chore: sync core logic updates

agent_loop.py

@@ -26,7 +26,7 @@ class BaseHandler:
             return ret
         else:
             yield f"❌ 未知工具: {tool_name}\n"
-            return StepOutcome(None, "未知工具", "ERROR")
+            return StepOutcome(None, next_prompt=f"未知工具 {tool_name}", should_exit=False)
 
 def json_default(o):
     if isinstance(o, set): return list(o)

agentmain.py

@@ -47,14 +47,18 @@ class GeneraticAgent:
         self.llm_no = 0
         self.stop_sig = False
         self.current_source = 'none'
+        self.handler = None
 
     def next_llm(self):
         self.llm_no = (self.llm_no + 1) % len(self.llmclient.raw_apis)
         self.llmclient.last_tools = ''
 
     def abort(self):
+        print('About to abort current task...')
         if not self.is_running: return
         self.stop_sig = True
+        if self.handler is not None: 
+            self.handler.code_stop_signal.append(1)
 
     def put_task(self, query, source="user"):
         self.display_queue.queue.clear()
@@ -73,7 +77,7 @@ class GeneraticAgent:
             
             sys_prompt = get_system_prompt()
             handler = GenericAgentHandler(None, self.history, './temp')
-
+            self.handler = handler
             self.llmclient.raw_api = self.llmclient.raw_apis[self.llm_no]
             gen = agent_runner_loop(self.llmclient, sys_prompt, 
                         raw_query, handler, TOOLS_SCHEMA, max_turns=25)
@@ -81,7 +85,8 @@ class GeneraticAgent:
             try:
                 full_response = ""; last_pos = 0
                 for chunk in gen:
-                    if self.stop_sig: break
+                    if self.stop_sig: 
+                        self.abort(); break
                     full_response += chunk
                     if len(full_response) - last_pos > 50:
                         self.display_queue.put({'next': f'{full_response}', 'source': source})

ga.py

@@ -7,7 +7,7 @@ sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
 
 from agent_loop import BaseHandler, StepOutcome, try_call_generator
 
-def code_run(code, code_type="python", timeout=60, cwd=None, code_cwd=None):
+def code_run(code, code_type="python", timeout=60, cwd=None, code_cwd=None, stop_signal=[]):
     """代码执行器
     python: 运行复杂的 .py 脚本（文件模式）
     powershell/bash: 运行单行指令（命令模式）
@@ -52,11 +52,14 @@ def code_run(code, code_type="python", timeout=60, cwd=None, code_cwd=None):
         t.start()
 
         while t.is_alive():
-            if time.time() - start_t > timeout:
+            istimeout = time.time() - start_t > timeout
+            if istimeout or len(stop_signal) > 0:
                 process.kill()
-                full_stdout.append("\n[Timeout Error] 超时强制终止")
+                print("[Debug] Process killed due to timeout or stop signal.")
+                if istimeout: full_stdout.append("\n[Timeout Error] 超时强制终止")
+                else: full_stdout.append("\n[Stopped] 用户强制终止")
                 break
-            time.sleep(0.2)
+            time.sleep(1)
 
         t.join(timeout=1)
         exit_code = process.poll()
@@ -242,6 +245,7 @@ class GenericAgentHandler(BaseHandler):
         self.focus = ""
         self.cwd = cwd
         self.history_info = last_history if last_history else []
+        self.code_stop_signal = []
 
     def _get_abs_path(self, path):
         if not path: return ""
@@ -274,7 +278,7 @@ class GenericAgentHandler(BaseHandler):
         raw_path = os.path.join(self.cwd, args.get("cwd", './'))
         cwd = os.path.normpath(os.path.abspath(raw_path))
         code_cwd = os.path.normpath(self.cwd)
-        result = yield from code_run(code, code_type, timeout, cwd, code_cwd=code_cwd)
+        result = yield from code_run(code, code_type, timeout, cwd, code_cwd=code_cwd, stop_signal=self.code_stop_signal)
         next_prompt = self._get_anchor_prompt() + warning
         return StepOutcome(result, next_prompt=next_prompt)
     
@@ -315,7 +319,7 @@ class GenericAgentHandler(BaseHandler):
         print("Web Execute JS Result:", smart_format(result))
         yield f"JS 执行结果:\n{smart_format(result)}\n"
         next_prompt = self._get_anchor_prompt()
-        return StepOutcome(result, next_prompt=next_prompt)
+        return StepOutcome(smart_format(result, max_str_len=5000), next_prompt=next_prompt)
     
     def do_file_patch(self, args, response):
         path = self._get_abs_path(args.get("path", ""))

sidercall.py

@@ -12,12 +12,15 @@ class SiderLLMSession:
         self.default_model = default_model
     def ask(self, prompt, model=None, stream=False):
         if model is None: model = self.default_model
-        if len(prompt) > 29000: 
+        if len(prompt) > 28000: 
             print(f"[Warn] Prompt too long ({len(prompt)} chars), truncating.")
-            prompt = prompt[-29000:]
+            prompt = prompt[-28000:]
         gen = self._core.chat(prompt, model)
-        if stream: return gen
+        full_text = ''.join(list(gen))
-        return ''.join(list(gen))
+        if stream:
+            def wrap_as_stream(): yield full_text
+            return wrap_as_stream()  # gen有奇怪的死循环行为，sider足够快
+        return full_text   
   
 class LLMSession:
     def __init__(self, api_key=oai_apikey, api_base=oai_apibase, model=oai_model, context_win=12000):
@@ -74,7 +77,7 @@ class LLMSession:
             keep = 0; tok = 0
             for m in reversed(self.raw_msgs):
                 l = len(str(m))//4
-                if tok + l > self.context_win//3: break
+                if tok + l > self.context_win*0.2: break
                 tok += l; keep += 1
             keep = max(2, keep)
             old, self.raw_msgs = self.raw_msgs[:-keep], self.raw_msgs[-keep:]
@@ -84,28 +87,29 @@ class LLMSession:
             messages += [{"role":"user", "content":p}]
             msg_lens = [1000 if isinstance(m["content"], list) else len(str(m["content"]))//4 for m in messages]
             summary = ''.join(list(self.raw_ask(messages, model, temperature=0.1)))
-            print('[Debug] Summary length:', len(summary)//4, '; Context lengths:', str(msg_lens))
+            print('[Debug] Summary length:', len(summary)//4, '; Orig context lengths:', str(msg_lens))
             if not summary.startswith("Error:"): 
                 self.raw_msgs.insert(0, {"role":"assistant", "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=None, image_base64=None, stream=False):
         if model is None: model = self.model
-        self.raw_msgs.append({"role": "user", "prompt": prompt, "image": image_base64})
-        messages = self.make_messages(self.raw_msgs[:-1], omit_images=True)
-        messages += self.make_messages([self.raw_msgs[-1]], omit_images=False)
-        msg_lens = [1000 if isinstance(m["content"], list) else len(str(m["content"]))//4 for m in messages]
-        total_len = sum(msg_lens)   # estimate token count
         def _ask_gen():
             content = ''
             with self.lock:
-                gen = self.raw_ask(messages, model)
+                self.raw_msgs.append({"role": "user", "prompt": prompt, "image": image_base64})
-                for chunk in gen:
+                messages = self.make_messages(self.raw_msgs[:-1], omit_images=True)
-                    content += chunk; yield chunk
+                messages += self.make_messages([self.raw_msgs[-1]], omit_images=False)
+                msg_lens = [1000 if isinstance(m["content"], list) else len(str(m["content"]))//4 for m in messages]
+                total_len = sum(msg_lens)   # estimate token count
+            gen = self.raw_ask(messages, model)
+            for chunk in gen:
+                content += chunk; yield chunk
             if not content.startswith("Error:"):
                 self.raw_msgs.append({"role": "assistant", "prompt": content, "image": None})
             if total_len > 5000: print(f"[Debug] Whole context length {total_len} {str(msg_lens)}.")
             if total_len > self.context_win: 
+                yield '[NextWillSummary]'
                 threading.Thread(target=self.summary_history, daemon=True).start()
         if stream: return _ask_gen()
         return ''.join(list(_ask_gen())) 
@@ -142,12 +146,18 @@ class ToolClient:
     def chat(self, messages, tools=None):
         full_prompt = self._build_protocol_prompt(messages, tools)      
         print("Full prompt length:", len(full_prompt), 'chars')
-        gen = self.raw_api(full_prompt, stream=True)
-        raw_text = ''
-        for chunk in gen:
-            raw_text += chunk; yield chunk
         with open('model_responses.txt', 'a', encoding='utf-8', errors="replace") as f:
-            f.write(f"=== Prompt ===\n{full_prompt}\n=== Response ===\n{raw_text}\n\n")
+            f.write(f"=== Prompt ===\n{full_prompt}\n")
+        gen = self.raw_api(full_prompt, stream=True)
+        raw_text = ''; summarytag = '[NextWillSummary]'
+        for chunk in gen:
+            raw_text += chunk; 
+            if chunk != summarytag: yield chunk
+        print('Complete response received.')
+        if raw_text.endswith(summarytag):
+            self.last_tools = ''; raw_text = raw_text[:-len(summarytag)]
+        with open('model_responses.txt', 'a', encoding='utf-8', errors="replace") as f:
+            f.write(f"=== Response ===\n{raw_text}\n\n")
         return self._parse_mixed_response(raw_text)
 
     def _build_protocol_prompt(self, messages, tools):