Harden telemetry delivery and refine recipe metadata

docs/Privacy.md

@@ -13,4 +13,4 @@ In addition, Olive may collect additional telemetry data such as:
 - Performance data
 - Exception information
 
-Collection of this additional telemetry can be disabled by adding the `--disable_telemetry` flag to any Olive CLI command, or by setting the `OLIVE_DISABLE_TELEMETRY` environment variable to `1` before running. Telemetry is also automatically disabled when a CI/CD environment is detected (e.g., GitHub Actions, Azure Pipelines, Jenkins). If telemetry is enabled, but cannot be sent to Microsoft, it will be stored locally and sent when a connection is available. You can override the default cache location by setting the `OLIVE_TELEMETRY_CACHE_DIR` environment variable to a valid directory path.
+Collection of this additional telemetry can be disabled by adding the `--disable_telemetry` flag to any Olive CLI command, or by setting the `OLIVE_DISABLE_TELEMETRY` environment variable to `1` before running. In CI/CD environments (e.g., GitHub Actions, Azure Pipelines, Jenkins), Olive suppresses the general heartbeat/action/error events and only emits the `OliveRecipe` event. The `OliveRecipe` event may include recipe metadata such as pass types, explicitly configured target settings, the host system type (including the default `LocalSystem` host) and any explicitly configured host accelerator settings, whether a custom package config was provided, a redacted snapshot of custom package-config overrides, and a redacted snapshot of explicitly supplied config overrides. Outside CI/CD environments, if telemetry is enabled but cannot be sent to Microsoft, it will be stored locally and sent when a connection is available. You can override the default cache location by setting the `OLIVE_TELEMETRY_CACHE_DIR` environment variable to a valid directory path.

docs/source/how-to/extending/custom-scripts.md

@@ -36,7 +36,7 @@ class MyDataLoader:
 
 @Registry.register_dataloader()
 def my_dataloader(dataset, batch_size):
-    return MyDataloader(dataset, batch_size)
+    return MyDataLoader(dataset, batch_size)
 
 @Registry.register_post_process()
 def my_post_process(output):

olive/cache.py

@@ -439,13 +439,19 @@ def save_model(
                             else:
                                 from olive.passes.onnx.common import resave_model
 
+                                component_output_name = (
+                                    component_name
+                                    if Path(component_name).suffix == ".onnx"
+                                    else f"{component_name}.onnx"
+                                )
+
                                 resave_model(
                                     ModelConfig.model_validate(component_model_json).create_model().model_path,
-                                    actual_output_dir / f"{component_name}.onnx",
+                                    actual_output_dir / component_output_name,
                                     saved_external_files=saved_external_files,
                                 )
                                 component_model_json["config"][resource_name] = str(actual_output_dir)
-                                component_model_json["config"]["onnx_file_name"] = f"{component_name}.onnx"
+                                component_model_json["config"]["onnx_file_name"] = component_output_name
 
                         copied_components.append(component_model_json)
 

olive/cli/auto_opt.py

@@ -2,6 +2,7 @@
 # Copyright (c) Microsoft Corporation. All rights reserved.
 # Licensed under the MIT License.
 # --------------------------------------------------------------------------
+import logging
 from argparse import ArgumentParser
 from collections import OrderedDict
 from copy import deepcopy
@@ -25,13 +26,19 @@
 from olive.package_config import OlivePackageConfig
 from olive.telemetry import action
 
+logger = logging.getLogger(__name__)
+
 
 class AutoOptCommand(BaseOliveCLICommand):
     @staticmethod
     def register_subcommand(parser: ArgumentParser):
         sub_parser = parser.add_parser(
             "auto-opt",
-            help="Automatically optimize the performance of the input model.",
+            help=(
+                "Automatically optimize the performance of the input model.\n"
+                "**** DEPRECATION WARNING ****\n"
+                '"auto-opt" command is deprecated in favor of "optimize".'
+            ),
         )
 
         # Model options
@@ -174,6 +181,11 @@ def register_subcommand(parser: ArgumentParser):
 
     @action
     def run(self):
+        logger.warning(
+            "**** DEPRECATION WARNING ****\n"
+            '"auto-opt" command is deprecated in favor of "optimize". Please switch to using "optimize".\n'
+            "Deprecated commands will be removed entirely in future release."
+        )
         return self._run_workflow()
 
     def _get_run_config(self, tempdir) -> dict:

olive/cli/base.py

@@ -42,13 +42,24 @@ def _run_workflow(self):
             if self.args.dry_run:
                 print("Dry run mode enabled. Configuration file is generated but no optimization is performed.")
                 return None
-            workflow_output = olive_run(run_config)
+            workflow_output = olive_run(run_config, recipe_telemetry_metadata=self._get_recipe_telemetry_metadata())
             if not workflow_output.has_output_model():
                 print("No output model produced. Please check the log for details.")
             else:
                 print(f"Model is saved at {self.args.output_path}")
             return workflow_output
 
+    def _get_recipe_telemetry_metadata(self) -> dict[str, str]:
+        recipe_name = self.__class__.__name__
+        if recipe_name.endswith("Command"):
+            recipe_name = recipe_name[: -len("Command")]
+        return {
+            "recipe_name": recipe_name,
+            "recipe_command": recipe_name,
+            "recipe_source": "generated_cli",
+            "recipe_format": "generated",
+        }
+
     @staticmethod
     def _parse_extra_options(kv_items):
         from onnxruntime_genai import __version__ as OrtGenaiVersion