fix(aibox): prevent tool results from corrupting conversation and breaking API requests
Root causes of API request failures after tool calls: 1. reasoning_content (an API response field) was echoed back in assistant messages, which could cause API format errors 2. tool_call id could be empty string when model didn't return one in a streaming chunk, producing invalid tool_calls that caused 400 errors 3. Tool execute() could return None or non-string types; direct string operations (len(), + "\n", [:200]) raised TypeError and produced non-string content in tool messages, breaking JSON serialization 4. Tool output (e.g. from run_command) could contain control characters (NULL/BEL/BS) that corrupted JSON payloads 5. When API request failed (network/4xx/5xx/parse error), messages added in that turn (user msg, assistant msg with tool_calls, tool responses) remained in self.messages, permanently poisoning conversation history so all subsequent requests would also fail Fixes: - Stop sending reasoning_content back to API in message construction; normalize assistant message content: null when tool_calls present, "" when neither content nor tool_calls exist, str otherwise - Sanitize tool messages: ensure tool_call_id is non-empty (fallback id) and content is always a string - Generate fallback tool_call id when model omits it; handle streaming id delivery where id arrives in a later chunk - Add _sanitize_tool_result(): coerce None/non-string to str, strip control characters (preserve \n \t \r) to prevent JSON/API corruption - Wrap execute_tool call in try/except in _handle_tool_calls for double safety; ensure history logging never crashes - Truncate oversized results with an explicit note instead of replacing with a generic error that lost all useful output - Add _rollback_messages(to_length) and record msgs_before_turn at start of think_and_respond; on any exception (RequestException, JSONDecodeError, or unexpected Exception), rollback self.messages to the pre-turn state so the conversation is not left in a broken state - In _handle_tool_calls, wrap execute_tool in try/except and always produce a safe string result
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+101
-31
@@ -6710,6 +6710,25 @@ class DeepSeekChat:
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self.logger.error(f"保存工具结果失败: {e}")
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return None
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@staticmethod
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def _sanitize_tool_result(result) -> str:
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"""将工具返回值安全转换为字符串，清理控制字符，防止破坏 API 请求。"""
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if result is None:
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return ""
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if not isinstance(result, str):
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try:
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result = str(result)
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except Exception:
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return f"⚠️ 工具返回了无法序列化的结果类型: {type(result).__name__}"
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# 清理控制字符：保留 \n \t \r，移除其他可能导致 JSON/API 问题的控制字符
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cleaned_chars = []
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for ch in result:
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code = ord(ch)
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if ch in ('\n', '\t', '\r') or code >= 0x20:
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cleaned_chars.append(ch)
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# 跳过 NULL、BEL、BS 等控制字符
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return ''.join(cleaned_chars)
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def _handle_tool_calls(self, tool_calls: List[Dict], output_callback: Callable = None) -> List[Dict]:
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"""处理工具调用 - 所有工具的输出都进行发送，并在开始和结束时发送两个回车"""
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if not tool_calls:
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@@ -6727,25 +6746,29 @@ class DeepSeekChat:
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for tool_call in tool_calls:
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function = tool_call.get("function", {})
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tool_name = function.get("name")
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tool_name = function.get("name", "unknown")
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arguments = function.get("arguments", "{}")
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tc_id = tool_call.get("id") or f"call_fallback_{self.stats['tool_calls']}_{int(time.time()*1000)}"
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try:
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args = json.loads(arguments) if arguments else {}
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except json.JSONDecodeError:
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args = {}
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# 【修改】开始调用工具时发送两个回车
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# 开始调用工具时发送提示
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if output_callback:
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output_callback("line", "\n\n")
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output_callback("line", f"🔧 调用工具: {tool_name}\n")
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# 直接调用 execute_tool（同步）。
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# - 若工具支持流式：execute_tool 内部开线程调 execute_streaming(**args)，
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# 收集输出后转发到 current_output_queue（即此处的 output_queue），join 后返回。
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# - 若工具不支持流式：execute_tool 直接调 execute(**args) 返回结果。
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# 两种情况下 execute_tool 返回时执行均已完成，args 完整传入，不再有参数丢失。
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result = self.tool_registry.execute_tool(tool_name, **args)
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result_raw = None
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try:
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result_raw = self.tool_registry.execute_tool(tool_name, **args)
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except Exception as e:
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result_raw = f"❌ 工具 {tool_name} 执行异常: {str(e)}"
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self.logger.error(f"工具 {tool_name} 执行异常: {e}")
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# 安全转换并清理结果
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result = self._sanitize_tool_result(result_raw)
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# 排空 output_queue，把流式行输出转发给 output_callback
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has_stream_output = False
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@@ -6753,7 +6776,7 @@ class DeepSeekChat:
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try:
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msg_type, content = output_queue.get_nowait()
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if output_callback and msg_type in ("line", "complete"):
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output_callback("line", content)
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output_callback("line", str(content) if content is not None else "")
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has_stream_output = True
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except queue.Empty:
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break
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@@ -6762,36 +6785,39 @@ class DeepSeekChat:
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if not has_stream_output and output_callback and result:
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output_callback("line", result + "\n")
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# 检查结果大小，如果超过阈值，不返回结果，只返回提示信息
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if result and len(result) > MAX_RESULT_LENGTH:
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# 不保存文件，直接返回提示信息
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result = f"⚠️ 工具 {tool_name} 执行结果过大（{len(result)} 字符），超过限制（{MAX_RESULT_LENGTH} 字符），已放弃返回结果。\n\n请考虑：\n1. 使用更精确的查询条件\n2. 使用其他工具获取部分数据\n3. 优化查询方式减少结果数量"
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# 检查结果大小，如果超过阈值，截断返回提示信息
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if len(result) > MAX_RESULT_LENGTH:
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truncated_note = f"\n\n⚠️ 结果已截断（原始 {len(result)} 字符，限制 {MAX_RESULT_LENGTH} 字符）。请使用更精确的查询获取所需信息。"
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result = result[:MAX_RESULT_LENGTH] + truncated_note
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if output_callback:
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output_callback("line", result + "\n")
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output_callback("line", truncated_note + "\n")
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# 【修改】结束调用工具时发送两个回车
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# 结束调用工具时发送换行
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if output_callback:
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output_callback("line", "\n\n")
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# 历史记录（安全截断）
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if self.history_manager:
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self.history_manager.add_tool_call(tool_name, args, result[:200] + "..." if len(result) > 200 else result)
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try:
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history_preview = result[:200] + "..." if len(result) > 200 else result
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self.history_manager.add_tool_call(tool_name, args, history_preview)
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except Exception:
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pass
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if tool_name == "save_memory_and_end_conversation" and "✅" in result:
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# 检查是否结束对话
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end_conversation = (tool_name == "save_memory_and_end_conversation" and "✅" in result)
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if end_conversation:
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self.logger.info("检测到保存记忆并结束对话工具调用")
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self.conversation_active = False
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tool_messages.append({
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"role": "tool",
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"tool_call_id": tool_call.get("id"),
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"content": result
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})
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# 【修复】不直接返回，而是添加后继续处理，但设置标志让后续停止
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break
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tool_messages.append({
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"role": "tool",
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"tool_call_id": tool_call.get("id"),
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"tool_call_id": tc_id,
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"content": result
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})
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if end_conversation:
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break
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# 清除输出队列
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self.tool_registry.set_output_queue(None)
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@@ -6903,6 +6929,9 @@ class DeepSeekChat:
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enhanced_input = pre_prompt + "\n\n" + input_text + post_prompt
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# 记录本轮开始前的消息长度，用于 API 失败时回滚，防止坏消息污染对话历史
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msgs_before_turn = len(self.messages)
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self._add_message("user", enhanced_input)
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if self.history_manager:
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@@ -6921,19 +6950,32 @@ class DeepSeekChat:
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if msg["role"] == "system":
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enhanced_messages.append(msg)
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# 添加非系统消息，但确保消息结构正确
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# 添加非系统消息，确保消息结构正确
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for msg in self.messages:
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if msg["role"] != "system":
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if msg["role"] == "assistant":
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assistant_msg = {"role": "assistant"}
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if "content" in msg and msg["content"]:
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has_content = "content" in msg and msg["content"] is not None
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has_tool_calls = "tool_calls" in msg and msg["tool_calls"]
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if has_content:
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assistant_msg["content"] = msg["content"]
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if "reasoning_content" in msg:
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assistant_msg["reasoning_content"] = msg["reasoning_content"]
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if "tool_calls" in msg and msg["tool_calls"]:
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if has_tool_calls:
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assistant_msg["tool_calls"] = msg["tool_calls"]
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# 有 tool_calls 时 content 必须为 null（API 要求）
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assistant_msg["content"] = None
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elif not has_content:
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# 无 content 也无 tool_calls 时，设为空字符串避免 API 拒绝
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assistant_msg["content"] = ""
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# 注意：不回传 reasoning_content，它是 API 响应字段，回传可能导致请求失败
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enhanced_messages.append(assistant_msg)
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elif msg["role"] == "tool":
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# 确保 tool 消息 content 始终是字符串
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tool_msg = {
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"role": "tool",
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"tool_call_id": msg.get("tool_call_id", ""),
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"content": str(msg.get("content", "")) if msg.get("content") is not None else ""
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}
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enhanced_messages.append(tool_msg)
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else:
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enhanced_messages.append(msg)
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@@ -7036,14 +7078,22 @@ class DeepSeekChat:
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index = tc.get('index', 0)
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if index not in current_tool_calls:
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# 确保 tool_call id 非空，空 id 会导致 API 400 错误污染对话历史
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tc_id = tc.get('id', '') or f"call_{self.stats['tool_calls']}_{index}_{int(time.time()*1000)}"
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current_tool_calls[index] = {
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'id': tc.get('id', ''),
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'id': tc_id,
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'type': 'function',
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'function': {
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'name': '',
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'arguments': ''
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}
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}
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else:
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# 流式传输中 id 可能分片到达，后续补充
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existing_id = current_tool_calls[index].get('id', '')
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new_id = tc.get('id', '')
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if new_id and (not existing_id or existing_id.startswith('call_')):
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current_tool_calls[index]['id'] = new_id
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if 'function' in tc:
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if 'name' in tc['function']:
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@@ -7119,24 +7169,44 @@ class DeepSeekChat:
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return full_response if full_response else ""
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except requests.exceptions.RequestException as e:
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# 网络/HTTP 错误：回滚本轮添加的消息（user 消息 + 可能的 assistant/tool 消息），
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# 防止格式错误的消息污染历史导致后续请求持续失败
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self._rollback_messages(msgs_before_turn)
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error_msg = f"\n{i18n.get('error_prefix')}API请求失败: {str(e)}"
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if output_callback:
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output_callback("error", error_msg)
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self.stats["errors"].append(str(e))
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self.logger.error(f"API请求失败，已回滚消息到位置 {msgs_before_turn}: {e}")
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return error_msg
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except json.JSONDecodeError as e:
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# JSON 解析错误：回滚消息
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self._rollback_messages(msgs_before_turn)
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error_msg = f"\n{i18n.get('error_prefix')}API响应解析失败: {str(e)}"
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if output_callback:
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output_callback("error", error_msg)
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self.stats["errors"].append(str(e))
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self.logger.error(f"API响应解析失败，已回滚消息到位置 {msgs_before_turn}: {e}")
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return error_msg
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except Exception as e:
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# 未知错误：回滚消息，防止对话状态被破坏
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self._rollback_messages(msgs_before_turn)
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error_msg = f"\n{i18n.get('error_prefix')}{str(e)}"
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if output_callback:
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output_callback("error", error_msg)
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self.stats["errors"].append(str(e))
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self.logger.error(f"未知错误，已回滚消息到位置 {msgs_before_turn}: {e}")
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return error_msg
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def _rollback_messages(self, to_length: int):
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"""回滚 self.messages 到指定长度，用于 API 失败时恢复对话状态。"""
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try:
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current_len = len(self.messages)
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if current_len > to_length:
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del self.messages[to_length:]
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self.logger.info(f"消息已回滚，从 {current_len} 条回滚到 {len(self.messages)} 条")
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except Exception as e:
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self.logger.error(f"消息回滚失败: {e}")
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def _add_assistant_message_with_reasoning(self, content: str, reasoning_content: str = None, tool_calls: List = None):
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"""添加助手消息，包含 reasoning_content"""
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