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adapters/responses_cc_adapter.py

@@ -654,10 +654,6 @@ class ResponsesToCCStreamConverter:
             'completion_tokens': self._usage.get('output_tokens', 0),
             'total_tokens': self._usage.get('total_tokens', 0),
         }
-        if isinstance(self._usage.get('input_tokens_details'), dict):
-            chunk['usage']['prompt_tokens_details'] = dict(self._usage['input_tokens_details'])
-        if isinstance(self._usage.get('output_tokens_details'), dict):
-            chunk['usage']['completion_tokens_details'] = dict(self._usage['output_tokens_details'])
         return [chunk]
 
     def _make_chunk(self, delta: JsonDict, finish_reason: str | None = None) -> JsonDict:
@@ -682,44 +678,20 @@ def _copy_request_options(payload: JsonDict, result: JsonDict) -> None:
     """将 Responses 请求中的通用选项复制到 CC 请求体。"""
     if 'tools' in payload:
         result['tools'] = _convert_tools(payload['tools'])
-    for key in (
-        'temperature',
-        'top_p',
-        'tool_choice',
-        'parallel_tool_calls',
-        'truncation',
-        'store',
-        'metadata',
-        'conversation',
-        'previous_response_id',
-        'prompt_cache_key',
-        'service_tier',
-        'user',
-    ):
+    for key in ('temperature', 'top_p'):
         if key in payload:
             result[key] = payload[key]
     if 'max_output_tokens' in payload:
         result['max_tokens'] = payload['max_output_tokens']
+    if 'tool_choice' in payload:
+        result['tool_choice'] = payload['tool_choice']
 
 
 def _copy_responses_request_options(payload: JsonDict, result: JsonDict) -> None:
     """将聊天补全请求中的通用选项复制到原生 Responses 请求体。"""
     if 'tools' in payload:
         result['tools'] = _convert_cc_tools_to_responses(payload['tools'])
-    for key in (
-        'temperature',
-        'top_p',
-        'tool_choice',
-        'parallel_tool_calls',
-        'truncation',
-        'store',
-        'metadata',
-        'conversation',
-        'previous_response_id',
-        'prompt_cache_key',
-        'service_tier',
-        'user',
-    ):
+    for key in ('temperature', 'top_p', 'tool_choice'):
         if key in payload:
             result[key] = payload[key]
     if 'max_tokens' in payload:
@@ -942,18 +914,11 @@ def _make_function_call_output_item(tool_call: JsonDict) -> JsonDict:
 
 def _build_responses_usage(usage: JsonDict) -> JsonDict:
     """将 Chat Completions 的 usage 字段映射为 Responses usage 结构。"""
-    result = {
+    return {
         'input_tokens': usage.get('prompt_tokens', 0),
         'output_tokens': usage.get('completion_tokens', 0),
         'total_tokens': usage.get('total_tokens', 0),
     }
-    prompt_details = usage.get('prompt_tokens_details')
-    if isinstance(prompt_details, dict):
-        result['input_tokens_details'] = dict(prompt_details)
-    completion_details = usage.get('completion_tokens_details')
-    if isinstance(completion_details, dict):
-        result['output_tokens_details'] = dict(completion_details)
-    return result
 
 
 def _collect_cc_parts_from_responses_output(output_items: Any) -> tuple[str, str, list[JsonDict]]:

routes/chat.py

@@ -42,9 +42,6 @@ from routes.common import (
     build_responses_target,
     build_route_context,
     chat_error_chunk,
-    ensure_responses_cache_control,
-    attach_previous_response_id,
-    remember_response_id,
     inject_instructions_anthropic,
     inject_instructions_cc,
     inject_instructions_responses,
@@ -314,8 +311,6 @@ def _handle_responses_backend(ctx: RouteContext, payload: dict[str, Any], turn:
     responses_payload = cc_to_responses_request(payload)
     responses_payload['model'] = ctx.upstream_model
     responses_payload = inject_instructions_responses(responses_payload, ctx.custom_instructions, ctx.instructions_position)
-    responses_payload = ensure_responses_cache_control(responses_payload)
-    responses_payload = attach_previous_response_id(responses_payload)
     _dbg(
         '已转换为 Responses 请求：字段=' + str(list(responses_payload.keys()))
         + f' 输入项数={len(responses_payload.get("input", []))}'
@@ -350,7 +345,6 @@ def _handle_responses_non_stream(
     attach_upstream_response(turn, raw)
     _dbg('上游原始响应=' + json.dumps(raw, ensure_ascii=False, default=str)[:1000])
 
-    remember_response_id(payload, raw)
     data = responses_to_cc_response(raw, ctx.client_model)
     return _finalize_chat_response(ctx, data, turn=turn, debug_label='Responses 转回聊天补全后')
 
@@ -389,10 +383,6 @@ def _handle_responses_stream(
                     'completion_tokens': extracted_usage.get('output_tokens', 0),
                     'total_tokens': extracted_usage.get('total_tokens', 0),
                 }
-            if event_type == 'response.completed':
-                response_obj = event_data.get('response') if isinstance(event_data, dict) else None
-                if isinstance(response_obj, dict):
-                    remember_response_id(payload, response_obj)
             if event_count < 10:
                 _dbg(
                     f'上游事件#{event_count} 类型={event_type} 数据='

routes/common.py

@@ -7,11 +7,8 @@ SSE 消息拼装逻辑，避免 `chat.py` 和 `responses.py` 各自维护重复
 from __future__ import annotations
 
 from dataclasses import dataclass
-import hashlib
 import json
 import logging
-import threading
-import time
 from typing import Any
 
 import settings
@@ -19,10 +16,6 @@ from utils.http import build_anthropic_headers, build_gemini_headers, build_open
 
 logger = logging.getLogger(__name__)
 
-_RESPONSES_PREV_ID_LOCK = threading.Lock()
-_RESPONSES_PREV_ID_TTL = 86400
-_RESPONSES_PREV_IDS: dict[str, tuple[str, float]] = {}
-
 
 @dataclass(frozen=True)
 class RouteContext:
@@ -202,178 +195,6 @@ def inject_instructions_responses(payload: dict[str, Any], instructions: str, po
     return payload
 
 
-def ensure_responses_cache_control(payload: dict[str, Any]) -> dict[str, Any]:
-    """为 Responses 请求补齐自动 prompt caching 开关。
-
-    一些支持 `/v1/responses` 的上游会参考顶层 `cache_control` 来自动放置缓存断点。
-    Cursor 侧通常不会主动携带这个字段，因此这里在缺失时补一个保守的默认值，
-    同时允许调用方通过 body_modifications 或显式字段自行覆盖/关闭。
-    """
-    if not isinstance(payload, dict):
-        return payload
-    cache_control = payload.get('cache_control')
-    if isinstance(cache_control, dict) and cache_control.get('type'):
-        return payload
-    payload['cache_control'] = {'type': 'ephemeral'}
-    logger.info('已为 Responses 请求自动启用 cache_control=ephemeral')
-    return payload
-
-
-def attach_previous_response_id(payload: dict[str, Any]) -> dict[str, Any]:
-    """为多轮 Responses 请求补齐上一轮 response_id。
-
-    某些上游在 `/v1/responses` 多轮场景下，只有沿用 `previous_response_id` 才能稳定复用
-    上一轮的服务端响应链与缓存。Cursor 通常会回传完整历史，但不会主动带这个字段，
-    因此代理需要基于稳定对话键做一次轻量补齐。
-    """
-    if not isinstance(payload, dict) or payload.get('previous_response_id'):
-        return payload
-    key = _responses_prev_id_key(payload)
-    if not key:
-        return payload
-    previous_response_id = _get_previous_response_id(key)
-    if not previous_response_id:
-        return payload
-    payload['previous_response_id'] = previous_response_id
-    logger.info('已为 Responses 请求补齐 previous_response_id')
-    return payload
-
-
-def remember_response_id(payload: dict[str, Any], response_data: dict[str, Any]) -> None:
-    """记住当前对话最近一次上游 Responses response_id。"""
-    if not isinstance(payload, dict) or not isinstance(response_data, dict):
-        return
-    response_id = response_data.get('id')
-    if not isinstance(response_id, str) or not response_id.strip():
-        return
-    key = _responses_prev_id_key(payload)
-    if not key:
-        return
-    with _RESPONSES_PREV_ID_LOCK:
-        _RESPONSES_PREV_IDS[key] = (response_id.strip(), time.time())
-        _cleanup_previous_response_ids_locked()
-
-
-def _responses_prev_id_key(payload: dict[str, Any]) -> str:
-    """基于 Responses 请求的“对话根信息”生成稳定键。
-
-    这里故意不直接使用完整 `input` 作为键，因为多轮对话每轮都会追加历史；
-    如果把整段历史都纳入哈希，键会在每一轮变化，导致无法稳定取回上一轮的
-    `previous_response_id`。当前策略只取 instructions 与首轮 user/assistant 根消息。
-    """
-    instructions = payload.get('instructions') or ''
-    input_data = payload.get('input', [])
-    if isinstance(input_data, str):
-        seed_input = input_data
-    elif isinstance(input_data, list):
-        seed_input = _responses_root_seed_from_items(input_data)
-    else:
-        seed_input = json.dumps(input_data, ensure_ascii=False, default=str)
-    raw = instructions + '|' + seed_input
-    if not raw.strip('|'):
-        return ''
-    return hashlib.sha256(raw.encode('utf-8')).hexdigest()[:24]
-
-
-def _responses_root_seed_from_items(items: list[Any]) -> str:
-    """从 Responses `input` 中提取足够稳定的对话根片段。
-
-    目标不是完整还原会话，而是构造一个在同一段对话内尽量恒定、跨轮次可复用的
-    seed。这里沿用项目里 conversation seed 的思路：优先取第一条 user 与第一条
-    assistant；如果 assistant 还不存在，则只用第一条 user。
-    """
-    first_user = None
-    first_assistant = None
-    for item in items:
-        if isinstance(item, str):
-            if first_user is None:
-                first_user = {'role': 'user', 'content': item}
-            continue
-        if not isinstance(item, dict):
-            continue
-        item_type = item.get('type', '')
-        role = item.get('role', '')
-        if item_type == 'message' and role in ('user', 'assistant'):
-            normalized = {
-                'role': role,
-                'content': _responses_normalize_content(item.get('content', [])),
-            }
-            if role == 'user' and first_user is None:
-                first_user = normalized
-            elif role == 'assistant' and first_assistant is None:
-                first_assistant = normalized
-        elif role in ('user', 'assistant') and not item_type:
-            normalized = {
-                'role': role,
-                'content': _responses_normalize_content(item.get('content', '')),
-            }
-            if role == 'user' and first_user is None:
-                first_user = normalized
-            elif role == 'assistant' and first_assistant is None:
-                first_assistant = normalized
-        if first_user is not None and first_assistant is not None:
-            break
-    parts = []
-    if first_user is not None:
-        parts.append(first_user)
-    if first_assistant is not None:
-        parts.append(first_assistant)
-    return json.dumps(parts, ensure_ascii=False, separators=(',', ':'))
-
-
-def _responses_normalize_content(content: Any) -> str:
-    """把 Responses 各种 content 形态折叠成稳定文本。
-
-    这里的目标不是保真展示，而是降低结构差异对 key 计算的影响；只抽取会影响
-    会话根语义的文本型内容，忽略无关字段，避免同一轮请求因格式细节不同而得到
-    不同的 previous_response_id 键。
-    """
-    if isinstance(content, str):
-        return content.strip()
-    if not isinstance(content, list):
-        return str(content).strip() if content is not None else ''
-    texts: list[str] = []
-    for part in content:
-        if isinstance(part, str):
-            texts.append(part)
-            continue
-        if not isinstance(part, dict):
-            continue
-        if part.get('type') in ('input_text', 'output_text', 'text'):
-            texts.append(part.get('text', ''))
-        elif part.get('type') == 'summary_text':
-            texts.append(part.get('text', ''))
-    return '\n'.join(texts).strip()
-
-
-def _get_previous_response_id(key: str) -> str:
-    """按稳定键读取上一轮 response_id，并在过期时顺手清理。"""
-    with _RESPONSES_PREV_ID_LOCK:
-        entry = _RESPONSES_PREV_IDS.get(key)
-        if not entry:
-            return ''
-        response_id, ts = entry
-        if (time.time() - ts) >= _RESPONSES_PREV_ID_TTL:
-            _RESPONSES_PREV_IDS.pop(key, None)
-            return ''
-        return response_id
-
-
-def _cleanup_previous_response_ids_locked() -> None:
-    """清理过期的 previous_response_id 缓存项。
-
-    这张表只用于短期多轮续接；一旦对话长时间不活跃，就不再需要继续保留，
-    以免常驻进程运行过久后累计过多失效状态。
-    """
-    now = time.time()
-    expired = [
-        key for key, (_, ts) in _RESPONSES_PREV_IDS.items()
-        if (now - ts) >= _RESPONSES_PREV_ID_TTL
-    ]
-    for key in expired:
-        _RESPONSES_PREV_IDS.pop(key, None)
-
-
 def inject_instructions_anthropic(payload: dict[str, Any], instructions: str, position: str = 'prepend') -> dict[str, Any]:
     """向 Anthropic Messages 请求注入自定义指令（写入 system 字段）。
 

routes/responses.py

@@ -27,9 +27,6 @@ from routes.common import (
     build_openai_target,
     build_responses_target,
     build_route_context,
-    ensure_responses_cache_control,
-    attach_previous_response_id,
-    remember_response_id,
     inject_instructions_anthropic,
     inject_instructions_cc,
     inject_instructions_responses,
@@ -250,8 +247,6 @@ def _handle_responses_backend(ctx: RouteContext, payload: dict[str, Any], turn:
     payload = dict(payload)
     payload['model'] = ctx.upstream_model
     payload = inject_instructions_responses(payload, ctx.custom_instructions, ctx.instructions_position)
-    payload = ensure_responses_cache_control(payload)
-    payload = attach_previous_response_id(payload)
     url, headers = build_responses_target(ctx)
     payload = apply_body_modifications(payload, ctx.body_modifications)
     headers = apply_header_modifications(headers, ctx.header_modifications)
@@ -279,7 +274,6 @@ def _handle_responses_non_stream(
 
     response_data = resp.json()
     attach_upstream_response(turn, response_data)
-    remember_response_id(payload, response_data)
     response_data['model'] = ctx.client_model
     return _finalize_responses_response(
         response_data,
@@ -319,10 +313,6 @@ def _handle_responses_stream(
             extracted_usage = _extract_responses_usage(event_data)
             if extracted_usage:
                 last_usage = extracted_usage
-            if event_type == 'response.completed':
-                response_obj = event_data.get('response') if isinstance(event_data, dict) else None
-                if isinstance(response_obj, dict):
-                    remember_response_id(payload, response_obj)
             if event_count < 10:
                 _dbg(
                     f'上游事件#{event_count} 类型={event_type} 数据='
@@ -639,22 +629,4 @@ def _finalize_responses_response(
     attach_client_response(turn, response_data)
     finalize_turn(turn, usage=response_data.get('usage'))
 
-    output_items = response_data.get('output', [])
-    if isinstance(output_items, list):
-        for item in output_items:
-            if not isinstance(item, dict) or item.get('type') != 'reasoning':
-                continue
-            summary = item.get('summary', [])
-            if not isinstance(summary, list):
-                continue
-            reasoning_text = ''.join(
-                part.get('text', '')
-                for part in summary
-                if isinstance(part, dict) and part.get('type') == 'summary_text'
-            )
-            if reasoning_text:
-                cc_messages = responses_to_cc(request.get_json(silent=True, force=True) or {}).get('messages', [])
-                thinking_cache.store_from_response(cc_messages, reasoning_text)
-                break
-
     return jsonify(response_data)