feat(LAB-3307): handle export of comparison in llm_static

src/kili/domain/llm.py

@@ -138,6 +138,7 @@ class ProjectModelDict(TypedDict):
 class ChatItem(TypedDict):
     """Dict that represents a ChatItem."""
 
+    id: str
     content: str
     external_id: str
     model_name: Optional[str]
@@ -153,8 +154,9 @@ class ConversationLabel(TypedDict):
 
 
 class Conversation(TypedDict):
+    """Dict that represents a Conversation."""
+
     external_id: Optional[str]
     chat_items: List[ChatItem]
     label: Optional[ConversationLabel]
-    labeler: str
     metadata: Optional[dict]

src/kili/llm/services/export/dynamic.py

@@ -45,8 +45,19 @@ def export(
         for asset in assets:
             # obfuscate models here
             obfuscated_models = {}
-            for index, asset_project_model in enumerate(asset["assetProjectModels"]):
-                obfuscated_models[asset_project_model["id"]] = f"{chr(65 + index)}"
+            if asset.get("assetProjectModels"):
+                for index, asset_project_model in enumerate(asset["assetProjectModels"]):
+                    obfuscated_models[asset_project_model["id"]] = f"{chr(65 + index)}"
+            else:
+                model_names = {
+                    chat_item.get("modelName")
+                    for chat_item in asset["labels"][0]["chatItems"]
+                    if chat_item.get("modelName") is not None
+                }
+                obfuscated_models = {
+                    model_name: f"{chr(65 + index)}" for index, model_name in enumerate(model_names)
+                }
+
             for label in asset["labels"]:
                 result = {}
                 chat_items = label["chatItems"]
@@ -81,17 +92,23 @@ def export(
                     if step == total_rounds - 1 and formatted_response["conversation"]:
                         label_data["label"]["conversation"] = formatted_response["conversation"]
 
+                    if asset.get("assetProjectModels"):
+                        models = _format_models_object(
+                            asset["assetProjectModels"], obfuscated_models
+                        )
+                    else:
+                        models = {v: k for k, v in obfuscated_models.items()}
+
                     result[f"{step}"] = {
                         "external_id": asset["externalId"],
                         "metadata": asset["jsonMetadata"],
-                        "models": _format_models_object(
-                            asset["assetProjectModels"], obfuscated_models
-                        ),
+                        "models": models,
                         "labels": [label_data],
                         "raw_data": raw_data,
                         "status": asset["status"],
                     }
                 export_res.append(result)
+
         return export_res
 
     def _get_round_winner(self, completions, annotations, json_interface):
@@ -221,23 +238,22 @@ def _format_transcription_annotation(annotation):
 
 def _format_comparison_annotation(annotation, completions, job, obfuscated_models):
     """Return A_X or B_X depending of the evaluation completion and its score."""
-    model_id = None
+    model_key = None
     for completion in completions:
         if annotation["annotationValue"]["choice"]["firstId"] == completion["id"]:
-            model_id = completion["modelId"]
+            model_key = completion.get("modelId") or completion.get("modelName")
             break
 
-    if model_id is None:
-        # FIXME : model_id can be null on LLM_STATIC
-        return None
+    if model_key is None:
+        raise ValueError(f"Failed to found model of annotation {annotation['id']}")
 
     iteration = 0
     for _comparison_code, comparison_note in job["content"]["options"].items():
         iteration += 1
         if comparison_note["name"] == annotation["annotationValue"]["choice"]["code"]:
             break
 
-    return f"{obfuscated_models[model_id]}_{iteration}"
+    return f"{obfuscated_models[model_key]}_{iteration}"
 
 
 def _format_json_response(