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1d9c77522a
- 删除全部 Python 源码 (src/) 及 Alembic 迁移脚本，归档至 _deprecated_py_src/ - 重构 Rust gateway ai_pipeline: 拆分 planner/finalize 模块，新增 contracts/adaptation 层 - 重组 handlers 模块为 admin/public/proxy/internal/shared 子模块结构 - 新增 executor 模块，引入 Rust 原生数据库迁移 (aether-data/migrations) - 简化 CI/Docker 构建流程，移除 base image 二级构建，统一为单一 app image - 移除 Python 相关基础设施文件 (entrypoint.sh, gunicorn_conf.py, Dockerfile.base)
315 lines
12 KiB
Python
315 lines
12 KiB
Python
"""
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Thinking 整流器（Rectifier）
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采用 cc-switch 的"错误触发"模式，在遇到 Thinking 签名/结构错误时触发整流。
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核心功能：
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1. 移除所有 thinking 和 redacted_thinking 块
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2. 移除非 thinking 块上的 signature 字段
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3. 条件删除顶层 thinking 参数
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使用场景：
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当遇到 ThinkingSignatureException 时，调用 rectify() 整流请求体后重试一次。
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"""
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import copy
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import json
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from typing import Any
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from src.core.logger import logger
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class ThinkingRectifier:
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"""
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Thinking 整流器
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在遇到 Thinking 签名/结构错误时，整流请求体以便重试。
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采用"彻底清洗 + 条件禁用 thinking"策略。
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"""
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@staticmethod
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def rectify(request_body: dict[str, Any]) -> tuple[dict[str, Any], bool]:
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"""
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整流请求体
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执行以下操作：
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1. 移除所有 thinking 和 redacted_thinking 块
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2. 移除非 thinking 块上的 signature 字段
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3. 条件删除顶层 thinking 参数
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Args:
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request_body: 原始请求体
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Returns:
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Tuple[整流后的请求体, 是否有修改]
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"""
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if not request_body:
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return request_body, False
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# 深拷贝以避免修改原始数据
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rectified_body = copy.deepcopy(request_body)
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modified = False
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# 1. 整流 messages
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messages = rectified_body.get("messages", [])
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if messages:
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rectified_messages, messages_modified = ThinkingRectifier._rectify_messages(messages)
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if messages_modified:
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rectified_body["messages"] = rectified_messages
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modified = True
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# 2. 条件删除顶层 thinking 参数（使用整流后的 messages 判断）
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# 与 cc-switch 行为一致：在整流 messages 之后获取快照进行判断
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if ThinkingRectifier._should_remove_top_level_thinking(rectified_body):
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if "thinking" in rectified_body:
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del rectified_body["thinking"]
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modified = True
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logger.info("ThinkingRectifier: 已移除顶层 thinking 参数")
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return rectified_body, modified
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@staticmethod
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def rectify_signature_sensitive_blocks(
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request_body: dict[str, Any],
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) -> tuple[dict[str, Any], bool]:
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"""Second-stage rectification for signature-related failures.
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This is a more aggressive fallback than `rectify()`:
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- Removes all thinking/redacted_thinking blocks
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- Removes signature fields on remaining blocks
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- Degrades tool_use/tool_result blocks into plain text blocks
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- Disables top-level `thinking` when enabled
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"""
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if not request_body:
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return request_body, False
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rectified_body = copy.deepcopy(request_body)
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modified = False
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messages = rectified_body.get("messages", [])
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if isinstance(messages, list) and messages:
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new_messages: list[Any] = []
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for message in messages:
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if not isinstance(message, dict):
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new_messages.append(message)
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continue
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new_message = dict(message)
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content = message.get("content")
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if isinstance(content, list):
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new_content: list[Any] = []
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for block in content:
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if not isinstance(block, dict):
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new_content.append(block)
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continue
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block_type = block.get("type")
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if block_type in ("thinking", "redacted_thinking"):
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modified = True
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continue
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if block_type == "tool_use":
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# Degrade into text to avoid strict structure/signature validation.
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name = block.get("name")
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inp = block.get("input")
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try:
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inp_text = json.dumps(inp, ensure_ascii=False)
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except Exception:
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inp_text = str(inp)
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new_content.append(
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{
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"type": "text",
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"text": f"[tool_use] name={name} input={inp_text}",
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}
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)
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modified = True
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continue
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if block_type == "tool_result":
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raw = block.get("content")
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try:
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raw_text = json.dumps(raw, ensure_ascii=False)
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except Exception:
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raw_text = str(raw)
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new_content.append(
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{
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"type": "text",
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"text": f"[tool_result] {raw_text}",
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}
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)
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modified = True
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continue
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# Remove signature field (for any non-thinking block).
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if "signature" in block:
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new_block = {k: v for k, v in block.items() if k != "signature"}
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new_content.append(new_block)
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modified = True
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continue
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new_content.append(block)
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new_message["content"] = new_content
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new_messages.append(new_message)
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rectified_body["messages"] = new_messages
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# Stage-2: disable top-level thinking unconditionally when enabled.
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thinking_param = rectified_body.get("thinking")
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if isinstance(thinking_param, dict) and thinking_param.get("type") == "enabled":
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del rectified_body["thinking"]
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modified = True
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logger.info("ThinkingRectifier(stage2): 已移除顶层 thinking 参数")
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return rectified_body, modified
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@staticmethod
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def _rectify_messages(messages: list[dict[str, Any]]) -> tuple[list[dict[str, Any]], bool]:
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"""
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整流消息列表
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移除所有 thinking/redacted_thinking 块和 signature 字段
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Args:
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messages: 原始消息列表
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Returns:
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Tuple[整流后的消息列表, 是否有修改]
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"""
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if not messages:
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return messages, False
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modified = False
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result_messages: list[dict[str, Any]] = []
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thinking_removed = 0
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signature_removed = 0
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for message in messages:
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# 类型保护：跳过非 dict 消息
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if not isinstance(message, dict):
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result_messages.append(message)
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continue
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# 消息级浅拷贝：外层 rectify() 已深拷贝整个 request_body
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# content 会被重建为新列表，不会影响原始数据
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new_message = dict(message)
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content = message.get("content")
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if isinstance(content, list):
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new_content = []
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for block in content:
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if isinstance(block, dict):
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block_type = block.get("type")
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# 移除 thinking 和 redacted_thinking 块
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if block_type in ("thinking", "redacted_thinking"):
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thinking_removed += 1
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modified = True
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continue
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# 移除非 thinking 块上的 signature 字段
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if "signature" in block:
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new_block = {k: v for k, v in block.items() if k != "signature"}
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new_content.append(new_block)
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signature_removed += 1
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modified = True
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continue
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new_content.append(block)
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else:
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new_content.append(block)
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# 更新 content
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new_message["content"] = new_content
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# 如果整流后 assistant 消息的 content 为空，记录警告
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# （空 content 本身不是"修改"，只是检测到的状态，不设置 modified）
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# 保留消息是必要的：跳过会破坏对话结构（后续 tool_result 消息需要前置 assistant 消息）
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if new_message.get("role") == "assistant":
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effective_content = new_message.get("content")
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is_empty = not effective_content or (
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isinstance(effective_content, list) and len(effective_content) == 0
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)
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if is_empty:
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msg_idx = len(result_messages)
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logger.warning(
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f"ThinkingRectifier: assistant 消息整流后 content 为空 (message_index={msg_idx})"
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)
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result_messages.append(new_message)
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if thinking_removed > 0 or signature_removed > 0:
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logger.info(
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f"ThinkingRectifier: 移除了 {thinking_removed} 个 thinking 块, "
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f"{signature_removed} 个 signature 字段"
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)
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return result_messages, modified
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@staticmethod
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def _should_remove_top_level_thinking(body: dict[str, Any]) -> bool:
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"""
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判断是否应该删除顶层 thinking 参数
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与 cc-switch 行为一致：只检查最后一条 assistant 消息
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设计思路：
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- body 中的 messages 是整流后的状态，thinking 块已被移除
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- Claude API 只校验最后一条 assistant 消息的结构
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- 如果最后一条有 tool_use 但首块不是 thinking，需要禁用 thinking 参数
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Args:
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body: 整流后的请求体
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Returns:
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是否应该删除顶层 thinking 参数
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"""
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# 条件 1: thinking 参数存在且已启用
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thinking_param = body.get("thinking")
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if not isinstance(thinking_param, dict) or thinking_param.get("type") != "enabled":
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return False
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# 从 body 中获取 messages
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messages = body.get("messages", [])
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# 类型保护：确保 messages 是 list
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if not isinstance(messages, list) or not messages:
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return False
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# 条件 2: 找到最后一条 assistant 消息
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last_assistant = None
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for message in reversed(messages):
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if isinstance(message, dict) and message.get("role") == "assistant":
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last_assistant = message
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break
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if not last_assistant:
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return False
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content = last_assistant.get("content")
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if not isinstance(content, list) or not content:
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return False
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# 注意：传入的 messages 是整流后的状态，thinking 块已被移除
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# 因此只需检查是否有 tool_use，如果有则需要禁用 thinking 参数
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# （因为整流后的 assistant 消息不再以 thinking 块开头）
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# 检查是否有 tool_use
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has_tool_use = any(
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isinstance(block, dict) and block.get("type") == "tool_use" for block in content
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)
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# 整流后 assistant 消息不再以 thinking 块开头，如果有 tool_use 则需要禁用 thinking 参数
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# （Claude API 要求：启用 thinking 时，有 tool_use 的 assistant 消息必须以 thinking 块开头）
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if has_tool_use:
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logger.info(
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"ThinkingRectifier: 整流后 assistant 消息有 tool_use 但无 thinking 前缀，"
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"禁用 thinking 参数以通过 API 校验"
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)
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return True
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logger.debug("ThinkingRectifier: 整流后 assistant 消息无 tool_use，保留 thinking 参数")
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return False
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