Feat/line item executor plugin

frontend/src/components/custom-tools/add-llm-profile/AddLlmProfile.jsx

@@ -64,10 +64,6 @@ function AddLlmProfile({
 
   useEffect(() => {
     setAdaptorProfilesDropdown();
-
-    return () => {
-      setEditLlmProfileId(null);
-    };
   }, []);
 
   // Load retrieval strategies when tool_id is available (only once)
@@ -163,7 +159,7 @@ function AddLlmProfile({
 
   useEffect(() => {
     if (resetForm) {
-      form.resetFields();
+      form.setFieldsValue(formDetails);
       setResetForm(false);
     }
   }, [formDetails]);

frontend/src/components/custom-tools/manage-llm-profiles/ManageLlmProfiles.jsx

@@ -166,6 +166,7 @@ function ManageLlmProfiles() {
   }, [llmProfiles, defaultLlmProfile]);
 
   const handleAddNewLlmProfileBtnClick = () => {
+    setEditLlmProfileId(null);
     setIsAddLlm(true);
 
     try {

frontend/src/components/settings/settings/Settings.css

@@ -34,7 +34,6 @@
 }
 
 .settings-menu-item:first-child {
-  font-weight: 600;
   margin-bottom: 4px;
 }
 

workers/executor/executors/legacy_executor.py

@@ -1494,7 +1494,24 @@
             return
 
         if output.get(PSKeys.TYPE) == PSKeys.LINE_ITEM:
-            raise LegacyExecutorError(message="LINE_ITEM extraction is not supported.")
+            self._run_line_item_extraction(
+                output=output,
+                context=context,
+                structured_output=structured_output,
+                metadata=metadata,
+                metrics=metrics,
+                run_id=run_id,
+                execution_id=execution_id,
+                execution_source=execution_source,
+                platform_api_key=platform_api_key,
+                tool_id=tool_id,
+                doc_name=doc_name,
+                prompt_name=prompt_name,
+                file_path=file_path,
+                tool_settings=tool_settings,
+                shim=shim,
+            )
+            return
 
         usage_kwargs = {"run_id": run_id, "execution_id": execution_id}
         try:
@@ -1700,6 +1717,83 @@
             )
         shim.stream_log(f"Completed prompt: {prompt_name}")
 
+    def _run_line_item_extraction(
+        self,
+        output: dict[str, Any],
+        context: ExecutionContext,
+        structured_output: dict[str, Any],
+        metadata: dict[str, Any],
+        metrics: dict[str, Any],
+        run_id: str,
+        execution_id: str,
+        execution_source: str,
+        platform_api_key: str,
+        tool_id: str,
+        doc_name: str,
+        prompt_name: str,
+        file_path: str,
+        tool_settings: dict[str, Any],
+        shim: Any,
+    ) -> None:
+        """Delegate LINE_ITEM prompt to the line_item executor plugin."""
+        from executor.executors.constants import PromptServiceConstants as PSKeys
+
+        try:
+            line_item_executor = ExecutorRegistry.get("line_item")
+        except KeyError:
+            raise LegacyExecutorError(
+                message=(
+                    "LINE_ITEM extraction requires the line_item executor "
+                    "plugin. Install the line_item_extractor plugin."
+                )
+            )
+        line_item_ctx = ExecutionContext(
+            executor_name="line_item",
+            operation="line_item_extract",
+            run_id=run_id,
+            execution_source=execution_source,
+            organization_id=context.organization_id,
+            request_id=context.request_id,
+            executor_params={
+                "llm_adapter_instance_id": output.get(PSKeys.LLM, ""),
+                "tool_settings": tool_settings,
+                "output": output,
+                "prompt": output.get(PSKeys.PROMPTX, ""),
+                "file_path": file_path,
+                "PLATFORM_SERVICE_API_KEY": platform_api_key,
+                "execution_id": execution_id,
+                "tool_id": tool_id,
+                "file_name": doc_name,
+                "prompt_name": prompt_name,
+            },
+        )
+        line_item_ctx._log_component = self._log_component
+        line_item_ctx.log_events_id = self._log_events_id
+
+        shim.stream_log(f"Running line-item extraction for: {prompt_name}")
+        line_item_result = line_item_executor.execute(line_item_ctx)
+
+        if line_item_result.success:
+            data = line_item_result.data or {}
+            structured_output[prompt_name] = data.get("output", "")
+            line_item_metrics = data.get("metadata", {}).get("metrics", {})
+            metrics.setdefault(prompt_name, {}).update(
+                {"line_item_extraction": line_item_metrics}
+            )
+            context_list = data.get("context")
+            if context_list:
+                metadata[PSKeys.CONTEXT][prompt_name] = context_list
+            shim.stream_log(f"Line-item extraction completed for: {prompt_name}")
+            logger.info("LINE_ITEM extraction completed: prompt=%s", prompt_name)
+        else:
+            structured_output[prompt_name] = ""
+            logger.error(
+                "LINE_ITEM extraction failed for prompt=%s: %s",
+                prompt_name,
+                line_item_result.error,
+            )
+        shim.stream_log(f"Completed prompt: {prompt_name}")
+
     @staticmethod
     def _apply_type_conversion(
         output: dict[str, Any],
@@ -1732,16 +1826,19 @@
             )
 
         elif output_type == PSKeys.EMAIL:
-            email_prompt = (
-                f"Extract the email from the following text:\n{answer}"
-                f"\n\nOutput just the email. "
-                f"The email should be directly assignable to a string "
-                f"variable. No explanation is required. If you cannot "
-                f'extract the email, output "NA".'
-            )
-            structured_output[prompt_name] = LegacyExecutor._convert_scalar_answer(
-                answer, llm, answer_prompt_svc, email_prompt
-            )
+            if answer.lower() == "na":
+                structured_output[prompt_name] = answer
+            else:
+                email_prompt = (
+                    f"Extract the email from the following text:\n{answer}"
+                    f"\n\nOutput just the email. "
+                    f"The email should be directly assignable to a string "
+                    f"variable. No explanation is required. If you cannot "
+                    f'extract the email, output "NA".'
+                )
+                structured_output[prompt_name] = answer_prompt_svc.run_completion(
+                    llm=llm, prompt=email_prompt
+                )
 
         elif output_type == PSKeys.DATE:
             date_prompt = (

workers/tests/test_answer_prompt.py

@@ -562,8 +562,8 @@ def test_invalid_strategy_skips_retrieval(
         )
         result = executor._handle_answer_prompt(ctx)
 
-        # Answer stays "NA" which gets sanitized to None
-        assert result.data[PSKeys.OUTPUT]["field_a"] is None
+        # Answer stays "NA" (top-level NA is preserved, not sanitized)
+        assert result.data[PSKeys.OUTPUT]["field_a"] == "NA"
 
 
 class TestHandleAnswerPromptMultiPrompt:
@@ -687,21 +687,21 @@ def test_vectordb_closed(self, mock_shim_cls, mock_deps):
 class TestNullSanitization:
     """Tests for _sanitize_null_values."""
 
-    def test_na_string_becomes_none(self):
-        """Top-level 'NA' string → None."""
+    def test_na_string_preserved(self):
+        """Top-level 'NA' string is preserved (not sanitized to None)."""
         from executor.executors.legacy_executor import LegacyExecutor
 
         output = {"field": "NA"}
         result = LegacyExecutor._sanitize_null_values(output)
-        assert result["field"] is None
+        assert result["field"] == "NA"
 
-    def test_na_case_insensitive(self):
-        """'na' (lowercase) → None."""
+    def test_na_case_insensitive_preserved(self):
+        """Top-level 'na' (lowercase) is preserved (not sanitized to None)."""
         from executor.executors.legacy_executor import LegacyExecutor
 
         output = {"field": "na"}
         result = LegacyExecutor._sanitize_null_values(output)
-        assert result["field"] is None
+        assert result["field"] == "na"
 
     def test_nested_list_na(self):
         """NA in nested list items → None."""