Lagent & AgentLego 智能体应用搭建
一、概述
Lagent 是一个轻量级开源智能体框架，旨在让用户可以高效地构建基于大语言模型的智能体。同时它也提供了一些典型工具以增强大语言模型的能力。
AgentLego 是一个提供了多种开源工具 API 的多模态工具包，旨在像是乐高积木一样，让用户可以快速简便地拓展自定义工具，从而组装出自己的智能体。
两者关系
安装环境：
- Lagent：https://lagent.readthedocs.io/zh-cn/latest/get_started/install.html
- AgentLego：https://agentlego.readthedocs.io/zh-cn/latest/get_started.html
二、Lagent
2.1 Lagent Web Demo
使用LMDeploy部署api_server，并启动Lagent Web Demo。映射到本地端口访问
使用arxiv插件搜索文章
2.2 使用Lagent自定义工具
https://lagent.readthedocs.io/zh-cn/latest/tutorials/action.html
步骤：
- 继承 BaseAction 类
- 实现简单工具的 run 方法；或者实现工具包内每个子工具的功能
- 简单工具的 run 方法可选被 tool_api 装饰；工具包内每个子工具的功能都需要被 tool_api 装饰
下面我们将实现一个调用和风天气 API 的工具以完成实时天气查询的功能。
import json
import os
import requests
from typing import Optional, Type
from lagent.actions.base_action import BaseAction, tool_api
from lagent.actions.parser import BaseParser, JsonParser
from lagent.schema import ActionReturn, ActionStatusCode
class WeatherQuery(BaseAction):
"""Weather plugin for querying weather information."""
def __init__(self,
key: Optional[str] = None,
description: Optional[dict] = None,
parser: Type[BaseParser] = JsonParser,
enable: bool = True) -> None:
super().__init__(description, parser, enable)
key = os.environ.get('WEATHER_API_KEY', key)
if key is None:
raise ValueError(
'Please set Weather API key either in the environment '
'as WEATHER_API_KEY or pass it as `key`')
self.key = key
self.location_query_url = 'https://geoapi.qweather.com/v2/city/lookup'
self.weather_query_url = 'https://devapi.qweather.com/v7/weather/now'
@tool_api
def run(self, query: str) -> ActionReturn:
"""一个天气查询API。可以根据城市名查询天气信息。
Args:
query (:class:`str`): The city name to query.
"""
tool_return = ActionReturn(type=self.name)
status_code, response = self._search(query)
if status_code == -1:
tool_return.errmsg = response
tool_return.state = ActionStatusCode.HTTP_ERROR
elif status_code == 200:
parsed_res = self._parse_results(response)
tool_return.result = [dict(type='text', content=str(parsed_res))]
tool_return.state = ActionStatusCode.SUCCESS
else:
tool_return.errmsg = str(status_code)
tool_return.state = ActionStatusCode.API_ERROR
return tool_return
def _parse_results(self, results: dict) -> str:
"""Parse the weather results from QWeather API.
Args:
results (dict): The weather content from QWeather API
in json format.
Returns:
str: The parsed weather results.
"""
now = results['now']
data = [
f'数据观测时间: {now["obsTime"]}',
f'温度: {now["temp"]}°C',
f'体感温度: {now["feelsLike"]}°C',
f'天气: {now["text"]}',
f'风向: {now["windDir"]}，角度为 {now["wind360"]}°',
f'风力等级: {now["windScale"]}，风速为 {now["windSpeed"]} km/h',
f'相对湿度: {now["humidity"]}',
f'当前小时累计降水量: {now["precip"]} mm',
f'大气压强: {now["pressure"]} 百帕',
f'能见度: {now["vis"]} km',
]
return '\n'.join(data)
def _search(self, query: str):
# get city_code
try:
city_code_response = requests.get(
self.location_query_url,
params={'key': self.key, 'location': query}
)
except Exception as e:
return -1, str(e)
if city_code_response.status_code != 200:
return city_code_response.status_code, city_code_response.json()
city_code_response = city_code_response.json()
if len(city_code_response['location']) == 0:
return -1, '未查询到城市'
city_code = city_code_response['location'][0]['id']
# get weather
try:
weather_response = requests.get(
self.weather_query_url,
params={'key': self.key, 'location': city_code}
)
except Exception as e:
return -1, str(e)
return weather_response.status_code, weather_response.json()
获取和风天气API_KEY
https://dev.qweather.com/docs/api/
同样地开启api_server和lagent
天气助手
三、AgentLego
使用mmdet算法库中的RTMDet-Large模型
目标检测工具脚本：
import re
import cv2
from agentlego.apis import load_tool
# load tool
tool = load_tool('ObjectDetection', device='cuda')
# apply tool
visualization = tool('/root/agent/road.jpg')
print(visualization)
# visualize
image = cv2.imread('/root/agent/road.jpg')
preds = visualization.split('\n')
pattern = r'(\w+) \((\d+), (\d+), (\d+), (\d+)\), score (\d+)'
for pred in preds:
name, x1, y1, x2, y2, score = re.match(pattern, pred).groups()
x1, y1, x2, y2, score = int(x1), int(y1), int(x2), int(y2), int(score)
cv2.rectangle(image, (x1, y1), (x2, y2), (0, 255, 0), 1)
cv2.putText(image, f'{name} {score}', (x1, y1), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 0), 1)
cv2.imwrite('/root/agent/road_detection_direct.jpg', image)
demo
部署在应用中
3.3 自定义工具
使用MagicMakerImageGeneration 工具
油画
