268 lines
9.5 KiB
Python
268 lines
9.5 KiB
Python
"""路由层公共辅助
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收敛多个数据面路由都会用到的上下文解析、上游目标构造、日志输出和
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SSE 消息拼装逻辑，避免 `chat.py` 和 `responses.py` 各自维护重复实现。
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"""
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from __future__ import annotations
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from dataclasses import dataclass
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import hashlib
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import json
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import logging
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from typing import Any
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import settings
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from utils.http import build_anthropic_headers, build_gemini_headers, build_openai_headers
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logger = logging.getLogger(__name__)
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@dataclass(frozen=True)
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class RouteContext:
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"""数据面路由使用的标准请求上下文。
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路由层会先根据客户端模型名解析出统一上下文，后续处理函数只需要关心
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上游模型、后端类型、目标地址、鉴权信息、流式标记和自定义指令，
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而不必重复访问配置层。
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"""
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client_model: str
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upstream_model: str
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backend: str
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target_url: str
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api_key: str
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is_stream: bool
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custom_instructions: str
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instructions_position: str
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body_modifications: dict
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header_modifications: dict
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def build_route_context(client_model: str, is_stream: bool) -> RouteContext:
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"""解析模型映射，得到当前请求的统一路由上下文。"""
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mapping = settings.resolve_model(client_model)
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return RouteContext(
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client_model=client_model,
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upstream_model=mapping['upstream_model'],
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backend=mapping['backend'],
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target_url=mapping['target_url'],
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api_key=mapping['api_key'],
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is_stream=is_stream,
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custom_instructions=mapping.get('custom_instructions', ''),
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instructions_position=mapping.get('instructions_position', 'prepend'),
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body_modifications=mapping.get('body_modifications', {}),
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header_modifications=mapping.get('header_modifications', {}),
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)
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def build_openai_target(ctx: RouteContext) -> tuple[str, dict[str, str]]:
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"""根据路由上下文生成 OpenAI 兼容后端的地址和请求头。"""
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url = f'{ctx.target_url.rstrip("/")}/v1/chat/completions'
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headers = build_openai_headers(ctx.api_key)
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return url, headers
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def build_responses_target(ctx: RouteContext) -> tuple[str, dict[str, str]]:
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"""根据路由上下文生成 OpenAI Responses 后端的地址和请求头。"""
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url = f'{ctx.target_url.rstrip("/")}/v1/responses'
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headers = build_openai_headers(ctx.api_key)
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return url, headers
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def build_anthropic_target(ctx: RouteContext) -> tuple[str, dict[str, str]]:
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"""根据路由上下文生成 Anthropic 后端的地址和请求头。"""
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url = f'{ctx.target_url.rstrip("/")}/v1/messages'
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headers = build_anthropic_headers(ctx.api_key)
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return url, headers
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def build_gemini_target(ctx: RouteContext, stream: bool = False) -> tuple[str, dict[str, str]]:
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"""根据路由上下文生成 Gemini 后端的地址和请求头。
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Gemini URL 格式: {base}/v1/models/{model}:generateContent
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流式: {base}/v1/models/{model}:streamGenerateContent?alt=sse
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"""
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base = ctx.target_url.rstrip('/')
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model = ctx.upstream_model
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if stream:
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url = f'{base}/v1/models/{model}:streamGenerateContent?alt=sse'
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else:
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url = f'{base}/v1/models/{model}:generateContent'
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headers = build_gemini_headers(ctx.api_key)
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return url, headers
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def log_route_context(route_name: str, ctx: RouteContext, *, extra: str = '') -> None:
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"""统一输出路由级日志，避免不同入口的日志格式逐渐漂移。"""
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parts = [
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f'[{route_name}]',
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f'模型={ctx.client_model}',
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f'上游模型={ctx.upstream_model}',
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f'后端={ctx.backend}',
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f'流式={ctx.is_stream}',
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]
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if extra:
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parts.append(extra)
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logger.info(' '.join(parts))
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def log_usage(
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route_name: str,
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usage: dict[str, Any],
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*,
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input_key: str,
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output_key: str,
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) -> None:
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"""统一输出令牌统计日志。
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不同协议对 usage 字段命名不一致，这里只接收字段名，不在调用方重复拼接日志文案。
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"""
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logger.info(
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'[%s] 请求完成 输入令牌=%s 输出令牌=%s',
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route_name,
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usage.get(input_key, 0),
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usage.get(output_key, 0),
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)
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def sse_data_message(data: Any) -> str:
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"""构造仅包含 data 的 SSE 消息。"""
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payload = data if isinstance(data, str) else json.dumps(data, ensure_ascii=False)
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return f'data: {payload}\n\n'
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def sse_event_message(event_type: str, data: Any) -> str:
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"""构造带 event 名称的 SSE 消息。"""
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payload = data if isinstance(data, str) else json.dumps(data, ensure_ascii=False)
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return f'event: {event_type}\ndata: {payload}\n\n'
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def chat_error_chunk(message: str, error_type: str = 'upstream_error') -> str:
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"""构造聊天补全流式接口使用的错误消息。"""
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return sse_data_message({'error': {'message': message, 'type': error_type}})
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def responses_error_event(message: str) -> str:
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"""构造 Responses 流式接口使用的错误事件。"""
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return sse_event_message('error', {'error': message})
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# ─── 自定义指令注入 ──────────────────────────────
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def _merge_text(custom: str, existing: str, position: str) -> str:
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"""根据 position 决定自定义指令与原有内容的拼接顺序。"""
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if not existing:
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return custom
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if position == 'append':
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return existing + '\n\n' + custom
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return custom + '\n\n' + existing
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def inject_instructions_cc(payload: dict[str, Any], instructions: str, position: str = 'prepend') -> dict[str, Any]:
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"""向 Chat Completions 请求注入自定义指令。
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position='prepend' 时放在 system 消息开头，'append' 时放在末尾。
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"""
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if not instructions:
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return payload
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messages = payload.get('messages', [])
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if messages and messages[0].get('role') == 'system':
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first = messages[0]
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original = first.get('content') or ''
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first['content'] = _merge_text(instructions, original, position)
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else:
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messages.insert(0, {'role': 'system', 'content': instructions})
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payload['messages'] = messages
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logger.info('已注入自定义指令到 CC system 消息 (%d 字符, %s)', len(instructions), position)
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return payload
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def inject_instructions_responses(payload: dict[str, Any], instructions: str, position: str = 'prepend') -> dict[str, Any]:
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"""向 Responses 请求注入自定义指令（写入 instructions 字段）。
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position='prepend' 时放在 instructions 开头，'append' 时放在末尾。
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"""
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if not instructions:
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return payload
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existing = payload.get('instructions') or ''
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payload['instructions'] = _merge_text(instructions, existing, position)
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logger.info('已注入自定义指令到 Responses instructions (%d 字符, %s)', len(instructions), position)
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return payload
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def inject_instructions_anthropic(payload: dict[str, Any], instructions: str, position: str = 'prepend') -> dict[str, Any]:
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"""向 Anthropic Messages 请求注入自定义指令（写入 system 字段）。
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position='prepend' 时放在 system 开头，'append' 时放在末尾。
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"""
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if not instructions:
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return payload
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existing = payload.get('system') or ''
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if isinstance(existing, list):
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existing = '\n'.join(
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block.get('text', '') for block in existing
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if isinstance(block, dict) and block.get('type') == 'text'
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)
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payload['system'] = _merge_text(instructions, existing, position)
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logger.info('已注入自定义指令到 Anthropic system (%d 字符, %s)', len(instructions), position)
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return payload
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# ─── Body / Header 修改 ──────────────────────────
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def ensure_prompt_cache_key(payload: dict[str, Any]) -> dict[str, Any]:
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"""确保 Responses 请求携带 prompt_cache_key 以启用上游提示缓存。
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上游（如 sub2api）对原生 /v1/responses 请求不会自动生成 prompt_cache_key，
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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，
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使得相同模型和系统提示的对话可以共享缓存前缀。
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"""
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if payload.get('prompt_cache_key'):
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return payload
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model = payload.get('model', '')
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instructions = payload.get('instructions', '')
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seed = f'{model}|{instructions}'
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payload['prompt_cache_key'] = hashlib.sha256(seed.encode()).hexdigest()[:32]
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return payload
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def apply_body_modifications(payload: dict[str, Any], modifications: dict[str, Any]) -> dict[str, Any]:
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"""对转发请求体应用字段级修改。
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规则与 CursorProxy 一致：值为 null 的字段会被删除，其余字段设置/覆盖。
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"""
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if not modifications:
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return payload
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for key, value in modifications.items():
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if value is None:
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payload.pop(key, None)
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else:
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payload[key] = value
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logger.info('已应用 body_modifications: %s', list(modifications.keys()))
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return payload
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def apply_header_modifications(headers: dict[str, str], modifications: dict[str, Any]) -> dict[str, str]:
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"""对转发请求头应用字段级修改。
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规则同 body：值为 null 删除，其余设置/覆盖。
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"""
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if not modifications:
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return headers
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for key, value in modifications.items():
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if value is None:
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headers.pop(key, None)
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else:
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headers[key] = str(value)
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logger.info('已应用 header_modifications: %s', list(modifications.keys()))
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return headers
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