Remove all backward compatibility code in API+CLI+SDK

api/localprovider_pyproject.toml

@@ -32,7 +32,7 @@ dependencies = [
   "soundfile==0.13.1",
   "tensorboardX==2.6.2.2",
   "timm==1.0.15",
-  "transformerlab==0.1.37",
+  "transformerlab==0.1.38",
   "transformerlab-inference==0.2.52",
   "transformers==4.57.1",
   "wandb==0.23.1",

api/pyproject.toml

@@ -25,7 +25,7 @@ dependencies = [
   "python-dotenv==1.1.0",
   "python-multipart==0.0.20",
   "sqlalchemy[asyncio]==2.0.40",
-  "transformerlab==0.1.37",
+  "transformerlab==0.1.38",
   "transformerlab-inference==0.2.52",
   "uvicorn==0.35.0",
   "watchfiles==1.0.5",

api/test/api/test_model_service.py

@@ -65,29 +65,6 @@ async def test_list_installed_models_non_hf_with_model_filename(monkeypatch):
     assert "local_path" in result[0]
 
 
-@pytest.mark.asyncio
-async def test_list_installed_models_non_hf_directory_model(monkeypatch):
-    """A non-HuggingFace directory-based model (no model_filename) with files is marked local."""
-    from transformerlab.services import model_service
-
-    model = make_model("MyOrg/dir-model", source="local", model_filename="")
-    monkeypatch.setattr(model_service.ModelService, "list_all", AsyncMock(return_value=[model]))
-    monkeypatch.setattr(model_service, "get_models_dir", AsyncMock(return_value="/models"))
-
-    monkeypatch.setattr(model_service.storage, "join", lambda *parts: "/".join(parts))
-    monkeypatch.setattr(model_service.storage, "exists", AsyncMock(return_value=True))
-    monkeypatch.setattr(model_service.storage, "isdir", AsyncMock(return_value=True))
-    monkeypatch.setattr(
-        model_service.storage,
-        "ls",
-        AsyncMock(return_value=["/models/dir-model/weights.bin", "/models/dir-model/index.json"]),
-    )
-
-    result = await model_service.list_installed_models()
-    assert len(result) == 1
-    assert result[0]["stored_in_filesystem"] is True
-
-
 @pytest.mark.asyncio
 async def test_list_installed_models_non_hf_directory_only_index(monkeypatch):
     """A non-HuggingFace directory with only index.json is NOT marked as local."""

api/transformerlab/routers/experiment/task.py

@@ -1166,10 +1166,10 @@ async def import_task_from_gallery(
             interactive_type = gallery_entry.get("interactive_type") or gallery_entry.get("id") or "custom"
             interactive_gallery_id = gallery_entry.get("id")
 
-            # Resolve task setup/command from the gallery entry's source:
+            # Resolve task setup/run from the gallery entry's source:
             # 1. github_repo_url + github_repo_dir -> fetch task.yaml from GitHub
             # 2. local_task_dir -> read task.yaml from local filesystem
-            # 3. inline setup/command fields on the gallery entry
+            # 3. inline setup/run fields on the gallery entry
             github_repo_url = gallery_entry.get("github_repo_url")
             github_repo_dir = gallery_entry.get("github_repo_dir")
             github_repo_branch = gallery_entry.get("github_repo_branch")
@@ -1197,7 +1197,7 @@ async def import_task_from_gallery(
                 "plugin": "remote_orchestrator",
                 "experiment_id": experimentId,
                 "cluster_name": task_name,
-                "run": source_yaml_data.get("run", source_yaml_data.get("command", "")),
+                "run": source_yaml_data.get("run", ""),
                 "setup": source_yaml_data.get("setup", "") or gallery_entry.get("setup", ""),
                 "interactive_type": interactive_type,
                 "subtype": "interactive",

api/transformerlab/services/model_service.py

@@ -18,13 +18,7 @@
 
 
 async def list_installed_models() -> list:
-    """
-    TODO: Clean this up to remove legacy code.
-
-    Legacy function for getting a list of models from all sources.
-
-    Check both the filesystem and workspace for models.
-    """
+    """Get a list of installed models with filesystem metadata attached."""
 
     # Use SDK to get all models from the filesystem
     models = await ModelService.list_all()
@@ -37,7 +31,6 @@ async def list_installed_models() -> list:
         # model_filename can be:
         # - A filename (e.g., "model.gguf") for file-based models
         # - "." for directory-based models (indicates the directory itself)
-        # - Empty string for legacy models (should be treated as directory-based)
         model_filename = model.get("json_data", {}).get("model_filename", "")
         is_huggingface = model.get("json_data", {}).get("source", "") == "huggingface"
         has_model_filename = model_filename != ""
@@ -51,27 +44,12 @@ async def list_installed_models() -> list:
             # Remove the Starting TransformerLab/ prefix to handle the save_transformerlab_model function
             potential_path = storage.join(models_dir, secure_filename("/".join(model_id.split("/")[1:])))
 
-        # Check if model should be considered local:
-        # 1. If it has a model_filename set (and is not a HuggingFace model, OR is a HuggingFace model stored locally), OR
-        # 2. If the directory exists and has files other than index.json
+        # A model is considered local if model_filename is set (non-HF) or if the
+        # HF model has model_filename and the file/directory exists locally.
         is_local_model = False
         if not is_huggingface:
-            # For non-HuggingFace models, check if it has model_filename or files in directory
             if has_model_filename:
                 is_local_model = True
-            elif await storage.exists(potential_path) and await storage.isdir(potential_path):
-                # Check if directory has files other than index.json
-                try:
-                    files = await storage.ls(potential_path, detail=False)
-                    # Extract basenames from full paths returned by storage.ls()
-                    file_basenames = [posixpath.basename(f.rstrip("/")) for f in files]
-                    # Filter out index.json and other metadata files
-                    model_files = [f for f in file_basenames if f not in ["index.json", "_tlab_provenance.json"]]
-                    if model_files:
-                        is_local_model = True
-                except (OSError, PermissionError):
-                    # If we can't read the directory, skip it
-                    pass
         elif is_huggingface and has_model_filename:
             # For HuggingFace models, if they have a model_filename and the file/directory exists locally,
             # treat them as stored locally (e.g., downloaded GGUF files)
@@ -128,9 +106,6 @@ async def list_installed_models() -> list:
             elif model_filename:
                 # Other file-based models - append the filename
                 model["local_path"] = storage.join(model["local_path"], model_filename)
-            else:
-                # Legacy model without model_filename but with files - use directory path
-                model["local_path"] = model["local_path"]
 
     return models
 

api/transformerlab/services/task_service.py

@@ -22,30 +22,6 @@
 DEFAULT_TASK_YAML = 'name: my-task\nresources:\n  cpus: 2\n  memory: 4\nrun: "echo hello"'
 
 
-def _normalize_legacy_command(task: Optional[Dict[str, Any]]) -> Optional[Dict[str, Any]]:
-    """
-    Backward compatibility helper: some legacy tasks may still store their
-    entrypoint under the key "command" instead of "run". To avoid breaking
-    those when launching or exporting, expose "run" on read if it is missing
-    or empty but "command" is present. New code should only write "run".
-    """
-    if not task:
-        return task
-
-    # If run is already set and truthy, do nothing.
-    if task.get("run"):
-        return task
-
-    legacy_command = task.get("command")
-    if not legacy_command:
-        return task
-
-    # Return a shallow copy with run populated so callers always see run.
-    normalized = dict(task)
-    normalized["run"] = legacy_command
-    return normalized
-
-
 class TaskService:
     """Service for managing tasks using filesystem storage"""
 
@@ -54,35 +30,29 @@ def __init__(self):
 
     async def task_get_all(self) -> List[Dict[str, Any]]:
         """Get all tasks from filesystem"""
-        tasks = await self.task_service.list_all()
-        return [_normalize_legacy_command(t) or t for t in tasks]
+        return await self.task_service.list_all()
 
     async def task_get_by_id(self, task_id: str, experiment_id: Optional[str] = None) -> Optional[Dict[str, Any]]:
         """Get a specific task by ID"""
-        task = await self.task_service.get_by_id(task_id, experiment_id=experiment_id)
-        return _normalize_legacy_command(task)
+        return await self.task_service.get_by_id(task_id, experiment_id=experiment_id)
 
     async def task_get_by_type(self, task_type: str) -> List[Dict[str, Any]]:
         """Get all tasks of a specific type"""
-        tasks = await self.task_service.list_by_type(task_type)
-        return [_normalize_legacy_command(t) or t for t in tasks]
+        return await self.task_service.list_by_type(task_type)
 
     async def task_get_by_experiment(self, experiment_id: str) -> List[Dict[str, Any]]:
         """Get all tasks for a specific experiment"""
-        tasks = await self.task_service.list_by_experiment(experiment_id)
-        return [_normalize_legacy_command(t) or t for t in tasks]
+        return await self.task_service.list_by_experiment(experiment_id)
 
     async def task_get_by_type_in_experiment(self, task_type: str, experiment_id: str) -> List[Dict[str, Any]]:
         """Get all tasks of a specific type in a specific experiment"""
-        tasks = await self.task_service.list_by_type_in_experiment(task_type, experiment_id)
-        return [_normalize_legacy_command(t) or t for t in tasks]
+        return await self.task_service.list_by_type_in_experiment(task_type, experiment_id)
 
     async def task_get_by_subtype_in_experiment(
         self, experiment_id: str, subtype: str, task_type: Optional[str] = None
     ) -> List[Dict[str, Any]]:
         """Get all tasks for a specific experiment filtered by subtype and optionally by type"""
-        tasks = await self.task_service.list_by_subtype_in_experiment(experiment_id, subtype, task_type)
-        return [_normalize_legacy_command(t) or t for t in tasks]
+        return await self.task_service.list_by_subtype_in_experiment(experiment_id, subtype, task_type)
 
     async def add_task(self, task_data: Dict[str, Any]) -> str:
         """Create a new task - all fields stored directly in JSON"""

cli/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "transformerlab-cli"
-version = "0.0.50"
+version = "0.0.51"
 description = "Transformer Lab CLI"
 requires-python = ">=3.10"
 authors = [{ name = "Transformer Lab", email = "hello@transformerlab.ai" }]

cli/src/transformerlab_cli/commands/task.py

@@ -273,7 +273,13 @@ def _upload_path_to_server(path_to_upload: str) -> str:
             console.print(f"[error]Error:[/error] Upload init failed ({init_resp.status_code})")
             raise typer.Exit(1)
 
-        upload_id = init_resp.json()["upload_id"]
+        try:
+            upload_id = init_resp.json().get("upload_id")
+        except ValueError:
+            upload_id = None
+        if not upload_id:
+            console.print("[error]Error:[/error] Upload init returned no upload_id.")
+            raise typer.Exit(1)
         status_resp = api.get(f"/upload/{upload_id}/status")
         already_received: set[int] = set(
             status_resp.json().get("received", []) if status_resp.status_code == 200 else []

lab-sdk/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "transformerlab"
-version = "0.1.37"
+version = "0.1.38"
 description = "Python SDK for Transformer Lab"
 readme = "README.md"
 requires-python = ">=3.10"