ac50cd249a
- Fix thinking visibility by passing user overrides into streaming - Harden UserValves handling for mapping/instance inputs - Update bilingual README with per-user valves and troubleshooting
1555 lines
61 KiB
Python
1555 lines
61 KiB
Python
"""
|
||
title: GitHub Copilot Official SDK Pipe
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||
author: Fu-Jie
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||
author_url: https://github.com/Fu-Jie/awesome-openwebui
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||
funding_url: https://github.com/open-webui
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||
openwebui_id: ce96f7b4-12fc-4ac3-9a01-875713e69359
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||
description: 集成 GitHub Copilot SDK。支持动态模型、多轮对话、流式输出、多模态输入、无限会话及前端调试日志。
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||
version: 0.2.3
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requirements: github-copilot-sdk
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||
"""
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||
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||
import os
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||
import time
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||
import json
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import base64
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||
import tempfile
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||
import asyncio
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||
import logging
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||
import shutil
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import subprocess
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import sys
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||
from typing import Optional, Union, AsyncGenerator, List, Any, Dict
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||
from pydantic import BaseModel, Field
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from datetime import datetime, timezone
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import contextlib
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# 导入 Copilot SDK 模块
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from copilot import CopilotClient, define_tool
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# Setup logger
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logger = logging.getLogger(__name__)
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||
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||
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class RandomNumberParams(BaseModel):
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min: int = Field(description="最小值（包含）")
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||
max: int = Field(description="最大值（包含）")
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||
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||
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||
@define_tool(description="在指定范围内生成随机整数。")
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async def generate_random_number(params: RandomNumberParams) -> str:
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import random
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||
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if params.min >= params.max:
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raise ValueError("min 必须小于 max")
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number = random.randint(params.min, params.max)
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return f"生成的随机数: {number}"
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||
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class Pipe:
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class Valves(BaseModel):
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GH_TOKEN: str = Field(
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default="",
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description="GitHub 细粒度 Token（需要 Copilot Requests 权限）",
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)
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MODEL_ID: str = Field(
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default="gpt-5-mini",
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description="默认 Copilot 模型名（动态获取失败时使用）",
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||
)
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||
CLI_PATH: str = Field(
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||
default="/usr/local/bin/copilot",
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description="Copilot CLI 路径",
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||
)
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||
DEBUG: bool = Field(
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default=False,
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||
description="启用技术调试日志（连接信息等）",
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||
)
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||
LOG_LEVEL: str = Field(
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||
default="error",
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||
description="Copilot CLI 日志级别：none, error, warning, info, debug, all",
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||
)
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||
SHOW_THINKING: bool = Field(
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||
default=True,
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||
description="显示模型推理/思考过程",
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||
)
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||
SHOW_WORKSPACE_INFO: bool = Field(
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default=True,
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||
description="调试模式下显示会话工作空间路径与摘要",
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||
)
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||
EXCLUDE_KEYWORDS: str = Field(
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||
default="",
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||
description="排除包含这些关键词的模型（逗号分隔，如：codex, haiku）",
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||
)
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WORKSPACE_DIR: str = Field(
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||
default="",
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||
description="文件操作的受限工作区目录；为空则使用当前进程目录",
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||
)
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||
INFINITE_SESSION: bool = Field(
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||
default=True,
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||
description="启用无限会话（自动上下文压缩）",
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||
)
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||
COMPACTION_THRESHOLD: float = Field(
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||
default=0.8,
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||
description="后台压缩阈值 (0.0-1.0)",
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||
)
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||
BUFFER_THRESHOLD: float = Field(
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||
default=0.95,
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||
description="缓冲区耗尽阈值 (0.0-1.0)",
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||
)
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||
TIMEOUT: int = Field(
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||
default=300,
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||
description="每个流式分块超时（秒）",
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||
)
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||
CUSTOM_ENV_VARS: str = Field(
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||
default="",
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||
description='自定义环境变量（JSON 格式，例如 {"VAR": "value"}）',
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||
)
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||
ENABLE_TOOLS: bool = Field(
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||
default=False,
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||
description="启用自定义工具（例如：随机数）",
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||
)
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||
AVAILABLE_TOOLS: str = Field(
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default="all",
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description="可用工具：'all' 或逗号分隔列表（例如：'generate_random_number'）",
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||
)
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||
REASONING_EFFORT: str = Field(
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||
default="medium",
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||
description="推理强度级别: low, medium, high. (gpt-5.2-codex 额外支持 xhigh)",
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||
)
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||
ENFORCE_FORMATTING: bool = Field(
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||
default=True,
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||
description="在系统提示词中添加格式化指导，以提高输出的可读性（段落、换行、结构）。",
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)
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class UserValves(BaseModel):
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REASONING_EFFORT: str = Field(
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default="",
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||
description="推理强度级别 (low, medium, high, xhigh)。留空以使用全局设置。",
|
||
)
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||
CLI_PATH: str = Field(
|
||
default="",
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||
description="自定义 Copilot CLI 路径。留空以使用全局设置。",
|
||
)
|
||
DEBUG: bool = Field(
|
||
default=False,
|
||
description="启用技术调试日志（连接信息等）",
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||
)
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||
SHOW_THINKING: bool = Field(
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||
default=True,
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||
description="显示模型推理/思考过程",
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||
)
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||
MODEL_ID: str = Field(
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||
default="",
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||
description="自定义模型 ID (例如 gpt-4o)。留空以使用全局默认值。",
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||
)
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||
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||
def __init__(self):
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self.type = "pipe"
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self.id = "copilotsdk"
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self.name = "copilotsdk"
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self.valves = self.Valves()
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self.temp_dir = tempfile.mkdtemp(prefix="copilot_images_")
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self.thinking_started = False
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self._model_cache = [] # 模型列表缓存
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||
def __del__(self):
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try:
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shutil.rmtree(self.temp_dir)
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except:
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pass
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# ==================== 系统固定入口 ====================
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# pipe() 是 OpenWebUI 调用的稳定入口。
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# 将该部分放在前面，便于快速定位与维护。
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# ======================================================
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async def pipe(
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self,
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body: dict,
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__metadata__: Optional[dict] = None,
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__user__: Optional[dict] = None,
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__event_emitter__=None,
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||
__event_call__=None,
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) -> Union[str, AsyncGenerator]:
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return await self._pipe_impl(
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body,
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__metadata__=__metadata__,
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__user__=__user__,
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__event_emitter__=__event_emitter__,
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__event_call__=__event_call__,
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)
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# ==================== 功能性分区说明 ====================
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# 1) 工具注册：定义工具并在 _initialize_custom_tools 中注册
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# 2) 调试日志：_emit_debug_log / _emit_debug_log_sync
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# 3) 提示词/会话：_extract_system_prompt / _build_session_config / _build_prompt
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# 4) 运行流程：pipe() 负责请求，stream_response() 负责流式输出
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# ======================================================
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# ==================== 自定义工具示例 ====================
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# 工具注册：在模块级别添加 @define_tool 装饰的函数，
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# 然后在 _initialize_custom_tools() 的 all_tools 字典中注册。
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def _extract_text_from_content(self, content) -> str:
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"""从各种消息内容格式中提取文本内容"""
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if isinstance(content, str):
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return content
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elif isinstance(content, list):
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text_parts = []
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||
for item in content:
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||
if isinstance(item, dict) and item.get("type") == "text":
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text_parts.append(item.get("text", ""))
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return " ".join(text_parts)
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return ""
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||
def _apply_formatting_hint(self, prompt: str) -> str:
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"""在启用格式化时，向用户提示词追加轻量格式化要求。"""
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if not self.valves.ENFORCE_FORMATTING:
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return prompt
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if not prompt:
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return prompt
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if "[格式化指南]" in prompt or "[格式化要求]" in prompt:
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return prompt
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||
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formatting_hint = (
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"\n\n[格式化要求]\n" "请使用清晰的段落与换行，必要时使用项目符号列表。"
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)
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return f"{prompt}{formatting_hint}"
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||
|
||
def _dedupe_preserve_order(self, items: List[str]) -> List[str]:
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||
"""去重保序"""
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||
seen = set()
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||
result = []
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||
for item in items:
|
||
if not item or item in seen:
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||
continue
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||
seen.add(item)
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result.append(item)
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return result
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||
|
||
def _collect_model_ids(
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self, body: dict, request_model: str, real_model_id: str
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) -> List[str]:
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"""收集可能的模型 ID（来自请求/metadata/body params）"""
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model_ids: List[str] = []
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if request_model:
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model_ids.append(request_model)
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if request_model.startswith(f"{self.id}-"):
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model_ids.append(request_model[len(f"{self.id}-") :])
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if real_model_id:
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model_ids.append(real_model_id)
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metadata = body.get("metadata", {})
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if isinstance(metadata, dict):
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meta_model = metadata.get("model")
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meta_model_id = metadata.get("model_id")
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if isinstance(meta_model, str):
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model_ids.append(meta_model)
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if isinstance(meta_model_id, str):
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model_ids.append(meta_model_id)
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||
body_params = body.get("params", {})
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if isinstance(body_params, dict):
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for key in ("model", "model_id", "modelId"):
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val = body_params.get(key)
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if isinstance(val, str):
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model_ids.append(val)
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|
||
return self._dedupe_preserve_order(model_ids)
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||
|
||
async def _extract_system_prompt(
|
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self,
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||
body: dict,
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||
messages: List[dict],
|
||
request_model: str,
|
||
real_model_id: str,
|
||
__event_call__=None,
|
||
) -> tuple[Optional[str], str]:
|
||
"""从 metadata/模型 DB/body/messages 提取系统提示词"""
|
||
system_prompt_content: Optional[str] = None
|
||
system_prompt_source = ""
|
||
|
||
# 1) metadata.model.params.system
|
||
metadata = body.get("metadata", {})
|
||
if isinstance(metadata, dict):
|
||
meta_model = metadata.get("model")
|
||
if isinstance(meta_model, dict):
|
||
meta_params = meta_model.get("params")
|
||
if isinstance(meta_params, dict) and meta_params.get("system"):
|
||
system_prompt_content = meta_params.get("system")
|
||
system_prompt_source = "metadata.model.params"
|
||
await self._emit_debug_log(
|
||
f"从 metadata.model.params 提取系统提示词（长度: {len(system_prompt_content)}）",
|
||
__event_call__,
|
||
)
|
||
|
||
# 2) 模型 DB
|
||
if not system_prompt_content:
|
||
try:
|
||
from open_webui.models.models import Models
|
||
|
||
model_ids_to_try = self._collect_model_ids(
|
||
body, request_model, real_model_id
|
||
)
|
||
for mid in model_ids_to_try:
|
||
model_record = Models.get_model_by_id(mid)
|
||
if model_record and hasattr(model_record, "params"):
|
||
params = model_record.params
|
||
if isinstance(params, dict):
|
||
system_prompt_content = params.get("system")
|
||
if system_prompt_content:
|
||
system_prompt_source = f"model_db:{mid}"
|
||
await self._emit_debug_log(
|
||
f"从模型数据库提取系统提示词（长度: {len(system_prompt_content)}）",
|
||
__event_call__,
|
||
)
|
||
break
|
||
except Exception as e:
|
||
await self._emit_debug_log(
|
||
f"从模型数据库提取系统提示词失败: {e}",
|
||
__event_call__,
|
||
)
|
||
|
||
# 3) body.params.system
|
||
if not system_prompt_content:
|
||
body_params = body.get("params", {})
|
||
if isinstance(body_params, dict):
|
||
system_prompt_content = body_params.get("system")
|
||
if system_prompt_content:
|
||
system_prompt_source = "body_params"
|
||
await self._emit_debug_log(
|
||
f"从 body.params 提取系统提示词（长度: {len(system_prompt_content)}）",
|
||
__event_call__,
|
||
)
|
||
|
||
# 4) messages (role=system)
|
||
if not system_prompt_content:
|
||
for msg in messages:
|
||
if msg.get("role") == "system":
|
||
system_prompt_content = self._extract_text_from_content(
|
||
msg.get("content", "")
|
||
)
|
||
if system_prompt_content:
|
||
system_prompt_source = "messages_system"
|
||
await self._emit_debug_log(
|
||
f"从消息中提取系统提示词（长度: {len(system_prompt_content)}）",
|
||
__event_call__,
|
||
)
|
||
break
|
||
|
||
return system_prompt_content, system_prompt_source
|
||
|
||
def _build_client_config(self, body: dict) -> dict:
|
||
"""根据 Valves 和请求构建 CopilotClient 配置"""
|
||
cwd = self.valves.WORKSPACE_DIR if self.valves.WORKSPACE_DIR else os.getcwd()
|
||
client_config = {}
|
||
if os.environ.get("COPILOT_CLI_PATH"):
|
||
client_config["cli_path"] = os.environ["COPILOT_CLI_PATH"]
|
||
client_config["cwd"] = cwd
|
||
|
||
if self.valves.LOG_LEVEL:
|
||
client_config["log_level"] = self.valves.LOG_LEVEL
|
||
|
||
if self.valves.CUSTOM_ENV_VARS:
|
||
try:
|
||
custom_env = json.loads(self.valves.CUSTOM_ENV_VARS)
|
||
if isinstance(custom_env, dict):
|
||
client_config["env"] = custom_env
|
||
except:
|
||
pass
|
||
|
||
return client_config
|
||
|
||
def _build_session_config(
|
||
self,
|
||
chat_id: Optional[str],
|
||
real_model_id: str,
|
||
custom_tools: List[Any],
|
||
system_prompt_content: Optional[str],
|
||
is_streaming: bool,
|
||
reasoning_effort: str = "",
|
||
):
|
||
"""构建 Copilot SDK 的 SessionConfig"""
|
||
from copilot.types import SessionConfig, InfiniteSessionConfig
|
||
|
||
infinite_session_config = None
|
||
if self.valves.INFINITE_SESSION:
|
||
infinite_session_config = InfiniteSessionConfig(
|
||
enabled=True,
|
||
background_compaction_threshold=self.valves.COMPACTION_THRESHOLD,
|
||
buffer_exhaustion_threshold=self.valves.BUFFER_THRESHOLD,
|
||
)
|
||
|
||
system_message_config = None
|
||
if system_prompt_content or self.valves.ENFORCE_FORMATTING:
|
||
# 构建系统消息内容
|
||
system_parts = []
|
||
|
||
if system_prompt_content:
|
||
system_parts.append(system_prompt_content)
|
||
|
||
if self.valves.ENFORCE_FORMATTING:
|
||
formatting_instruction = (
|
||
"\n\n[格式化指南]\n"
|
||
"在提供解释或描述时：\n"
|
||
"- 使用清晰的段落分隔（双换行）\n"
|
||
"- 将长句拆分为多个短句\n"
|
||
"- 对多个要点使用项目符号或编号列表\n"
|
||
"- 为主要部分添加标题（##、###）\n"
|
||
"- 确保不同主题之间有适当的间距"
|
||
)
|
||
system_parts.append(formatting_instruction)
|
||
logger.info(f"[ENFORCE_FORMATTING] 已添加格式化指导到系统提示词")
|
||
|
||
if system_parts:
|
||
system_message_config = {
|
||
"mode": "append",
|
||
"content": "\n".join(system_parts),
|
||
}
|
||
|
||
# 准备会话配置参数
|
||
session_params = {
|
||
"session_id": chat_id if chat_id else None,
|
||
"model": real_model_id,
|
||
"streaming": is_streaming,
|
||
"tools": custom_tools,
|
||
"system_message": system_message_config,
|
||
"infinite_sessions": infinite_session_config,
|
||
}
|
||
|
||
# 如果不是默认值（medium），添加 reasoning_effort
|
||
if reasoning_effort and reasoning_effort.lower() != "medium":
|
||
session_params["reasoning_effort"] = reasoning_effort.lower()
|
||
|
||
return SessionConfig(**session_params)
|
||
|
||
def _dedupe_preserve_order(self, items: List[str]) -> List[str]:
|
||
"""去重保序"""
|
||
seen = set()
|
||
result = []
|
||
for item in items:
|
||
if not item or item in seen:
|
||
continue
|
||
seen.add(item)
|
||
result.append(item)
|
||
return result
|
||
|
||
def _collect_model_ids(
|
||
self, body: dict, request_model: str, real_model_id: str
|
||
) -> List[str]:
|
||
"""收集可能的模型 ID（来自请求/metadata/body params）"""
|
||
model_ids: List[str] = []
|
||
if request_model:
|
||
model_ids.append(request_model)
|
||
if request_model.startswith(f"{self.id}-"):
|
||
model_ids.append(request_model[len(f"{self.id}-") :])
|
||
if real_model_id:
|
||
model_ids.append(real_model_id)
|
||
|
||
metadata = body.get("metadata", {})
|
||
if isinstance(metadata, dict):
|
||
meta_model = metadata.get("model")
|
||
meta_model_id = metadata.get("model_id")
|
||
if isinstance(meta_model, str):
|
||
model_ids.append(meta_model)
|
||
if isinstance(meta_model_id, str):
|
||
model_ids.append(meta_model_id)
|
||
|
||
body_params = body.get("params", {})
|
||
if isinstance(body_params, dict):
|
||
for key in ("model", "model_id", "modelId"):
|
||
val = body_params.get(key)
|
||
if isinstance(val, str):
|
||
model_ids.append(val)
|
||
|
||
return self._dedupe_preserve_order(model_ids)
|
||
|
||
async def _extract_system_prompt(
|
||
self,
|
||
body: dict,
|
||
messages: List[dict],
|
||
request_model: str,
|
||
real_model_id: str,
|
||
__event_call__=None,
|
||
) -> tuple[Optional[str], str]:
|
||
"""从 metadata/模型 DB/body/messages 提取系统提示词"""
|
||
system_prompt_content: Optional[str] = None
|
||
system_prompt_source = ""
|
||
|
||
# 1) metadata.model.params.system
|
||
metadata = body.get("metadata", {})
|
||
if isinstance(metadata, dict):
|
||
meta_model = metadata.get("model")
|
||
if isinstance(meta_model, dict):
|
||
meta_params = meta_model.get("params")
|
||
if isinstance(meta_params, dict) and meta_params.get("system"):
|
||
system_prompt_content = meta_params.get("system")
|
||
system_prompt_source = "metadata.model.params"
|
||
await self._emit_debug_log(
|
||
f"从 metadata.model.params 提取系统提示词（长度: {len(system_prompt_content)}）",
|
||
__event_call__,
|
||
)
|
||
|
||
# 2) 模型 DB
|
||
if not system_prompt_content:
|
||
try:
|
||
from open_webui.models.models import Models
|
||
|
||
model_ids_to_try = self._collect_model_ids(
|
||
body, request_model, real_model_id
|
||
)
|
||
for mid in model_ids_to_try:
|
||
model_record = Models.get_model_by_id(mid)
|
||
if model_record and hasattr(model_record, "params"):
|
||
params = model_record.params
|
||
if isinstance(params, dict):
|
||
system_prompt_content = params.get("system")
|
||
if system_prompt_content:
|
||
system_prompt_source = f"model_db:{mid}"
|
||
await self._emit_debug_log(
|
||
f"从模型数据库提取系统提示词（长度: {len(system_prompt_content)}）",
|
||
__event_call__,
|
||
)
|
||
break
|
||
except Exception as e:
|
||
await self._emit_debug_log(
|
||
f"从模型数据库提取系统提示词失败: {e}",
|
||
__event_call__,
|
||
)
|
||
|
||
# 3) body.params.system
|
||
if not system_prompt_content:
|
||
body_params = body.get("params", {})
|
||
if isinstance(body_params, dict):
|
||
system_prompt_content = body_params.get("system")
|
||
if system_prompt_content:
|
||
system_prompt_source = "body_params"
|
||
await self._emit_debug_log(
|
||
f"从 body.params 提取系统提示词（长度: {len(system_prompt_content)}）",
|
||
__event_call__,
|
||
)
|
||
|
||
# 4) messages (role=system)
|
||
if not system_prompt_content:
|
||
for msg in messages:
|
||
if msg.get("role") == "system":
|
||
system_prompt_content = self._extract_text_from_content(
|
||
msg.get("content", "")
|
||
)
|
||
if system_prompt_content:
|
||
system_prompt_source = "messages_system"
|
||
await self._emit_debug_log(
|
||
f"从消息中提取系统提示词（长度: {len(system_prompt_content)}）",
|
||
__event_call__,
|
||
)
|
||
break
|
||
|
||
return system_prompt_content, system_prompt_source
|
||
|
||
def _initialize_custom_tools(self):
|
||
"""根据配置初始化自定义工具"""
|
||
if not self.valves.ENABLE_TOOLS:
|
||
return []
|
||
|
||
# 定义所有可用工具（在此注册新工具）
|
||
all_tools = {
|
||
"generate_random_number": generate_random_number,
|
||
}
|
||
|
||
# 根据配置过滤
|
||
if self.valves.AVAILABLE_TOOLS == "all":
|
||
return list(all_tools.values())
|
||
|
||
# 仅启用指定的工具
|
||
enabled = [t.strip() for t in self.valves.AVAILABLE_TOOLS.split(",")]
|
||
return [all_tools[name] for name in enabled if name in all_tools]
|
||
|
||
async def _emit_debug_log(self, message: str, __event_call__=None):
|
||
"""在 DEBUG 开启时将日志输出到前端控制台。"""
|
||
if not self.valves.DEBUG:
|
||
return
|
||
|
||
logger.debug(f"[Copilot Pipe] {message}")
|
||
|
||
if not __event_call__:
|
||
return
|
||
|
||
try:
|
||
js_code = f"""
|
||
(async function() {{
|
||
console.debug("%c[Copilot Pipe] " + {json.dumps(message, ensure_ascii=False)}, "color: #3b82f6;");
|
||
}})();
|
||
"""
|
||
await __event_call__({"type": "execute", "data": {"code": js_code}})
|
||
except Exception as e:
|
||
logger.debug(f"[Copilot Pipe] 前端调试日志失败: {e}")
|
||
|
||
def _emit_debug_log_sync(self, message: str, __event_call__=None):
|
||
"""在非异步上下文中输出调试日志。"""
|
||
if not self.valves.DEBUG:
|
||
return
|
||
|
||
try:
|
||
loop = asyncio.get_running_loop()
|
||
except RuntimeError:
|
||
logger.debug(f"[Copilot Pipe] {message}")
|
||
return
|
||
|
||
loop.create_task(self._emit_debug_log(message, __event_call__))
|
||
|
||
async def _emit_native_message(self, message_data: dict, __event_call__=None):
|
||
"""发送原生 OpenAI 格式消息事件用于工具调用/结果。"""
|
||
if not __event_call__:
|
||
return
|
||
|
||
try:
|
||
await __event_call__({"type": "message", "data": message_data})
|
||
await self._emit_debug_log(
|
||
f"已发送原生消息: {message_data.get('role')} - {list(message_data.keys())}",
|
||
__event_call__,
|
||
)
|
||
except Exception as e:
|
||
logger.warning(f"发送原生消息失败: {e}")
|
||
await self._emit_debug_log(
|
||
f"原生消息发送失败: {e}。回退到文本显示。", __event_call__
|
||
)
|
||
|
||
def _get_user_context(self):
|
||
"""获取用户上下文（占位，预留）。"""
|
||
return {}
|
||
|
||
def _get_chat_context(
|
||
self, body: dict, __metadata__: Optional[dict] = None, __event_call__=None
|
||
) -> Dict[str, str]:
|
||
"""
|
||
高度可靠的聊天上下文提取逻辑。
|
||
优先级：__metadata__ > body['chat_id'] > body['metadata']['chat_id']
|
||
"""
|
||
chat_id = ""
|
||
source = "none"
|
||
|
||
# 1. 优先从 __metadata__ 获取 (OpenWebUI 注入的最可靠来源)
|
||
if __metadata__ and isinstance(__metadata__, dict):
|
||
chat_id = __metadata__.get("chat_id", "")
|
||
if chat_id:
|
||
source = "__metadata__"
|
||
|
||
# 2. 其次从 body 顶层获取
|
||
if not chat_id and isinstance(body, dict):
|
||
chat_id = body.get("chat_id", "")
|
||
if chat_id:
|
||
source = "body_root"
|
||
|
||
# 3. 最后从 body.metadata 获取
|
||
if not chat_id and isinstance(body, dict):
|
||
body_metadata = body.get("metadata", {})
|
||
if isinstance(body_metadata, dict):
|
||
chat_id = body_metadata.get("chat_id", "")
|
||
if chat_id:
|
||
source = "body_metadata"
|
||
|
||
# 调试：记录 ID 来源
|
||
if chat_id:
|
||
self._emit_debug_log_sync(
|
||
f"提取到 ChatID: {chat_id} (来源: {source})", __event_call__
|
||
)
|
||
else:
|
||
# 如果还是没找到，记录一下 body 的键，方便排查
|
||
keys = list(body.keys()) if isinstance(body, dict) else "not a dict"
|
||
self._emit_debug_log_sync(
|
||
f"警告: 未能提取到 ChatID。Body 键: {keys}", __event_call__
|
||
)
|
||
|
||
return {
|
||
"chat_id": str(chat_id).strip(),
|
||
}
|
||
|
||
async def pipes(self) -> List[dict]:
|
||
"""动态获取模型列表"""
|
||
# 如果有缓存，直接返回
|
||
if self._model_cache:
|
||
return self._model_cache
|
||
|
||
await self._emit_debug_log("正在动态获取模型列表...")
|
||
try:
|
||
self._setup_env()
|
||
if not self.valves.GH_TOKEN:
|
||
return [{"id": f"{self.id}-error", "name": "Error: GH_TOKEN not set"}]
|
||
|
||
client_config = {}
|
||
if os.environ.get("COPILOT_CLI_PATH"):
|
||
client_config["cli_path"] = os.environ["COPILOT_CLI_PATH"]
|
||
|
||
client = CopilotClient(client_config)
|
||
try:
|
||
await client.start()
|
||
models = await client.list_models()
|
||
|
||
# 更新缓存
|
||
self._model_cache = []
|
||
exclude_list = [
|
||
k.strip().lower()
|
||
for k in self.valves.EXCLUDE_KEYWORDS.split(",")
|
||
if k.strip()
|
||
]
|
||
|
||
models_with_info = []
|
||
for m in models:
|
||
# 兼容字典和对象访问方式
|
||
m_id = (
|
||
m.get("id") if isinstance(m, dict) else getattr(m, "id", str(m))
|
||
)
|
||
m_name = (
|
||
m.get("name")
|
||
if isinstance(m, dict)
|
||
else getattr(m, "name", m_id)
|
||
)
|
||
m_policy = (
|
||
m.get("policy")
|
||
if isinstance(m, dict)
|
||
else getattr(m, "policy", {})
|
||
)
|
||
m_billing = (
|
||
m.get("billing")
|
||
if isinstance(m, dict)
|
||
else getattr(m, "billing", {})
|
||
)
|
||
|
||
# 检查策略状态
|
||
state = (
|
||
m_policy.get("state")
|
||
if isinstance(m_policy, dict)
|
||
else getattr(m_policy, "state", "enabled")
|
||
)
|
||
if state == "disabled":
|
||
continue
|
||
|
||
# 过滤逻辑
|
||
if any(kw in m_id.lower() for kw in exclude_list):
|
||
continue
|
||
|
||
# 获取倍率
|
||
multiplier = (
|
||
m_billing.get("multiplier", 1)
|
||
if isinstance(m_billing, dict)
|
||
else getattr(m_billing, "multiplier", 1)
|
||
)
|
||
|
||
# 格式化显示名称
|
||
if multiplier == 0:
|
||
display_name = f"-🔥 {m_id} (unlimited)"
|
||
else:
|
||
display_name = f"-{m_id} ({multiplier}x)"
|
||
|
||
models_with_info.append(
|
||
{
|
||
"id": f"{self.id}-{m_id}",
|
||
"name": display_name,
|
||
"multiplier": multiplier,
|
||
"raw_id": m_id,
|
||
}
|
||
)
|
||
|
||
# 排序：倍率升序，然后是原始ID升序
|
||
models_with_info.sort(key=lambda x: (x["multiplier"], x["raw_id"]))
|
||
self._model_cache = [
|
||
{"id": m["id"], "name": m["name"]} for m in models_with_info
|
||
]
|
||
|
||
await self._emit_debug_log(
|
||
f"成功获取 {len(self._model_cache)} 个模型 (已过滤)"
|
||
)
|
||
return self._model_cache
|
||
except Exception as e:
|
||
await self._emit_debug_log(f"获取模型列表失败: {e}")
|
||
# 失败时返回默认模型
|
||
return [
|
||
{
|
||
"id": f"{self.id}-{self.valves.MODEL_ID}",
|
||
"name": f"GitHub Copilot ({self.valves.MODEL_ID})",
|
||
}
|
||
]
|
||
finally:
|
||
await client.stop()
|
||
except Exception as e:
|
||
await self._emit_debug_log(f"Pipes Error: {e}")
|
||
return [
|
||
{
|
||
"id": f"{self.id}-{self.valves.MODEL_ID}",
|
||
"name": f"GitHub Copilot ({self.valves.MODEL_ID})",
|
||
}
|
||
]
|
||
|
||
async def _get_client(self):
|
||
"""Helper to get or create a CopilotClient instance."""
|
||
# 确定工作空间目录
|
||
cwd = self.valves.WORKSPACE_DIR if self.valves.WORKSPACE_DIR else os.getcwd()
|
||
|
||
client_config = {}
|
||
if os.environ.get("COPILOT_CLI_PATH"):
|
||
client_config["cli_path"] = os.environ["COPILOT_CLI_PATH"]
|
||
client_config["cwd"] = cwd
|
||
|
||
# 设置日志级别
|
||
if self.valves.LOG_LEVEL:
|
||
client_config["log_level"] = self.valves.LOG_LEVEL
|
||
|
||
# 添加自定义环境变量
|
||
if self.valves.CUSTOM_ENV_VARS:
|
||
try:
|
||
custom_env = json.loads(self.valves.CUSTOM_ENV_VARS)
|
||
if isinstance(custom_env, dict):
|
||
client_config["env"] = custom_env
|
||
except:
|
||
pass # 静默失败，因为这是同步方法且不应影响主流程
|
||
|
||
client = CopilotClient(client_config)
|
||
await client.start()
|
||
return client
|
||
|
||
def _setup_env(self, __event_call__=None):
|
||
cli_path = self.valves.CLI_PATH
|
||
found = False
|
||
|
||
if os.path.exists(cli_path):
|
||
found = True
|
||
|
||
if not found:
|
||
sys_path = shutil.which("copilot")
|
||
if sys_path:
|
||
cli_path = sys_path
|
||
found = True
|
||
|
||
if not found:
|
||
try:
|
||
subprocess.run(
|
||
"curl -fsSL https://gh.io/copilot-install | bash",
|
||
shell=True,
|
||
check=True,
|
||
)
|
||
if os.path.exists(self.valves.CLI_PATH):
|
||
cli_path = self.valves.CLI_PATH
|
||
found = True
|
||
except:
|
||
pass
|
||
|
||
if found:
|
||
os.environ["COPILOT_CLI_PATH"] = cli_path
|
||
cli_dir = os.path.dirname(cli_path)
|
||
if cli_dir not in os.environ["PATH"]:
|
||
os.environ["PATH"] = f"{cli_dir}:{os.environ['PATH']}"
|
||
|
||
if self.valves.DEBUG:
|
||
self._emit_debug_log_sync(
|
||
f"Copilot CLI 已定位: {cli_path}", __event_call__
|
||
)
|
||
|
||
if self.valves.GH_TOKEN:
|
||
os.environ["GH_TOKEN"] = self.valves.GH_TOKEN
|
||
os.environ["GITHUB_TOKEN"] = self.valves.GH_TOKEN
|
||
else:
|
||
if self.valves.DEBUG:
|
||
self._emit_debug_log_sync("Warning: GH_TOKEN 未设置。", __event_call__)
|
||
|
||
def _process_images(self, messages, __event_call__=None):
|
||
attachments = []
|
||
text_content = ""
|
||
if not messages:
|
||
return "", []
|
||
last_msg = messages[-1]
|
||
content = last_msg.get("content", "")
|
||
|
||
if isinstance(content, list):
|
||
for item in content:
|
||
if item.get("type") == "text":
|
||
text_content += item.get("text", "")
|
||
elif item.get("type") == "image_url":
|
||
image_url = item.get("image_url", {}).get("url", "")
|
||
if image_url.startswith("data:image"):
|
||
try:
|
||
header, encoded = image_url.split(",", 1)
|
||
ext = header.split(";")[0].split("/")[-1]
|
||
file_name = f"image_{len(attachments)}.{ext}"
|
||
file_path = os.path.join(self.temp_dir, file_name)
|
||
with open(file_path, "wb") as f:
|
||
f.write(base64.b64decode(encoded))
|
||
attachments.append(
|
||
{
|
||
"type": "file",
|
||
"path": file_path,
|
||
"display_name": file_name,
|
||
}
|
||
)
|
||
self._emit_debug_log_sync(
|
||
f"Image processed: {file_path}", __event_call__
|
||
)
|
||
except Exception as e:
|
||
self._emit_debug_log_sync(
|
||
f"Image error: {e}", __event_call__
|
||
)
|
||
else:
|
||
text_content = str(content)
|
||
return text_content, attachments
|
||
|
||
def _sync_copilot_config(self, reasoning_effort: str, __event_call__=None):
|
||
"""
|
||
动态更新 ~/.copilot/config.json 中的 reasoning_effort 设置。
|
||
如果 API 注入被忽略，这提供了最后的保障。
|
||
"""
|
||
if not reasoning_effort:
|
||
return
|
||
|
||
effort = reasoning_effort
|
||
|
||
# 检查模型对 xhigh 的支持
|
||
# 目前仅 gpt-5.2-codex 支持 xhigh
|
||
# 在 _sync_copilot_config 中很难获得准确的当前模型 ID，
|
||
# 因此这里我们放宽限制，允许写入 xhigh。
|
||
# 如果模型不支持，Copilot CLI 可能会忽略或降级处理，但这比在这里硬编码判断更安全，
|
||
# 因为获取当前请求的 body 需要修改函数签名。
|
||
|
||
try:
|
||
# 目标标准路径 ~/.copilot/config.json
|
||
config_path = os.path.expanduser("~/.copilot/config.json")
|
||
config_dir = os.path.dirname(config_path)
|
||
|
||
# 仅在目录存在时执行（避免在错误环境创建垃圾文件）
|
||
if not os.path.exists(config_dir):
|
||
return
|
||
|
||
data = {}
|
||
# 读取现有配置
|
||
if os.path.exists(config_path):
|
||
try:
|
||
with open(config_path, "r") as f:
|
||
data = json.load(f)
|
||
except Exception:
|
||
data = {}
|
||
|
||
# 如果值有变化则更新
|
||
current_val = data.get("reasoning_effort")
|
||
if current_val != effort:
|
||
data["reasoning_effort"] = effort
|
||
try:
|
||
with open(config_path, "w") as f:
|
||
json.dump(data, f, indent=4)
|
||
|
||
self._emit_debug_log_sync(
|
||
f"已动态更新 ~/.copilot/config.json: reasoning_effort='{effort}'",
|
||
__event_call__,
|
||
)
|
||
except Exception as e:
|
||
self._emit_debug_log_sync(
|
||
f"写入 config.json 失败: {e}", __event_call__
|
||
)
|
||
except Exception as e:
|
||
self._emit_debug_log_sync(f"配置同步检查失败: {e}", __event_call__)
|
||
|
||
# ==================== 内部实现 ====================
|
||
# _pipe_impl() 包含主请求处理逻辑。
|
||
# ================================================
|
||
async def _pipe_impl(
|
||
self,
|
||
body: dict,
|
||
__metadata__: Optional[dict] = None,
|
||
__user__: Optional[dict] = None,
|
||
__event_emitter__=None,
|
||
__event_call__=None,
|
||
) -> Union[str, AsyncGenerator]:
|
||
self._setup_env(__event_call__)
|
||
if not self.valves.GH_TOKEN:
|
||
return "Error: 请在 Valves 中配置 GH_TOKEN。"
|
||
|
||
# 解析用户选择的模型
|
||
request_model = body.get("model", "")
|
||
real_model_id = self.valves.MODEL_ID # 默认值
|
||
|
||
# 确定有效的推理强度和调试设置
|
||
if __user__:
|
||
raw_valves = __user__.get("valves", {})
|
||
if isinstance(raw_valves, self.UserValves):
|
||
user_valves = raw_valves
|
||
elif isinstance(raw_valves, dict):
|
||
user_valves = self.UserValves(**raw_valves)
|
||
else:
|
||
user_valves = self.UserValves()
|
||
else:
|
||
user_valves = self.UserValves()
|
||
effective_reasoning_effort = (
|
||
user_valves.REASONING_EFFORT
|
||
if user_valves.REASONING_EFFORT
|
||
else self.valves.REASONING_EFFORT
|
||
)
|
||
# 如果用户启用了 DEBUG，则覆盖全局设置
|
||
if user_valves.DEBUG:
|
||
self.valves.DEBUG = True
|
||
|
||
# 处理 SHOW_THINKING（优先使用用户设置）
|
||
show_thinking = (
|
||
user_valves.SHOW_THINKING
|
||
if user_valves.SHOW_THINKING is not None
|
||
else self.valves.SHOW_THINKING
|
||
)
|
||
|
||
if request_model.startswith(f"{self.id}-"):
|
||
real_model_id = request_model[len(f"{self.id}-") :]
|
||
await self._emit_debug_log(
|
||
f"使用选择的模型: {real_model_id}", __event_call__
|
||
)
|
||
|
||
messages = body.get("messages", [])
|
||
if not messages:
|
||
return "No messages."
|
||
|
||
# 使用改进的助手获取 Chat ID
|
||
chat_ctx = self._get_chat_context(body, __metadata__, __event_call__)
|
||
chat_id = chat_ctx.get("chat_id")
|
||
|
||
# 从多个来源提取系统提示词
|
||
system_prompt_content, system_prompt_source = await self._extract_system_prompt(
|
||
body, messages, request_model, real_model_id, __event_call__
|
||
)
|
||
|
||
if system_prompt_content:
|
||
preview = system_prompt_content[:60].replace("\n", " ")
|
||
await self._emit_debug_log(
|
||
f"系统提示词已确认（来源: {system_prompt_source}, 长度: {len(system_prompt_content)}, 预览: {preview}）",
|
||
__event_call__,
|
||
)
|
||
|
||
is_streaming = body.get("stream", False)
|
||
await self._emit_debug_log(f"请求流式传输: {is_streaming}", __event_call__)
|
||
|
||
client = CopilotClient(self._build_client_config(body))
|
||
should_stop_client = True
|
||
try:
|
||
await client.start()
|
||
|
||
# 初始化自定义工具
|
||
custom_tools = self._initialize_custom_tools()
|
||
if custom_tools:
|
||
tool_names = [t.name for t in custom_tools]
|
||
await self._emit_debug_log(
|
||
f"已启用 {len(custom_tools)} 个自定义工具: {tool_names}",
|
||
__event_call__,
|
||
)
|
||
|
||
session = None
|
||
|
||
if chat_id:
|
||
try:
|
||
# 尝试直接使用 chat_id 作为 session_id 恢复会话
|
||
session = await client.resume_session(chat_id)
|
||
await self._emit_debug_log(
|
||
f"已通过 ChatID 恢复会话: {chat_id}", __event_call__
|
||
)
|
||
|
||
# 显示工作空间信息（如果可用）
|
||
if self.valves.DEBUG and self.valves.SHOW_WORKSPACE_INFO:
|
||
if session.workspace_path:
|
||
await self._emit_debug_log(
|
||
f"会话工作空间: {session.workspace_path}",
|
||
__event_call__,
|
||
)
|
||
|
||
is_new_session = False
|
||
except Exception as e:
|
||
# 恢复失败，磁盘上可能不存在该会话
|
||
reasoning_effort = (effective_reasoning_effort,)
|
||
await self._emit_debug_log(
|
||
f"会话 {chat_id} 不存在或已过期 ({str(e)})，将创建新会话。",
|
||
__event_call__,
|
||
)
|
||
session = None
|
||
|
||
if session is None:
|
||
session_config = self._build_session_config(
|
||
chat_id,
|
||
real_model_id,
|
||
custom_tools,
|
||
system_prompt_content,
|
||
is_streaming,
|
||
)
|
||
if system_prompt_content:
|
||
await self._emit_debug_log(
|
||
f"配置系统消息（模式: append）",
|
||
__event_call__,
|
||
)
|
||
|
||
# 显示系统配置预览
|
||
if system_prompt_content or self.valves.ENFORCE_FORMATTING:
|
||
preview_parts = []
|
||
if system_prompt_content:
|
||
preview_parts.append(
|
||
f"自定义提示词: {system_prompt_content[:100]}..."
|
||
)
|
||
if self.valves.ENFORCE_FORMATTING:
|
||
preview_parts.append("格式化指导: 已启用")
|
||
|
||
if isinstance(session_config, dict):
|
||
system_config = session_config.get("system_message", {})
|
||
else:
|
||
system_config = getattr(session_config, "system_message", None)
|
||
|
||
if isinstance(system_config, dict):
|
||
full_content = system_config.get("content", "")
|
||
else:
|
||
full_content = ""
|
||
|
||
await self._emit_debug_log(
|
||
f"系统消息配置 - {', '.join(preview_parts)} (总长度: {len(full_content)} 字符)",
|
||
__event_call__,
|
||
)
|
||
|
||
session = await client.create_session(config=session_config)
|
||
|
||
# 获取新会话 ID
|
||
new_sid = getattr(session, "session_id", getattr(session, "id", None))
|
||
await self._emit_debug_log(f"创建了新会话: {new_sid}", __event_call__)
|
||
|
||
# 显示新会话的工作空间信息
|
||
if self.valves.DEBUG and self.valves.SHOW_WORKSPACE_INFO:
|
||
if session.workspace_path:
|
||
await self._emit_debug_log(
|
||
f"会话工作空间: {session.workspace_path}",
|
||
__event_call__,
|
||
)
|
||
|
||
# 构建 Prompt（基于会话：仅发送最新用户输入）
|
||
prompt = self._apply_formatting_hint(last_text)
|
||
|
||
send_payload = {"prompt": prompt, "mode": "immediate"}
|
||
if attachments:
|
||
send_payload["attachments"] = attachments
|
||
|
||
if body.get("stream", False):
|
||
# 确定 UI 显示的会话状态消息
|
||
init_msg = ""
|
||
if self.valves.DEBUG:
|
||
if is_new_session:
|
||
new_sid = getattr(
|
||
session, "session_id", getattr(session, "id", "unknown")
|
||
)
|
||
init_msg = f"> [Debug] 创建了新会话: {new_sid}\n"
|
||
else:
|
||
init_msg = f"> [Debug] 已通过 ChatID 恢复会话: {chat_id}\n"
|
||
|
||
return self.stream_response(
|
||
client,
|
||
session,
|
||
send_payload,
|
||
init_msg,
|
||
__event_call__,
|
||
reasoning_effort=effective_reasoning_effort,
|
||
show_thinking=show_thinking,
|
||
)
|
||
else:
|
||
try:
|
||
response = await session.send_and_wait(send_payload)
|
||
return response.data.content if response else "Empty response."
|
||
finally:
|
||
# 清理：如果没有 chat_id（临时会话），销毁会话
|
||
if not chat_id:
|
||
try:
|
||
await session.destroy()
|
||
except Exception as cleanup_error:
|
||
await self._emit_debug_log(
|
||
f"会话清理警告: {cleanup_error}",
|
||
__event_call__,
|
||
)
|
||
except Exception as e:
|
||
await self._emit_debug_log(f"请求错误: {e}", __event_call__)
|
||
return f"Error: {str(e)}"
|
||
finally:
|
||
if should_stop_client:
|
||
try:
|
||
await client.stop()
|
||
except:
|
||
pass
|
||
|
||
async def stream_response(
|
||
self,
|
||
client,
|
||
session,
|
||
send_payload,
|
||
init_message: str = "",
|
||
__event_call__=None,
|
||
reasoning_effort: str = "",
|
||
show_thinking: bool = True,
|
||
) -> AsyncGenerator:
|
||
"""
|
||
从 Copilot SDK 流式传输响应，处理各种事件类型。
|
||
遵循官方 SDK 模式进行事件处理和流式传输。
|
||
"""
|
||
from copilot.generated.session_events import SessionEventType
|
||
|
||
queue = asyncio.Queue()
|
||
done = asyncio.Event()
|
||
SENTINEL = object()
|
||
# 使用本地状态来处理并发和跟踪
|
||
state = {"thinking_started": False, "content_sent": False}
|
||
has_content = False # 追踪是否已经输出了内容
|
||
active_tools = {} # 映射 tool_call_id 到工具名称
|
||
|
||
def get_event_type(event) -> str:
|
||
"""提取事件类型为字符串，处理枚举和字符串类型。"""
|
||
if hasattr(event, "type"):
|
||
event_type = event.type
|
||
# 处理 SessionEventType 枚举
|
||
if hasattr(event_type, "value"):
|
||
return event_type.value
|
||
return str(event_type)
|
||
return "unknown"
|
||
|
||
def safe_get_data_attr(event, attr: str, default=None):
|
||
"""
|
||
安全地从 event.data 提取属性。
|
||
同时处理字典访问和对象属性访问。
|
||
"""
|
||
if not hasattr(event, "data") or event.data is None:
|
||
return default
|
||
|
||
data = event.data
|
||
|
||
# 首先尝试作为字典
|
||
if isinstance(data, dict):
|
||
return data.get(attr, default)
|
||
|
||
# 尝试作为对象属性
|
||
return getattr(data, attr, default)
|
||
|
||
def handler(event):
|
||
"""
|
||
事件处理器，遵循官方 SDK 模式。
|
||
处理流式增量、推理、工具事件和会话状态。
|
||
"""
|
||
event_type = get_event_type(event)
|
||
|
||
# === 消息增量事件（主要流式内容）===
|
||
if event_type == "assistant.message_delta":
|
||
# 官方：Python SDK 使用 event.data.delta_content
|
||
delta = safe_get_data_attr(
|
||
event, "delta_content"
|
||
) or safe_get_data_attr(event, "deltaContent")
|
||
if delta:
|
||
state["content_sent"] = True
|
||
if state["thinking_started"]:
|
||
queue.put_nowait("\n</think>\n")
|
||
state["thinking_started"] = False
|
||
queue.put_nowait(delta)
|
||
|
||
# === 完整消息事件（非流式响应） ===
|
||
elif event_type == "assistant.message":
|
||
# 处理完整消息（当 SDK 返回完整内容而不是增量时）
|
||
content = safe_get_data_attr(event, "content") or safe_get_data_attr(
|
||
event, "message"
|
||
)
|
||
if content:
|
||
state["content_sent"] = True
|
||
if state["thinking_started"]:
|
||
queue.put_nowait("\n</think>\n")
|
||
state["thinking_started"] = False
|
||
queue.put_nowait(content)
|
||
|
||
# === 推理增量事件（思维链流式传输）===
|
||
elif event_type == "assistant.reasoning_delta":
|
||
delta = safe_get_data_attr(
|
||
event, "delta_content"
|
||
) or safe_get_data_attr(event, "deltaContent")
|
||
if delta:
|
||
# 如果内容已经开始，抑制迟到的推理
|
||
if state["content_sent"]:
|
||
return
|
||
|
||
if not state["thinking_started"] and show_thinking:
|
||
queue.put_nowait("<think>\n")
|
||
state["thinking_started"] = True
|
||
if state["thinking_started"]:
|
||
queue.put_nowait(delta)
|
||
|
||
# === 完整推理事件（非流式推理） ===
|
||
elif event_type == "assistant.reasoning":
|
||
# 处理完整推理内容
|
||
reasoning = safe_get_data_attr(event, "content") or safe_get_data_attr(
|
||
event, "reasoning"
|
||
)
|
||
if reasoning:
|
||
# 如果内容已经开始，抑制延迟到达的推理
|
||
if state["content_sent"]:
|
||
return
|
||
|
||
if not state["thinking_started"] and show_thinking:
|
||
queue.put_nowait("<think>\n")
|
||
state["thinking_started"] = True
|
||
if state["thinking_started"]:
|
||
queue.put_nowait(reasoning)
|
||
|
||
# === 工具执行事件 ===
|
||
elif event_type == "tool.execution_start":
|
||
tool_name = (
|
||
safe_get_data_attr(event, "name")
|
||
or safe_get_data_attr(event, "tool_name")
|
||
or "未知工具"
|
||
)
|
||
tool_call_id = safe_get_data_attr(event, "tool_call_id", "")
|
||
|
||
# 获取工具参数
|
||
tool_args = {}
|
||
try:
|
||
args_obj = safe_get_data_attr(event, "arguments")
|
||
if isinstance(args_obj, dict):
|
||
tool_args = args_obj
|
||
elif isinstance(args_obj, str):
|
||
tool_args = json.loads(args_obj)
|
||
except:
|
||
pass
|
||
|
||
if tool_call_id:
|
||
active_tools[tool_call_id] = {
|
||
"name": tool_name,
|
||
"arguments": tool_args,
|
||
}
|
||
|
||
# 在显示工具前关闭思考标签
|
||
if state["thinking_started"]:
|
||
queue.put_nowait("\n</think>\n")
|
||
state["thinking_started"] = False
|
||
|
||
# 使用改进的格式展示工具调用
|
||
if tool_args:
|
||
tool_args_json = json.dumps(tool_args, indent=2, ensure_ascii=False)
|
||
tool_display = f"\n\n<details>\n<summary>🔧 执行工具: {tool_name}</summary>\n\n**参数:**\n\n```json\n{tool_args_json}\n```\n\n</details>\n\n"
|
||
else:
|
||
tool_display = f"\n\n<details>\n<summary>🔧 执行工具: {tool_name}</summary>\n\n*无参数*\n\n</details>\n\n"
|
||
|
||
queue.put_nowait(tool_display)
|
||
|
||
self._emit_debug_log_sync(f"工具开始: {tool_name}", __event_call__)
|
||
|
||
elif event_type == "tool.execution_complete":
|
||
tool_call_id = safe_get_data_attr(event, "tool_call_id", "")
|
||
tool_info = active_tools.get(tool_call_id)
|
||
|
||
# 处理旧的字符串格式和新的字典格式
|
||
if isinstance(tool_info, str):
|
||
tool_name = tool_info
|
||
elif isinstance(tool_info, dict):
|
||
tool_name = tool_info.get("name", "未知工具")
|
||
else:
|
||
tool_name = "未知工具"
|
||
|
||
# 尝试获取结果内容
|
||
result_content = ""
|
||
result_type = "success"
|
||
try:
|
||
result_obj = safe_get_data_attr(event, "result")
|
||
if hasattr(result_obj, "content"):
|
||
result_content = result_obj.content
|
||
elif isinstance(result_obj, dict):
|
||
result_content = result_obj.get("content", "")
|
||
result_type = result_obj.get("result_type", "success")
|
||
if not result_content:
|
||
# 如果没有 content 字段，尝试序列化整个字典
|
||
result_content = json.dumps(
|
||
result_obj, indent=2, ensure_ascii=False
|
||
)
|
||
except Exception as e:
|
||
self._emit_debug_log_sync(f"提取结果时出错: {e}", __event_call__)
|
||
result_type = "failure"
|
||
result_content = f"错误: {str(e)}"
|
||
|
||
# 使用改进的格式展示工具结果
|
||
if result_content:
|
||
status_icon = "✅" if result_type == "success" else "❌"
|
||
|
||
# 尝试检测内容类型以便更好地格式化
|
||
is_json = False
|
||
try:
|
||
json_obj = (
|
||
json.loads(result_content)
|
||
if isinstance(result_content, str)
|
||
else result_content
|
||
)
|
||
if isinstance(json_obj, (dict, list)):
|
||
result_content = json.dumps(
|
||
json_obj, indent=2, ensure_ascii=False
|
||
)
|
||
is_json = True
|
||
except:
|
||
pass
|
||
|
||
# 根据内容类型格式化
|
||
if is_json:
|
||
# JSON 内容：使用代码块和语法高亮
|
||
result_display = f"\n<details>\n<summary>{status_icon} 执行结果: {tool_name}</summary>\n\n```json\n{result_content}\n```\n\n</details>\n\n"
|
||
else:
|
||
# 纯文本：保留格式，不使用代码块
|
||
result_display = f"\n<details>\n<summary>{status_icon} 执行结果: {tool_name}</summary>\n\n{result_content}\n\n</details>\n\n"
|
||
|
||
queue.put_nowait(result_display)
|
||
|
||
elif event_type == "tool.execution_progress":
|
||
# 工具执行进度更新（用于长时间运行的工具）
|
||
tool_call_id = safe_get_data_attr(event, "tool_call_id", "")
|
||
tool_info = active_tools.get(tool_call_id)
|
||
tool_name = (
|
||
tool_info.get("name", "未知工具")
|
||
if isinstance(tool_info, dict)
|
||
else "未知工具"
|
||
)
|
||
|
||
progress = safe_get_data_attr(event, "progress", 0)
|
||
message = safe_get_data_attr(event, "message", "")
|
||
|
||
if message:
|
||
progress_display = f"\n> 🔄 **{tool_name}**: {message}\n"
|
||
queue.put_nowait(progress_display)
|
||
|
||
self._emit_debug_log_sync(
|
||
f"工具进度: {tool_name} - {progress}%", __event_call__
|
||
)
|
||
|
||
elif event_type == "tool.execution_partial_result":
|
||
# 流式工具结果（用于增量输出的工具）
|
||
tool_call_id = safe_get_data_attr(event, "tool_call_id", "")
|
||
tool_info = active_tools.get(tool_call_id)
|
||
tool_name = (
|
||
tool_info.get("name", "未知工具")
|
||
if isinstance(tool_info, dict)
|
||
else "未知工具"
|
||
)
|
||
|
||
partial_content = safe_get_data_attr(event, "content", "")
|
||
if partial_content:
|
||
queue.put_nowait(partial_content)
|
||
|
||
self._emit_debug_log_sync(f"工具部分结果: {tool_name}", __event_call__)
|
||
|
||
# === 使用统计事件 ===
|
||
elif event_type == "assistant.usage":
|
||
# 当前助手回合的 token 使用量
|
||
if self.valves.DEBUG:
|
||
input_tokens = safe_get_data_attr(event, "input_tokens", 0)
|
||
output_tokens = safe_get_data_attr(event, "output_tokens", 0)
|
||
total_tokens = safe_get_data_attr(event, "total_tokens", 0)
|
||
pass
|
||
|
||
elif event_type == "session.usage_info":
|
||
# 会话累计使用信息
|
||
pass
|
||
|
||
# === 会话状态事件 ===
|
||
elif event_type == "session.compaction_start":
|
||
self._emit_debug_log_sync("会话压缩已开始", __event_call__)
|
||
|
||
elif event_type == "session.compaction_complete":
|
||
self._emit_debug_log_sync("会话压缩已完成", __event_call__)
|
||
|
||
elif event_type == "session.idle":
|
||
# 会话处理完成 - 发出完成信号
|
||
done.set()
|
||
try:
|
||
queue.put_nowait(SENTINEL)
|
||
except:
|
||
pass
|
||
|
||
elif event_type == "session.error":
|
||
error_msg = safe_get_data_attr(event, "message", "未知错误")
|
||
queue.put_nowait(f"\n[错误: {error_msg}]")
|
||
done.set()
|
||
try:
|
||
queue.put_nowait(SENTINEL)
|
||
except:
|
||
pass
|
||
|
||
unsubscribe = session.on(handler)
|
||
|
||
self._emit_debug_log_sync(f"已订阅事件。正在发送请求...", __event_call__)
|
||
|
||
# 使用 asyncio.create_task 防止 session.send 阻塞流读取
|
||
# 如果 SDK 实现等待完成。
|
||
send_task = asyncio.create_task(session.send(send_payload))
|
||
self._emit_debug_log_sync(f"Prompt 已发送 (异步任务已启动)", __event_call__)
|
||
|
||
# 安全的初始 yield，带错误处理
|
||
try:
|
||
if self.valves.DEBUG:
|
||
yield "<think>\n"
|
||
if init_message:
|
||
yield init_message
|
||
|
||
if reasoning_effort and reasoning_effort != "off":
|
||
yield f"> [Debug] 已注入推理强度 (Reasoning Effort): {reasoning_effort.upper()}\n"
|
||
|
||
yield "> [Debug] 连接已建立，等待响应...\n"
|
||
self.thinking_started = True
|
||
except Exception as e:
|
||
# 如果初始 yield 失败，记录但继续处理
|
||
self._emit_debug_log_sync(f"初始 yield 警告: {e}", __event_call__)
|
||
|
||
try:
|
||
while not done.is_set():
|
||
try:
|
||
chunk = await asyncio.wait_for(
|
||
queue.get(), timeout=float(self.valves.TIMEOUT)
|
||
)
|
||
if chunk is SENTINEL:
|
||
break
|
||
if chunk:
|
||
has_content = True
|
||
try:
|
||
yield chunk
|
||
except Exception as yield_error:
|
||
# 客户端关闭连接，优雅停止
|
||
self._emit_debug_log_sync(
|
||
f"Yield 错误（客户端断开连接？）: {yield_error}",
|
||
__event_call__,
|
||
)
|
||
break
|
||
except asyncio.TimeoutError:
|
||
if done.is_set():
|
||
break
|
||
if self.thinking_started:
|
||
try:
|
||
yield f"> [Debug] 等待响应中 (已超过 {self.valves.TIMEOUT} 秒)...\n"
|
||
except:
|
||
# 如果超时期间 yield 失败，连接已断开
|
||
break
|
||
continue
|
||
|
||
while not queue.empty():
|
||
chunk = queue.get_nowait()
|
||
if chunk is SENTINEL:
|
||
break
|
||
if chunk:
|
||
has_content = True
|
||
try:
|
||
yield chunk
|
||
except:
|
||
# 连接关闭，停止 yielding
|
||
break
|
||
|
||
if self.thinking_started:
|
||
try:
|
||
yield "\n</think>\n"
|
||
has_content = True
|
||
except:
|
||
pass # 连接已关闭
|
||
|
||
# 核心修复：如果整个过程没有任何输出，返回一个提示，防止 OpenWebUI 报错
|
||
if not has_content:
|
||
try:
|
||
yield "⚠️ Copilot 未返回任何内容。请检查模型 ID 是否正确，或尝试在 Valves 中开启 DEBUG 模式查看详细日志。"
|
||
except:
|
||
pass # 连接已关闭
|
||
|
||
except Exception as e:
|
||
try:
|
||
yield f"\n[Stream Error: {str(e)}]"
|
||
except:
|
||
pass # 连接已关闭
|
||
finally:
|
||
unsubscribe()
|
||
# 销毁会话对象以释放内存，但保留磁盘数据
|
||
await session.destroy()
|