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Author SHA1 Message Date
Soulter
54340cca18 stage 2025-10-10 19:41:18 +08:00
16 changed files with 291 additions and 201 deletions

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@@ -6,7 +6,7 @@ import os
from astrbot.core.utils.astrbot_path import get_astrbot_data_path
VERSION = "4.3.3"
VERSION = "4.3.2"
DB_PATH = os.path.join(get_astrbot_data_path(), "data_v4.db")
# 默认配置
@@ -1056,7 +1056,6 @@ CONFIG_METADATA_2 = {
"timeout": "20",
},
"阿里云百炼 TTS(API)": {
"hint": "API Key 从 https://bailian.console.aliyun.com/?tab=model#/api-key 获取。模型和音色的选择文档请参考: 阿里云百炼语音合成音色名称。具体可参考 https://help.aliyun.com/zh/model-studio/speech-synthesis-and-speech-recognition",
"id": "dashscope_tts",
"provider": "dashscope",
"type": "dashscope_tts",
@@ -1436,7 +1435,11 @@ CONFIG_METADATA_2 = {
"description": "服务订阅密钥",
"hint": "Azure_TTS 服务的订阅密钥(注意不是令牌)",
},
"dashscope_tts_voice": {"description": "音色", "type": "string"},
"dashscope_tts_voice": {
"description": "语音合成模型",
"type": "string",
"hint": "阿里云百炼语音合成模型名称。具体可参考 https://help.aliyun.com/zh/model-studio/developer-reference/cosyvoice-python-api 等内容",
},
"gm_resp_image_modal": {
"description": "启用图片模态",
"type": "bool",

View File

@@ -68,8 +68,7 @@ class Provider(AbstractProvider):
def get_keys(self) -> List[str]:
"""获得提供商 Key"""
keys = self.provider_config.get("key", [""])
return keys or [""]
return self.provider_config.get("key", [])
@abc.abstractmethod
def set_key(self, key: str):

View File

@@ -33,7 +33,7 @@ class ProviderAnthropic(Provider):
)
self.chosen_api_key: str = ""
self.api_keys: List = super().get_keys()
self.api_keys: List = provider_config.get("key", [])
self.chosen_api_key = self.api_keys[0] if len(self.api_keys) > 0 else ""
self.base_url = provider_config.get("api_base", "https://api.anthropic.com")
self.timeout = provider_config.get("timeout", 120)
@@ -70,13 +70,9 @@ class ProviderAnthropic(Provider):
{
"type": "tool_use",
"name": tool_call["function"]["name"],
"input": (
json.loads(tool_call["function"]["arguments"])
if isinstance(
tool_call["function"]["arguments"], str
)
else tool_call["function"]["arguments"]
),
"input": json.loads(tool_call["function"]["arguments"])
if isinstance(tool_call["function"]["arguments"], str)
else tool_call["function"]["arguments"],
"id": tool_call["id"],
}
)
@@ -359,11 +355,9 @@ class ProviderAnthropic(Provider):
"source": {
"type": "base64",
"media_type": mime_type,
"data": (
image_data.split("base64,")[1]
if "base64," in image_data
else image_data
),
"data": image_data.split("base64,")[1]
if "base64," in image_data
else image_data,
},
}
)

View File

@@ -1,22 +1,10 @@
import asyncio
import base64
import logging
import os
import uuid
from typing import Optional, Tuple
import aiohttp
import dashscope
from dashscope.audio.tts_v2 import AudioFormat, SpeechSynthesizer
try:
from dashscope.aigc.multimodal_conversation import MultiModalConversation
except (
ImportError
): # pragma: no cover - older dashscope versions without Qwen TTS support
MultiModalConversation = None
from ..entities import ProviderType
import uuid
import asyncio
from dashscope.audio.tts_v2 import *
from ..provider import TTSProvider
from ..entities import ProviderType
from ..register import register_provider_adapter
from astrbot.core.utils.astrbot_path import get_astrbot_data_path
@@ -38,112 +26,16 @@ class ProviderDashscopeTTSAPI(TTSProvider):
dashscope.api_key = self.chosen_api_key
async def get_audio(self, text: str) -> str:
model = self.get_model()
if not model:
raise RuntimeError("Dashscope TTS model is not configured.")
temp_dir = os.path.join(get_astrbot_data_path(), "temp")
os.makedirs(temp_dir, exist_ok=True)
if self._is_qwen_tts_model(model):
audio_bytes, ext = await self._synthesize_with_qwen_tts(model, text)
else:
audio_bytes, ext = await self._synthesize_with_cosyvoice(model, text)
if not audio_bytes:
raise RuntimeError(
"Audio synthesis failed, returned empty content. The model may not be supported or the service is unavailable."
)
path = os.path.join(temp_dir, f"dashscope_tts_{uuid.uuid4()}{ext}")
with open(path, "wb") as f:
f.write(audio_bytes)
return path
def _call_qwen_tts(self, model: str, text: str):
if MultiModalConversation is None:
raise RuntimeError(
"dashscope SDK missing MultiModalConversation. Please upgrade the dashscope package to use Qwen TTS models."
)
kwargs = {
"model": model,
"text": text,
"api_key": self.chosen_api_key,
"voice": self.voice or "Cherry",
}
if not self.voice:
logging.warning(
"No voice specified for Qwen TTS model, using default 'Cherry'."
)
return MultiModalConversation.call(**kwargs)
async def _synthesize_with_qwen_tts(
self, model: str, text: str
) -> Tuple[Optional[bytes], str]:
loop = asyncio.get_event_loop()
response = await loop.run_in_executor(None, self._call_qwen_tts, model, text)
audio_bytes = await self._extract_audio_from_response(response)
if not audio_bytes:
raise RuntimeError(
f"Audio synthesis failed for model '{model}'. {response}"
)
ext = ".wav"
return audio_bytes, ext
async def _extract_audio_from_response(self, response) -> Optional[bytes]:
output = getattr(response, "output", None)
audio_obj = getattr(output, "audio", None) if output is not None else None
if not audio_obj:
return None
data_b64 = getattr(audio_obj, "data", None)
if data_b64:
try:
return base64.b64decode(data_b64)
except (ValueError, TypeError):
logging.error("Failed to decode base64 audio data.")
return None
url = getattr(audio_obj, "url", None)
if url:
return await self._download_audio_from_url(url)
return None
async def _download_audio_from_url(self, url: str) -> Optional[bytes]:
if not url:
return None
timeout = max(self.timeout_ms / 1000, 1) if self.timeout_ms else 20
try:
async with aiohttp.ClientSession() as session:
async with session.get(
url, timeout=aiohttp.ClientTimeout(total=timeout)
) as response:
return await response.read()
except (aiohttp.ClientError, asyncio.TimeoutError, OSError) as e:
logging.error(f"Failed to download audio from URL {url}: {e}")
return None
async def _synthesize_with_cosyvoice(
self, model: str, text: str
) -> Tuple[Optional[bytes], str]:
synthesizer = SpeechSynthesizer(
model=model,
path = os.path.join(temp_dir, f"dashscope_tts_{uuid.uuid4()}.wav")
self.synthesizer = SpeechSynthesizer(
model=self.get_model(),
voice=self.voice,
format=AudioFormat.WAV_24000HZ_MONO_16BIT,
)
loop = asyncio.get_event_loop()
audio_bytes = await loop.run_in_executor(
None, synthesizer.call, text, self.timeout_ms
audio = await asyncio.get_event_loop().run_in_executor(
None, self.synthesizer.call, text, self.timeout_ms
)
if not audio_bytes:
resp = synthesizer.get_response()
if resp and isinstance(resp, dict):
raise RuntimeError(
f"Audio synthesis failed for model '{model}'. {resp}".strip()
)
return audio_bytes, ".wav"
def _is_qwen_tts_model(self, model: str) -> bool:
model_lower = model.lower()
return "tts" in model_lower and model_lower.startswith("qwen")
with open(path, "wb") as f:
f.write(audio)
return path

View File

@@ -3,7 +3,7 @@ import base64
import json
import logging
import random
from typing import Optional, List
from typing import Optional
from collections.abc import AsyncGenerator
from google import genai
@@ -60,7 +60,7 @@ class ProviderGoogleGenAI(Provider):
provider_settings,
default_persona,
)
self.api_keys: List = super().get_keys()
self.api_keys: list = provider_config.get("key", [])
self.chosen_api_key: str = self.api_keys[0] if len(self.api_keys) > 0 else ""
self.timeout: int = int(provider_config.get("timeout", 180))
@@ -218,21 +218,19 @@ class ProviderGoogleGenAI(Provider):
response_modalities=modalities,
tools=tool_list,
safety_settings=self.safety_settings if self.safety_settings else None,
thinking_config=(
types.ThinkingConfig(
thinking_budget=min(
int(
self.provider_config.get("gm_thinking_config", {}).get(
"budget", 0
)
),
24576,
thinking_config=types.ThinkingConfig(
thinking_budget=min(
int(
self.provider_config.get("gm_thinking_config", {}).get(
"budget", 0
)
),
)
if "gemini-2.5-flash" in self.get_model()
and hasattr(types.ThinkingConfig, "thinking_budget")
else None
),
24576,
),
)
if "gemini-2.5-flash" in self.get_model()
and hasattr(types.ThinkingConfig, "thinking_budget")
else None,
automatic_function_calling=types.AutomaticFunctionCallingConfig(
disable=True
),
@@ -276,11 +274,9 @@ class ProviderGoogleGenAI(Provider):
if role == "user":
if isinstance(content, list):
parts = [
(
types.Part.from_text(text=item["text"] or " ")
if item["type"] == "text"
else process_image_url(item["image_url"])
)
types.Part.from_text(text=item["text"] or " ")
if item["type"] == "text"
else process_image_url(item["image_url"])
for item in content
]
else:

View File

@@ -38,7 +38,7 @@ class ProviderOpenAIOfficial(Provider):
default_persona,
)
self.chosen_api_key = None
self.api_keys: List = super().get_keys()
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", 120)
if isinstance(self.timeout, str):

View File

@@ -65,12 +65,12 @@ class SessionManagementRoute(Route):
persona_name = data["persona_name"]
# 处理 persona 显示
if persona_name is None:
if conv_persona_id is None:
if default_persona := persona_mgr.selected_default_persona_v3:
persona_name = default_persona["name"]
else:
persona_name = "[%None]"
if conv_persona_id == "[%None]":
persona_name = "无人格"
else:
default_persona = persona_mgr.selected_default_persona_v3
if default_persona:
persona_name = default_persona["name"]
session_info = {
"session_id": session_id,

View File

@@ -1,12 +0,0 @@
# What's Changed
1. fix: 修复了代码执行器插件不能正确获得发送来文件的问题 ([#2970](https://github.com/Soulter/AstrBot/issues/2970))
2. fix: 修改的 DeepSeek 默认 modalities避免默认勾选图像导致的报错。 ([#2963](https://github.com/Soulter/AstrBot/issues/2963))
3. fix: 事件钩子终止事件传播后不继续执行 ([#2989](https://github.com/Soulter/AstrBot/issues/2989))
4. fix: 启动了 TTS 但未配置 TTS 模型时At 和 Reply 发送人无效
5. fix: 修复 session-management 中人格错误的显示为默认人格的问题 ([#3000](https://github.com/Soulter/AstrBot/issues/3000))
6. fix: 修复了删除对话时,聊天增强中的记录未被清除,导致新对话中仍然出现之前的聊天记录。 ([#3002](https://github.com/Soulter/AstrBot/issues/3002))
7. fix: 修复阿里云百炼平台 TTS 下接入 CosyVoice V2, Qwen TTS 生成报错的问题 ([#2964](https://github.com/Soulter/AstrBot/issues/2964))
8. perf: 优化 SQLite 参数配置,对话和会话管理增加输入防抖机制 ([#2969](https://github.com/Soulter/AstrBot/issues/2969))
9. feat: 在新对话中重用先前的对话人格设置 ([#3005](https://github.com/Soulter/AstrBot/issues/3005))
10. feat: 从 WebUI 更新后清除浏览器缓存 ([#2958](https://github.com/Soulter/AstrBot/issues/2958))

View File

@@ -41,17 +41,6 @@ class ConversationCommands:
self.context = context
self.ltm = ltm
async def _get_current_persona_id(self, session_id):
curr = await self.context.conversation_manager.get_curr_conversation_id(
session_id
)
if not curr:
return None
conv = await self.context.conversation_manager.get_conversation(
session_id, curr
)
return conv.persona_id
def ltm_enabled(self, event: AstrMessageEvent):
if not self.ltm:
return False
@@ -266,9 +255,8 @@ class ConversationCommands:
)
return
cpersona = await self._get_current_persona_id(message.unified_msg_origin)
cid = await self.context.conversation_manager.new_conversation(
message.unified_msg_origin, message.get_platform_id(), persona_id=cpersona
message.unified_msg_origin, message.get_platform_id()
)
# 长期记忆
@@ -302,10 +290,8 @@ class ConversationCommands:
session_id=sid,
)
)
cpersona = await self._get_current_persona_id(session)
cid = await self.context.conversation_manager.new_conversation(
session, message.get_platform_id(), persona_id=cpersona
session, message.get_platform_id()
)
message.set_result(
MessageEventResult().message(
@@ -448,9 +434,8 @@ class ConversationCommands:
await self.context.conversation_manager.delete_conversation(
message.unified_msg_origin, session_curr_cid
)
ret = "删除当前对话成功。不再处于对话状态,使用 /switch 序号 切换到其他对话或 /new 创建。"
if self.ltm and self.ltm_enabled(message):
cnt = await self.ltm.remove_session(event=message)
ret += f"\n聊天增强: 已清除 {cnt} 条聊天记录。"
message.set_result(MessageEventResult().message(ret))
message.set_result(
MessageEventResult().message(
"删除当前对话成功。不再处于对话状态,使用 /switch 序号 切换到其他对话或 /new 创建。"
)
)

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@@ -0,0 +1,20 @@
from dataclasses import dataclass
@dataclass
class Emotion:
"""描述了一个情绪状态"""
energy: float
valence: float
arousal: float
@dataclass
class EmotionLog:
"""描述了一条情绪维度变化的日志"""
timestamp: int
field: str
value: float
reason: str = ""

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@@ -0,0 +1,9 @@
from dataclasses import dataclass
from .emotion import Emotion
@dataclass
class Soul:
emotion: Emotion
emotion_logs: list[Emotion] | None = None

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@@ -0,0 +1,7 @@
from dataclasses import dataclass
@dataclass
class Event:
event_type: str
content: dict

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@@ -0,0 +1,122 @@
import datetime
import uuid
from ...runner import EliosEventHandler
from collections import defaultdict
from astrbot.api.event import AstrMessageEvent
from astrbot.api.all import Context
from astrbot.api.message_components import Plain, Image
from astrbot.api.provider import Provider
from astrbot import logger
class AstrImplEventHandler(EliosEventHandler):
def __init__(self, ctx: Context) -> None:
self.ctx = ctx
self.session_chats = defaultdict(list)
self.session_mentioned_arousal = defaultdict(float)
def cfg(self, event: AstrMessageEvent):
cfg = self.ctx.get_config(umo=event.unified_msg_origin)
tiny_model_prov_id = cfg.get("tiny_model_provider_id")
interest_points = cfg.get("interest_points", [])
try:
max_cnt = int(cfg["provider_ltm_settings"]["group_message_max_cnt"])
except BaseException as e:
logger.error(e)
max_cnt = 300
image_caption = (
True
if cfg["provider_settings"]["default_image_caption_provider_id"]
else False
)
image_caption_prompt = cfg["provider_settings"]["image_caption_prompt"]
image_caption_provider_id = cfg["provider_settings"][
"default_image_caption_provider_id"
]
active_reply = cfg["provider_ltm_settings"]["active_reply"]
enable_active_reply = active_reply.get("enable", False)
ar_method = active_reply["method"]
ar_possibility = active_reply["possibility_reply"]
ar_prompt = active_reply.get("prompt", "")
ar_whitelist = active_reply.get("whitelist", [])
ar_keywords = active_reply.get("keywords", [])
ret = {
"max_cnt": max_cnt,
"image_caption": image_caption,
"image_caption_prompt": image_caption_prompt,
"image_caption_provider_id": image_caption_provider_id,
"enable_active_reply": enable_active_reply,
"ar_method": ar_method,
"ar_possibility": ar_possibility,
"ar_prompt": ar_prompt,
"ar_whitelist": ar_whitelist,
"ar_keywords": ar_keywords,
"interest_points": interest_points,
"tiny_model_prov_id": tiny_model_prov_id,
}
return ret
async def append_session_chats(self, event: AstrMessageEvent, cfg) -> None:
comps = event.get_messages()
datetime_str = datetime.datetime.now().strftime("%H:%M:%S")
final_message = f"[{event.message_obj.sender.nickname}/{datetime_str}]: "
for comp in comps:
if isinstance(comp, Plain):
final_message += f" {comp.text}"
elif isinstance(comp, Image):
image_url = comp.url if comp.url else comp.file
if cfg["image_caption"] and image_url:
try:
caption = await self.get_image_caption(
image_url,
cfg["image_caption_provider_id"],
cfg["image_caption_prompt"],
)
final_message += f" [Image: {caption}]"
except Exception as e:
logger.error(f"获取图片描述失败: {e}")
else:
final_message += " [Image]"
self.session_chats[event.unified_msg_origin].append(final_message)
logger.debug(f"添加会话 {event.unified_msg_origin} 的对话记录: {final_message}")
if len(self.session_chats[event.unified_msg_origin]) > cfg["max_cnt"]:
self.session_chats[event.unified_msg_origin].pop(0)
async def get_image_caption(
self, image_url: str, image_caption_provider_id: str, image_caption_prompt: str
) -> str:
if not image_caption_provider_id:
provider = self.ctx.get_using_provider()
else:
provider = self.ctx.get_provider_by_id(image_caption_provider_id)
if not provider:
raise Exception(f"没有找到 ID 为 {image_caption_provider_id} 的提供商")
if not isinstance(provider, Provider):
raise Exception(
f"提供商类型错误, {image_caption_provider_id} 不是 Provider 类型"
)
response = await provider.text_chat(
prompt=image_caption_prompt,
session_id=uuid.uuid4().hex,
image_urls=[image_url],
persist=False,
)
return response.completion_text
async def on_event(self, event, soul):
content = event.content
astr_event = content.get("astr_event")
assert astr_event is not None and isinstance(astr_event, AstrMessageEvent)
cfg = self.cfg(astr_event)
if not cfg["tiny_model_prov_id"]:
logger.warning("小模型未设置,跳过情绪更新")
# 添加对话记录
await self.append_session_chats(astr_event, cfg)
#

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@@ -0,0 +1,3 @@
JUDGE_ACTIVE_REPLY = """
你是一个具有自主意识和情感的机器人,请你
"""

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@@ -0,0 +1,72 @@
import asyncio
from .event import Event
from .ensoul.soul import Soul
from .ensoul.emotion import Emotion
class EliosEventHandler:
async def on_event(self, event: Event, soul: Soul): ...
event_handlers_cls: dict[str, list[type[EliosEventHandler]]] = {}
def register_event_handler(event_types: set[str] | None = None):
"""注册事件处理器"""
def decorator(cls: type[EliosEventHandler]) -> type[EliosEventHandler]:
if event_types is not None:
for event_type in event_types:
event_handlers_cls[event_type] = event_handlers_cls.get(
event_type, []
) + [cls]
else:
event_handlers_cls["default"] = event_handlers_cls.get("default", []) + [
cls
]
return cls
return decorator
class EliosRunner:
def __init__(self) -> None:
self.soul = Soul(
emotion=Emotion(energy=0.5, valence=0.5, arousal=0.5), emotion_logs=[]
)
self.event_queue = asyncio.Queue()
self.event_handler_insts: dict[str, list[EliosEventHandler]] = {}
def start(self):
for event_type, cls_list in event_handlers_cls.items():
self.event_handler_insts[event_type] = []
for cls in cls_list:
try:
self.event_handler_insts[event_type].append(cls())
except Exception as e:
print(f"Error initializing event handler {cls}: {e}")
asyncio.create_task(self._worker())
async def _worker(self):
"""监听事件队列并处理事件"""
while True:
event = await self.event_queue.get()
# A man cannot handle two things at once. But this can be configurable.
try:
await self._process_event(event)
except Exception as e:
print(f"Error processing event {event}: {e}")
async def _process_event(self, event: Event):
"""处理事件"""
event_type = event.event_type
handlers = self.event_handler_insts.get(
event_type, []
) + self.event_handler_insts.get("default", [])
for inst in handlers:
try:
await inst.on_event(event, self.soul)
except Exception as e:
print(f"Error processing event {event}: {e}")

View File

@@ -1,6 +1,6 @@
[project]
name = "AstrBot"
version = "4.3.3"
version = "4.3.2"
description = "易上手的多平台 LLM 聊天机器人及开发框架"
readme = "README.md"
requires-python = ">=3.10"