small update / fix

src/axolotl/cli/config.py

@@ -14,8 +14,8 @@ import yaml
 from transformers.utils import is_torch_bf16_gpu_available
 
 from axolotl.integrations.base import PluginManager
-from axolotl.telemetry import TelemetryManager
 from axolotl.telemetry.errors import send_errors
+from axolotl.telemetry.manager import TelemetryManager
 from axolotl.utils.comet_ import setup_comet_env_vars
 from axolotl.utils.config import (
     normalize_cfg_datasets,

src/axolotl/telemetry/callbacks.py

@@ -45,7 +45,7 @@ class TelemetryCallback(TrainerCallback):
         **kwargs,  # pylint: disable=unused-argument
     ):
         """Handle training start."""
-        self.telemetry_manager.send_event(event_type="train-start")
+        self.telemetry_manager.send_event(event_type="train-started")
 
     def on_train_end(
         self,
@@ -57,7 +57,7 @@ class TelemetryCallback(TrainerCallback):
         """Handle training end."""
         # Send training completion event
         self.telemetry_manager.send_event(
-            event_type="train-end",
+            event_type="train-ended",
             properties={
                 "loss": state.log_history[-1].get("loss", 0)
                 if state.log_history

src/axolotl/telemetry/errors.py

@@ -148,7 +148,7 @@ def send_errors(func: Callable) -> Callable:
 
                 # Send error telemetry
                 telemetry_manager.send_event(
-                    event_type=f"{module_path}-error",
+                    event_type=f"{module_path}-errored",
                     properties={
                         "exception": str(exception),
                         "stack_trace": stack_trace,

src/axolotl/train.py

@@ -22,8 +22,8 @@ from axolotl.contribs.lgpl.unsloth import (  # pylint: disable = no-name-in-modu
     fix_untrained_tokens,
 )
 from axolotl.logging_config import configure_logging
-from axolotl.telemetry import TelemetryManager
 from axolotl.telemetry.errors import send_errors
+from axolotl.telemetry.manager import TelemetryManager
 from axolotl.utils.dict import DictDefault
 from axolotl.utils.freeze import freeze_layers_except
 from axolotl.utils.models import load_model, load_processor, load_tokenizer
@@ -90,11 +90,11 @@ def train(
         model.generation_config.do_sample = True
 
     TELEMETRY_MANAGER.send_event(
-        event_type="model-load", properties=model.config.to_dict()
+        event_type="model-loaded", properties=model.config.to_dict()
     )
     if peft_config:
         TELEMETRY_MANAGER.send_event(
-            event_type="peft-config-load", properties=peft_config.to_dict()
+            event_type="peft-config-loaded", properties=peft_config.to_dict()
         )
 
     model_ref = None