Merge pull request #356 from roboflow/lean/deploy-versionless-model

Versionless model deploy/upload

roboflow/__init__.py

@@ -15,7 +15,7 @@
 from roboflow.models import CLIPModel, GazeModel  # noqa: F401
 from roboflow.util.general import write_line
 
-__version__ = "1.1.52"
+__version__ = "1.1.53"
 
 
 def check_key(api_key, model, notebook, num_retries=0):

roboflow/core/workspace.py

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 import concurrent.futures
 import glob
 import json
@@ -10,11 +12,12 @@
 
 from roboflow.adapters import rfapi
 from roboflow.adapters.rfapi import AnnotationSaveError, ImageUploadError, RoboflowError
-from roboflow.config import API_URL, CLIP_FEATURIZE_URL, DEMO_KEYS
+from roboflow.config import API_URL, APP_URL, CLIP_FEATURIZE_URL, DEMO_KEYS
 from roboflow.core.project import Project
 from roboflow.util import folderparser
 from roboflow.util.active_learning_utils import check_box_size, clip_encode, count_comparisons
 from roboflow.util.image_utils import load_labelmap
+from roboflow.util.model_processor import process
 from roboflow.util.two_stage_utils import ocr_infer
 
 
@@ -566,6 +569,73 @@ def active_learning(
             prediction_results if type(raw_data_location) is not np.ndarray else prediction_results[-1]["predictions"]
         )
 
+    def deploy_model(
+        self,
+        model_type: str,
+        model_path: str,
+        project_ids: list[str],
+        model_name: str,
+        filename: str = "weights/best.pt",
+    ):
+        """Uploads provided weights file to Roboflow.
+        Args:
+            model_type (str): The type of the model to be deployed.
+            model_path (str): File path to the model weights to be uploaded.
+            project_ids (list[str]): List of project IDs to deploy the model to.
+            filename (str, optional): The name of the weights file. Defaults to "weights/best.pt".
+        """
+
+        if not project_ids:
+            raise ValueError("At least one project ID must be provided")
+
+        # Validate if provided project URLs belong to user's projects
+        user_projects = set(project.split("/")[-1] for project in self.projects())
+        for project_id in project_ids:
+            if project_id not in user_projects:
+                raise ValueError(f"Project {project_id} is not accessible in this workspace")
+
+        zip_file_name = process(model_type, model_path, filename)
+
+        if zip_file_name is None:
+            raise RuntimeError("Failed to process model")
+
+        self._upload_zip(model_type, model_path, project_ids, model_name, zip_file_name)
+
+    def _upload_zip(
+        self,
+        model_type: str,
+        model_path: str,
+        project_ids: list[str],
+        model_name: str,
+        model_file_name: str,
+    ):
+        # This endpoint returns a signed URL to upload the model
+        res = requests.post(
+            f"{API_URL}/{self.url}/models/prepareUpload?api_key={self.__api_key}&modelType={model_type}&modelName={model_name}&projectIds={','.join(project_ids)}&nocache=true"
+        )
+        try:
+            res.raise_for_status()
+        except Exception as e:
+            print(f"An error occured when getting the model deployment URL: {e}")
+            return
+
+        # Upload the model to the signed URL
+        res = requests.put(
+            res.json()["url"],
+            data=open(os.path.join(model_path, model_file_name), "rb"),
+        )
+        try:
+            res.raise_for_status()
+
+            for project_id in project_ids:
+                print(
+                    f"View the status of your deployment for project {project_id} at:"
+                    f" {APP_URL}/{self.url}/{project_id}/models"
+                )
+
+        except Exception as e:
+            print(f"An error occured when uploading the model: {e}")
+
     def __str__(self):
         projects = self.projects()
         json_value = {"name": self.name, "url": self.url, "projects": projects}

roboflow/roboflowpy.py

@@ -79,10 +79,20 @@ def upload_model(args):
     rf = roboflow.Roboflow(args.api_key)
     workspace = rf.workspace(args.workspace)
 
-    # Deploy to specific version
-    project = workspace.project(args.project)
-    version = project.version(args.version_number)
-    version.deploy(str(args.model_type), str(args.model_path), str(args.filename))
+    if args.version_number is not None:
+        # Deploy to specific version
+        project = workspace.project(args.project)
+        version = project.version(args.version_number)
+        version.deploy(str(args.model_type), str(args.model_path), str(args.filename))
+    else:
+        # Deploy to multiple projects
+        workspace.deploy_model(
+            model_type=str(args.model_type),
+            model_path=str(args.model_path),
+            project_ids=args.project,
+            model_name=str(args.model_name),
+            filename=str(args.filename),
+        )
 
 
 def list_projects(args):
@@ -479,13 +489,15 @@ def _add_upload_model_parser(subparsers):
     upload_model_parser.add_argument(
         "-p",
         dest="project",
-        help="project_id to upload the model into",
+        action="append",  # Allow multiple projects
+        help="project_id to upload the model into (can be specified multiple times)",
     )
     upload_model_parser.add_argument(
         "-v",
         dest="version_number",
         type=int,
-        help="version number to upload the model to",
+        help="version number to upload the model to (optional)",
+        default=None,
     )
     upload_model_parser.add_argument(
         "-t",
@@ -503,6 +515,11 @@ def _add_upload_model_parser(subparsers):
         default="weights/best.pt",
         help="name of the model file",
     )
+    upload_model_parser.add_argument(
+        "-n",
+        dest="model_name",
+        help="name of the model",
+    )
     upload_model_parser.set_defaults(func=upload_model)