feat: Add eot_token property to ControlModel and derived classes.

Task: PHS-492

CHANGELOG.md

@@ -6,7 +6,7 @@
 ...
 
 ### New Features
-...
+ - Add `eot_token` property to `ControlModel` and derived classes (`LuminousControlModel`, `Llama2InstructModel` and `Llama3InstructModel`) and let `PromptBasedClassify` use this property instead of a hardcoded string.
 
 ### Fixes
 ...

src/intelligence_layer/core/model.py

@@ -209,6 +209,11 @@ def __init__(
             )
         super().__init__(name, client)
 
+    @property
+    @abstractmethod
+    def eot_token(self) -> str:
+        pass
+
     @abstractmethod
     def to_instruct_prompt(
         self,
@@ -256,6 +261,10 @@ def __init__(
     ) -> None:
         super().__init__(name, client)
 
+    @property
+    def eot_token(self) -> str:
+        return "<|endoftext|>"
+
     def to_instruct_prompt(
         self,
         instruction: str,
@@ -300,6 +309,10 @@ def __init__(
     ) -> None:
         super().__init__(name, client)
 
+    @property
+    def eot_token(self) -> str:
+        return "<|endoftext|>"
+
     def to_instruct_prompt(
         self,
         instruction: str,
@@ -330,7 +343,6 @@ class Llama3InstructModel(ControlModel):
 
 {{response_prefix}}{% endif %}"""
     )
-    EOT_TOKEN = "<|eot_id|>"
 
     RECOMMENDED_MODELS = [
         "llama-3-8b-instruct",
@@ -344,14 +356,18 @@ def __init__(
     ) -> None:
         super().__init__(name, client)
 
+    @property
+    def eot_token(self) -> str:
+        return "<|eot_id|>"
+
     def _add_eot_token_to_stop_sequences(self, input: CompleteInput) -> CompleteInput:
         # remove this once the API supports the llama-3 EOT_TOKEN
         params = input.__dict__
         if isinstance(params["stop_sequences"], list):
-            if self.EOT_TOKEN not in params["stop_sequences"]:
-                params["stop_sequences"].append(self.EOT_TOKEN)
+            if self.eot_token not in params["stop_sequences"]:
+                params["stop_sequences"].append(self.eot_token)
         else:
-            params["stop_sequences"] = [self.EOT_TOKEN]
+            params["stop_sequences"] = [self.eot_token]
         return CompleteInput(**params)
 
     def complete(self, input: CompleteInput, tracer: Tracer) -> CompleteOutput:

src/intelligence_layer/examples/classify/prompt_based_classify.py

@@ -122,7 +122,7 @@ def _log_probs_per_label(
 
     def _prepare_label_for_echo_task(self, label: str) -> str:
         label = label if re.match(r"^\s+", label) else f" {label}"
-        return label + "<|endoftext|>"
+        return label + self._model.eot_token
 
     def _compute_scores(
         self,