some more detailed comments

Signed-off-by: nigel brown <[email protected]>

Author: therealnb

poetry.lock

@@ -1,6 +1,11 @@
 """
 A module for spotting suspicious commands using the embeddings
 from our local LLM and a futher ANN categorisier.
+
+The code in here is used for inference. The training code is in
+SuspiciousCommandsTrainer. The split is because we don't want to
+install torch on a docker, it is too big. So we train the model on
+a local machine and then use the generated onnx file for inference.
 """
 
 import os

src/codegate/pipeline/suspicious_commands/suspicious_commands.py

@@ -1,6 +1,11 @@
 """
 A module for spotting suspicious commands using the embeddings
 from our local LLM and a futher ANN categorisier.
+
+The classes in here are not used for inference. The split is
+because we don't want to install torch on a docker, it is too
+big. So we train the model on a local machine and then use the
+generated onnx file for inference on the docker.
 """
 
 import os
@@ -51,11 +56,12 @@ def forward(self, x):
 
 class SuspiciousCommandsTrainer(SuspiciousCommands):
     """
-    Class to handle suspicious command detection using a neural network.
+    Class to train suspicious command detection using a neural network.
 
     Attributes:
         model_path (str): Path to the model.
-        inference_engine (LlamaCppInferenceEngine): Inference engine for embedding.
+        inference_engine (LlamaCppInferenceEngine): Inference engine for
+        embedding.
         simple_nn (SimpleNN): Neural network model.
     """
 

src/codegate/pipeline/suspicious_commands/suspicious_commands_trainer.py

@@ -89,6 +89,9 @@ def test_initialization(sc):
 async def test_train_and_save():
     """
     Test the training process of the SuspiciousCommands instance.
+    This test is skipped if the model file is there. Also, the
+    training code will need torch installed to run. This is not
+    included in the default toml file.
     """
     if os.path.exists(MODEL_FILE):
         return