v1.20.0

controller/attribute/util.py

@@ -250,7 +250,6 @@ def prepare_llm_response_code(
     llm_playground_config: Union[Dict[str, Any], None] = None,
     llm_ac_cache_access_link: Union[str, None] = None,
     llm_ac_cache_file_upload_link: Union[str, None] = None,
-    num_workers: int = 100,
     max_api_call_retries: int = 5,
     retry_sleep_seconds: int = 5,
 ) -> str:
@@ -294,6 +293,14 @@ async def ac(record):
     )
     validate_llm_config(llm_config=llm_config)
 
+    num_workers = 50
+    if (
+        llm_config is not None
+        and enums.LLMProvider.from_string(llm_config.get("llmIdentifier", "Open ai"))
+        == enums.LLMProvider.AZURE_FOUNDRY
+    ):
+        num_workers = 25
+
     try:
         llm_config_mapping = {
             "@@API_KEY@@": llm_config["apiKey"],

controller/misc/manager.py

@@ -93,7 +93,7 @@ def finalize_customer_buttons(
     for e in buttons:
         e[key_name] = name_lookup[str(e[key])]
         e[key_name] = (
-            (e[key_name]["first"] + " " + e[key_name]["last"])
+            (e[key_name]["first"] or "" + " " + e[key_name]["last"] or "")
             if e[key_name]
             else "Unknown"
         )

controller/project/manager.py

@@ -155,6 +155,11 @@ def get_all_projects_by_user(organization_id) -> List[Project]:
         else:
             p["num_data_scale_uploaded"] = record.get_count_scale_uploaded(p["id"])
 
+        p["is_integration_project"] = any(
+            p["name"].startswith(f"[{integration_type.value}]")
+            for integration_type in enums.CognitionIntegrationType
+        )
+
         del p["created_by"]
 
     return project_dicts

fast_api/routes/embedding.py

@@ -16,7 +16,7 @@
 from controller.auth import manager as auth_manager
 from controller.embedding.connector import collection_on_qdrant
 from submodules.model.enums import TaskType
-from submodules.model.business_objects import embedding
+from submodules.model.business_objects import embedding as embedding_bo
 from submodules.model.cognition_objects import environment_variable as env_var_db_bo
 from submodules.model.util import sql_alchemy_to_dict
 from util import notification, spacy_util
@@ -51,13 +51,16 @@ def language_models(request: Request) -> List:
     dependencies=[Depends(auth_manager.check_project_access_dep)],
 )
 def get_embeddings(project_id: str) -> List:
-    embeddings_extended = embedding.get_all_embeddings_by_project_id_extended(
+    embeddings_extended = embedding_bo.get_all_embeddings_by_project_id_extended(
         project_id
     )
     data = [
         {
             **sql_alchemy_to_dict(embedding),
             "on_qdrant": collection_on_qdrant(project_id, embedding["id"]),
+            "count": sql_alchemy_to_dict(
+                embedding_bo.get_tensor_count(embedding["id"])
+            ),
         }
         for embedding in embeddings_extended
     ]