a custom handler; see [Referencing other stores](#referencing-other-stores-s3-gcs-azure) below for complete S3, GCS, and Azure examples. With `checksum=True` (the default), Trackio probes the source to fill in `size` and a checksum: - -- `file://` is stream-hashed to a sha256; its size is read from disk. -- `hf://` uses the LFS sha256 (or the git blob id); `http(s)://` uses the server `ETag`. - -Every checksum is stored in a single `digest` field — the sha256 for local/LFS references, or the provider's ETag for HTTP or object-store references. - -A URI that denotes a directory (`file://`) or a repo path (`hf://`) is **expanded** into one reference entry per object, each named by its path relative to the prefix (nested under `name=` when given). `max_objects` (default 10,000) caps the expansion and raises if exceeded. - -When no checksum can be obtained — for example a server with no `ETag` — the reference is still recorded, using **the URI itself as the `digest`**, and a warning is emitted. A local `file://` path that doesn't exist is the exception: it raises rather than being recorded, since a missing local file is almost always a mistake — use `add_file` to stage a local file. Pass `checksum=False` to skip the per-object checksum — a single object then records just its URI — and `name=` to set the logical path. - -A reference's version identity comes from its URI, size, and `digest`, so re-logging identical references de-duplicates to one version, while a changed URI, size, or checksum creates a new one — exactly like file content. When the URI is used as the `digest`, identity therefore tracks the URI and not the content. - -URIs are recorded verbatim, and manifests can be synced to a Hugging Face Dataset. A URI that embeds a credential — a presigned `https://` URL or an Azure SAS token — would expose that credential to anyone who can read the Dataset, so `add_reference` warns when a URI's query string looks signed; prefer the object's canonical unsigned URI (e.g. `s3://bucket/key`). - -Reference bytes are never uploaded to a Space or bucket, but they can be fetched on demand. `download()` downloads each referenced object into the directory (via `httpx2`, `huggingface_hub`, or your registered handler), which can transfer a large amount of data. Before fetching, each object's source is re-probed and its current checksum compared against the recorded one — a mismatch warns that the source may have changed but the download proceeds. Each object is written atomically, and one already present on disk is skipped without re-checking the source, so repeated calls are cheap and idempotent: - -```python -artifact = trackio.use_artifact("training-set:latest") -path = artifact.download() # downloads staged files AND referenced objects -``` - -To work with the pointers *without* downloading, read them from the artifact instead: - -```python -print(artifact.references) # [{'path': ..., 'ref': 's3://...', 'size': ..., 'digest': ...}, ...] -print(artifact.get_entry_uri("eval.json")) # "s3://my-bucket/eval.json" -``` - -An unfetchable reference (a missing local file, an unreachable URL, or a scheme with no registered handler) raises when `download()` reaches it. - -## Referencing other stores (S3, GCS, Azure) - -Trackio deliberately ships no cloud-vendor SDKs. To reference objects in a store it doesn't handle natively, subclass `trackio.ReferenceHandler` and register an instance with `trackio.register_reference_handler`. A handler implements four methods: - -- `matches(scheme, uri)` — whether this handler owns the URI. Registered handlers are consulted *before* the built-ins, so a handler may also claim specific `https://` hosts (as the Azure example below does) ahead of the generic HTTP handler. -- `resolve(uri, checksum, max_objects)` — probe the source and return a list of `trackio.ResolvedReference` entries: one entry with `relkey=None` for a single object, or one entry per object (with `relkey` set to the object's path relative to the prefix) when the URI denotes a prefix. Set `size` and `digest` when the source can be probed (the provider's ETag works fine as a digest — Trackio treats reference digests as opaque tokens); return them as `None` to record the reference un-checksummed, in which case Trackio falls back to the URI as the digest and warns. -- `fetch(uri, dest)` — download the single object at `uri` to the local path `dest` (called by `Artifact.download()`). -- `hint()` — a one-line actionable message shown in the warning when `resolve` produced no checksum. - -Keys discovered during prefix expansion should be percent-encoded when synthesizing each entry's `uri` (and decoded in `fetch`), since manifest URIs may not contain spaces. - -### S3 (`s3://`, via `boto3`) - -```python -from urllib.parse import quote, unquote, urlsplit - -import boto3 - -import trackio - -class S3Handler(trackio.ReferenceHandler): - def matches(self, scheme, uri): - return scheme == "s3" - - def resolve(self, uri, checksum, max_objects): - parts = urlsplit(uri) - bucket, key = parts.netloc, unquote(parts.path.lstrip("/")) - client = boto3.client("s3") - if key and not key.endswith("/"): - head = client.head_object(Bucket=bucket, Key=key) - return [ - trackio.ResolvedReference( - relkey=None, - uri=uri, - size=int(head["ContentLength"]), - digest=head["ETag"].strip('"') if checksum else None, - ) - ] - base = key[: key.rfind("/") + 1] - entries = [] - pages = client.get_paginator("list_objects_v2").paginate( - Bucket=bucket, Prefix=key - ) - for page in pages: - for obj in page.get("Contents", []): - if obj["Key"].endswith("/"): - continue - if len(entries) >= max_objects: - raise ValueError( - f"{uri} expands to more than {max_objects} objects; " - "pass max_objects= to raise the limit." - ) - entries.append( - trackio.ResolvedReference( - relkey=obj["Key"][len(base):], - uri=f"s3://{bucket}/{quote(obj['Key'], safe='/')}", - size=int(obj["Size"]), - digest=obj["ETag"].strip('"') if checksum else None, - ) - ) - return entries - - def fetch(self, uri, dest): - parts = urlsplit(uri) - with open(dest, "wb") as f: - boto3.client("s3").download_fileobj( - parts.netloc, unquote(parts.path.lstrip("/")), f - ) - - def hint(self): - return "Configure AWS credentials so the object can be probed for an ETag." - -trackio.register_reference_handler(S3Handler()) - -artifact = trackio.Artifact(name="training-set", type="dataset") -artifact.add_reference("s3://my-bucket/shards/") # expands to one entry per object -trackio.log_artifact(artifact) -``` - -### Google Cloud Storage (`gs://`, via `google-cloud-storage`) - -```python -from urllib.parse import quote, unquote, urlsplit - -from google.cloud import storage - -import trackio - -class GcsHandler(trackio.ReferenceHandler): - def matches(self, scheme, uri): - return scheme == "gs" - - def resolve(self, uri, checksum, max_objects): - parts = urlsplit(uri) - bucket, key = parts.netloc, unquote(parts.path.lstrip("/")) - client = storage.Client() - if key and not key.endswith("/"): - blob = client.bucket(bucket).get_blob(key) - if blob is None: - raise ValueError(f"No such GCS object: {uri}") - return [ - trackio.ResolvedReference( - relkey=None, - uri=uri, - size=blob.size, - digest=blob.etag.strip('"') if checksum else None, - ) - ] - base = key[: key.rfind("/") + 1] - entries = [] - for blob in client.list_blobs(bucket, prefix=key): - if blob.name.endswith("/"): - continue - if len(entries) >= max_objects: - raise ValueError( - f"{uri} expands to more than {max_objects} objects; " - "pass max_objects= to raise the limit." - ) - entries.append( - trackio.ResolvedReference( - relkey=blob.name[len(base):], - uri=f"gs://{bucket}/{quote(blob.name, safe='/')}", - size=blob.size, - digest=blob.etag.strip('"') if checksum else None, - ) - ) - return entries - - def fetch(self, uri, dest): - parts = urlsplit(uri) - key = unquote(parts.path.lstrip("/")) - storage.Client().bucket(parts.netloc).blob(key).download_to_filename( - str(dest) - ) - - def hint(self): - return "Configure GCP credentials so the object can be probed for an ETag." - -trackio.register_reference_handler(GcsHandler()) -``` - -### Azure Blob Storage (via `azure-storage-blob` + `azure-identity`) - -Azure blobs are addressed by plain `https://` URLs (`https://.blob.core.windows.net//`), so this handler claims them by host suffix — registering it makes it win over Trackio's generic HTTP handler: - -```python -from urllib.parse import quote, unquote, urlsplit - -from azure.identity import DefaultAzureCredential -from azure.storage.blob import BlobServiceClient - -import trackio - -class AzureHandler(trackio.ReferenceHandler): - def matches(self, scheme, uri): - return scheme in ("http", "https") and urlsplit( - uri - ).netloc.lower().endswith(".blob.core.windows.net") - - def _split(self, uri): - parts = urlsplit(uri) - container, _, blob_name = parts.path.lstrip("/").partition("/") - return f"{parts.scheme}://{parts.netloc}", container, unquote(blob_name) - - def _service(self, account_url): - return BlobServiceClient(account_url, credential=DefaultAzureCredential()) - - def resolve(self, uri, checksum, max_objects): - account_url, container, blob_name = self._split(uri) - service = self._service(account_url) - if blob_name and not blob_name.endswith("/"): - props = service.get_blob_client(container, blob_name).get_blob_properties() - return [ - trackio.ResolvedReference( - relkey=None, - uri=uri, - size=props.size, - digest=props.etag.strip('"') if checksum else None, - ) - ] - base = blob_name[: blob_name.rfind("/") + 1] - entries = [] - container_client = service.get_container_client(container) - for blob in container_client.list_blobs(name_starts_with=blob_name): - if blob.name.endswith("/"): - continue - if len(entries) >= max_objects: - raise ValueError( - f"{uri} expands to more than {max_objects} objects; " - "pass max_objects= to raise the limit." - ) - entries.append( - trackio.ResolvedReference( - relkey=blob.name[len(base):], - uri=f"{account_url}/{container}/{quote(blob.name, safe='/')}", - size=blob.size, - digest=blob.etag.strip('"') if checksum else None, - ) - ) - return entries - - def fetch(self, uri, dest): - account_url, container, blob_name = self._split(uri) - downloader = ( - self._service(account_url) - .get_blob_client(container, blob_name) - .download_blob() - ) - with open(dest, "wb") as f: - downloader.readinto(f) - - def hint(self): - return "Configure Azure credentials so the blob can be probed for an ETag." - -trackio.register_reference_handler(AzureHandler()) -``` - -These handlers raise when the source can't be probed; if you'd rather record an un-checksummed reference in that case (for example, when cataloging data behind auth you can't reach at log time), catch the provider error inside `resolve` and return `[trackio.ResolvedReference(relkey=None, uri=uri)]` — Trackio will fall back to the URI as the digest and warn, using your `hint()`. - -Register handlers in every process that adds *or downloads* such references: `Artifact.download()` needs the handler to fetch the bytes, and a URI whose scheme has no registered handler raises. - -## Browsing artifacts in the dashboard - -The dashboard's **Artifacts** tab (shown once a project has artifacts) lists artifacts grouped by type, with each version's aliases, size, and file count. Selecting a version shows its file manifest — click a file to download it — plus its metadata and lineage: the run that produced it and the runs that used it, each linking to the run's detail page. - -Each version also has a **Lineage** section showing an interactive graph of the version's lineage: artifact versions and runs as nodes, with arrows from a run to the artifacts it logged and from an artifact to the runs that used it. The selected version is highlighted. To keep large graphs readable, five or more similar nodes with identical connections (for example, the many checkpoints a single run logged) are grouped into a single **cluster** node showing the count — click the cluster to search its members and extract individual ones back into the graph. Drag to pan, use Ctrl/Cmd + scroll (or the +/− buttons) to zoom, and click any node to open a summary with a link to that run or artifact version. - -Run detail pages show the same lineage from the other direction, with **Output artifacts** and **Input artifacts** sections linking back to the Artifacts tab. - -## Remote storage - -When your run targets a Hugging Face Space or self-hosted server (see [Track](track)), artifact files are content-addressed and uploaded once: Trackio skips blobs the server already has, so re-logging shared files is cheap. Artifact metadata and blobs are persisted alongside your other run data to the configured HF Dataset or bucket. - diff --git a/trackio/main/en/cli_commands.md b/trackio/main/en/cli_commands.md deleted file mode 100644 index 9f018109874dddae3b69a5a8109382996d681f0a..0000000000000000000000000000000000000000 --- a/trackio/main/en/cli_commands.md +++ /dev/null @@ -1,633 +0,0 @@ -# CLI Commands - -Trackio provides a comprehensive set of CLI commands that enable you to query project, run, metric, and Space information without needing to start the MCP server. Commands work against local data by default, or against a remote HF Space when `--space` is provided. This is particularly useful for LLM agents and automation scripts. With structured JSON output and programmatic access to all experiment data, Trackio is designed to support autonomous ML experiments run by LLMs. - -## Querying Remote Spaces - -All `list`, `get`, and `query` commands that read dashboard data support querying a remote Hugging Face Space instead of local data. Pass the `--space` flag with either a Space ID or full URL: - -```sh -# Using a Space ID -trackio list projects --space username/my-space - -# Using a Space URL -trackio list projects --space https://username-my-space.hf.space - -# Works with any list/get/query command -trackio get metric --project "my-project" --run "my-run" --metric "loss" --space username/my-space -``` - -For private Spaces, pass `--hf-token` or ensure you are logged in via `huggingface-cli login`: - -```sh -trackio list projects --space username/private-space --hf-token hf_xxxxx -``` - -> **Note:** The `show`, `status`, `sync`, `freeze`, `skills`, `registry`, and `list spaces` commands do not support `--space`. Use `trackio list spaces` to discover Trackio dashboards on the Hugging Face Hub, then pass one of those Space IDs to commands such as `trackio list projects --space username/my-space`. - -## Registry Commands - -Create a registry and, when useful, define a typed collection before linking into it: - -```sh -trackio registry create models --description "Models we deploy" -trackio registry create-collection models/churn-model --type model --description "Churn predictor" -``` - -Link a local artifact version, promote a collection version by moving an alias, or unlink a version: - -```sh -trackio registry link models/churn-model experiments/resnet:v3 --alias staging -trackio registry promote models/churn-model production v0 -trackio registry unlink models/churn-model v0 -``` - -Inspect collections and their audit history: - -```sh -trackio registry list models -trackio registry show models/churn-model -trackio registry events models -``` - -All registry commands accept `--bucket-id org/bucket` for a bucket-backed registry and `--json` for structured output. `--alias` is repeatable. Targets may be written as either `models/churn-model` or `registry-models/churn-model`. - -The `link` command resolves `project/artifact:version-or-alias` from local Trackio data; omit the suffix to resolve `latest`. Publishing an artifact that only exists on a remote Space still uses the Python API so Trackio can record the source's remote storage coordinates. - -## Sync Command - -Upload a local project to a Hugging Face Space: - -```sh -trackio sync --project "my-project" --space-id "username/space_id" -``` - -Deploy as a static Space (reads from an HF Bucket, no server needed): - -```sh -trackio sync --project "my-project" --space-id "username/space_id" --sdk static -``` - -Static Spaces serve data directly from the browser and therefore require public snapshot data. `--sdk static --private` is not supported; use the default Gradio SDK for private dashboards. - -Sync all projects that have unsynced data to their configured Spaces: - -```sh -trackio sync --all -``` - -| Flag | Description | -|------|-------------| -| `--project` | The name of the project to sync (required unless `--all` is used) | -| `--space-id` | The HF Space ID to sync to (e.g. `username/space_id`). If not provided, uses the previously-configured Space | -| `--all` | Sync all projects with unsynced data | -| `--sdk` | `gradio` (default) for a live server, or `static` for a read-only bucket-backed Space | -| `--private` | Make the Space private if creating a new Gradio Space. Not supported with `--sdk static` | -| `--force` | Overwrite the existing database without prompting | - -## Freeze Command - -Create a read-only static Space snapshot from a live Gradio Space: - -```sh -trackio freeze --space-id "username/my-space" --project "my-project" -``` - -Specify a custom destination Space: - -```sh -trackio freeze --space-id "username/my-space" --project "my-project" --new-space-id "username/my-snapshot" -``` - -| Flag | Description | -|------|-------------| -| `--space-id` | The source Gradio Space ID (required) | -| `--project` | The project to freeze (required) | -| `--new-space-id` | The destination static Space ID. Defaults to `{space_id}_static` | -| `--private` | Not supported for static frozen snapshots | - -> **Note:** The source must be a Gradio Space with a bucket mounted at `/data`. If the destination Space already exists and is not a Trackio static Space, `freeze` will refuse to overwrite it. -> The frozen Space is a snapshot. Later metrics synced to the original Gradio Space do not appear in the frozen static Space unless you run `freeze` again. -> Static frozen snapshots require public destination data, so `trackio freeze --private` is not supported. - -### Bump - -Upgrade an existing Trackio Space to the Trackio version installed locally: - -```sh -trackio bump username/my-space -``` - -`trackio bump --space username/my-space` does the same thing. - -The Space is paused while it upgrades, so training jobs keep logging to the Space's bucket inbox. Its databases are backed up to `trackio-backups/` in the same bucket, its Trackio pin is updated, and it restarts so the new version migrates the data. If the upgraded Space fails to start or reports fewer rows than before, the backup and the previous Space files are restored. - -To keep the original Space untouched, copy it and its bucket into a new Space running the local version instead: - -```sh -trackio bump username/my-space --new-space username/my-space-v2 --new-bucket username/my-space-v2-bucket -``` - -| Flag | Description | -|------|-------------| -| `space_id` | The Trackio Space to upgrade (required, or pass it with `--space`) | -| `--new-space` | Create this Space from a copy of `space_id` instead of upgrading in place | -| `--new-bucket` | The bucket for `--new-space`. Defaults to `{new_space}-bucket` | - -> **Note:** `bump` supports Gradio Spaces running Trackio 0.21.0 or newer with a bucket mounted at `/data`, and never downgrades a Space. Older Spaces stored their data in a Hugging Face Dataset instead of a bucket. - -## List Commands - -### List All Projects - -List all available projects: - -```sh -trackio list projects -``` - -Output in JSON format: - -```sh -trackio list projects --json -``` - -### List Trackio Spaces - -List Trackio dashboard Spaces owned by your Hugging Face account and organizations: - -```sh -trackio list spaces -``` - -Output in JSON format: - -```sh -trackio list spaces --json -``` - -List Trackio Spaces under a specific user or organization namespace: - -```sh -trackio list spaces --author "username-or-org" -``` - -Limit the number of returned Spaces: - -```sh -trackio list spaces --limit 10 -``` - -For private Spaces, pass `--hf-token` or ensure you are logged in via `huggingface-cli login`. - -### List Runs for a Project - -List all runs in a specific project: - -```sh -trackio list runs --project "my-project" -``` - -Output in JSON format: - -```sh -trackio list runs --project "my-project" --json -``` - -### List Metrics for a Run - -List all metrics tracked in a specific run: - -```sh -trackio list metrics --project "my-project" --run "my-run" -``` - -Output in JSON format: - -```sh -trackio list metrics --project "my-project" --run "my-run" --json -``` - -### List System Metrics for a Run - -List all system metrics (e.g., GPU metrics) for a specific run: - -```sh -trackio list system-metrics --project "my-project" --run "my-run" -``` - -Output in JSON format: - -```sh -trackio list system-metrics --project "my-project" --run "my-run" --json -``` - -### List Reports - -List markdown reports in a project (across all runs): - -```sh -trackio list reports --project "my-project" -``` - -List markdown reports for a specific run: - -```sh -trackio list reports --project "my-project" --run "my-run" -``` - -Output in JSON format: - -```sh -trackio list reports --project "my-project" --run "my-run" --json -``` - -### List Traces - -List [traces](./traces) (agent or conversation sessions) across all runs in a project: - -```sh -trackio list traces --project "my-project" -``` - -Each row shows the trace's status, wall-clock latency, cost, operation count, and -the user request that started it. Filter by run, step, or text: - -```sh -trackio list traces --project "my-project" --run "production" -trackio list traces --project "my-project" --step 12 -trackio list traces --project "my-project" --search "rate limit" -``` - -Search matches message content, trace metadata, and each span's name, kind, -model, status, and error. Control ordering and paging: - -```sh -trackio list traces --project "my-project" --sort step_desc --limit 100 --offset 50 -``` - -`--sort` accepts `request_time_desc` (default), `request_time_asc`, `step_asc`, -and `step_desc`. Adding `--json` includes a `summary` rollup per trace. - -## Get Commands - -### Get Trace - -Show one trace with its full execution tree: - -```sh -trackio get trace --project "my-project" --trace-id "fe04ed264a8a4bd6afcf266b56d9297e" -``` - -``` -Trace fe04ed264a8a4bd6afcf266b56d9297e - Run: production - Totals: error | 25.0s | $0.33 | 101338 in / 1804 out tokens | 21 operation(s) - -Execution: - answer-research-question [span] 25.0s - generate-research-response [span] 23.7s - acquire-sandbox [span] 914ms - dispatch-model-request [span] 2.18s - provider-request [generation] 2.18s my-model 8347->239 tok $0.03 - ERROR run-bash-command [tool] 168ms - -> {"exit_code": 2, "stderr": "hf datasets list: error: unrecognized arguments: --full"} -``` - -`--trace-id` accepts the short id printed by `trackio list traces` or the full -stored id. Add `--json` for the complete trace, including span inputs and -outputs. - -### Get Trace Summary - -Roll every span up by operation name to see where latency, tokens, and cost go, -and which operations fail: - -```sh -trackio get trace-summary --project "my-project" -``` - -``` -operation | kind | calls | errors | avg_ms | max_ms | input_tokens | output_tokens | cost_usd -provider-request | generation | 205 | 0 | 3380.8 | 5535.0 | 2915829 | 63020 | 9.6928 -run-bash-command | tool | 157 | 25 | 818.4 | 1548.0 | 0 | 0 | 0.0 -acquire-sandbox | span | 48 | 0 | 2438.6 | 10615.0 | 0 | 0 | 0.0 -``` - -Restrict to one run with `--run`, or emit machine-readable rows with `--json`. -For anything the rollup does not cover, query the `traces` table directly with -[`trackio query project`](#query-command) — `spans` is a JSON column, so -`json_each` works. - -### Get Project Summary - -Get a detailed summary of a project, including the number of runs and recent activity: - -```sh -trackio get project --project "my-project" -``` - -Output in JSON format: - -```sh -trackio get project --project "my-project" --json -``` - -The summary includes: -- Project name -- Number of runs -- List of all runs -- Last activity (maximum step across all runs) - -### Get Run Summary - -Get a detailed summary of a specific run, including metrics and configuration: - -```sh -trackio get run --project "my-project" --run "my-run" -``` - -Output in JSON format: - -```sh -trackio get run --project "my-project" --run "my-run" --json -``` - -The summary includes: -- Project and run names -- Number of log entries -- Last step -- List of all metrics -- Run configuration (excluding internal fields) - -### Get Metric Values - -Get all values for a specific metric in a run: - -```sh -trackio get metric --project "my-project" --run "my-run" --metric "loss" -``` - -Output in JSON format: - -```sh -trackio get metric --project "my-project" --run "my-run" --metric "loss" --json -``` - -The output includes: -- Step number -- Timestamp -- Metric value - -#### Filtering by Step or Time - -You can filter metric values to a specific step or a window around a step/timestamp. This is useful for inspecting metrics around the time an alert was fired. - -```sh -# Get metric at exactly step 200 -trackio get metric --project "my-project" --run "my-run" --metric "loss" --step 200 - -# Get metrics in a window around step 200 (±10 steps, the default) -trackio get metric --project "my-project" --run "my-run" --metric "loss" --around 200 - -# Get metrics in a window around step 200 (±50 steps) -trackio get metric --project "my-project" --run "my-run" --metric "loss" --around 200 --window 50 - -# Get metrics within ±60 seconds of a timestamp -trackio get metric --project "my-project" --run "my-run" --metric "loss" --at-time "2025-06-01T12:05:30" --window 60 -``` - -| Flag | Description | -|------|-------------| -| `--step N` | Return the metric at exactly step N | -| `--around N` | Return metrics in a window around step N | -| `--at-time T` | Return metrics in a window around ISO 8601 timestamp T | -| `--window W` | Window size: ±steps for `--around`, ±seconds for `--at-time` (default: 10) | - -### Get Metrics Snapshot - -Get **all** metrics at/around a step or timestamp in a single call. This is the fastest way for an agent to understand the state of a run at a specific point — for example, right when an alert fired. - -```sh -# All metrics at step 200 -trackio get snapshot --project "my-project" --run "my-run" --step 200 --json - -# All metrics in a window around step 200 (±5 steps) -trackio get snapshot --project "my-project" --run "my-run" --around 200 --window 5 --json - -# All metrics within ±60 seconds of a timestamp -trackio get snapshot --project "my-project" --run "my-run" --at-time "2025-06-01T12:05:30" --window 60 --json -``` - -Example JSON output: - -```json -{ - "project": "my-project", - "run": "my-run", - "around": 200, - "window": 5, - "metrics": { - "loss": [ - {"step": 196, "timestamp": "2025-06-01T12:04:50", "value": 0.42}, - {"step": 200, "timestamp": "2025-06-01T12:05:30", "value": 0.45} - ], - "accuracy": [ - {"step": 196, "timestamp": "2025-06-01T12:04:50", "value": 0.88}, - {"step": 200, "timestamp": "2025-06-01T12:05:30", "value": 0.87} - ], - "lr": [ - {"step": 196, "timestamp": "2025-06-01T12:04:50", "value": 0.0001}, - {"step": 200, "timestamp": "2025-06-01T12:05:30", "value": 0.0001} - ] - } -} -``` - -### Get System Metric Values - -Get system metric values for a run. If no metric name is provided, all system metrics are returned: - -```sh -# Get all system metrics -trackio get system-metric --project "my-project" --run "my-run" - -# Get a specific system metric -trackio get system-metric --project "my-project" --run "my-run" --metric "gpu_utilization" -``` - -Output in JSON format: - -```sh -trackio get system-metric --project "my-project" --run "my-run" --metric "gpu_utilization" --json -``` - -### Get Report Content - -Print markdown report entries for a specific report name in a run: - -```sh -trackio get report --project "my-project" --run "my-run" --report "training_report" -``` - -Output in JSON format: - -```sh -trackio get report --project "my-project" --run "my-run" --report "training_report" --json -``` - -## Query Command - -Use `trackio query` when you need a catch-all read-only SQL query that is not already covered by `trackio list` or `trackio get`. - -### Run a Query Against a Project Database - -```sh -trackio query project --project "my-project" --sql "SELECT run_name, MAX(step) AS last_step FROM metrics GROUP BY run_name ORDER BY last_step DESC" -``` - -Output in JSON format: - -```sh -trackio query project --project "my-project" --sql "SELECT name FROM sqlite_master WHERE type = 'table' ORDER BY name" --json -``` - -Query a remote Space: - -```sh -trackio query project --project "my-project" --sql "SELECT COUNT(*) AS num_alerts FROM alerts" --space username/my-space --json -``` - -`trackio query` only supports read-only `SELECT`, `WITH`, and safe schema `PRAGMA` queries. - -Common schema inspection examples: - -```sh -# Inspect table columns -trackio query project --project "my-project" --sql "PRAGMA table_info(metrics)" - -# Inspect indexes -trackio query project --project "my-project" --sql "PRAGMA index_list(alerts)" - -# List tables -trackio query project --project "my-project" --sql "SELECT name FROM sqlite_master WHERE type = 'table' ORDER BY name" -``` - -The response includes: - -- `project` -- `query` -- `columns` -- `rows` -- `row_count` - -For the full SQLite and parquet layout, see the [Storage Schema and Direct Queries](./storage_schema). - -## Output Formats - -All `list`, `get`, and `query` commands support two output formats: - -1. **Human-readable** (default): Formatted text output suitable for terminal viewing -2. **JSON** (with `--json` flag): Structured JSON output suitable for programmatic consumption - -## Error Handling - -The CLI commands include comprehensive validation and error handling: - -- If a project doesn't exist, an error message is displayed -- If a run doesn't exist in a project, an error message is displayed -- If a metric doesn't exist in a run, an error message is displayed -- If a report doesn't exist in a run, an error message is displayed -- If a query is not read-only, the CLI exits with an error - -All errors are written to stderr and the command exits with a non-zero exit code. - -## Example Workflow - -Here's a typical workflow for exploring your Trackio data: - -```sh -# 1. List all projects -trackio list projects - -# 2. List runs in a project -trackio list runs --project "my-project" - -# 3. Get project summary -trackio get project --project "my-project" - -# 4. Get run summary -trackio get run --project "my-project" --run "my-run" - -# 5. List metrics in the run -trackio list metrics --project "my-project" --run "my-run" - -# 6. Get specific metric values -trackio get metric --project "my-project" --run "my-run" --metric "loss" - -# 7. Get all metrics at a specific step (e.g. where an alert fired) -trackio get snapshot --project "my-project" --run "my-run" --step 200 --json - -# 8. Get system metrics (if available) -trackio list system-metrics --project "my-project" --run "my-run" - -# 9. List reports in a run -trackio list reports --project "my-project" --run "my-run" - -# 10. Print report markdown in terminal -trackio get report --project "my-project" --run "my-run" --report "training_report" - -# 11. Run a direct SQL query -trackio query project --project "my-project" --sql "SELECT run_name, MAX(step) AS last_step FROM metrics GROUP BY run_name" -``` - -### Querying a Remote Space - -The same workflow works against a remote Space — just add `--space`: - -```sh -# List projects on a remote Space -trackio list projects --space username/my-space - -# Get metric values from a remote Space -trackio get metric --project "my-project" --run "my-run" --metric "loss" --space username/my-space --json -``` - -## Use Cases - -### LLM Agents - -These CLI commands are particularly useful for LLM agents that need to: -- Discover available projects and runs -- Query metric values programmatically -- Inspect metrics around an alert with `get snapshot` or `get metric --around` -- Run direct SQL for cases not covered by the structured commands -- Get summaries without starting a server -- Parse structured JSON output for further processing - -### Automation Scripts - -You can use these commands in shell scripts and automation pipelines: - -```sh -#!/bin/bash -PROJECT="my-project" -RUN="my-run" - -# Get the latest loss value -LATEST_LOSS=$(trackio get metric --project "$PROJECT" --run "$RUN" --metric "loss" --json | jq -r '.values[-1].value') -echo "Latest loss: $LATEST_LOSS" -``` - -### Integration with Other Tools - -The JSON output format makes it easy to integrate with other tools: - -```sh -# Pipe to jq for filtering -trackio list runs --project "my-project" --json | jq '.runs[] | select(startswith("train"))' - -# Export to file -trackio get run --project "my-project" --run "my-run" --json > run_summary.json -``` - diff --git a/trackio/main/en/deploy_embed.md b/trackio/main/en/deploy_embed.md deleted file mode 100644 index c653bcbcbb80099cf916020e929d52e05fa3b633..0000000000000000000000000000000000000000 --- a/trackio/main/en/deploy_embed.md +++ /dev/null @@ -1,125 +0,0 @@ -# Deploying and Embedding Dashboards - -## Deploying to Hugging Face Spaces - -When calling [init()](/docs/trackio/main/en/api#trackio.init), by default the service will run locally and store project data on the local machine. - -But if you pass a `space_id` to [init()](/docs/trackio/main/en/api#trackio.init), like: - -```py -trackio.init(project="my-project", space_id="orgname/space_id") -``` - -or - -```py -trackio.init(project="my-project", space_id="username/space_id") -``` - -it will use an existing or automatically deploy a new Hugging Face Space as needed. You should be logged in with the `huggingface-cli` locally and your token should have write permissions to create the Space. - -## Syncing Local Projects to Spaces - -If you've been logging locally and want to upload your data to a Space after the fact, use `sync`: - -```py -trackio.sync(project="my-project", space_id="username/space_id") -``` - -Or from the CLI: - -```sh -trackio sync --project "my-project" --space-id "username/space_id" -``` - -By default, `sync` deploys a **Gradio Space** with a live server. You can also deploy a **static Space** that reads from an HF Bucket (no server needed): - -```py -trackio.sync(project="my-project", space_id="username/space_id", sdk="static") -``` - -```sh -trackio sync --project "my-project" --space-id "username/space_id" --sdk static -``` - -Static Spaces are lightweight and free — they serve a read-only dashboard backed by Parquet files in an HF Bucket. Because the dashboard runs entirely in the browser, static Trackio Spaces require public snapshot data and do not support `private=True`. Use the default Gradio Space (`sdk="gradio"`) for private dashboards. - -## Freezing a Space Snapshot - -If you have a live Gradio Space and want to create a read-only static snapshot of a project's data, use `freeze`: - -```py -trackio.freeze(space_id="username/my-space", project="my-project") -``` - -Or from the CLI: - -```sh -trackio freeze --space-id "username/my-space" --project "my-project" -``` - -This creates a new static Space (by default named `{space_id}_static`) containing a snapshot of the project's data from the source Space's bucket. The original Space is not modified. - -Note that`freeze()` is a one-time snapshot. If new metrics are later uploaded to the original Gradio Space, the frozen static Space will not update automatically. -The source Gradio Space can use a private bucket, but the frozen static snapshot is public data. `freeze(private=True)` is not supported; use a Gradio Space if the frozen dashboard must stay private. - -You can customize the destination: - -```py -trackio.freeze( - space_id="username/my-space", - project="my-project", - new_space_id="username/my-snapshot", -) -``` - -> **Note:** `freeze()` requires the source to be a Gradio Space with a bucket mounted at `/data`. If the destination Space already exists and is not a Trackio static Space, `freeze()` will refuse to overwrite it. - -## Embedding a Trackio Dashboard - -One of the reasons we created `trackio` was to make it easy to embed live dashboards on websites, blog posts, or anywhere else you can embed a website. - -![image](https://github.com/user-attachments/assets/77f1424b-737b-4f04-b828-a12b2c1af4ef) - -If your Trackio dashboard is hosted on Spaces, you can embed it anywhere using an ` -``` - -You can also filter the dashboard to display only specific projects or metrics using query parameters. Supported parameters include: - -* `project` (string): Show only a specific project. -* `metrics` (comma-separated list): Show only specific metrics, e.g., `train_loss,train_accuracy`. -* `sidebar` (string, `"auto"`, `"visible"`, `"collapsed"`, or `"hidden"`): - - * `"auto"` opens or collapses the sidebar based on the viewport width and is the default. - * `"visible"` starts with the full sidebar open. - * `"collapsed"` starts with only the narrow rail. - * `"hidden"` hides the sidebar completely. - - Explicit modes are not changed when the viewport is resized. -* `footer` (string, `"false"`): When set to `"false"`, hides the Gradio footer. By default, the footer is visible. -* `xmin` (number): Set the initial minimum value for the x-axis limits across all metrics plots. -* `xmax` (number): Set the initial maximum value for the x-axis limits across all metrics plots. -* `smoothing` (number): Set the initial value of the smoothing slider (0-20, where 0 = no smoothing). -* `plots_per_row` (`auto` or integer from 1 to 6): Set the initial value of the **Plots per row** control. The default is `auto`, which fits plots to the available width. -* `accordion` (string, `"hidden"`): When set to `"hidden"`, hides the section header accordions around metric groups. By default, section headers are visible. - -You can customize your ` -``` - - -``` - -You can also filter the dashboard to display only specific projects or metrics using query parameters. Supported parameters include: - -* `project` (string): Show only a specific project. -* `metrics` (comma-separated list): Show only specific metrics, e.g., `train_loss,train_accuracy`. -* `sidebar` (string, `"auto"`, `"visible"`, `"collapsed"`, or `"hidden"`): - - * `"auto"` opens or collapses the sidebar based on the viewport width and is the default. - * `"visible"` starts with the full sidebar open. - * `"collapsed"` starts with only the narrow rail. - * `"hidden"` hides the sidebar completely. - - Explicit modes are not changed when the viewport is resized. -* `footer` (string, `"false"`): When set to `"false"`, hides the Gradio footer. By default, the footer is visible. -* `xmin` (number): Set the initial minimum value for the x-axis limits across all metrics plots. -* `xmax` (number): Set the initial maximum value for the x-axis limits across all metrics plots. -* `smoothing` (number): Set the initial value of the smoothing slider (0-20, where 0 = no smoothing). -* `plots_per_row` (`auto` or integer from 1 to 6): Set the initial value of the **Plots per row** control. The default is `auto`, which fits plots to the available width. -* `accordion` (string, `"hidden"`): When set to `"hidden"`, hides the section header accordions around metric groups. By default, section headers are visible. - -You can customize your ` -``` - - -``` - -You can also filter the dashboard to display only specific projects or metrics using query parameters. Supported parameters include: - -* `project` (string): Show only a specific project. -* `metrics` (comma-separated list): Show only specific metrics, e.g., `train_loss,train_accuracy`. -* `sidebar` (string, `"auto"`, `"visible"`, `"collapsed"`, or `"hidden"`): - - * `"auto"` opens or collapses the sidebar based on the viewport width and is the default. - * `"visible"` starts with the full sidebar open. - * `"collapsed"` starts with only the narrow rail. - * `"hidden"` hides the sidebar completely. - - Explicit modes are not changed when the viewport is resized. -* `footer` (string, `"false"`): When set to `"false"`, hides the Gradio footer. By default, the footer is visible. -* `xmin` (number): Set the initial minimum value for the x-axis limits across all metrics plots. -* `xmax` (number): Set the initial maximum value for the x-axis limits across all metrics plots. -* `smoothing` (number): Set the initial value of the smoothing slider (0-20, where 0 = no smoothing). -* `plots_per_row` (`auto` or integer from 1 to 6): Set the initial value of the **Plots per row** control. The default is `auto`, which fits plots to the available width. -* `accordion` (string, `"hidden"`): When set to `"hidden"`, hides the section header accordions around metric groups. By default, section headers are visible. - -You can customize your ` -``` - - -``` - -You can also filter the dashboard to display only specific projects or metrics using query parameters. Supported parameters include: - -* `project` (string): Show only a specific project. -* `metrics` (comma-separated list): Show only specific metrics, e.g., `train_loss,train_accuracy`. -* `sidebar` (string, `"auto"`, `"visible"`, `"collapsed"`, or `"hidden"`): - - * `"auto"` opens or collapses the sidebar based on the viewport width and is the default. - * `"visible"` starts with the full sidebar open. - * `"collapsed"` starts with only the narrow rail. - * `"hidden"` hides the sidebar completely. - - Explicit modes are not changed when the viewport is resized. -* `footer` (string, `"false"`): When set to `"false"`, hides the Gradio footer. By default, the footer is visible. -* `xmin` (number): Set the initial minimum value for the x-axis limits across all metrics plots. -* `xmax` (number): Set the initial maximum value for the x-axis limits across all metrics plots. -* `smoothing` (number): Set the initial value of the smoothing slider (0-20, where 0 = no smoothing). -* `plots_per_row` (`auto` or integer from 1 to 6): Set the initial value of the **Plots per row** control. The default is `auto`, which fits plots to the available width. -* `accordion` (string, `"hidden"`): When set to `"hidden"`, hides the section header accordions around metric groups. By default, section headers are visible. - -You can customize your ` -``` - -