支持保存历史对话, 规范代码

This commit is contained in:
2024-11-17 00:56:50 +08:00
parent 45d25b90aa
commit 690881ccae
8 changed files with 161 additions and 94 deletions

View File

@ -14,8 +14,11 @@ from azure.ai.inference.models import SystemMessage
from .config import config
nickname_json = None
praises_json = None
async def get_image_b64(url):
# noinspection LongLine
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"
}
@ -28,7 +31,7 @@ async def get_image_b64(url):
content_type = response.headers.get("Content-Type")
if not content_type:
content_type = mimetypes.guess_type(url)[0]
image_format = content_type.split("/")[1] if content_type else "jpeg"
# image_format = content_type.split("/")[1] if content_type else "jpeg"
base64_image = base64.b64encode(image_data).decode("utf-8")
data_url = f"data:{content_type};base64,{base64_image}"
return data_url
@ -36,7 +39,13 @@ async def get_image_b64(url):
return None
async def make_chat(client: ChatCompletionsClient, msg, model_name: str):
async def make_chat(client: ChatCompletionsClient, msg: list, model_name: str):
"""调用ai获取回复
参数:
client: 用于与AI模型进行通信
msg: 消息内容
model_name: 指定AI模型名"""
return await client.complete(
messages=msg,
model=model_name,
@ -47,9 +56,29 @@ async def make_chat(client: ChatCompletionsClient, msg, model_name: str):
def get_praises():
praises_file = store.get_plugin_data_file(
"praises.json"
) # 夸赞名单文件使用localstore存储
global praises_json
if praises_json is None:
praises_file = store.get_plugin_data_file("praises.json") # 夸赞名单文件使用localstore存储
if not os.path.exists(praises_file):
init_data = {
"like": [
{
"name": "Asankilp",
"advantages": "赋予了Marsho猫娘人格使用vim与vscode为Marsho写了许多代码使Marsho更加可爱",
}
]
}
with open(praises_file, "w", encoding="utf-8") as f:
json.dump(init_data, f, ensure_ascii=False, indent=4)
with open(praises_file, "r", encoding="utf-8") as f:
data = json.load(f)
praises_json = data
return praises_json
async def refresh_praises_json():
global praises_json
praises_file = store.get_plugin_data_file("praises.json")
if not os.path.exists(praises_file):
init_data = {
"like": [
@ -63,7 +92,7 @@ def get_praises():
json.dump(init_data, f, ensure_ascii=False, indent=4)
with open(praises_file, "r", encoding="utf-8") as f:
data = json.load(f)
return data
praises_json = data
def build_praises():
@ -74,16 +103,16 @@ def build_praises():
return "\n".join(result)
async def save_context_to_json(name: str, context: Any):
context_dir = store.get_plugin_data_dir() / "contexts"
async def save_context_to_json(name: str, context: Any, path: str):
context_dir = store.get_plugin_data_dir() / path
os.makedirs(context_dir, exist_ok=True)
file_path = os.path.join(context_dir, f"{name}.json")
with open(file_path, "w", encoding="utf-8") as json_file:
json.dump(context, json_file, ensure_ascii=False, indent=4)
async def load_context_from_json(name: str):
context_dir = store.get_plugin_data_dir() / "contexts"
async def load_context_from_json(name: str, path:str):
context_dir = store.get_plugin_data_dir() / path
os.makedirs(context_dir, exist_ok=True)
file_path = os.path.join(context_dir, f"{name}.json")
try:
@ -109,22 +138,25 @@ async def set_nickname(user_id: str, name: str):
nickname_json = data
# noinspection PyBroadException
async def get_nicknames():
'''获取nickname_json, 优先来源于全局变量'''
"""获取nickname_json, 优先来源于全局变量"""
global nickname_json
if nickname_json is None:
filename = store.get_plugin_data_file("nickname.json")
try:
with open(filename, "r", encoding="utf-8") as f:
nickname_json = json.load(f)
nickname_json = json.load(f)
except Exception:
nickname_json = {}
return nickname_json
async def refresh_nickname_json():
'''强制刷新nickname_json, 刷新全局变量'''
"""强制刷新nickname_json, 刷新全局变量"""
global nickname_json
filename = store.get_plugin_data_file("nickname.json")
# noinspection PyBroadException
try:
with open(filename, "r", encoding="utf-8") as f:
nickname_json = json.load(f)
@ -151,6 +183,7 @@ def get_prompt():
def suggest_solution(errinfo: str) -> str:
# noinspection LongLine
suggestions = {
"content_filter": "消息已被内容过滤器过滤。请调整聊天内容后重试。",
"RateLimitReached": "模型达到调用速率限制。请稍等一段时间或联系Bot管理员。",