From 573e1fe36ea8bcb516316756f9d58a16cf763d91 Mon Sep 17 00:00:00 2001
From: huanghuoguoguo <1051233107@qq.com>
Date: Sun, 7 Jun 2026 22:03:25 +0800
Subject: [PATCH] style: simplify wrapped expressions

---
 src/langbot/pkg/api/http/service/monitoring.py | 12 +++---------
 src/langbot/pkg/pipeline/preproc/preproc.py    |  6 +-----
 src/langbot/pkg/provider/runners/localagent.py |  8 ++------
 3 files changed, 6 insertions(+), 20 deletions(-)

diff --git a/src/langbot/pkg/api/http/service/monitoring.py b/src/langbot/pkg/api/http/service/monitoring.py
index 78761c6a..3e8e0cde 100644
--- a/src/langbot/pkg/api/http/service/monitoring.py
+++ b/src/langbot/pkg/api/http/service/monitoring.py
@@ -517,12 +517,8 @@ class MonitoringService:
                 sqlalchemy.func.coalesce(sqlalchemy.func.sum(LLMCall.total_tokens), 0),
                 sqlalchemy.func.coalesce(sqlalchemy.func.sum(LLMCall.duration), 0),
                 sqlalchemy.func.coalesce(sqlalchemy.func.sum(LLMCall.cost), 0.0),
-                sqlalchemy.func.sum(
-                    sqlalchemy.case((LLMCall.status == 'success', 1), else_=0)
-                ),
-                sqlalchemy.func.sum(
-                    sqlalchemy.case((LLMCall.status == 'error', 1), else_=0)
-                ),
+                sqlalchemy.func.sum(sqlalchemy.case((LLMCall.status == 'success', 1), else_=0)),
+                sqlalchemy.func.sum(sqlalchemy.case((LLMCall.status == 'error', 1), else_=0)),
                 # Count of successful calls that nonetheless recorded zero tokens —
                 # a data-quality signal that usage reporting may be broken upstream.
                 sqlalchemy.func.sum(
@@ -578,9 +574,7 @@ class MonitoringService:
                 sqlalchemy.func.coalesce(sqlalchemy.func.sum(LLMCall.total_tokens), 0),
                 sqlalchemy.func.coalesce(sqlalchemy.func.sum(LLMCall.duration), 0),
                 sqlalchemy.func.coalesce(sqlalchemy.func.sum(LLMCall.cost), 0.0),
-                sqlalchemy.func.sum(
-                    sqlalchemy.case((LLMCall.status == 'error', 1), else_=0)
-                ),
+                sqlalchemy.func.sum(sqlalchemy.case((LLMCall.status == 'error', 1), else_=0)),
             ).group_by(LLMCall.model_name)
         )
         by_model_result = await self.ap.persistence_mgr.execute_async(by_model_query)
diff --git a/src/langbot/pkg/pipeline/preproc/preproc.py b/src/langbot/pkg/pipeline/preproc/preproc.py
index e180b0d2..84e9070c 100644
--- a/src/langbot/pkg/pipeline/preproc/preproc.py
+++ b/src/langbot/pkg/pipeline/preproc/preproc.py
@@ -159,11 +159,7 @@ class PreProcessor(stage.PipelineStage):
 
         # Check if this model supports vision, if not, remove all images
         # TODO this checking should be performed in runner, and in this stage, the image should be reserved
-        if (
-            selected_runner == 'local-agent'
-            and llm_model
-            and 'vision' not in (llm_model.model_entity.abilities or [])
-        ):
+        if selected_runner == 'local-agent' and llm_model and 'vision' not in (llm_model.model_entity.abilities or []):
             for msg in query.messages:
                 if isinstance(msg.content, list):
                     for me in msg.content:
diff --git a/src/langbot/pkg/provider/runners/localagent.py b/src/langbot/pkg/provider/runners/localagent.py
index 11c56699..b95b77f0 100644
--- a/src/langbot/pkg/provider/runners/localagent.py
+++ b/src/langbot/pkg/provider/runners/localagent.py
@@ -469,9 +469,7 @@ class LocalAgentRunner(runner.RequestRunner):
                     query,
                     use_llm_model,
                     req_messages,
-                    query.use_funcs
-                    if _model_has_ability(use_llm_model, 'func_call')
-                    else [],
+                    query.use_funcs if _model_has_ability(use_llm_model, 'func_call') else [],
                     extra_args=use_llm_model.model_entity.extra_args,
                     remove_think=remove_think,
                 )
@@ -487,9 +485,7 @@ class LocalAgentRunner(runner.RequestRunner):
                     query,
                     use_llm_model,
                     req_messages,
-                    query.use_funcs
-                    if _model_has_ability(use_llm_model, 'func_call')
-                    else [],
+                    query.use_funcs if _model_has_ability(use_llm_model, 'func_call') else [],
                     extra_args=use_llm_model.model_entity.extra_args,
                     remove_think=remove_think,
                 )