feat(chat): 优化工具调用输出处理，确保兼容性和稳定性

- 在 chat_agent 函数中，确保工具调用输出为字符串类型，避免 SQLite 不支持列表类型的问题
- 更新 load_chat_model 函数，新增 stream_usage 参数以支持流式使用
- 移除不必要的代码，简化 utils.py 文件，提升可读性
- 优化 AgentStatsComponent.vue，移除冗余样式，提升性能和用户体验

server/routers/chat_router.py

@@ -211,10 +211,16 @@ async def chat_agent(
                     name = msg_dict.get("name", "")
 
                     if tool_call_id:
+                        # 确保tool_output是字符串类型，避免SQLite不支持列表类型
+                        if isinstance(content, list):
+                            tool_output = json.dumps(content) if content else ""
+                        else:
+                            tool_output = str(content)
+
                         # 通过 LangGraph tool_call_id 精确匹配并更新
                         updated_tc = conv_mgr.update_tool_call_output(
                             langgraph_tool_call_id=tool_call_id,
-                            tool_output=content,
+                            tool_output=tool_output,
                             status="success",
                         )
                         if updated_tc:

src/agents/common/models.py

@@ -26,6 +26,7 @@ def load_chat_model(fully_specified_name: str, **kwargs) -> BaseChatModel:
             model=model_name,
             api_key=SecretStr(api_key),
             base_url=base_url,
+            stream_usage=True,
         )
 
     model_info = config.model_names.get(provider, {})
@@ -40,6 +41,7 @@ def load_chat_model(fully_specified_name: str, **kwargs) -> BaseChatModel:
             api_key=SecretStr(api_key),
             base_url=base_url,
             api_base=base_url,
+            stream_usage=True,
         )
 
     elif provider == "together":
@@ -49,6 +51,7 @@ def load_chat_model(fully_specified_name: str, **kwargs) -> BaseChatModel:
             model=model,
             api_key=SecretStr(api_key),
             base_url=base_url,
+            stream_usage=True,
         )
 
     else:
@@ -59,6 +62,7 @@ def load_chat_model(fully_specified_name: str, **kwargs) -> BaseChatModel:
                 model=model,
                 api_key=SecretStr(api_key),
                 base_url=base_url,
+                stream_usage=True,
             )
         except Exception as e:
             raise ValueError(f"Model provider {provider} load failed, {e} \n {traceback.format_exc()}")

src/agents/common/utils.py

@@ -1,71 +1,8 @@
-import os
-import traceback
 from datetime import UTC, datetime
 
-from langchain_core.language_models import BaseChatModel
 from langchain_core.messages import AIMessageChunk, ToolMessage
 from langchain_core.runnables import RunnableConfig
-from pydantic import SecretStr
-
-from src import config
 from src.agents.common.base import BaseAgent
-from src.models import get_custom_model
-from src.utils import get_docker_safe_url
-
-
-def load_chat_model(fully_specified_name: str, **kwargs) -> BaseChatModel:
-    """
-    Load a chat model from a fully specified name.
-    """
-    provider, model = fully_specified_name.split("/", maxsplit=1)
-
-    if provider == "custom":
-        from langchain_openai import ChatOpenAI
-
-        model_info = get_custom_model(model)
-        api_key = model_info.get("api_key") or "custom_model"
-        base_url = get_docker_safe_url(model_info["api_base"])
-        model_name = model_info.get("name") or "custom_model"
-        return ChatOpenAI(
-            model=model_name,
-            api_key=SecretStr(api_key),
-            base_url=base_url,
-        )
-
-    model_info = config.model_names.get(provider, {})
-    api_key = os.getenv(model_info["env"][0], model_info["env"][0])
-    base_url = get_docker_safe_url(model_info["base_url"])
-
-    if provider in ["deepseek", "dashscope"]:
-        from langchain_deepseek import ChatDeepSeek
-
-        return ChatDeepSeek(
-            model=model,
-            api_key=SecretStr(api_key),
-            base_url=base_url,
-            api_base=base_url,
-        )
-
-    elif provider == "together":
-        from langchain_together import ChatTogether
-
-        return ChatTogether(
-            model=model,
-            api_key=SecretStr(api_key),
-            base_url=base_url,
-        )
-
-    else:
-        try:  # 其他模型，默认使用OpenAIBase, like openai, zhipuai
-            from langchain_openai import ChatOpenAI
-
-            return ChatOpenAI(
-                model=model,
-                api_key=SecretStr(api_key),
-                base_url=base_url,
-            )
-        except Exception as e:
-            raise ValueError(f"Model provider {provider} load failed, {e} \n {traceback.format_exc()}")
 
 
 async def agent_cli(agent: BaseAgent, config: RunnableConfig | None = None):

web/src/components/dashboard/AgentStatsComponent.vue

@@ -63,8 +63,6 @@
         :data-source="topPerformers"
         size="small"
         :pagination="false"
-        :row-class-name="getRowClassName"
-        :scroll="{ y: 240 }"
       >
         <template #bodyCell="{ column, record, index }">
           <template v-if="column.key === 'rank'">
@@ -190,12 +188,6 @@ const getScoreColor = (score) => {
   return '#a3d8e8'
 }
 
-const getRowClassName = (record, index) => {
-  if (index === 0) return 'top-rank first'
-  if (index === 1) return 'top-rank second'
-  if (index === 2) return 'top-rank third'
-  return ''
-}
 
 // 初始化对话数和工具调用数合并图表
 const initConversationToolChart = () => {
@@ -396,18 +388,6 @@ defineExpose({
   }
 }
 
-// 排名样式优化
-:deep(.ant-table-tbody > tr.top-rank.first) {
-  background: linear-gradient(90deg, rgba(255, 215, 0, 0.1) 0%, transparent 100%);
-}
-
-:deep(.ant-table-tbody > tr.top-rank.second) {
-  background: linear-gradient(90deg, rgba(192, 192, 192, 0.1) 0%, transparent 100%);
-}
-
-:deep(.ant-table-tbody > tr.top-rank.third) {
-  background: linear-gradient(90deg, rgba(205, 127, 50, 0.1) 0%, transparent 100%);
-}
 
 :deep(.ant-progress-bg) {
   transition: all 0.3s ease;