diff --git a/agent_loop.py b/agent_loop.py
index 7f53380..5d02ff0 100644
--- a/agent_loop.py
+++ b/agent_loop.py
@@ -48,8 +48,8 @@ def agent_runner_loop(client, system_prompt, user_input, handler, tools_schema,
         response = client.chat(messages=messages, tools=tools_schema)
 
         if response.thinking: yield '<thinking>' + response.thinking + '</thinking>\n\n'
-        if '</summary>```'  in response.content: response.content = response.content.replace('</summary>```', '</summary>\n```')
         showcontent = response.content
+        if '</summary>' in showcontent: showcontent = showcontent.replace('</summary>', '</summary>\n\n')
         if '</file_content>' in showcontent:
             showcontent = re.sub(r'<file_content>\s*(.*?)\s*</file_content>', r'\n````\n<file_content>\n\1\n</file_content>\n````', showcontent, flags=re.DOTALL)
         yield showcontent + '\n\n'
diff --git a/agentapp.py b/agentapp.py
index 27750f4..c2c100a 100644
--- a/agentapp.py
+++ b/agentapp.py
@@ -18,8 +18,11 @@ from agent_loop import agent_runner_loop, StepOutcome, BaseHandler
 @st.cache_resource
 def init():
     if not os.path.exists('temp'): os.makedirs('temp')
-    mainllm = SiderLLMSession(multiturns=6)
-    llmclient = ToolClient(mainllm.ask, auto_save_tokens=True)
+    llm_sessions = [SiderLLMSession(default_model="gemini-3.0-flash"), 
+                    SiderLLMSession(default_model="gpt-5-mini"), 
+                    SiderLLMSession(default_model="claude-4.5-haiku"), 
+                    LLMSession()]
+    llmclient = ToolClient([x.ask for x in llm_sessions], auto_save_tokens=True)
     return llmclient
 
 llmclient = init()
@@ -47,6 +50,7 @@ def agent_backend_stream(raw_query):
     sys_prompt = get_system_prompt()
     handler = GenericAgentHandler(None, history, './temp')
     llmclient.last_tools = ''   
+    llmclient.raw_api = llmclient.raw_apis[st.session_state.get("llm_no", 0)]
     ret = yield from agent_runner_loop(llmclient,
         sys_prompt, raw_query, handler,
         TOOLS_SCHEMA, max_turns=25)
@@ -62,6 +66,13 @@ for msg in st.session_state.messages:
     with st.chat_message(msg["role"]):
         st.markdown(msg["content"])
 
+with st.sidebar:
+    current_idx = st.session_state.get("llm_no", 0)
+    st.caption(f"LLM Core: {current_idx}")
+    if st.button("切换备用链路"):
+        st.session_state.llm_no = (st.session_state.get("llm_no", 0) + 1) % len(llmclient.raw_apis)
+        st.rerun()
+
 if prompt := st.chat_input("请输入指令"):
     st.session_state.messages.append({"role": "user", "content": prompt})
     with st.chat_message("user"):
diff --git a/ga.py b/ga.py
index a75fa7d..605d605 100644
--- a/ga.py
+++ b/ga.py
@@ -66,12 +66,12 @@ def code_run(code: str, code_type: str = "python", timeout: int = 60, cwd: str =
         status = "success" if exit_code == 0 else "error"
         status_icon = "✅" if exit_code == 0 else "❌"
         if exit_code is None: status_icon = "⏳" 
-        output_snippet = (stdout_str[:100] + '...' + stdout_str[-100:]) if len(stdout_str) > 300 else stdout_str
+        output_snippet = smart_format(stdout_str, max_str_len=600, omit_str='\n[omitted long output]\n')
         yield f"[Status] {status_icon} Exit Code: {exit_code}\n[Stdout]\n{output_snippet}\n"
-        if process.stdout: process.stdout.close()
+        if process.stdout: threading.Thread(target=process.stdout.close, daemon=True).start()
         return {
             "status": status,
-            "stdout": stdout_str[-2000:],
+            "stdout": smart_format(stdout_str, max_str_len=4000, omit_str='\n[omitted long output]\n'),
             "exit_code": exit_code
         }
     except Exception as e:
@@ -198,7 +198,7 @@ def file_read(path, start=1, keyword=None, count=100, show_linenos=True):
     try:
         with open(path, 'r', encoding='utf-8', errors='replace') as f:
             stream = (
-                (i, (l[:L_MAX].rstrip() + TAG if len(l) > L_MAX else l.rstrip()))
+                (i, (l[:L_MAX].rstrip() + TAG if len(l) > L_MAX else l.rstrip('\r\n')))
                 for i, l in enumerate(f, 1)
             )
             stream = itertools.dropwhile(lambda x: x[0] < start, stream)
@@ -211,15 +211,15 @@ def file_read(path, start=1, keyword=None, count=100, show_linenos=True):
                     before.append((i, l))
                 else: return f"Keyword '{keyword}' not found after line {start}."
             else: res = itertools.islice(stream, count)
-            return "\n".join(f"{i}| {l}" if show_linenos else l for i, l in res)
+            return "\n".join(f"{i}|{l}" if show_linenos else l for i, l in res)
     except Exception as e:
         return f"Error: {str(e)}"
 
-def smart_format(data, max_depth=2, max_str_len=100):
+def smart_format(data, max_depth=2, max_str_len=100, omit_str=' ... '):
     def truncate(obj, depth):
         if isinstance(obj, str):
-            if len(obj) > max_str_len: return f"{obj[:max_str_len//2]} ... {obj[-max_str_len//2:]}"
-            return obj
+            if len(obj) < max_str_len+len(omit_str)*2: return obj
+            return f"{obj[:max_str_len//2]}{omit_str}{obj[-max_str_len//2:]}"
         if depth >= max_depth: return truncate(str(obj), depth + 1)
         if isinstance(obj, dict): return {k: truncate(v, depth + 1) for k, v in obj.items()}
         if isinstance(obj, list): return [truncate(i, depth + 1) for i in obj]
@@ -259,15 +259,17 @@ class GenericAgentHandler(BaseHandler):
         # 从 response.content 中提取代码块, 匹配 ```python ... ``` 或 ```powershell ... ```
         pattern = rf"```{code_type}\n(.*?)\n```"
         matches = re.findall(pattern, response.content, re.DOTALL)
+        warning = ""
         if not matches:
-            return StepOutcome(None, next_prompt=f"【系统错误】：你调用了 code_run，但未在回复中提供 ```{code_type} 代码块。请重新输出代码并附带工具调用。")       
-        # 提取最后一个代码块（通常是模型修正后的最终逻辑）
-        code = matches[-1].strip()
+            code = args.get("code")
+            if not code: return StepOutcome(None, next_prompt=f"【系统错误】：你调用了 code_run，但未在回复中提供 ```{code_type} 代码块。请重新输出代码并附带工具调用。")
+            warning = "\n下次要记得在回复中提供代码块，而不是放在参数中"
+        else: code = matches[-1].strip()   # 提取最后一个代码块（通常是模型修正后的最终逻辑）
         timeout = args.get("timeout", 60)
         raw_path = os.path.join(self.cwd, args.get("cwd", './'))
         cwd = os.path.normpath(os.path.abspath(raw_path))
         result = yield from code_run(code, code_type, timeout, cwd)
-        next_prompt = self._get_anchor_prompt()
+        next_prompt = self._get_anchor_prompt() + warning
         return StepOutcome(result, next_prompt=next_prompt)
     
     def do_ask_user(self, args, response):
diff --git a/sidercall.py b/sidercall.py
index 1418f49..6c78a1d 100644
--- a/sidercall.py
+++ b/sidercall.py
@@ -8,9 +8,11 @@ except ImportError:
     capikey = ""
 
 class SiderLLMSession:
-    def __init__(self, multiturns=6):
+    def __init__(self, multiturns=6, default_model="gemini-3.0-flash"):
         self._core = Session(cookie=sider_cookie, proxies={'https':'127.0.0.1:2082'})   
-    def ask(self, prompt, model="gemini-3.0-flash"):
+        self.default_model = default_model
+    def ask(self, prompt, model=None):
+        if model is None: model = self.default_model
         if len(prompt) > 29000: 
             print(f"[Warn] Prompt too long ({len(prompt)} chars), truncating.")
             prompt = prompt[-29000:]
@@ -44,7 +46,7 @@ class LLMSession:
             elif not omit_images and msg['image']:
                 messages.append({"role": msg['role'], "content": [
                     {"type": "image_url", "image_url": {"url": f"data:image/png;base64,{msg['image']}"}},
-                    {"type": "text", "text": msg['prompt']}   ]})
+                    {"type": "text", "text": msg['prompt']} ]})
             else:
                 messages.append({"role": msg['role'], "content": msg['prompt']})
         return messages
@@ -56,8 +58,10 @@ class LLMSession:
         p = "Summarize prev summary and prev conversations into compact memory (facts/decisions/constraints/open questions). Do NOT restate long schemas. The new summary should less than 1000 tokens.\n"
         messages = self.make_messages(old, omit_images=True)
         messages += [{"role":"user", "content":p}]
-        self.summary = self.raw_ask(messages, model, temperature=0.1)
-        self.raw_msgs.insert(0, {"role":"system", "prompt":"Prev summary:\n"+self.summary, "image":None})
+        summary = self.raw_ask(messages, model, temperature=0.1)
+        if not summary.startswith("Error:"): 
+            self.raw_msgs.insert(0, {"role":"system", "prompt":"Prev summary:\n"+summary, "image":None})
+        else: self.raw_msgs = old + self.raw_msgs   # 不做了，下次再做
 
     def ask(self, prompt, model="openai/gpt-5.1", image_base64=None):
         self.raw_msgs.append({"role": "user", "prompt": prompt, "image": image_base64})
@@ -92,7 +96,9 @@ class MockResponse:
 
 class ToolClient:
     def __init__(self, raw_api_func, auto_save_tokens=False):
-        self.raw_api = raw_api_func
+        if isinstance(raw_api_func, list): self.raw_apis = raw_api_func
+        else: self.raw_apis = [raw_api_func]
+        self.raw_api = self.raw_apis[0]
         self.auto_save_tokens = auto_save_tokens
         self.last_tools = ''
         self.total_cd_tokens = 0