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10 commits

Author SHA1 Message Date
root
4c6bede153 you hua le rizhi de xianshi 2026-05-05 14:30:31 +08:00
root
e373295cf5 add admin log 2026-05-05 13:42:35 +08:00
h88782481
bec7b3e5ef 修复缓存命中问题 2026-04-29 11:14:00 +08:00
h88782481
251437a760 尝试修复/v1/responses后端没有命中缓存的情况 2026-04-14 16:14:06 +08:00
h88782481
cb7350b100 更新docker-compose镜像名称 2026-04-05 22:13:30 +08:00
h88782481
a8f5ada8e1 回退旧版本 2026-03-26 11:34:27 +08:00
h88782481
cd577d17c3 修复bug 2026-03-26 11:29:02 +08:00
h88782481
70361242ab 重构代码 2026-03-22 08:24:19 +08:00
h88782481
56faf4fcf1 优化缓存命中问题 2026-03-15 16:26:07 +08:00
h88782481
2f2a3cce41 回滚 2026-03-15 14:10:15 +08:00
13 changed files with 605 additions and 349 deletions

View file

@ -159,6 +159,18 @@ api2cursor/
- `file_path``path` 字段映射
- `finish_reason` 修正
============================
增加缓存在api2cursor里面的body修改中加个你喜欢的随意字段
{
"prompt_cache_key": "GPT5-4-xxx-xxx"
}
openai 开 fast 模式
{
"service_tier": "priority"
}
## 许可证
[MIT](LICENSE)

View file

@ -261,6 +261,12 @@ def _convert_request_message(message: Any) -> tuple[JsonDict | None, str | None]
anthropic_role = 'assistant' if role == 'assistant' else 'user'
anthropic_content = _convert_content(message)
if role == 'assistant' and message.get('reasoning_content'):
thinking_block = {'type': 'thinking', 'thinking': message['reasoning_content']}
blocks = _to_blocks(anthropic_content)
blocks.insert(0, thinking_block)
anthropic_content = blocks
if role == 'assistant' and 'tool_calls' in message:
anthropic_content = _append_tool_use_blocks(anthropic_content, message.get('tool_calls', []))
@ -463,6 +469,8 @@ def _convert_content_part(part: Any) -> JsonDict | None:
return {'type': 'text', 'text': part.get('text', '')}
if part_type == 'image_url':
return _convert_image(part)
if part_type == 'image':
return part
if part_type in ('tool_use', 'tool_result'):
return part
return None
@ -574,38 +582,16 @@ _EPHEMERAL = {'type': 'ephemeral'}
def optimize_cache_control(request: JsonDict) -> None:
"""自动设置最优的 Anthropic cache_control 断点
"""为 Anthropic Messages 请求启用顶层自动 prompt caching
算法移植自 CursorProxy ensure_cache_control.go
1. 归一化所有消息 content 为数组格式
2. 清空所有已有 cache_control
3. 注入结构锚点tools 末尾 + system 末尾
4. 注入消息锚点最后一个可缓存块 + 窗口边界
5. 总断点数不超过 4
2026 Claude API 已支持在请求顶层使用 `cache_control` 开启自动缓存
由上游自动把断点放到最后一个可缓存块并随多轮对话前移相比手动在嵌套
content blocks 上打断点这种方式对 Anthropic 兼容中转站更稳定也更接近
`/v1/responses` 通过顶层字段启用缓存的思路
"""
_normalize_message_contents(request)
_clear_all_cache_controls(request)
structural = _inject_structural_anchors(request)
remaining = _MAX_BREAKPOINTS - structural
if remaining <= 0:
return
refs = _collect_cacheable_block_refs(request)
if not refs:
return
desired = 1 if len(refs) < _BLOCK_WINDOW else 2
anchors = min(desired, remaining)
if anchors >= 1 and refs:
refs[-1]['cache_control'] = _EPHEMERAL
if anchors >= 2 and len(refs) > 1:
target = len(refs) - _BLOCK_WINDOW
idx = _pick_window_anchor(refs, target)
if idx is not None and idx != len(refs) - 1:
refs[idx]['cache_control'] = _EPHEMERAL
request['cache_control'] = dict(_EPHEMERAL)
def _normalize_message_contents(request: JsonDict) -> None:
@ -620,6 +606,7 @@ def _normalize_message_contents(request: JsonDict) -> None:
def _clear_all_cache_controls(request: JsonDict) -> None:
"""清空所有已有的 cache_control 字段。"""
request.pop('cache_control', None)
for tool in request.get('tools', []):
tool.pop('cache_control', None)

View file

@ -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:
@ -731,7 +703,11 @@ def _append_responses_input_item(
instructions: list[str],
input_items: list[JsonDict],
) -> None:
"""将单条 Chat Completions 消息追加为 Responses `input` 项。"""
"""将单条 Chat Completions 消息追加为 Responses `input` 项。
尽量使用 EasyInputMessage 格式{role, content}以减少 token 开销
提高上游 prompt caching 的前缀匹配命中率
"""
if not isinstance(message, dict):
return
@ -752,21 +728,26 @@ def _append_responses_input_item(
})
return
item: JsonDict = {
'type': 'message',
'role': role or 'user',
'content': _content_to_responses_parts(content, role),
}
input_items.append(item)
text = _content_to_text(content)
has_tool_calls = bool(message.get('tool_calls'))
if role == 'assistant':
if role == 'assistant' and has_tool_calls:
if text:
input_items.append({
'type': 'message',
'role': 'assistant',
'content': [{'type': 'output_text', 'text': text}],
})
for tool_call in message.get('tool_calls') or []:
input_items.append(_build_responses_function_call_item(tool_call))
else:
input_items.append({'role': role or 'user', 'content': text or ''})
def _convert_input_items(items: list[Any], messages: list[JsonDict]) -> None:
"""将 Responses `input` 数组重建为 Chat Completions `messages` 列表。"""
index = 0
pending_reasoning: str | None = None
while index < len(items):
item = items[index]
@ -782,20 +763,35 @@ def _convert_input_items(items: list[Any], messages: list[JsonDict]) -> None:
item_type = item.get('type', '')
role = item.get('role', '')
if item_type == 'reasoning':
pending_reasoning = _extract_reasoning_text(item)
index += 1
continue
if role and not item_type:
messages.append({
msg: JsonDict = {
'role': role,
'content': _normalize_simple_content(item.get('content', '')),
})
}
if role == 'assistant' and pending_reasoning:
msg['reasoning_content'] = pending_reasoning
pending_reasoning = None
messages.append(msg)
index += 1
continue
if item_type == 'message':
consumed = _append_message_item(items, start=index, messages=messages)
if item.get('role') == 'assistant' and pending_reasoning and messages:
messages[-1]['reasoning_content'] = pending_reasoning
pending_reasoning = None
index += consumed
continue
if item_type == 'function_call':
if pending_reasoning and messages and messages[-1].get('role') == 'assistant':
messages[-1]['reasoning_content'] = pending_reasoning
pending_reasoning = None
_append_function_call_item(item, messages)
index += 1
continue
@ -942,18 +938,11 @@ 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]]:

View file

@ -1,6 +1,7 @@
services:
api2cursor:
build: .
container_name: api2cursor
ports:
- "${PROXY_PORT:-3029}:${PROXY_PORT:-3029}"
env_file:

View file

@ -13,6 +13,7 @@ from flask import Blueprint, request, jsonify, send_from_directory
import settings
from config import Config
from utils.request_history import request_history
logger = logging.getLogger(__name__)
@ -202,6 +203,15 @@ def get_stats():
return jsonify(usage_tracker.get_stats())
@bp.route('/api/admin/request-logs', methods=['GET'])
def get_request_logs():
"""返回最近 500 条请求日志。"""
err = _check_auth()
if err:
return err
return jsonify({'items': request_history.get_recent(500)})
# ─── 内部辅助 ─────────────────────────────────────

View file

@ -9,6 +9,7 @@ from __future__ import annotations
import json
import logging
from time import perf_counter
from typing import Any
import settings
@ -42,9 +43,7 @@ from routes.common import (
build_responses_target,
build_route_context,
chat_error_chunk,
ensure_responses_cache_control,
attach_previous_response_id,
remember_response_id,
ensure_prompt_cache_key,
inject_instructions_anthropic,
inject_instructions_cc,
inject_instructions_responses,
@ -61,6 +60,7 @@ from utils.http import (
iter_responses_sse,
sse_response,
)
from utils.request_history import request_history
from utils.request_logger import (
append_client_event,
append_upstream_event,
@ -115,6 +115,7 @@ def chat_completions():
client_model = payload.get('model', 'unknown')
is_stream = payload.get('stream', False)
ctx = build_route_context(client_model, is_stream)
request_started_at = perf_counter()
turn = start_turn(
route='chat',
client_model=client_model,
@ -130,15 +131,16 @@ def chat_completions():
log_route_context('聊天补全', ctx, extra=f'消息数={message_count}')
_log_messages(payload)
payload['messages'] = thinking_cache.inject(payload.get('messages', []))
if ctx.backend != 'responses':
payload['messages'] = thinking_cache.inject(payload.get('messages', []))
if ctx.backend == 'openai':
return _handle_openai_backend(ctx, payload, turn)
return _handle_openai_backend(ctx, payload, turn, request_started_at)
if ctx.backend == 'responses':
return _handle_responses_backend(ctx, payload, turn)
return _handle_responses_backend(ctx, payload, turn, request_started_at)
if ctx.backend == 'gemini':
return _handle_gemini_backend(ctx, payload, turn)
return _handle_anthropic_backend(ctx, payload, turn)
return _handle_gemini_backend(ctx, payload, turn, request_started_at)
return _handle_anthropic_backend(ctx, payload, turn, request_started_at)
def _normalize_chat_payload(payload: dict[str, Any]) -> tuple[dict[str, Any], int]:
@ -159,7 +161,12 @@ def _normalize_chat_payload(payload: dict[str, Any]) -> tuple[dict[str, Any], in
return payload, message_count
def _handle_openai_backend(ctx: RouteContext, payload: dict[str, Any], turn: dict[str, Any]):
def _handle_openai_backend(
ctx: RouteContext,
payload: dict[str, Any],
turn: dict[str, Any],
request_started_at: float,
):
"""处理走 OpenAI 兼容后端的聊天补全请求。"""
_dbg(
'原始请求字段=' + str(list(payload.keys())) + ' '
@ -183,8 +190,8 @@ def _handle_openai_backend(ctx: RouteContext, payload: dict[str, Any], turn: dic
headers = apply_header_modifications(headers, ctx.header_modifications)
if ctx.is_stream:
return _handle_openai_stream(ctx, payload, url, headers, turn)
return _handle_openai_non_stream(ctx, payload, url, headers, turn)
return _handle_openai_stream(ctx, payload, url, headers, turn, request_started_at)
return _handle_openai_non_stream(ctx, payload, url, headers, turn, request_started_at)
def _handle_openai_non_stream(
@ -193,6 +200,7 @@ def _handle_openai_non_stream(
url: str,
headers: dict[str, str],
turn: dict[str, Any],
request_started_at: float,
):
"""处理 OpenAI 兼容后端的非流式返回。"""
payload['stream'] = False
@ -208,7 +216,14 @@ def _handle_openai_non_stream(
_dbg('上游原始响应=' + json.dumps(raw, ensure_ascii=False, default=str)[:1000])
data = fix_response(raw)
return _finalize_chat_response(ctx, data, turn=turn, debug_label='修复后响应')
return _finalize_chat_response(
ctx,
data,
turn=turn,
debug_label='修复后响应',
request_started_at=request_started_at,
upstream_url=url,
)
def _handle_openai_stream(
@ -217,6 +232,7 @@ def _handle_openai_stream(
url: str,
headers: dict[str, str],
turn: dict[str, Any],
request_started_at: float,
):
"""处理 OpenAI 兼容后端的流式返回。"""
payload['stream'] = True
@ -259,7 +275,18 @@ def _handle_openai_stream(
'chunk_count': len(client_chunks),
'usage': last_usage,
})
finalize_turn(turn, usage=last_usage)
duration_ms = int((perf_counter() - request_started_at) * 1000)
request_history.record(
route='chat',
client_model=ctx.client_model,
actual_model=ctx.upstream_model,
backend=ctx.backend,
upstream_url=url,
usage=last_usage,
duration_ms=duration_ms,
started_at=(turn or {}).get('started_at'),
)
finalize_turn(turn, usage=last_usage, duration_ms=duration_ms)
return
append_upstream_event(turn, {'type': 'openai_chunk', 'data': chunk})
@ -300,12 +327,28 @@ def _handle_openai_stream(
'chunk_count': len(client_chunks),
'usage': last_usage,
})
finalize_turn(turn, usage=last_usage)
duration_ms = int((perf_counter() - request_started_at) * 1000)
request_history.record(
route='chat',
client_model=ctx.client_model,
actual_model=ctx.upstream_model,
backend=ctx.backend,
upstream_url=url,
usage=last_usage,
duration_ms=duration_ms,
started_at=(turn or {}).get('started_at'),
)
finalize_turn(turn, usage=last_usage, duration_ms=duration_ms)
return sse_response(generate())
def _handle_responses_backend(ctx: RouteContext, payload: dict[str, Any], turn: dict[str, Any] | None):
def _handle_responses_backend(
ctx: RouteContext,
payload: dict[str, Any],
turn: dict[str, Any] | None,
request_started_at: float,
):
"""处理走原生 Responses 后端的聊天补全请求。
当上游只支持 `/v1/responses` 需要先把聊天补全请求转换为 Responses 请求
@ -314,8 +357,7 @@ 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)
responses_payload = ensure_prompt_cache_key(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", []))}'
@ -326,8 +368,8 @@ def _handle_responses_backend(ctx: RouteContext, payload: dict[str, Any], turn:
headers = apply_header_modifications(headers, ctx.header_modifications)
if ctx.is_stream:
return _handle_responses_stream(ctx, responses_payload, url, headers, turn)
return _handle_responses_non_stream(ctx, responses_payload, url, headers, turn)
return _handle_responses_stream(ctx, responses_payload, url, headers, turn, request_started_at)
return _handle_responses_non_stream(ctx, responses_payload, url, headers, turn, request_started_at)
def _handle_responses_non_stream(
@ -336,6 +378,7 @@ def _handle_responses_non_stream(
url: str,
headers: dict[str, str],
turn: dict[str, Any] | None,
request_started_at: float,
):
"""处理原生 Responses 后端的非流式返回。"""
payload['stream'] = False
@ -350,9 +393,15 @@ 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')
return _finalize_chat_response(
ctx,
data,
turn=turn,
debug_label='Responses 转回聊天补全后',
request_started_at=request_started_at,
upstream_url=url,
)
def _handle_responses_stream(
@ -361,6 +410,7 @@ def _handle_responses_stream(
url: str,
headers: dict[str, str],
turn: dict[str, Any] | None,
request_started_at: float,
):
"""处理原生 Responses 后端的流式返回。"""
payload['stream'] = True
@ -389,10 +439,6 @@ 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='
@ -428,12 +474,28 @@ def _handle_responses_stream(
'chunk_count': len(client_chunks),
'usage': last_usage,
})
finalize_turn(turn, usage=last_usage)
duration_ms = int((perf_counter() - request_started_at) * 1000)
request_history.record(
route='chat',
client_model=ctx.client_model,
actual_model=ctx.upstream_model,
backend=ctx.backend,
upstream_url=url,
usage=last_usage,
duration_ms=duration_ms,
started_at=(turn or {}).get('started_at'),
)
finalize_turn(turn, usage=last_usage, duration_ms=duration_ms)
return sse_response(generate())
def _handle_gemini_backend(ctx: RouteContext, payload: dict[str, Any], turn: dict[str, Any] | None):
def _handle_gemini_backend(
ctx: RouteContext,
payload: dict[str, Any],
turn: dict[str, Any] | None,
request_started_at: float,
):
"""处理走 Gemini Contents 后端的聊天补全请求。"""
payload = inject_instructions_cc(payload, ctx.custom_instructions, ctx.instructions_position)
gemini_payload = cc_to_gemini_request(payload)
@ -447,8 +509,8 @@ def _handle_gemini_backend(ctx: RouteContext, payload: dict[str, Any], turn: dic
headers = apply_header_modifications(headers, ctx.header_modifications)
if ctx.is_stream:
return _handle_gemini_stream(ctx, gemini_payload, url, headers, turn)
return _handle_gemini_non_stream(ctx, gemini_payload, url, headers, turn)
return _handle_gemini_stream(ctx, gemini_payload, url, headers, turn, request_started_at)
return _handle_gemini_non_stream(ctx, gemini_payload, url, headers, turn, request_started_at)
def _handle_gemini_non_stream(
@ -457,6 +519,7 @@ def _handle_gemini_non_stream(
url: str,
headers: dict[str, str],
turn: dict[str, Any] | None,
request_started_at: float,
):
"""处理 Gemini 后端的非流式返回。"""
attach_upstream_request(turn, payload, headers)
@ -471,7 +534,14 @@ def _handle_gemini_non_stream(
_dbg('上游原始响应=' + json.dumps(raw, ensure_ascii=False, default=str)[:1000])
data = gemini_to_cc_response(raw)
return _finalize_chat_response(ctx, data, turn=turn, debug_label='Gemini 转回聊天补全后')
return _finalize_chat_response(
ctx,
data,
turn=turn,
debug_label='Gemini 转回聊天补全后',
request_started_at=request_started_at,
upstream_url=url,
)
def _handle_gemini_stream(
@ -480,6 +550,7 @@ def _handle_gemini_stream(
url: str,
headers: dict[str, str],
turn: dict[str, Any] | None,
request_started_at: float,
):
"""处理 Gemini 后端的流式返回。"""
converter = GeminiStreamConverter()
@ -542,12 +613,28 @@ def _handle_gemini_stream(
'chunk_count': len(client_chunks),
'usage': last_usage,
})
finalize_turn(turn, usage=last_usage)
duration_ms = int((perf_counter() - request_started_at) * 1000)
request_history.record(
route='chat',
client_model=ctx.client_model,
actual_model=ctx.upstream_model,
backend=ctx.backend,
upstream_url=url,
usage=last_usage,
duration_ms=duration_ms,
started_at=(turn or {}).get('started_at'),
)
finalize_turn(turn, usage=last_usage, duration_ms=duration_ms)
return sse_response(generate())
def _handle_anthropic_backend(ctx: RouteContext, payload: dict[str, Any], turn: dict[str, Any] | None):
def _handle_anthropic_backend(
ctx: RouteContext,
payload: dict[str, Any],
turn: dict[str, Any] | None,
request_started_at: float,
):
"""处理走 Anthropic Messages 后端的聊天补全请求。"""
payload['model'] = ctx.upstream_model
anthropic_payload = cc_to_messages_request(payload)
@ -562,8 +649,8 @@ def _handle_anthropic_backend(ctx: RouteContext, payload: dict[str, Any], turn:
headers = apply_header_modifications(headers, ctx.header_modifications)
if ctx.is_stream:
return _handle_anthropic_stream(ctx, anthropic_payload, url, headers, turn)
return _handle_anthropic_non_stream(ctx, anthropic_payload, url, headers, turn)
return _handle_anthropic_stream(ctx, anthropic_payload, url, headers, turn, request_started_at)
return _handle_anthropic_non_stream(ctx, anthropic_payload, url, headers, turn, request_started_at)
def _handle_anthropic_non_stream(
@ -572,6 +659,7 @@ def _handle_anthropic_non_stream(
url: str,
headers: dict[str, str],
turn: dict[str, Any] | None,
request_started_at: float,
):
"""处理 Anthropic 后端的非流式返回。"""
payload['stream'] = False
@ -587,7 +675,14 @@ def _handle_anthropic_non_stream(
_dbg('上游原始响应=' + json.dumps(raw, ensure_ascii=False, default=str)[:1000])
data = messages_to_cc_response(raw)
return _finalize_chat_response(ctx, data, turn=turn, debug_label='Messages 转回聊天补全后')
return _finalize_chat_response(
ctx,
data,
turn=turn,
debug_label='Messages 转回聊天补全后',
request_started_at=request_started_at,
upstream_url=url,
)
def _handle_anthropic_stream(
@ -596,6 +691,7 @@ def _handle_anthropic_stream(
url: str,
headers: dict[str, str],
turn: dict[str, Any] | None,
request_started_at: float,
):
"""处理 Anthropic 后端的流式返回。
@ -680,7 +776,18 @@ def _handle_anthropic_stream(
'chunk_count': len(client_chunks),
'usage': last_usage,
})
finalize_turn(turn, usage=last_usage)
duration_ms = int((perf_counter() - request_started_at) * 1000)
request_history.record(
route='chat',
client_model=ctx.client_model,
actual_model=ctx.upstream_model,
backend=ctx.backend,
upstream_url=url,
usage=last_usage,
duration_ms=duration_ms,
started_at=(turn or {}).get('started_at'),
)
finalize_turn(turn, usage=last_usage, duration_ms=duration_ms)
return sse_response(generate())
@ -691,6 +798,8 @@ def _finalize_chat_response(
*,
turn: dict[str, Any] | None,
debug_label: str,
request_started_at: float,
upstream_url: str,
):
"""统一收尾非流式聊天补全响应。
@ -703,9 +812,21 @@ def _finalize_chat_response(
_dbg(debug_label + '=' + json.dumps(data, ensure_ascii=False, default=str)[:1000])
log_usage('聊天补全', data.get('usage', {}), input_key='prompt_tokens', output_key='completion_tokens')
usage_tracker.record(ctx.client_model, data.get('usage'))
usage = data.get('usage')
duration_ms = int((perf_counter() - request_started_at) * 1000)
usage_tracker.record(ctx.client_model, usage)
request_history.record(
route='chat',
client_model=ctx.client_model,
actual_model=ctx.upstream_model,
backend=ctx.backend,
upstream_url=upstream_url,
usage=usage,
duration_ms=duration_ms,
started_at=(turn or {}).get('started_at'),
)
attach_client_response(turn, data)
finalize_turn(turn, usage=data.get('usage'))
finalize_turn(turn, usage=usage, duration_ms=duration_ms)
for choice in data.get('choices', []):
msg = choice.get('message', {})

View file

@ -10,8 +10,6 @@ from dataclasses import dataclass
import hashlib
import json
import logging
import threading
import time
from typing import Any
import settings
@ -19,10 +17,6 @@ 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 +196,6 @@ 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
"""
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)。
@ -397,6 +219,23 @@ def inject_instructions_anthropic(payload: dict[str, Any], instructions: str, po
# ─── Body / Header 修改 ──────────────────────────
def ensure_prompt_cache_key(payload: dict[str, Any]) -> dict[str, Any]:
"""确保 Responses 请求携带 prompt_cache_key 以启用上游提示缓存。
上游 sub2api对原生 /v1/responses 请求不会自动生成 prompt_cache_key
导致提示缓存无法命中这里根据模型名 + instructions 生成稳定的 cache key
使得相同模型和系统提示的对话可以共享缓存前缀
"""
if payload.get('prompt_cache_key'):
return payload
model = payload.get('model', '')
instructions = payload.get('instructions', '')
seed = f'{model}|{instructions}'
payload['prompt_cache_key'] = hashlib.sha256(seed.encode()).hexdigest()[:32]
return payload
def apply_body_modifications(payload: dict[str, Any], modifications: dict[str, Any]) -> dict[str, Any]:
"""对转发请求体应用字段级修改。

View file

@ -7,6 +7,7 @@ Anthropic Messages API 透传。当 Cursor 直接发送 Anthropic 格式请求
import json
import logging
from time import perf_counter
import requests as req_lib
from flask import Blueprint, request, jsonify
@ -15,6 +16,7 @@ import settings
from config import Config
from routes.common import apply_body_modifications, apply_header_modifications, inject_instructions_anthropic
from utils.http import build_anthropic_headers, forward_request, sse_response
from utils.request_history import request_history
from utils.request_logger import (
append_client_event,
append_upstream_event,
@ -40,6 +42,7 @@ def messages_passthrough():
model = payload.get('model', 'unknown')
is_stream = payload.get('stream', False)
request_started_at = perf_counter()
logger.info(f'[透传] model={model} 流式={is_stream}')
mapping = settings.resolve_model(model)
@ -78,7 +81,18 @@ def messages_passthrough():
attach_upstream_response(turn, data)
_inject_thinking(data)
attach_client_response(turn, data)
finalize_turn(turn)
duration_ms = int((perf_counter() - request_started_at) * 1000)
request_history.record(
route='messages',
client_model=model,
actual_model=model,
backend='anthropic',
upstream_url=url,
usage=data.get('usage'),
duration_ms=duration_ms,
started_at=(turn or {}).get('started_at'),
)
finalize_turn(turn, usage=data.get('usage'), duration_ms=duration_ms)
return jsonify(data)
def generate():
@ -108,7 +122,18 @@ def messages_passthrough():
'type': 'messages.stream.summary',
'event_count': len(client_events),
})
finalize_turn(turn)
duration_ms = int((perf_counter() - request_started_at) * 1000)
request_history.record(
route='messages',
client_model=model,
actual_model=model,
backend='anthropic',
upstream_url=url,
usage=None,
duration_ms=duration_ms,
started_at=(turn or {}).get('started_at'),
)
finalize_turn(turn, duration_ms=duration_ms)
except req_lib.RequestException as e:
logger.error(f'请求上游失败: {e}')
attach_error(turn, {'stage': 'request_exception', 'message': str(e)})

View file

@ -8,6 +8,7 @@ from __future__ import annotations
import json
import logging
from time import perf_counter
from typing import Any
import settings
@ -27,9 +28,7 @@ from routes.common import (
build_openai_target,
build_responses_target,
build_route_context,
ensure_responses_cache_control,
attach_previous_response_id,
remember_response_id,
ensure_prompt_cache_key,
inject_instructions_anthropic,
inject_instructions_cc,
inject_instructions_responses,
@ -46,6 +45,7 @@ from utils.http import (
iter_responses_sse,
sse_response,
)
from utils.request_history import request_history
from utils.request_logger import (
append_client_event,
append_upstream_event,
@ -80,6 +80,7 @@ def responses_endpoint():
client_model = payload.get('model', 'unknown')
is_stream = payload.get('stream', False)
request_started_at = perf_counter()
ctx = build_route_context(client_model, is_stream)
turn = start_turn(
route='responses',
@ -96,12 +97,12 @@ def responses_endpoint():
cc_payload = _build_cc_payload(payload, ctx)
if ctx.backend == 'openai':
return _handle_openai_backend(ctx, cc_payload, turn)
return _handle_openai_backend(ctx, cc_payload, turn, request_started_at)
if ctx.backend == 'responses':
return _handle_responses_backend(ctx, payload, turn)
return _handle_responses_backend(ctx, payload, turn, request_started_at)
if ctx.backend == 'gemini':
return _handle_gemini_backend(ctx, cc_payload, turn)
return _handle_anthropic_backend(ctx, cc_payload, turn)
return _handle_gemini_backend(ctx, cc_payload, turn, request_started_at)
return _handle_anthropic_backend(ctx, cc_payload, turn, request_started_at)
def _build_cc_payload(payload: dict[str, Any], ctx: RouteContext) -> dict[str, Any]:
@ -121,7 +122,12 @@ def _build_cc_payload(payload: dict[str, Any], ctx: RouteContext) -> dict[str, A
return cc_payload
def _handle_openai_backend(ctx: RouteContext, cc_payload: dict[str, Any], turn: dict[str, Any]):
def _handle_openai_backend(
ctx: RouteContext,
cc_payload: dict[str, Any],
turn: dict[str, Any],
request_started_at: float,
):
"""处理走 OpenAI 兼容后端的 Responses 请求。"""
cc_payload = normalize_request(cc_payload)
_dbg(
@ -134,8 +140,8 @@ def _handle_openai_backend(ctx: RouteContext, cc_payload: dict[str, Any], turn:
headers = apply_header_modifications(headers, ctx.header_modifications)
if ctx.is_stream:
return _handle_openai_stream(ctx, cc_payload, url, headers, turn)
return _handle_openai_non_stream(ctx, cc_payload, url, headers, turn)
return _handle_openai_stream(ctx, cc_payload, url, headers, turn, request_started_at)
return _handle_openai_non_stream(ctx, cc_payload, url, headers, turn, request_started_at)
def _handle_openai_non_stream(
@ -144,6 +150,7 @@ def _handle_openai_non_stream(
url: str,
headers: dict[str, str],
turn: dict[str, Any],
request_started_at: float,
):
"""处理 OpenAI 兼容后端的非流式 Responses 返回。"""
cc_payload['stream'] = False
@ -165,6 +172,9 @@ def _handle_openai_non_stream(
client_model=ctx.client_model,
turn=turn,
debug_label='转换为 Responses 后',
ctx=ctx,
request_started_at=request_started_at,
upstream_url=url,
)
@ -174,6 +184,7 @@ def _handle_openai_stream(
url: str,
headers: dict[str, str],
turn: dict[str, Any] | None,
request_started_at: float,
):
"""处理 OpenAI 兼容后端的流式 Responses 返回。"""
cc_payload['stream'] = True
@ -214,7 +225,18 @@ def _handle_openai_stream(
'model': ctx.client_model,
'event_count': len(client_events),
})
finalize_turn(turn)
duration_ms = int((perf_counter() - request_started_at) * 1000)
request_history.record(
route='responses',
client_model=ctx.client_model,
actual_model=ctx.upstream_model,
backend=ctx.backend,
upstream_url=url,
usage=None,
duration_ms=duration_ms,
started_at=(turn or {}).get('started_at'),
)
finalize_turn(turn, duration_ms=duration_ms)
return
append_upstream_event(turn, {'type': 'openai_chunk', 'data': chunk})
@ -241,7 +263,12 @@ def _handle_openai_stream(
return sse_response(generate())
def _handle_responses_backend(ctx: RouteContext, payload: dict[str, Any], turn: dict[str, Any] | None):
def _handle_responses_backend(
ctx: RouteContext,
payload: dict[str, Any],
turn: dict[str, Any] | None,
request_started_at: float,
):
"""处理走原生 Responses 后端的请求。
当中转站本身就只支持 `/v1/responses` 不需要再绕到聊天补全中间协议
@ -250,15 +277,14 @@ 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)
payload = ensure_prompt_cache_key(payload)
url, headers = build_responses_target(ctx)
payload = apply_body_modifications(payload, ctx.body_modifications)
headers = apply_header_modifications(headers, ctx.header_modifications)
if ctx.is_stream:
return _handle_responses_stream(ctx, payload, url, headers, turn)
return _handle_responses_non_stream(ctx, payload, url, headers, turn)
return _handle_responses_stream(ctx, payload, url, headers, turn, request_started_at)
return _handle_responses_non_stream(ctx, payload, url, headers, turn, request_started_at)
def _handle_responses_non_stream(
@ -267,6 +293,7 @@ def _handle_responses_non_stream(
url: str,
headers: dict[str, str],
turn: dict[str, Any] | None,
request_started_at: float,
):
"""处理原生 Responses 后端的非流式返回。"""
payload['stream'] = False
@ -279,13 +306,15 @@ 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,
client_model=ctx.client_model,
turn=turn,
debug_label='原生 Responses 返回后',
ctx=ctx,
request_started_at=request_started_at,
upstream_url=url,
)
@ -295,6 +324,7 @@ def _handle_responses_stream(
url: str,
headers: dict[str, str],
turn: dict[str, Any] | None,
request_started_at: float,
):
"""处理原生 Responses 后端的流式返回。"""
payload['stream'] = True
@ -319,10 +349,6 @@ 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='
@ -353,7 +379,18 @@ def _handle_responses_stream(
'event_count': len(client_events),
'usage': last_usage,
})
finalize_turn(turn, usage=last_usage)
duration_ms = int((perf_counter() - request_started_at) * 1000)
request_history.record(
route='responses',
client_model=ctx.client_model,
actual_model=ctx.upstream_model,
backend=ctx.backend,
upstream_url=url,
usage=last_usage,
duration_ms=duration_ms,
started_at=(turn or {}).get('started_at'),
)
finalize_turn(turn, usage=last_usage, duration_ms=duration_ms)
return sse_response(generate())
@ -377,7 +414,12 @@ def _extract_responses_usage(event_data: dict[str, Any]) -> dict[str, Any] | Non
return None
def _handle_gemini_backend(ctx: RouteContext, cc_payload: dict[str, Any], turn: dict[str, Any] | None):
def _handle_gemini_backend(
ctx: RouteContext,
cc_payload: dict[str, Any],
turn: dict[str, Any] | None,
request_started_at: float,
):
"""处理走 Gemini Contents 后端的 Responses 请求。"""
gemini_payload = cc_to_gemini_request(cc_payload)
_dbg(
@ -390,8 +432,8 @@ def _handle_gemini_backend(ctx: RouteContext, cc_payload: dict[str, Any], turn:
headers = apply_header_modifications(headers, ctx.header_modifications)
if ctx.is_stream:
return _handle_gemini_stream(ctx, gemini_payload, url, headers, turn)
return _handle_gemini_non_stream(ctx, gemini_payload, url, headers, turn)
return _handle_gemini_stream(ctx, gemini_payload, url, headers, turn, request_started_at)
return _handle_gemini_non_stream(ctx, gemini_payload, url, headers, turn, request_started_at)
def _handle_gemini_non_stream(
@ -400,6 +442,7 @@ def _handle_gemini_non_stream(
url: str,
headers: dict[str, str],
turn: dict[str, Any] | None,
request_started_at: float,
):
"""处理 Gemini 后端的非流式 Responses 返回。"""
attach_upstream_request(turn, payload, headers)
@ -420,6 +463,9 @@ def _handle_gemini_non_stream(
client_model=ctx.client_model,
turn=turn,
debug_label='Gemini 转回 Responses 后',
ctx=ctx,
request_started_at=request_started_at,
upstream_url=url,
)
@ -429,6 +475,7 @@ def _handle_gemini_stream(
url: str,
headers: dict[str, str],
turn: dict[str, Any] | None,
request_started_at: float,
):
"""处理 Gemini 后端的流式 Responses 返回。"""
converter = ResponsesStreamConverter(model=ctx.client_model)
@ -495,12 +542,28 @@ def _handle_gemini_stream(
'event_count': len(client_events),
'usage': last_usage,
})
finalize_turn(turn, usage=last_usage)
duration_ms = int((perf_counter() - request_started_at) * 1000)
request_history.record(
route='responses',
client_model=ctx.client_model,
actual_model=ctx.upstream_model,
backend=ctx.backend,
upstream_url=url,
usage=last_usage,
duration_ms=duration_ms,
started_at=(turn or {}).get('started_at'),
)
finalize_turn(turn, usage=last_usage, duration_ms=duration_ms)
return sse_response(generate())
def _handle_anthropic_backend(ctx: RouteContext, cc_payload: dict[str, Any], turn: dict[str, Any] | None):
def _handle_anthropic_backend(
ctx: RouteContext,
cc_payload: dict[str, Any],
turn: dict[str, Any] | None,
request_started_at: float,
):
"""处理走 Anthropic 后端的 Responses 请求。"""
anthropic_payload = cc_to_messages_request(cc_payload)
_dbg(
@ -513,8 +576,8 @@ def _handle_anthropic_backend(ctx: RouteContext, cc_payload: dict[str, Any], tur
headers = apply_header_modifications(headers, ctx.header_modifications)
if ctx.is_stream:
return _handle_anthropic_stream(ctx, anthropic_payload, url, headers, turn)
return _handle_anthropic_non_stream(ctx, anthropic_payload, url, headers, turn)
return _handle_anthropic_stream(ctx, anthropic_payload, url, headers, turn, request_started_at)
return _handle_anthropic_non_stream(ctx, anthropic_payload, url, headers, turn, request_started_at)
def _handle_anthropic_non_stream(
@ -523,6 +586,7 @@ def _handle_anthropic_non_stream(
url: str,
headers: dict[str, str],
turn: dict[str, Any] | None,
request_started_at: float,
):
"""处理 Anthropic 后端的非流式 Responses 返回。"""
anthropic_payload['stream'] = False
@ -544,6 +608,9 @@ def _handle_anthropic_non_stream(
client_model=ctx.client_model,
turn=turn,
debug_label='Messages 转回 Responses 后',
ctx=ctx,
request_started_at=request_started_at,
upstream_url=url,
)
@ -553,6 +620,7 @@ def _handle_anthropic_stream(
url: str,
headers: dict[str, str],
turn: dict[str, Any] | None,
request_started_at: float,
):
"""处理 Anthropic 后端的流式 Responses 返回。
@ -608,7 +676,18 @@ def _handle_anthropic_stream(
'model': ctx.client_model,
'event_count': len(client_events),
})
finalize_turn(turn)
duration_ms = int((perf_counter() - request_started_at) * 1000)
request_history.record(
route='responses',
client_model=ctx.client_model,
actual_model=ctx.upstream_model,
backend=ctx.backend,
upstream_url=url,
usage=None,
duration_ms=duration_ms,
started_at=(turn or {}).get('started_at'),
)
finalize_turn(turn, duration_ms=duration_ms)
return sse_response(generate())
@ -619,6 +698,9 @@ def _finalize_responses_response(
client_model: str,
turn: dict[str, Any],
debug_label: str,
ctx: RouteContext,
request_started_at: float,
upstream_url: str,
):
"""统一收尾非流式 Responses 响应。
@ -629,32 +711,26 @@ def _finalize_responses_response(
_dbg(debug_label + '=' + json.dumps(response_data, ensure_ascii=False, default=str)[:1000])
log_usage('响应生成', response_data.get('usage', {}), input_key='input_tokens', output_key='output_tokens')
usage = response_data.get('usage')
duration_ms = int((perf_counter() - request_started_at) * 1000)
usage_tracker.record(
client_model,
response_data.get('usage'),
usage,
input_key='input_tokens',
output_key='output_tokens',
)
request_history.record(
route='responses',
client_model=client_model,
actual_model=ctx.upstream_model,
backend=ctx.backend,
upstream_url=upstream_url,
usage=usage,
duration_ms=duration_ms,
started_at=(turn or {}).get('started_at'),
)
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
finalize_turn(turn, usage=usage, duration_ms=duration_ms)
return jsonify(response_data)

View file

@ -9,7 +9,7 @@ body{font-family:-apple-system,BlinkMacSystemFont,'Segoe UI','PingFang SC','Micr
input,select,button,textarea{font-family:inherit;font-size:inherit}
a{color:var(--primary);text-decoration:none}
code{background:var(--input);padding:1px 5px;border-radius:4px;font-size:12px;font-family:Consolas,Monaco,monospace}
.container{max-width:960px;margin:0 auto;padding:0 20px}
.container{width:min(100%,1680px);margin:0 auto;padding:0 20px}
#login{display:flex;align-items:center;justify-content:center;min-height:100vh;background:linear-gradient(145deg,#0b1120 0%,#121a2e 50%,#0b1120 100%)}
.login-card{background:var(--card);border:1px solid var(--border);border-radius:16px;padding:40px;width:380px;box-shadow:0 20px 60px rgba(0,0,0,.4)}
@ -83,3 +83,11 @@ main{padding:28px 0 60px}
.toast-ok{background:#065f46;color:#a7f3d0}
.toast-err{background:#7f1d1d;color:#fca5a5}
@keyframes slideIn{from{transform:translateX(100px);opacity:0}to{transform:none;opacity:1}}
.request-logs-wrap{overflow:auto}
.request-logs-table{min-width:1100px}
.request-logs-table td{vertical-align:top}
.log-url{max-width:320px;word-break:break-all;color:var(--muted)}
.log-status{display:inline-flex;align-items:center;padding:2px 8px;border-radius:999px;font-size:12px;font-weight:600}
.status-ok{background:rgba(34,197,94,.15);color:var(--green)}
.status-error{background:rgba(239,68,68,.15);color:var(--red)}

View file

@ -4,7 +4,7 @@
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>API 2 Cursor - 管理面板</title>
<link rel="stylesheet" href="/static/admin.css">
<link rel="stylesheet" href="/static/admin.css?v=20260505-2">
</head>
<body>
@ -90,6 +90,16 @@
</div>
<div id="statsContent"><div class="empty">加载中…</div></div>
</div>
<!-- 请求日志 -->
<div class="card">
<div class="card-header">
<h2>最近 500 条请求日志</h2>
<button class="btn btn-ghost btn-sm" onclick="loadRequestLogs()">刷新</button>
</div>
<div class="hint" style="margin-top:-12px;margin-bottom:16px">显示请求时间、请求模型、实际上游模型、上游 URL、Token 统计、耗时和状态。</div>
<div id="requestLogsContent"><div class="empty">加载中…</div></div>
</div>
</main>
</div>
@ -180,6 +190,6 @@
<div class="toast-area" id="toasts"></div>
<script src="/static/admin.js"></script>
<script src="/static/admin.js?v=20260505-2"></script>
</body>
</html>

View file

@ -72,6 +72,7 @@ async function loadDashboard() {
await loadMappings();
checkHealth();
loadStats();
loadRequestLogs();
} catch (e) {
toast('加载设置失败: ' + e.message, false);
}
@ -104,6 +105,58 @@ async function loadStats() {
}
}
async function loadRequestLogs() {
const el = document.getElementById('requestLogsContent');
try {
const data = await api('/api/admin/request-logs');
const items = data.items || [];
if (!items.length) {
el.innerHTML = '<div class="empty">暂无请求日志</div>';
return;
}
let html = '<div class="request-logs-wrap"><table class="stats-table request-logs-table"><thead><tr><th>请求时间</th><th>请求模型</th><th>实际模型</th><th>上游 URL</th><th>Tokens</th><th>耗时</th><th>状态</th></tr></thead><tbody>';
for (const item of items) {
const usage = item.usage || {};
let tokens = '输 ' + fmtNum(usage.input_tokens) + ' / 出 ' + fmtNum(usage.output_tokens) + ' / 总 ' + fmtNum(usage.total_tokens);
if (Number(usage.cache_read_tokens || 0) > 0 || Number(usage.cache_write_tokens || 0) > 0) {
tokens += ' / 缓存读 ' + fmtNum(usage.cache_read_tokens) + ' / 缓存写 ' + fmtNum(usage.cache_write_tokens);
}
const statusClass = item.status === 'ok' ? 'status-ok' : 'status-error';
const statusText = item.status === 'ok' ? '成功' : '异常';
html += '<tr>'
+ '<td>' + esc(fmtTime(item.requested_at)) + '</td>'
+ '<td>' + esc(item.requested_model || '-') + '</td>'
+ '<td>' + esc(item.actual_model || '-') + '</td>'
+ '<td class="log-url" title="' + esc(item.upstream_url || '') + '">' + esc(item.upstream_url || '-') + '</td>'
+ '<td>' + esc(tokens) + '</td>'
+ '<td>' + fmtNum(item.duration_ms) + ' ms</td>'
+ '<td><span class="log-status ' + statusClass + '">' + statusText + '</span></td>'
+ '</tr>';
}
html += '</tbody></table></div>';
el.innerHTML = html;
} catch (e) {
el.innerHTML = '<div class="empty">加载请求日志失败</div>';
}
}
function fmtNum(value) {
return Number(value || 0).toLocaleString();
}
function fmtTime(value) {
if (!value) return '-';
const d = new Date(value);
if (Number.isNaN(d.getTime())) return String(value);
const pad = n => String(n).padStart(2, '0');
return d.getFullYear() + '-'
+ pad(d.getMonth() + 1) + '-'
+ pad(d.getDate()) + ' '
+ pad(d.getHours()) + ':'
+ pad(d.getMinutes()) + ':'
+ pad(d.getSeconds());
}
async function checkHealth() {
try {
const r = await fetch(API + '/health');

125
utils/request_history.py Normal file
View file

@ -0,0 +1,125 @@
"""请求历史记录。
为管理后台提供最近请求查询能力默认仅保留最近 500
重启后会从磁盘恢复最近一次快照
"""
from __future__ import annotations
import json
import os
import threading
from collections import deque
from datetime import datetime, timezone
from typing import Any
from settings import DATA_DIR
_MAX_RECORDS = 500
_FILE_PATH = os.path.join(DATA_DIR, 'request_logs.json')
def _now_iso() -> str:
return datetime.now(timezone.utc).isoformat().replace('+00:00', 'Z')
def _safe_int(value: Any) -> int:
try:
return int(value or 0)
except (TypeError, ValueError):
return 0
def _normalize_usage(usage: dict[str, Any] | None) -> dict[str, int]:
usage = usage or {}
input_tokens = _safe_int(
usage.get('prompt_tokens', usage.get('input_tokens', 0))
)
output_tokens = _safe_int(
usage.get('completion_tokens', usage.get('output_tokens', 0))
)
total_tokens = _safe_int(usage.get('total_tokens', input_tokens + output_tokens))
prompt_details = usage.get('prompt_tokens_details')
input_details = usage.get('input_tokens_details')
cache_read_tokens = _safe_int(usage.get('cache_read_input_tokens', 0))
cache_write_tokens = _safe_int(usage.get('cache_creation_input_tokens', 0))
if isinstance(prompt_details, dict):
cache_read_tokens = max(cache_read_tokens, _safe_int(prompt_details.get('cached_tokens', 0)))
if isinstance(input_details, dict):
cache_read_tokens = max(cache_read_tokens, _safe_int(input_details.get('cached_tokens', 0)))
return {
'input_tokens': input_tokens,
'output_tokens': output_tokens,
'total_tokens': total_tokens,
'cache_read_tokens': cache_read_tokens,
'cache_write_tokens': cache_write_tokens,
}
class RequestHistory:
def __init__(self) -> None:
self._lock = threading.Lock()
self._records: deque[dict[str, Any]] = deque(maxlen=_MAX_RECORDS)
self._load()
def record(
self,
*,
route: str,
client_model: str,
actual_model: str,
backend: str,
upstream_url: str,
usage: dict[str, Any] | None,
duration_ms: int,
started_at: str | None = None,
status: str = 'ok',
error_message: str = '',
) -> None:
record = {
'requested_at': started_at or _now_iso(),
'route': route,
'requested_model': client_model or '',
'actual_model': actual_model or '',
'backend': backend or '',
'upstream_url': upstream_url or '',
'duration_ms': max(_safe_int(duration_ms), 0),
'status': status or 'ok',
'error_message': error_message or '',
'usage': _normalize_usage(usage),
'recorded_at': _now_iso(),
}
with self._lock:
self._records.appendleft(record)
self._persist_locked()
def get_recent(self, limit: int = _MAX_RECORDS) -> list[dict[str, Any]]:
size = max(1, min(_safe_int(limit), _MAX_RECORDS))
with self._lock:
return list(self._records)[:size]
def _load(self) -> None:
if not os.path.exists(_FILE_PATH):
return
try:
with open(_FILE_PATH, 'r', encoding='utf-8') as f:
data = json.load(f)
if not isinstance(data, list):
return
for item in data[:_MAX_RECORDS]:
if isinstance(item, dict):
self._records.append(item)
except (OSError, json.JSONDecodeError):
self._records.clear()
def _persist_locked(self) -> None:
os.makedirs(DATA_DIR, exist_ok=True)
with open(_FILE_PATH, 'w', encoding='utf-8') as f:
json.dump(list(self._records), f, ensure_ascii=False, indent=2)
request_history = RequestHistory()