Merge branch 'master' into better-stream

2025-04-15 21:22:08 +08:00
parent 3753fce912 4c02857ec5
commit 4c546f2f53
19 changed files with 604 additions and 340 deletions
@@ -13,10 +13,11 @@ _✨ 易上手的多平台 LLM 聊天机器人及开发框架 ✨_
 [![GitHub release (latest by date)](https://img.shields.io/github/v/release/Soulter/AstrBot?style=for-the-badge&color=76bad9)](https://github.com/Soulter/AstrBot/releases/latest)
 <img src="https://img.shields.io/badge/python-3.10+-blue.svg?style=for-the-badge&color=76bad9" alt="python">
 <a href="https://hub.docker.com/r/soulter/astrbot"><img alt="Docker pull" src="https://img.shields.io/docker/pulls/soulter/astrbot.svg?style=for-the-badge&color=76bad9"/></a>
-<a  href="https://qm.qq.com/cgi-bin/qm/qr?k=wtbaNx7EioxeaqS9z7RQWVXPIxg2zYr7&jump_from=webapi&authKey=vlqnv/AV2DbJEvGIcxdlNSpfxVy+8vVqijgreRdnVKOaydpc+YSw4MctmEbr0k5"><img alt="Static Badge" src="https://img.shields.io/badge/QQ群-775869627-purple?style=for-the-badge&color=76bad9"></a>
+<a  href="https://qm.qq.com/cgi-bin/qm/qr?k=wtbaNx7EioxeaqS9z7RQWVXPIxg2zYr7&jump_from=webapi&authKey=vlqnv/AV2DbJEvGIcxdlNSpfxVy+8vVqijgreRdnVKOaydpc+YSw4MctmEbr0k5"><img alt="QQ_community" src="https://img.shields.io/badge/QQ群-775869627-purple?style=for-the-badge&color=76bad9"></a>
+<a  href="https://t.me/+hAsD2Ebl5as3NmY1"><img alt="Telegram_community" src="https://img.shields.io/badge/Telegram-AstrBot-purple?style=for-the-badge&color=76bad9"></a>
 [![wakatime](https://wakatime.com/badge/user/915e5316-99c6-4563-a483-ef186cf000c9/project/018e705a-a1a7-409a-a849-3013485e6c8e.svg?style=for-the-badge&color=76bad9)](https://wakatime.com/badge/user/915e5316-99c6-4563-a483-ef186cf000c9/project/018e705a-a1a7-409a-a849-3013485e6c8e)
-![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fstats&query=v&label=7%E6%97%A5%E6%B4%BB%E8%B7%83%E9%87%8F&cacheSeconds=10800&style=for-the-badge&color=3b618e)
-![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fplugin-num&query=%24.result&suffix=%E4%B8%AA&style=for-the-badge&label=%E6%8F%92%E4%BB%B6%E5%B8%82%E5%9C%BA&cacheSeconds=7200)
+![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fstats&query=v&label=7%E6%97%A5%E6%B4%BB%E8%B7%83%E9%87%8F&cacheSeconds=3600&style=for-the-badge&color=3b618e)
+![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fplugin-num&query=%24.result&suffix=%E4%B8%AA&style=for-the-badge&label=%E6%8F%92%E4%BB%B6%E5%B8%82%E5%9C%BA&cacheSeconds=3600)


 <a href="https://github.com/Soulter/AstrBot/blob/master/README_en.md">English</a> ｜
@@ -23,7 +23,10 @@ db_helper = SQLiteDatabase(DB_PATH)
 sp = (
    SharedPreferences()
 )  # 简单的偏好设置存储, 这里后续应该存储到数据库中, 一些部分可以存储到配置中
-pip_installer = PipInstaller(astrbot_config.get("pip_install_arg", ""))
+pip_installer = PipInstaller(
+    astrbot_config.get("pip_install_arg", ""),
+    astrbot_config.get("pypi_index_url", None),
+)
 web_chat_queue = asyncio.Queue(maxsize=32)
 web_chat_back_queue = asyncio.Queue(maxsize=32)
 WEBUI_SK = "Advanced_System_for_Text_Response_and_Bot_Operations_Tool"
@@ -98,7 +98,7 @@ DEFAULT_CONFIG = {
    "wake_prefix": ["/"],
    "log_level": "INFO",
    "pip_install_arg": "",
-    "plugin_repo_mirror": "",
+    "pypi_index_url": "https://mirrors.aliyun.com/pypi/simple/",
    "knowledge_db": {},
    "persona": [],
    "timezone": "",
@@ -529,6 +529,7 @@ CONFIG_METADATA_2 = {
                            "model": "gemini-2.0-flash-exp",
                        },
                        "gm_resp_image_modal": False,
+                        "gm_native_coderunner": False,
                        "gm_safety_settings": {
                            "harassment": "BLOCK_MEDIUM_AND_ABOVE",
                            "hate_speech": "BLOCK_MEDIUM_AND_ABOVE",
@@ -705,6 +706,12 @@ CONFIG_METADATA_2 = {
                        "type": "bool",
                        "hint": "启用后，将支持返回图片内容。需要模型支持，否则会报错。具体支持模型请查看 Google Gemini 官方网站。温馨提示，如果您需要生成图片，请关闭 `启用群员识别` 配置获得更好的效果。",
                    },
+                    "gm_native_coderunner": {
+                        "description": "启用原生代码执行器",
+                        "type": "bool",
+                        "hint": "启用后所有函数工具将全部失效",
+                        "obvious_hint": True,
+                    },
                    "gm_safety_settings": {
                        "description": "安全过滤器",
                        "type": "object",
@@ -1222,16 +1229,10 @@ CONFIG_METADATA_2 = {
                "type": "string",
                "hint": "安装插件依赖时，会使用 Python 的 pip 工具。这里可以填写额外的参数，如 `--break-system-package` 等。",
            },
-            "plugin_repo_mirror": {
-                "description": "插件仓库镜像",
+            "pypi_index_url": {
+                "description": "PyPI 软件仓库地址",
                "type": "string",
-                "hint": "已废弃，请使用管理面板->设置页的代理地址选择",
-                "obvious_hint": True,
-                "options": [
-                    "default",
-                    "https://ghp.ci/",
-                    "https://github-mirror.us.kg/",
-                ],
+                "hint": "安装 Python 依赖时请求的 PyPI 软件仓库地址。默认为 https://mirrors.aliyun.com/pypi/simple/",
            },
        },
    },
@@ -106,7 +106,7 @@ class AstrBotCoreLifecycle:
        await self.pipeline_scheduler.initialize()

        # 初始化更新器
-        self.astrbot_updator = AstrBotUpdator(self.astrbot_config["plugin_repo_mirror"])
+        self.astrbot_updator = AstrBotUpdator()

        # 初始化事件总线
        self.event_bus = EventBus(self.event_queue, self.pipeline_scheduler)
@@ -1,6 +1,8 @@
 import abc
 import asyncio
 import re
+import hashlib
+import uuid
 from dataclasses import dataclass
 from typing import List, Union, Optional, AsyncGenerator

@@ -402,8 +404,13 @@ class AstrMessageEvent(abc.ABC):
        Args:
            message (MessageChain): 消息链，具体使用方式请参考文档。
        """
+        # Leverage BLAKE2 hash function to generate a non-reversible hash of the sender ID for privacy.
+        hash_obj = hashlib.blake2b(self.get_sender_id().encode("utf-8"), digest_size=16)
+        sid = str(uuid.UUID(bytes=hash_obj.digest()))
        asyncio.create_task(
-            Metric.upload(msg_event_tick=1, adapter_name=self.platform_meta.name)
+            Metric.upload(
+                msg_event_tick=1, adapter_name=self.platform_meta.name, sid=sid
+            )
        )
        self._has_send_oper = True

@@ -30,7 +30,7 @@ class AiocqhttpMessageEvent(AstrMessageEvent):
                # convert to base64
                bs64 = await segment.convert_to_base64()
                d["data"] = {
-                    "file": bs64,
+                    "file": f"base64://{bs64}",
                }
            elif isinstance(segment, At):
                d["data"] = {
@@ -1,4 +1,5 @@
 import asyncio
+import re
 import sys
 import uuid

@@ -118,8 +119,6 @@ class TelegramPlatformAdapter(Platform):

            if commands:
                await self.client.set_my_commands(commands)
-                for cmd in commands:
-                    logger.debug(f"已注册指令: /{cmd.command} - {cmd.description}")

        except Exception as e:
            logger.error(f"向 Telegram 注册指令时发生错误: {e!s}")
@@ -167,6 +166,10 @@ class TelegramPlatformAdapter(Platform):
        if not cmd_name or cmd_name in skip_commands:
            return None

+        if not re.match(r"^[a-z0-9_]+$", cmd_name) or len(cmd_name) > 32:
+            logger.warning(f"跳过无法注册的命令: {cmd_name}")
+            return None
+
        # Build description.
        description = handler_metadata.desc or (
            f"指令组: {cmd_name} (包含多个子指令)" if is_group else f"指令: {cmd_name}"
@@ -155,7 +155,7 @@ class ProviderRequest:
        if self.image_urls:
            user_content = {
                "role": "user",
-                "content": [{"type": "text", "text": self.prompt}],
+                "content": [{"type": "text", "text": self.prompt if self.prompt else "[图片]"}],
            }
            for image_url in self.image_urls:
                if image_url.startswith("http"):
@@ -1,121 +1,54 @@
-import base64
-import aiohttp
-import json
-import random
 import asyncio
+import base64
+import json
+import logging
+import random
+from typing import Dict, List, Optional, AsyncGenerator
+
+from google import genai
+from google.genai import types
+from google.genai.errors import APIError
+
 import astrbot.core.message.components as Comp
-from astrbot.core.message.message_event_result import MessageChain
-from astrbot.core.utils.io import download_image_by_url
-from astrbot.core.db import BaseDatabase
-from astrbot.api.provider import Provider, Personality
 from astrbot import logger
-from astrbot.core.provider.func_tool_manager import FuncCall
-from typing import List
-from ..register import register_provider_adapter
+from astrbot.api.provider import Personality, Provider
+from astrbot.core.db import BaseDatabase
+from astrbot.core.message.message_event_result import MessageChain
 from astrbot.core.provider.entities import LLMResponse
+from astrbot.core.provider.func_tool_manager import FuncCall
+from astrbot.core.utils.io import download_image_by_url
+
+from ..register import register_provider_adapter


-class SimpleGoogleGenAIClient:
-    def __init__(self, api_key: str, api_base: str, timeout: int = 120) -> None:
-        self.api_key = api_key
-        if api_base.endswith("/"):
-            self.api_base = api_base[:-1]
-        else:
-            self.api_base = api_base
-        self.client = aiohttp.ClientSession(trust_env=True)
-        self.timeout = timeout
+class SuppressNonTextPartsWarning(logging.Filter):
+    """过滤 Gemini SDK 中的非文本部分警告"""

-    async def models_list(self) -> List[str]:
-        request_url = f"{self.api_base}/v1beta/models?key={self.api_key}"
-        async with self.client.get(request_url, timeout=self.timeout) as resp:
-            response = await resp.json()
+    def filter(self, record):
+        return "there are non-text parts in the response" not in record.getMessage()

-            models = []
-            for model in response["models"]:
-                if "generateContent" in model["supportedGenerationMethods"]:
-                    models.append(model["name"].replace("models/", ""))
-            return models

-    async def generate_content(
-        self,
-        contents: List[dict],
-        model: str = "gemini-1.5-flash",
-        system_instruction: str = "",
-        tools: dict = None,
-        modalities: List[str] = ["Text"],
-        safety_settings: List[dict] = [],
-    ):
-        payload = {}
-        if system_instruction:
-            payload["system_instruction"] = {"parts": {"text": system_instruction}}
-        if tools:
-            payload["tools"] = [tools]
-        payload["contents"] = contents
-        payload["generationConfig"] = {
-            "responseModalities": modalities,
-        }
-        payload["safetySettings"] = [
-            {"category": s["category"], "threshold": s["threshold"]}
-            for s in safety_settings
-        ]
-        logger.debug(f"payload: {payload}")
-        request_url = (
-            f"{self.api_base}/v1beta/models/{model}:generateContent?key={self.api_key}"
-        )
-        async with self.client.post(
-            request_url, json=payload, timeout=self.timeout
-        ) as resp:
-            if "application/json" in resp.headers.get("Content-Type"):
-                try:
-                    response = await resp.json()
-                except Exception as e:
-                    text = await resp.text()
-                    logger.error(f"Gemini 返回了非 json 数据: {text}")
-                    raise e
-                return response
-            else:
-                text = await resp.text()
-                logger.error(f"Gemini 返回了非 json 数据: {text}")
-                raise Exception("Gemini 返回了非 json 数据： ")
+logging.getLogger("google_genai.types").addFilter(SuppressNonTextPartsWarning())

-    async def stream_generate_content(
-        self,
-        contents: List[dict],
-        model: str = "gemini-1.5-flash",
-        system_instruction: str = "",
-        tools: dict = None,
-        modalities: List[str] = ["Text"],
-        safety_settings: List[dict] = [],
-    ):
-        payload = {}
-        if system_instruction:
-            payload["system_instruction"] = {"parts": {"text": system_instruction}}
-        if tools:
-            payload["tools"] = [tools]
-        payload["contents"] = contents
-        payload["generationConfig"] = {
-            "responseModalities": modalities,
-            "stream": True,
-        }
-        payload["safetySettings"] = [
-            {"category": s["category"], "threshold": s["threshold"]}
-            for s in safety_settings
-        ]
-        logger.debug(f"payload: {payload}")
-        request_url = (
-            f"{self.api_base}/v1beta/models/{model}:streamGenerateContent?key={self.api_key}"
-        )
-        async with self.client.post(
-            request_url, json=payload, timeout=self.timeout
-        ) as resp:
-            async for line in resp.content:
-                if line:
-                    yield line

@register_provider_adapter(
    "googlegenai_chat_completion", "Google Gemini Chat Completion 提供商适配器"
 )
 class ProviderGoogleGenAI(Provider):
+    CATEGORY_MAPPING = {
+        "harassment": types.HarmCategory.HARM_CATEGORY_HARASSMENT,
+        "hate_speech": types.HarmCategory.HARM_CATEGORY_HATE_SPEECH,
+        "sexually_explicit": types.HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT,
+        "dangerous_content": types.HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT,
+    }
+
+    THRESHOLD_MAPPING = {
+        "BLOCK_NONE": types.HarmBlockThreshold.BLOCK_NONE,
+        "BLOCK_ONLY_HIGH": types.HarmBlockThreshold.BLOCK_ONLY_HIGH,
+        "BLOCK_MEDIUM_AND_ABOVE": types.HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE,
+        "BLOCK_LOW_AND_ABOVE": types.HarmBlockThreshold.BLOCK_LOW_AND_ABOVE,
+    }
+
    def __init__(
        self,
        provider_config: dict,
@@ -131,183 +64,351 @@ class ProviderGoogleGenAI(Provider):
            db_helper,
            default_persona,
        )
-        self.chosen_api_key = None
        self.api_keys: List = provider_config.get("key", [])
-        self.chosen_api_key = self.api_keys[0] if len(self.api_keys) > 0 else None
-        self.timeout = provider_config.get("timeout", 180)
-        if isinstance(self.timeout, str):
-            self.timeout = int(self.timeout)
-        self.client = SimpleGoogleGenAIClient(
-            api_key=self.chosen_api_key,
-            api_base=provider_config.get("api_base", None),
-            timeout=self.timeout,
-        )
+        self.chosen_api_key: str = self.api_keys[0] if len(self.api_keys) > 0 else None
+        self.timeout: int = int(provider_config.get("timeout", 180))
+
+        self.api_base: Optional[str] = provider_config.get("api_base", None)
+        if self.api_base and self.api_base.endswith("/"):
+            self.api_base = self.api_base[:-1]
+
+        self._init_client()
        self.set_model(provider_config["model_config"]["model"])
+        self._init_safety_settings()

-        safety_mapping = {
-            "harassment": "HARM_CATEGORY_HARASSMENT",
-            "hate_speech": "HARM_CATEGORY_HATE_SPEECH",
-            "sexually_explicit": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
-            "dangerous_content": "HARM_CATEGORY_DANGEROUS_CONTENT",
-        }
+    def _init_client(self) -> None:
+        """初始化Gemini客户端"""
+        self.client = genai.Client(
+            api_key=self.chosen_api_key,
+            http_options=types.HttpOptions(
+                base_url=self.api_base,
+                timeout=self.timeout * 1000,  # 毫秒
+            ),
+        ).aio

-        self.safety_settings = []
+    def _init_safety_settings(self) -> None:
+        """初始化安全设置"""
        user_safety_config = self.provider_config.get("gm_safety_settings", {})
-        for config_key, harm_category in safety_mapping.items():
-            if threshold := user_safety_config.get(config_key):
-                self.safety_settings.append(
-                    {"category": harm_category, "threshold": threshold}
+        self.safety_settings = [
+            types.SafetySetting(
+                category=harm_category, threshold=self.THRESHOLD_MAPPING[threshold_str]
+            )
+            for config_key, harm_category in self.CATEGORY_MAPPING.items()
+            if (threshold_str := user_safety_config.get(config_key))
+            and threshold_str in self.THRESHOLD_MAPPING
+        ]
+
+    async def _handle_api_error(self, e: APIError, keys: List[str]) -> bool:
+        """处理API错误，返回是否需要重试"""
+        if e.code == 429 or "API key not valid" in e.message:
+            keys.remove(self.chosen_api_key)
+            if len(keys) > 0:
+                self.set_key(random.choice(keys))
+                logger.info(
+                    f"检测到 Key 异常({e.message})，正在尝试更换 API Key 重试... 当前 Key: {self.chosen_api_key[:12]}..."
                )
+                await asyncio.sleep(1)
+                return True
+            else:
+                logger.error(
+                    f"检测到 Key 异常({e.message})，且已没有可用的 Key。 当前 Key: {self.chosen_api_key[:12]}..."
+                )
+                raise Exception("达到了 Gemini 速率限制, 请稍后再试...")
+        else:
+            logger.error(
+                f"发生了错误(gemini_source)。Provider 配置如下: {self.provider_config}"
+            )
+            raise e

-    async def get_models(self):
-        return await self.client.models_list()
+    async def _prepare_query_config(
+        self,
+        tools: Optional[FuncCall] = None,
+        system_instruction: Optional[str] = None,
+        temperature: Optional[float] = 0.7,
+        modalities: Optional[List[str]] = None,
+    ) -> types.GenerateContentConfig:
+        """准备查询配置"""
+        if not modalities:
+            modalities = ["Text"]

-    async def _query(self, payloads: dict, tools: FuncCall) -> LLMResponse:
-        tool = None
-        if tools:
-            tool = tools.get_func_desc_google_genai_style()
-            if not tool:
-                tool = None
+        # 流式输出不支持图片模态
+        if (
+            self.provider_settings.get("streaming_response", False)
+            and "Image" in modalities
+        ):
+            logger.warning("流式输出不支持图片模态，已自动降级为文本模态")
+            modalities = ["Text"]

-        system_instruction = ""
+        tool_list = None
+        if self.provider_config.get("gm_native_coderunner", False):
+            if tools:
+                logger.warning("Gemini原生代码执行器已启用，函数工具将被忽略")
+            tool_list = [types.Tool(code_execution=types.ToolCodeExecution())]
+        elif tools and (func_desc := tools.get_func_desc_google_genai_style()):
+            tool_list = [
+                types.Tool(function_declarations=func_desc["function_declarations"])
+            ]
+
+        return types.GenerateContentConfig(
+            system_instruction=system_instruction,
+            temperature=temperature,
+            response_modalities=modalities,
+            tools=tool_list,
+            safety_settings=self.safety_settings if self.safety_settings else None,
+            automatic_function_calling=types.AutomaticFunctionCallingConfig(
+                disable=True
+            ),
+        )
+
+    @staticmethod
+    def _prepare_conversation(payloads: Dict) -> List[types.Content]:
+        """准备 Gemini SDK 的 Content 列表"""
+
+        def create_text_part(text: str) -> types.UserContent:
+            content_a = text if text else " "
+            if not text:
+                logger.warning("文本内容为空，已添加空格占位")
+            return types.UserContent(parts=[types.Part.from_text(text=content_a)])
+
+        def process_image_url(image_url_dict: dict) -> types.Part:
+            url = image_url_dict["url"]
+            mime_type = url.split(":")[1].split(";")[0]
+            image_bytes = base64.b64decode(url.split(",", 1)[1])
+            return types.Part.from_bytes(data=image_bytes, mime_type=mime_type)
+
+        gemini_contents: List[types.Content] = []
        for message in payloads["messages"]:
-            if message["role"] == "system":
-                system_instruction = message["content"]
-                break
+            role, content = message["role"], message.get("content")

-        google_genai_conversation = []
-        for message in payloads["messages"]:
-            if message["role"] == "user":
-                if isinstance(message["content"], str):
-                    if not message["content"]:
-                        message["content"] = " "
+            if role == "user":
+                if isinstance(content, str):
+                    gemini_contents.append(create_text_part(content))
+                elif isinstance(content, list):
+                    parts = [
+                        types.Part.from_text(text=item["text"] or " ")
+                        if item["type"] == "text"
+                        else process_image_url(item["image_url"])
+                        for item in content
+                    ]
+                    gemini_contents.append(types.UserContent(parts=parts))

-                    google_genai_conversation.append(
-                        {"role": "user", "parts": [{"text": message["content"]}]}
-                    )
-                elif isinstance(message["content"], list):
-                    # images
-                    parts = []
-                    for part in message["content"]:
-                        if part["type"] == "text":
-                            if not part["text"]:
-                                part["text"] = ""
-                            parts.append({"text": part["text"]})
-                        elif part["type"] == "image_url":
-                            parts.append(
-                                {
-                                    "inline_data": {
-                                        "mime_type": "image/jpeg",
-                                        "data": part["image_url"]["url"].replace(
-                                            "data:image/jpeg;base64,", ""
-                                        ),  # base64
-                                    }
-                                }
-                            )
-                    google_genai_conversation.append({"role": "user", "parts": parts})
-
-            elif message["role"] == "assistant":
-                if "content" in message:
-                    if not message["content"]:
-                        message["content"] = " "
-                    google_genai_conversation.append(
-                        {"role": "model", "parts": [{"text": message["content"]}]}
+            elif role == "assistant":
+                if content:
+                    gemini_contents.append(
+                        types.ModelContent(parts=[types.Part.from_text(text=content)])
                    )
                elif "tool_calls" in message:
-                    # tool calls in the last turn
-                    parts = []
-                    for tool_call in message["tool_calls"]:
-                        parts.append(
-                            {
-                                "functionCall": {
-                                    "name": tool_call["function"]["name"],
-                                    "args": json.loads(
-                                        tool_call["function"]["arguments"]
-                                    ),
-                                }
-                            }
-                        )
-                    google_genai_conversation.append({"role": "model", "parts": parts})
-            elif message["role"] == "tool":
-                parts = []
-                parts.append(
-                    {
-                        "functionResponse": {
-                            "name": message["tool_call_id"],
-                            "response": {
-                                "name": message["tool_call_id"],
-                                "content": message["content"],
-                            },
-                        }
-                    }
+                    gemini_contents.extend(
+                        [
+                            types.ModelContent(
+                                parts=[
+                                    types.Part.from_function_call(
+                                        name=tool["function"]["name"],
+                                        args=json.loads(tool["function"]["arguments"]),
+                                    )
+                                ]
+                            )
+                            for tool in message["tool_calls"]
+                        ]
+                    )
+                else:
+                    logger.warning("assistant 角色的消息内容为空，已添加空格占位")
+                    gemini_contents.append(
+                        types.ModelContent(parts=[types.Part.from_text(text=" ")])
+                    )
+
+            elif role == "tool":
+                gemini_contents.append(
+                    types.UserContent(
+                        parts=[
+                            types.Part.from_function_response(
+                                name=message["tool_call_id"],
+                                response={
+                                    "name": message["tool_call_id"],
+                                    "content": message["content"],
+                                },
+                            )
+                        ]
+                    )
                )
-                google_genai_conversation.append({"role": "user", "parts": parts})

-        logger.debug(f"google_genai_conversation: {google_genai_conversation}")
+        return gemini_contents

-        modalites = ["Text"]
-        if self.provider_config.get("gm_resp_image_modal", False):
-            modalites.append("Image")
+    @staticmethod
+    def _process_content_parts(
+        result: types.GenerateContentResponse, llm_response: LLMResponse
+    ) -> MessageChain:
+        """处理内容部分并构建消息链"""
+        finish_reason = result.candidates[0].finish_reason
+        result_parts: Optional[types.Part] = result.candidates[0].content.parts

-        loop = True
-        while loop:
-            loop = False
-            result = await self.client.generate_content(
-                contents=google_genai_conversation,
-                model=self.get_model(),
-                system_instruction=system_instruction,
-                tools=tool,
-                modalities=modalites,
-                safety_settings=self.safety_settings,
-            )
-            logger.debug(f"result: {result}")
+        if finish_reason == types.FinishReason.SAFETY:
+            raise Exception("模型生成内容未通过用户定义的内容安全检查")

-            # Developer instruction is not enabled for models/gemini-2.0-flash-exp
-            if "Developer instruction is not enabled" in str(result):
-                logger.warning(
-                    f"{self.get_model()} 不支持 system prompt, 已自动去除, 将会影响人格设置。"
-                )
-                system_instruction = ""
-                loop = True
+        if finish_reason in {
+            types.FinishReason.PROHIBITED_CONTENT,
+            types.FinishReason.SPII,
+            types.FinishReason.BLOCKLIST,
+            types.FinishReason.IMAGE_SAFETY,
+        }:
+            raise Exception("模型生成内容违反Gemini平台政策")

-            elif "Function calling is not enabled" in str(result):
-                logger.warning(
-                    f"{self.get_model()} 不支持函数调用，已自动去除，不影响使用。"
-                )
-                tool = None
-                loop = True
+        if not result_parts:
+            logger.debug(result.candidates)
+            raise Exception("API 返回的内容为空。")

-            elif "Multi-modal output is not supported" in str(result):
-                logger.warning(
-                    f"{self.get_model()} 不支持多模态输出，降级为文本模态重新请求。"
-                )
-                modalites = ["Text"]
-                loop = True
-
-            elif "candidates" not in result:
-                raise Exception("Gemini 返回异常结果: " + str(result))
-
-        candidates = result["candidates"][0]["content"]["parts"]
-        llm_response = LLMResponse("assistant")
        chain = []
-        for candidate in candidates:
-            if "text" in candidate:
-                chain.append(Comp.Plain(candidate["text"]))
-            elif "functionCall" in candidate:
-                llm_response.role = "tool"
-                llm_response.tools_call_args.append(candidate["functionCall"]["args"])
-                llm_response.tools_call_name.append(candidate["functionCall"]["name"])
-                llm_response.tools_call_ids.append(
-                    candidate["functionCall"]["name"]
-                )  # 没有 tool id
-            elif "inlineData" in candidate:
-                mime_type: str = candidate["inlineData"]["mimeType"]
-                if mime_type.startswith("image/"):
-                    chain.append(Comp.Image.fromBase64(candidate["inlineData"]["data"]))
+        part: types.Part

-        llm_response.result_chain = MessageChain(chain=chain)
+        # 暂时这样Fallback
+        if all(
+            part.inline_data and part.inline_data.mime_type.startswith("image/")
+            for part in result_parts
+        ):
+            chain.append(Comp.Plain("这是图片"))
+        for part in result_parts:
+            if part.text:
+                chain.append(Comp.Plain(part.text))
+            elif part.function_call:
+                llm_response.role = "tool"
+                llm_response.tools_call_name.append(part.function_call.name)
+                llm_response.tools_call_args.append(part.function_call.args)
+                # gemini 返回的 function_call.id 可能为 None
+                llm_response.tools_call_ids.append(
+                    part.function_call.id or part.function_call.name
+                )
+            elif part.inline_data and part.inline_data.mime_type.startswith("image/"):
+                chain.append(Comp.Image.fromBytes(part.inline_data.data))
+        return MessageChain(chain=chain)
+
+    async def _query(
+        self, payloads: dict, tools: FuncCall, temperature: float = 0.7
+    ) -> LLMResponse:
+        """非流式请求 Gemini API"""
+        system_instruction = next(
+            (msg["content"] for msg in payloads["messages"] if msg["role"] == "system"),
+            None,
+        )
+
+        modalities = ["Text"]
+        if self.provider_config.get("gm_resp_image_modal", False):
+            modalities.append("Image")
+
+        conversation = self._prepare_conversation(payloads)
+
+        result: Optional[types.GenerateContentResponse] = None
+        while True:
+            try:
+                config = await self._prepare_query_config(
+                    tools, system_instruction, temperature, modalities
+                )
+                result = await self.client.models.generate_content(
+                    model=self.get_model(),
+                    contents=conversation,
+                    config=config,
+                )
+
+                if result.candidates[0].finish_reason == types.FinishReason.RECITATION:
+                    if temperature > 2:
+                        raise Exception("温度参数已超过最大值2，仍然发生recitation")
+                    temperature += 0.2
+                    logger.warning(
+                        f"发生了recitation，正在提高温度至{temperature:.1f}重试..."
+                    )
+                    continue
+
+                break
+
+            except APIError as e:
+                if "Developer instruction is not enabled" in e.message:
+                    logger.warning(
+                        f"{self.get_model()} 不支持 system prompt，已自动去除(影响人格设置)"
+                    )
+                    system_instruction = None
+                elif "Function calling is not enabled" in e.message:
+                    logger.warning(f"{self.get_model()} 不支持函数调用，已自动去除")
+                    tools = None
+                elif (
+                    "Multi-modal output is not supported" in e.message
+                    or "Model does not support the requested response modalities"
+                    in e.message
+                ):
+                    logger.warning(
+                        f"{self.get_model()} 不支持多模态输出，降级为文本模态"
+                    )
+                    modalities = ["Text"]
+                else:
+                    raise
+                continue
+
+        llm_response = LLMResponse("assistant")
+        llm_response.result_chain = self._process_content_parts(result, llm_response)
        return llm_response

+    async def _query_stream(
+        self, payloads: dict, tools: FuncCall, temperature: float = 0.7
+    ) -> AsyncGenerator[LLMResponse, None]:
+        """流式请求 Gemini API"""
+        system_instruction = next(
+            (msg["content"] for msg in payloads["messages"] if msg["role"] == "system"),
+            None,
+        )
+
+        conversation = self._prepare_conversation(payloads)
+
+        result = None
+        while True:
+            try:
+                config = await self._prepare_query_config(
+                    tools, system_instruction, temperature
+                )
+                result = await self.client.models.generate_content_stream(
+                    model=self.get_model(),
+                    contents=conversation,
+                    config=config,
+                )
+                break
+            except APIError as e:
+                if "Developer instruction is not enabled" in e.message:
+                    logger.warning(
+                        f"{self.get_model()} 不支持 system prompt，已自动去除(影响人格设置)"
+                    )
+                    system_instruction = None
+                elif "Function calling is not enabled" in e.message:
+                    logger.warning(f"{self.get_model()} 不支持函数调用，已自动去除")
+                    tools = None
+                else:
+                    raise
+                continue
+
+        async for chunk in result:
+            llm_response = LLMResponse("assistant", is_chunk=True)
+
+            if chunk.candidates[0].content.parts and any(
+                part.function_call for part in chunk.candidates[0].content.parts
+            ):
+                llm_response = LLMResponse("assistant", is_chunk=False)
+                llm_response.result_chain = self._process_content_parts(
+                    chunk, llm_response
+                )
+                yield llm_response
+                break
+
+            if chunk.text:
+                llm_response.result_chain = MessageChain(chain=[Comp.Plain(chunk.text)])
+                yield llm_response
+
+            if chunk.candidates[0].finish_reason:
+                llm_response = LLMResponse("assistant", is_chunk=False)
+                if not chunk.candidates[0].content.parts:
+                    llm_response.result_chain = MessageChain(chain=[Comp.Plain(" ")])
+                else:
+                    llm_response.result_chain = self._process_content_parts(
+                        chunk, llm_response
+                    )
+                yield llm_response
+                break
+
    async def text_chat(
        self,
        prompt: str,
@@ -320,7 +421,6 @@ class ProviderGoogleGenAI(Provider):
        **kwargs,
    ) -> LLMResponse:
        new_record = await self.assemble_context(prompt, image_urls)
-        context_query = []
        context_query = [*contexts, new_record]
        if system_prompt:
            context_query.insert(0, {"role": "system", "content": system_prompt})
@@ -337,82 +437,92 @@ class ProviderGoogleGenAI(Provider):
        model_config["model"] = self.get_model()

        payloads = {"messages": context_query, **model_config}
-        llm_response = None

        retry = 10
        keys = self.api_keys.copy()
-        chosen_key = random.choice(keys)
+        temp = kwargs.get("temperature", 0.7)  # 暂定默认温度为0.7

-        for i in range(retry):
+        for _ in range(retry):
            try:
-                self.client.api_key = chosen_key
-                llm_response = await self._query(payloads, func_tool)
+                return await self._query(payloads, func_tool, temp)
+            except APIError as e:
+                if await self._handle_api_error(e, keys):
+                    continue
                break
-            except Exception as e:
-                if "429" in str(e) or "API key not valid" in str(e):
-                    keys.remove(chosen_key)
-                    if len(keys) > 0:
-                        chosen_key = random.choice(keys)
-                        logger.info(
-                            f"检测到 Key 异常({str(e)})，正在尝试更换 API Key 重试... 当前 Key: {chosen_key[:12]}..."
-                        )
-                        await asyncio.sleep(1)
-                        continue
-                    else:
-                        logger.error(
-                            f"检测到 Key 异常({str(e)})，且已没有可用的 Key。 当前 Key: {chosen_key[:12]}..."
-                        )
-                        raise Exception("达到了 Gemini 速率限制, 请稍后再试...")
-                else:
-                    logger.error(
-                        f"发生了错误(gemini_source)。Provider 配置如下: {self.provider_config}"
-                    )
-                    raise e
-
-        return llm_response

    async def text_chat_stream(
        self,
-        prompt,
-        session_id=None,
-        image_urls=...,
-        func_tool=None,
-        contexts=...,
+        prompt: str,
+        session_id: str = None,
+        image_urls: List[str] = [],
+        func_tool: FuncCall = None,
+        contexts=[],
        system_prompt=None,
        tool_calls_result=None,
        **kwargs,
-    ):
-        # raise NotImplementedError("This method is not implemented yet.")
-        # 调用 text_chat 模拟流式
-        llm_response = await self.text_chat(
-            prompt=prompt,
-            session_id=session_id,
-            image_urls=image_urls,
-            func_tool=func_tool,
-            contexts=contexts,
-            system_prompt=system_prompt,
-            tool_calls_result=tool_calls_result,
-        )
-        llm_response.is_chunk = True
-        yield llm_response
-        llm_response.is_chunk = False
-        yield llm_response
+    ) -> AsyncGenerator[LLMResponse, None]:
+        new_record = await self.assemble_context(prompt, image_urls)
+        context_query = [*contexts, new_record]
+        if system_prompt:
+            context_query.insert(0, {"role": "system", "content": system_prompt})
+
+        for part in context_query:
+            if "_no_save" in part:
+                del part["_no_save"]
+
+        # tool calls result
+        if tool_calls_result:
+            context_query.extend(tool_calls_result.to_openai_messages())
+
+        model_config = self.provider_config.get("model_config", {})
+        model_config["model"] = self.get_model()
+
+        payloads = {"messages": context_query, **model_config}
+
+        retry = 10
+        keys = self.api_keys.copy()
+        temp = kwargs.get("temperature", 0.7)  # 暂定默认温度为0.7
+
+        for _ in range(retry):
+            try:
+                async for response in self._query_stream(payloads, func_tool, temp):
+                    yield response
+                break
+            except APIError as e:
+                if await self._handle_api_error(e, keys):
+                    continue
+                break
+
+    async def get_models(self):
+        try:
+            models = await self.client.models.list()
+            return [
+                m.name.replace("models/", "")
+                for m in models
+                if "generateContent" in m.supported_actions
+            ]
+        except APIError as e:
+            raise Exception(f"获取模型列表失败: {e.message}")

    def get_current_key(self) -> str:
-        return self.client.api_key
+        return self.chosen_api_key

    def get_keys(self) -> List[str]:
        return self.api_keys

    def set_key(self, key):
-        self.client.api_key = key
+        self.chosen_api_key = key
+        self._init_client()

    async def assemble_context(self, text: str, image_urls: List[str] = None):
        """
        组装上下文。
        """
        if image_urls:
-            user_content = {"role": "user", "content": [{"type": "text", "text": text}]}
+            user_content = {
+                "role": "user",
+                "content": [{"type": "text", "text": text if text else "[图片]"}],
+            }
            for image_url in image_urls:
                if image_url.startswith("http"):
                    image_path = await download_image_by_url(image_url)
@@ -444,5 +554,4 @@ class ProviderGoogleGenAI(Provider):
        return ""

    async def terminate(self):
-        await self.client.client.close()
        logger.info("Google GenAI 适配器已终止。")
@@ -505,7 +505,7 @@ class ProviderOpenAIOfficial(Provider):
    async def assemble_context(self, text: str, image_urls: List[str] = None) -> dict:
        """组装成符合 OpenAI 格式的 role 为 user 的消息段"""
        if image_urls:
-            user_content = {"role": "user", "content": [{"type": "text", "text": text}]}
+            user_content = {"role": "user", "content": [{"type": "text", "text": text if text else "[图片]"}]}
            for image_url in image_urls:
                if image_url.startswith("http"):
                    image_path = await download_image_by_url(image_url)
@@ -28,7 +28,7 @@ from .filter.permission import PermissionTypeFilter, PermissionType

 class PluginManager:
    def __init__(self, context: Context, config: AstrBotConfig):
-        self.updator = PluginUpdator(config["plugin_repo_mirror"])
+        self.updator = PluginUpdator()

        self.context = context
        self.context._star_manager = self
@@ -1,10 +1,42 @@
 import aiohttp
 import sys
+import os
+import socket
+import uuid
 from astrbot.core.config import VERSION
 from astrbot.core import db_helper, logger


 class Metric:
+    _iid_cache = None
+
+    @staticmethod
+    def get_installation_id():
+        """获取或创建一个唯一的安装ID"""
+        if Metric._iid_cache is not None:
+            return Metric._iid_cache
+
+        config_dir = os.path.join(os.path.expanduser("~"), ".astrbot")
+        id_file = os.path.join(config_dir, ".installation_id")
+
+        if os.path.exists(id_file):
+            try:
+                with open(id_file, "r") as f:
+                    Metric._iid_cache = f.read().strip()
+                    return Metric._iid_cache
+            except Exception:
+                pass
+        try:
+            os.makedirs(config_dir, exist_ok=True)
+            installation_id = str(uuid.uuid4())
+            with open(id_file, "w") as f:
+                f.write(installation_id)
+            Metric._iid_cache = installation_id
+            return installation_id
+        except Exception:
+            Metric._iid_cache = "null"
+            return "null"
+
    @staticmethod
    async def upload(**kwargs):
        """
@@ -16,6 +48,14 @@ class Metric:
        kwargs["v"] = VERSION
        kwargs["os"] = sys.platform
        payload = {"metrics_data": kwargs}
+        try:
+            kwargs["hn"] = socket.gethostname()
+        except Exception:
+            pass
+        try:
+            kwargs["iid"] = Metric.get_installation_id()
+        except Exception:
+            pass
        try:
            if "adapter_name" in kwargs:
                db_helper.insert_platform_metrics({kwargs["adapter_name"]: 1})
@@ -24,6 +64,7 @@ class Metric:
        except Exception as e:
            logger.error(f"保存指标到数据库失败: {e}")
            pass
+        print(f"上传指标: {payload}")

        try:
            async with aiohttp.ClientSession(trust_env=True) as session:
@@ -5,8 +5,9 @@ logger = logging.getLogger("astrbot")


 class PipInstaller:
-    def __init__(self, pip_install_arg: str):
+    def __init__(self, pip_install_arg: str, pypi_index_url: str = None):
        self.pip_install_arg = pip_install_arg
+        self.pypi_index_url = pypi_index_url

    def install(
        self,
@@ -20,10 +21,9 @@ class PipInstaller:
        elif requirements_path:
            args.extend(["-r", requirements_path])

-        if not mirror:
-            mirror = "https://mirrors.aliyun.com/pypi/simple/"
+        index_url = mirror or self.pypi_index_url or "https://pypi.org/simple"

-        args.extend(["--trusted-host", "mirrors.aliyun.com", "-i", mirror])
+        args.extend(["--trusted-host", "mirrors.aliyun.com", "-i", index_url])

        if self.pip_install_arg:
            args.extend(self.pip_install_arg.split())
@@ -136,10 +136,11 @@ class UpdateRoute(Route):

        data = await request.json
        package = data.get("package", "")
+        mirror = data.get("mirror", None)
        if not package:
            return Response().error("缺少参数 package 或不合法。").__dict__
        try:
-            pip_installer.install(package)
+            pip_installer.install(package, mirror=mirror)
            return Response().ok(None, "安装成功。").__dict__
        except Exception as e:
            logger.error(f"/api/update_pip: {traceback.format_exc()}")
@@ -27,8 +27,8 @@ import axios from 'axios';
            </v-card-title>
            <v-card-text>
              <v-text-field v-model="pipInstallPayload.package" label="*库名，如 llmtuner" variant="outlined"></v-text-field>
-              <v-text-field v-model="pipInstallPayload.mirror" label="镜像站链接（可选）" variant="outlined"></v-text-field>
-              <small>如果不填镜像站链接，默认使用阿里云镜像：https://mirrors.aliyun.com/pypi/simple/</small>
+              <v-text-field v-model="pipInstallPayload.mirror" label="强制 PyPI 软件仓库链接（可选）" variant="outlined"></v-text-field>
+              <small>强制 PyPI 软件仓库链接 > 配置项 `PyPI 软件仓库地址`</small>
              <div>
                <small>{{ status }}</small>
              </div>
@@ -839,10 +839,30 @@ export default {

        // 格式化消息内容
        formatMessage(content) {
-            if (!content) return '空消息';

+            // content 可能是数组
+            // [{"type": "image_url", "image_url": {"url": url_or_base64}}, {"type": "text", "text": "text"}]
+
+            let final_content = content;
+            if (Array.isArray(content)) {
+                // 处理数组内容
+                final_content = content.map(item => {
+                    if (item.type === 'image_url') {
+                        return `<img src="${item.image_url.url}" alt="Image" />`;
+                    } else if (item.type === 'text') {
+                        return item.text;
+                    }
+                    return '';
+                }).join('\n');
+            } else if (typeof content === 'object') {
+                // 处理对象内容
+                final_content = Object.values(content).join('');
+            } else if (typeof content === 'string') {
+                // 处理字符串内容
+                final_content = content;
+            } else if (!final_content) return '空消息';
            // 使用marked处理Markdown格式
-            return marked(content);
+            return marked(final_content);
        },

        // 显示成功消息
@@ -19,6 +19,7 @@ dependencies = [
    "defusedxml>=0.7.1",
    "dingtalk-stream>=0.22.1",
    "docstring-parser>=0.16",
+    "google-genai>=1.10.0",
    "googlesearch-python>=1.3.0",
    "lark-oapi>=1.4.12",
    "lxml-html-clean>=0.4.1",
@@ -29,4 +29,5 @@ defusedxml
 mcp
 certifi
 pip
-telegramify-markdown
+telegramify-markdown
+google-genai
@@ -209,6 +209,7 @@ dependencies = [
    { name = "defusedxml" },
    { name = "dingtalk-stream" },
    { name = "docstring-parser" },
+    { name = "google-genai" },
    { name = "googlesearch-python" },
    { name = "lark-oapi" },
    { name = "lxml-html-clean" },
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