v1.3.1 - The CLI Rewrite: Built for Agents

This release rewrites the Roboflow CLI from the ground up to serve as the canonical machine interface for the Roboflow platform. Every command now supports --json for structured output, follows a consistent noun verb pattern, and provides actionable error messages to make Roboflow accessible to coding agents, CI/CD pipelines, and automation workflows.

Highlights

🏗️ Modular CLI architecture — The monolithic CLI has been decomposed into 18 handler modules organized by resource (project, version, image, model, workspace, etc.), each with a clean noun-verb pattern. (#445)

📡 REST API feature parity — 22 new API adapter functions and corresponding CLI commands for folders, annotation batches/jobs, workflows, workspace stats, version creation, video status, and universe search. (#446)

⚡ Typer framework migration — Migrated from argparse to typer for Rich-formatted help, built-in shell completion, type-safe parameters, and consistency with the Roboflow Inference CLI. (#447)

New Commands

Group	Commands
annotation batch	list, get
annotation job	list, get, create
folder	list, create, delete
workflow	list, get, create, update, version-list, fork
workspace stats	team, usage, plan
version create	Create new dataset versions from CLI
video status	Check async video inference job status
universe search	Search public datasets and models
model infer	Run inference (canonical form of infer)
image search	Unified workspace/project search with optional -p flag
completion	bash, zsh, fish — shell completion scripts

Agent Experience (AX)

• --json everywhere — Every command supports --json for structured output with a stable schema
• Structured errors — {"error": {"message": "...", "hint": "..."}} on stderr with exit codes (0=success, 1=error, 2=auth, 3=not found)
• No interactive prompts when all required flags are provided
• Actionable hints — Errors tell you what went wrong AND what to do next
• Auto-detected plan limits — Plan-gated errors automatically suggest upgrade paths
• API key sanitization — Credentials are stripped from error messages

Developer Experience (DX)

• Rich-formatted help — Color-coded commands, options, and descriptions
• Alphabetized commands and options at every level
• Flattened top-level help — roboflow --help shows all commands as noun verb in a single view
• Shell completion — roboflow completion bash/zsh/fish generates completion scripts

SDK Additions

• Workspace.list_folders(), create_folder(), delete_folder()
• Workspace.get_team_stats(), get_usage_stats(), get_plan_info()
• Project.list_batches(), get_batch(), list_jobs(), get_job(), create_job()
• Project.list_workflows(), get_workflow(), create_workflow(), update_workflow()
• Workspace.delete_image() (#442)
• Key-value metadata support for image upload (#440)
• Search export with download and extraction (#439)

Breaking Changes

• Python 3.9 dropped — Minimum version is now Python 3.10+
• typer>=0.12.0 added as a dependency (replaces argparse for CLI)

Backwards Compatibility

All legacy CLI commands and flags continue to work. The old roboflow upload, roboflow download, roboflow login forms are preserved as hidden aliases. Scripts importing from roboflow.roboflowpy remain functional.

Other Changes

• Added confidence argument to keypoint detection model (#354)
• Added large RF-DETR sizes and segmentation model upload (#434)
• Flexible annotation/image filename matching (#417)
• Project.delete_images() method (#424)
• Configurable training epochs (#420)
• Pre-commit hooks updated (#387)

Full Changelog: v1.2.16...v1.3.1

Workspace level new methods

At the workspace level you can now search and delete images.

Sample code using both:

"""Delete all orphan images matching a workspace-level search query.

Usage:
    python tests/manual/demo_search_delete.py
"""

from roboflow import Roboflow

QUERY = "project:false"
PAGE_SIZE = 100
DELETE_BATCH_SIZE = 1000
DRY_RUN = False  # set to False to actually delete

WORKSPACE_SLUG = "workspace"


def main():
    rf = Roboflow()
    workspace = rf.workspace(WORKSPACE_SLUG)

    print(f"Workspace: {workspace.url}")
    print(f"Query: {QUERY}")
    print(f"Dry run: {DRY_RUN}")
    print()

    # Collect all matching image IDs.
    # When deleting (not dry run), skip continuation tokens because deleted
    # images shift the result set — always re-search from page 1.
    all_ids = []
    token = None
    while True:
        page = workspace.search(
            QUERY,
            page_size=PAGE_SIZE,
            fields=["filename"],
            continuation_token=token,
        )
        results = page.get("results", [])
        if not results:
            break
        total = page.get("total", "?")
        all_ids.extend(img["id"] for img in results)
        print(f"Found {len(all_ids)}/{total} images so far...")
        token = page.get("continuationToken")
        if not token:
            break

    print(f"\nTotal images matching '{QUERY}': {len(all_ids)}")

    if not all_ids:
        print("Nothing to delete.")
        return

    if DRY_RUN:
        print("\n[DRY RUN] Would delete the above images. Set DRY_RUN=False to proceed.")
        return

    for i in range(0, len(all_ids), DELETE_BATCH_SIZE):
        batch = all_ids[i : i + DELETE_BATCH_SIZE]
        print(f"Deleting batch {i // DELETE_BATCH_SIZE + 1} ({len(batch)} images)...")
        result = workspace.delete_images(batch)
        print(f"  deleted={result.get('deletedSources')}, skipped={result.get('skippedSources')}")

    print(f"\nDone. Deleted {len(all_ids)} images.")


if __name__ == "__main__":
    main()

1.2.15 - Upload images with metadata

We now make it available to the python sdk to upload metadata when starting upload

Export search results functionality

We provide a new method to export images and annotations based on search queries.
It replicates the Asset Library Download functionality on the CLI.

RFDETR large and seg models upload

Includes model upload for new rf-detr models.
pi_heif discontinued Python3.9 support, so this is handled in the release as well.

Add yolo26 upload

Users can now upload yolo26 models from ultralytics 8.4.1 or higher

v1.2.11

What's Changed

• adds curlable script to sign urls to images in s3 buckets by @tonylampada in #419
• Add ability to configure model training epochs by @PawelPeczek-Roboflow in #420

Full Changelog: v1.2.10...v1.2.11

v1.2.10

What's Changed

• Added Confidence Argument to keypoint detection model by @Greenstan in #354
• Add 'rfdetr-seg-preview' to supported model types by @capjamesg in #414
• Bump version to 1.2.10 by @iurisilvio in #416

New Contributors

• @Greenstan made their first contribution in #354

Full Changelog: v1.2.9...v1.2.10

v1.2.9

What's Changed

• fix is_prediction function call by @sberan in #413

Full Changelog: v1.2.8...v1.2.9

v1.2.8

What's Changed

• Add are_predictions flag to dataset upload by @sberan in #412

Full Changelog: v1.2.7...v1.2.8