Update testbed for tools_enabled

Author: gotsysdba

src/client/content/config/tabs/settings.py

@@ -363,17 +363,21 @@ def spring_ai_conf_check(ll_model: dict, embed_model: dict) -> str:
 def spring_ai_obaas(src_dir, file_name, provider, ll_config, embed_config):
     """Get the system prompt for SpringAI export"""
 
+    ## FUTURE FEATURE:
     # Determine which system prompt would be active based on tools_enabled
-    tools_enabled = state.client_settings.get("tools_enabled", [])
+    # tools_enabled = state.client_settings.get("tools_enabled", [])
 
     # Select prompt name based on tools configuration
-    if not tools_enabled:
-        prompt_name = "optimizer_basic-default"
-        if state.client_settings["vector_search"]["enabled"]:
-            prompt_name = "optimizer_vs-no-tools-default"
-    else:
-        # Tools are enabled, use tools-default prompt
-        prompt_name = "optimizer_tools-default"
+    # if not tools_enabled:
+    #     prompt_name = "optimizer_basic-default"
+    #     if state.client_settings["vector_search"]["enabled"]:
+    #         prompt_name = "optimizer_vs-no-tools-default"
+    # else:
+    #     # Tools are enabled, use tools-default prompt
+    #     prompt_name = "optimizer_tools-default"
+    ## Legacy Feature:
+    if "Vector Search" in state.client_settings["tools_enabled"]:
+        prompt_name = "optimizer_vs-no-tools-default"
 
     # Find the prompt in configs
     sys_prompt_obj = next((item for item in state.prompt_configs if item["name"] == prompt_name), None)

src/client/content/testbed.py

@@ -85,9 +85,12 @@ def create_gauge(value):
     st.dataframe(ll_settings_reversed, hide_index=True)
     if report["settings"]["testbed"]["judge_model"]:
         st.markdown(f"**Judge Model**: {report['settings']['testbed']['judge_model']}")
-    # if discovery; then list out the tables that were discovered (MCP implementation)
-    # if report["settings"]["vector_search"].get("discovery"):
-    if report["settings"]["vector_search"]["enabled"]:
+    # Backward compatibility
+    try:
+        vs_enabled = report["settings"]["vector_search"]["enabled"]
+    except KeyError:
+        vs_enabled = "Vector Search" in report["settings"]["tools_enabled"]
+    if vs_enabled:
         st.subheader("Vector Search Settings")
         st.markdown(f"""**Database**: {report["settings"]["database"]["alias"]};
             **Vector Store**: {report["settings"]["vector_search"]["vector_store"]}
@@ -100,6 +103,8 @@ def create_gauge(value):
         if report["settings"]["vector_search"]["search_type"] == "Similarity":
             embed_settings.drop(["score_threshold", "fetch_k", "lambda_mult"], axis=1, inplace=True)
         st.dataframe(embed_settings, hide_index=True)
+        # if discovery; then list out the tables that were discovered (MCP implementation)
+        # if report["settings"]["vector_search"].get("discovery"):
     else:
         st.markdown("**Evaluated without Vector Search**")
 
@@ -516,7 +521,7 @@ def render_evaluation_ui(available_ll_models: list) -> None:
         key="evaluate_button",
         help="Evaluation will automatically save the TestSet to the Database",
         on_click=qa_update_db,
-        disabled=not state.enable_client,
+        disabled=not state.get("enable_client", True),
     ):
         with st.spinner("Starting Q&A evaluation... please be patient.", show_time=True):
             st_common.clear_state_key("testbed_evaluations")