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添加基础的 LLM 支持

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This commit is contained in:
钟晓帕
2025-11-05 18:40:13 +08:00
parent 9320815d3f
commit a5f4ae9bdc
5 changed files with 303 additions and 1 deletions
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64
konabot/common/llm/__init__.py Normal file
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@ -0,0 +1,64 @@
from typing import Any
import openai
from loguru import logger
from openai.types.chat import ChatCompletion, ChatCompletionMessage, ChatCompletionMessageParam
from pydantic import BaseModel, Field
from konabot.common.path import CONFIG_PATH
LLM_CONFIG_PATH = CONFIG_PATH / 'llm.json'
if not LLM_CONFIG_PATH.exists():
LLM_CONFIG_PATH.write_text("{}")
class LLMInfo(BaseModel):
base_url: str
api_key: str
model_name: str
def get_openai_client(self):
return openai.AsyncClient(
api_key=self.api_key,
base_url=self.base_url,
)
async def chat(
self,
messages: list[ChatCompletionMessageParam],
timeout: float | None = 30.0,
max_tokens: int | None = None,
**kwargs: Any,
) -> ChatCompletionMessage:
logger.info(f"调用 LLM: BASE_URL={self.base_url} MODEL_NAME={self.model_name}")
completion: ChatCompletion = await self.get_openai_client().chat.completions.create(
messages=messages,
model=self.model_name,
max_tokens=max_tokens,
timeout=timeout,
stream=False,
**kwargs,
)
choice = completion.choices[0]
logger.info(
f"调用 LLM 完成: BASE_URL={self.base_url} MODEL_NAME={self.model_name} REASON={choice.finish_reason}"
)
return choice.message
class LLMConfig(BaseModel):
llms: dict[str, LLMInfo] = Field(default_factory=dict)
default_llm: str = "Qwen2.5-7B-Instruct"
llm_config = LLMConfig.model_validate_json(LLM_CONFIG_PATH.read_text())
def get_llm(llm_model: str | None = None):
if llm_model is None:
llm_model = llm_config.default_llm
if llm_model not in llm_config.llms:
raise NotImplementedError("LLM 未配置，该功能无法使用")
return llm_config.llms[llm_model]

3
konabot/common/path.py
View File

@ -6,6 +6,7 @@ FONTS_PATH = ASSETS_PATH / "fonts"
SRC_PATH = Path(__file__).resolve().parent.parent
DATA_PATH = SRC_PATH.parent / "data"
LOG_PATH = DATA_PATH / "logs"
CONFIG_PATH = DATA_PATH / "config"
DOCS_PATH = SRC_PATH / "docs"
DOCS_PATH_MAN1 = DOCS_PATH / "user"
@ -19,3 +20,5 @@ if not DATA_PATH.exists():
if not LOG_PATH.exists():
LOG_PATH.mkdir()
CONFIG_PATH.mkdir(exist_ok=True)

40
konabot/plugins/llm_test.py Normal file
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@ -0,0 +1,40 @@
"""
肥肠危险注意：本文件仅用于开发环境测试 LLM 模块能否正常工作！
请不要在生产环境启用它！
"""
import nonebot
from nonebot_plugin_alconna import Alconna, Args, on_alconna
from pydantic import BaseModel
from konabot.common.llm import get_llm
from konabot.common.longtask import DepLongTaskTarget
class LLMTestConfig(BaseModel):
debug_enable_llm_test: bool = False
config = nonebot.get_plugin_config(LLMTestConfig)
if config.debug_enable_llm_test:
cmd = on_alconna(Alconna(
"debug-ask-llm",
Args["prompt", str],
))
@cmd.handle()
async def _(prompt: str, target: DepLongTaskTarget):
llm = get_llm()
msg = await llm.chat(
[
{"role": "user", "content": prompt}
],
timeout=None,
max_tokens=1024,
)
content = msg.content or ""
await target.send_message(content)

196
poetry.lock generated
View File

@ -803,6 +803,23 @@ type = "legacy"
url = "https://pypi.tuna.tsinghua.edu.cn/simple"
reference = "mirrors"
[[package]]
name = "distro"
version = "1.9.0"
description = "Distro - an OS platform information API"
optional = false
python-versions = ">=3.6"
groups = ["main"]
files = [
{file = "distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2"},
{file = "distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed"},
]
[package.source]
type = "legacy"
url = "https://pypi.tuna.tsinghua.edu.cn/simple"
reference = "mirrors"
[[package]]
name = "exceptiongroup"
version = "1.3.0"
@ -1333,6 +1350,123 @@ type = "legacy"
url = "https://pypi.tuna.tsinghua.edu.cn/simple"
reference = "mirrors"
[[package]]
name = "jiter"
version = "0.11.1"
description = "Fast iterable JSON parser."
optional = false
python-versions = ">=3.9"
groups = ["main"]
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reference = "mirrors"
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reference = "mirrors"
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1
pyproject.toml
View File

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