书生·浦语第二期实战营(初夏专场)-作业6

书生·浦语第二期实战营(初夏专场)-作业6

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Lagent Web Demo

环境安装

mkdir -p /root/agent

studio-conda -t agent -o pytorch-2.1.2


#安装 Lagent 和 AgentLego
cd /root/agent
conda activate agent
git clone https://gitee.com/internlm/lagent.git
cd lagent && git checkout 581d9fb && pip install -e . && cd ..
git clone https://gitee.com/internlm/agentlego.git
cd agentlego && git checkout 7769e0d && pip install -e . && cd ..

#安装其他依赖
conda activate agent
pip install lmdeploy==0.3.0

#准备 Tutorial
cd /root/agent
git clone -b camp2 https://gitee.com/internlm/Tutorial.git

使用lmdeploy启动服务端

conda activate agent
lmdeploy serve api_server /root/share/new_models/Shanghai_AI_Laboratory/internlm2-chat-7b \
--server-name 127.0.0.1 \
--model-name internlm2-chat-7b \
--cache-max-entry-count 0.1

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运行客户端

conda activate agent
cd /root/agent/lagent/examples
streamlit run internlm2_agent_web_demo.py --server.address 127.0.0.1 --server.port 7860

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加入端口映射

ssh -CNg -L 7860:127.0.0.1:7860 -L 23333:127.0.0.1:23333 root@ssh.intern-ai.org.cn -p 你的 ssh 端口号

结果如下

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创建自定义工具，天气查询结果如下

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AgentLego

#环境安装下载
cd /root/agent
wget http://download.openmmlab.com/agentlego/road.jpg

conda activate agent
pip install openmim==0.3.9
mim install mmdet==3.3.0

#创建目标检测工具代码
touch /root/agent/direct_use.py

写入代码

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)

直接执行

python /root/agent/direct_use.py

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结果如下

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启动webui

conda activate agent
cd /root/agent/agentlego/webui
python one_click.py

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使用webui客户端描述输入图片，结果如下

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加入新工具栏，magicmaker_image_generation后，执行如下

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