# The InvokeAI Download Queue The DownloadQueueService provides a multithreaded parallel download queue for arbitrary URLs, with queue prioritization, event handling, and restart capabilities. ## Simple Example ``` from invokeai.app.services.download import DownloadQueueService, TqdmProgress download_queue = DownloadQueueService() for url in ['https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/a-painting-of-a-fire.png?raw=true', 'https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/birdhouse.png?raw=true', 'https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/missing.png', 'https://civitai.com/api/download/models/152309?type=Model&format=SafeTensor', ]: # urls start downloading as soon as download() is called download_queue.download(source=url, dest='/tmp/downloads', on_progress=TqdmProgress().update ) download_queue.join() # wait for all downloads to finish for job in download_queue.list_jobs(): print(job.model_dump_json(exclude_none=True, indent=4),"\n") ``` Output: ``` { "source": "https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/a-painting-of-a-fire.png?raw=true", "dest": "/tmp/downloads", "id": 0, "priority": 10, "status": "completed", "download_path": "/tmp/downloads/a-painting-of-a-fire.png", "job_started": "2023-12-04T05:34:41.742174", "job_ended": "2023-12-04T05:34:42.592035", "bytes": 666734, "total_bytes": 666734 } { "source": "https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/birdhouse.png?raw=true", "dest": "/tmp/downloads", "id": 1, "priority": 10, "status": "completed", "download_path": "/tmp/downloads/birdhouse.png", "job_started": "2023-12-04T05:34:41.741975", "job_ended": "2023-12-04T05:34:42.652841", "bytes": 774949, "total_bytes": 774949 } { "source": "https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/missing.png", "dest": "/tmp/downloads", "id": 2, "priority": 10, "status": "error", "job_started": "2023-12-04T05:34:41.742079", "job_ended": "2023-12-04T05:34:42.147625", "bytes": 0, "total_bytes": 0, "error_type": "HTTPError(Not Found)", "error": "Traceback (most recent call last):\n File \"/home/lstein/Projects/InvokeAI/invokeai/app/services/download/download_default.py\", line 182, in _download_next_item\n self._do_download(job)\n File \"/home/lstein/Projects/InvokeAI/invokeai/app/services/download/download_default.py\", line 206, in _do_download\n raise HTTPError(resp.reason)\nrequests.exceptions.HTTPError: Not Found\n" } { "source": "https://civitai.com/api/download/models/152309?type=Model&format=SafeTensor", "dest": "/tmp/downloads", "id": 3, "priority": 10, "status": "completed", "download_path": "/tmp/downloads/xl_more_art-full_v1.safetensors", "job_started": "2023-12-04T05:34:42.147645", "job_ended": "2023-12-04T05:34:43.735990", "bytes": 719020768, "total_bytes": 719020768 } ``` ## The API The default download queue is `DownloadQueueService`, an implementation of ABC `DownloadQueueServiceBase`. It juggles multiple background download requests and provides facilities for interrogating and cancelling the requests. Access to a current or past download task is mediated via `DownloadJob` objects which report the current status of a job request ### The Queue Object A default download queue is located in `ApiDependencies.invoker.services.download_queue`. However, you can create additional instances if you need to isolate your queue from the main one. ``` queue = DownloadQueueService(event_bus=events) ``` `DownloadQueueService()` takes three optional arguments: | **Argument** | **Type** | **Default** | **Description** | |----------------|-----------------|---------------|-----------------| | `max_parallel_dl` | int | 5 | Maximum number of simultaneous downloads allowed | | `event_bus` | EventServiceBase | None | System-wide FastAPI event bus for reporting download events | | `requests_session` | requests.sessions.Session | None | An alternative requests Session object to use for the download | `max_parallel_dl` specifies how many download jobs are allowed to run simultaneously. Each will run in a different thread of execution. `event_bus` is an EventServiceBase, typically the one created at InvokeAI startup. If present, download events are periodically emitted on this bus to allow clients to follow download progress. `requests_session` is a url library requests Session object. It is used for testing. ### The Job object The queue operates on a series of download job objects. These objects specify the source and destination of the download, and keep track of the progress of the download. The only job type currently implemented is `DownloadJob`, a pydantic object with the following fields: | **Field** | **Type** | **Default** | **Description** | |----------------|-----------------|---------------|-----------------| | _Fields passed in at job creation time_ | | `source` | AnyHttpUrl | | Where to download from | | `dest` | Path | | Where to download to | | `access_token` | str | | [optional] string containing authentication token for access | | `on_start` | Callable | | [optional] callback when the download starts | | `on_progress` | Callable | | [optional] callback called at intervals during download progress | | `on_complete` | Callable | | [optional] callback called after successful download completion | | `on_error` | Callable | | [optional] callback called after an error occurs | | `id` | int | auto assigned | Job ID, an integer >= 0 | | `priority` | int | 10 | Job priority. Lower priorities run before higher priorities | | | | _Fields updated over the course of the download task_ | `status` | DownloadJobStatus| | Status code | | `download_path` | Path | | Path to the location of the downloaded file | | `job_started` | float | | Timestamp for when the job started running | | `job_ended` | float | | Timestamp for when the job completed or errored out | | `job_sequence` | int | | A counter that is incremented each time a model is dequeued | | `bytes` | int | 0 | Bytes downloaded so far | | `total_bytes` | int | 0 | Total size of the file at the remote site | | `error_type` | str | | String version of the exception that caused an error during download | | `error` | str | | String version of the traceback associated with an error | | `cancelled` | bool | False | Set to true if the job was cancelled by the caller| When you create a job, you can assign it a `priority`. If multiple jobs are queued, the job with the lowest priority runs first. Every job has a `source` and a `dest`. `source` is a pydantic.networks AnyHttpUrl object. The `dest` is a path on the local filesystem that specifies the destination for the downloaded object. Its semantics are described below. When the job is submitted, it is assigned a numeric `id`. The id can then be used to fetch the job object from the queue. The `status` field is updated by the queue to indicate where the job is in its lifecycle. Values are defined in the string enum `DownloadJobStatus`, a symbol available from `invokeai.app.services.download_manager`. Possible values are: | **Value** | **String Value** | ** Description ** | |--------------|---------------------|-------------------| | `WAITING` | waiting | Job is on the queue but not yet running| | `RUNNING` | running | The download is started | | `COMPLETED` | completed | Job has finished its work without an error | | `ERROR` | error | Job encountered an error and will not run again| `job_started` and `job_ended` indicate when the job was started (using a python timestamp) and when it completed. In case of an error, the job's status will be set to `DownloadJobStatus.ERROR`, the text of the Exception that caused the error will be placed in the `error_type` field and the traceback that led to the error will be in `error`. A cancelled job will have status `DownloadJobStatus.ERROR` and an `error_type` field of "DownloadJobCancelledException". In addition, the job's `cancelled` property will be set to True. ### Callbacks Download jobs can be associated with a series of callbacks, each with the signature `Callable[["DownloadJob"], None]`. The callbacks are assigned using optional arguments `on_start`, `on_progress`, `on_complete` and `on_error`. When the corresponding event occurs, the callback wil be invoked and passed the job. The callback will be run in a `try:` context in the same thread as the download job. Any exceptions that occur during execution of the callback will be caught and converted into a log error message, thereby allowing the download to continue. #### `TqdmProgress` The `invokeai.app.services.download.download_default` module defines a class named `TqdmProgress` which can be used as an `on_progress` handler to display a completion bar in the console. Use as follows: ``` from invokeai.app.services.download import TqdmProgress download_queue.download(source='http://some.server.somewhere/some_file', dest='/tmp/downloads', on_progress=TqdmProgress().update ) ``` ### Events If the queue was initialized with the InvokeAI event bus (the case when using `ApiDependencies.invoker.services.download_queue`), then download events will also be issued on the bus. The events are: * `download_started` -- This is issued when a job is taken off the queue and a request is made to the remote server for the URL headers, but before any data has been downloaded. The event payload will contain the keys `source` and `download_path`. The latter contains the path that the URL will be downloaded to. * `download_progress -- This is issued periodically as the download runs. The payload contains the keys `source`, `download_path`, `current_bytes` and `total_bytes`. The latter two fields can be used to display the percent complete. * `download_complete` -- This is issued when the download completes successfully. The payload contains the keys `source`, `download_path` and `total_bytes`. * `download_error` -- This is issued when the download stops because of an error condition. The payload contains the fields `error_type` and `error`. The former is the text representation of the exception, and the latter is a traceback showing where the error occurred. ### Job control To create a job call the queue's `download()` method. You can list all jobs using `list_jobs()`, fetch a single job by its with `id_to_job()`, cancel a running job with `cancel_job()`, cancel all running jobs with `cancel_all_jobs()`, and wait for all jobs to finish with `join()`. #### job = queue.download(source, dest, priority, access_token) Create a new download job and put it on the queue, returning the DownloadJob object. #### jobs = queue.list_jobs() Return a list of all active and inactive `DownloadJob`s. #### job = queue.id_to_job(id) Return the job corresponding to given ID. Return a list of all active and inactive `DownloadJob`s. #### queue.prune_jobs() Remove inactive (complete or errored) jobs from the listing returned by `list_jobs()`. #### queue.join() Block until all pending jobs have run to completion or errored out.