Revert "deploy model in workspace" - Will be released soon.

Author: lrosemberg

roboflow/core/workspace.py

@@ -1,5 +1,3 @@
-from __future__ import annotations
-
 import concurrent.futures
 import glob
 import json
@@ -12,12 +10,11 @@
 
 from roboflow.adapters import rfapi
 from roboflow.adapters.rfapi import AnnotationSaveError, ImageUploadError, RoboflowError
-from roboflow.config import API_URL, APP_URL, CLIP_FEATURIZE_URL, DEMO_KEYS
+from roboflow.config import API_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
 
 
@@ -569,74 +566,6 @@ 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}