Any]:#检查请求体是否为空ifnotvalues:raiseValueError("Empty request body")#如果 values 是 dict 类型,将其键名转换为小写if isinstance(values, dict):return{key.lower(): valueforkey, valueinvalues.items()}else:returnvalues
return {"status": "success", "message": "删除魔兽世界角色 id {id}成功"} 此时查询数据库数据id=666的数据内容已经不存在了 MariaDB [wow]> select * from wow_info where id=666 \G; Empty set (0.000 sec) 7-4-3. 项目实战总结 这个 FastAPI 项目展示了一个完整的后端应用程序,用于管理魔...
timeout=time_out)#print(response)returnresponse.json()# 启动网关if__name__=="__main__":impor...
也可以使用python中的requests库进行调用,如下所示: importrequestsimportjsondefget_completion(prompt):headers={'Content-Type':'application/json'}data={"prompt":prompt,"history":[]}response=requests.post(url='http://127.0.0.1:6006',headers=headers,data=json.dumps(data))returnresponse.json()['r...
return 'pass' else: return 'fail' async def chat(query): position = 0 try: for response in model.chat_stream(tokenizer, query, history = None): result = response[position:] position = len(response) yield result except Exception:
cookies } return res 请求结果 代码语言:javascript 代码运行次数:0 运行 AI代码解释 { "host": "127.0.0.1", "port": 54364, "method": "GET", "base_url": { "_url": "http://127.0.0.1:8080/" }, "headers": { "host": "127.0.0.1:8080", "connection": "keep-alive", "sec-ch-ua"...
asyncdefjson(self)->typing.Any:ifnothasattr(self,"_json"):# pragma: no branchbody=awaitself.body()self._json=json.loads(body)returnself._json form¶ form(*,max_files=1000,max_fields=1000,max_part_size=1024*1024) PARAMETERDESCRIPTION ...
= info.get('name', '') if not name: return {'success': False, 'msg': 'name 参数不可省略,不可为空!'...整个过程中,对类型的检查全都由 FastApi 自己完成。我们省下来很多时间。我用了 Flask 四年,但在使用了 5 分钟 FastApi 以后,我决定以后不再使用 Flask 了。...其中main表示我...
response.set_cookie("Authorization", value=f"Bearer {token}", httponly=True, max_age=1800, expires=1800, samesite="lax", secure=False, )returnresponse@router.get("/users/whoami", response_model=UserOutSchema, dependencies=[Depends(get_current_user)] ...
return model def clear(self) -> None: if torch.cuda.is_available(): for device in self.devices: with torch.cuda.device(device): torch.cuda.empty_cache() torch.cuda.ipc_collect() def answer(self, query: str, history): response, history = self.model.chat(self.tokenizer, query, history...