# 10.Lagent 自定义你的 Agent 智能体
# 1.使用 Lagent 自定义一个智能体，并使用 Lagent Web Demo 成功部署与调用
# 1.1 Lagent智能体
Lagent (opens new window) 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.
Lagent 包含三个主要模块：agents，llms 和 actions。
- agents 实现了多种智能体，如 ReAct，AutoGPT。
- llms 支持多种大语言模型，包括在 HuggingFace 上托管的开源模型（Llama-2, InterLM）及 GPT3.5/4 等闭源模型。
- actions 包含一系列工具，并提供工具执行器来统一管理
详细参考 Lagent文档 (opens new window)
# 1.2 环境安装
# 创建环境
conda create -n agent_camp3 python=3.10 -y
# 激活环境
conda activate agent_camp3
# 安装 torch
conda install pytorch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 pytorch-cuda=12.1 -c pytorch -c nvidia -y
# 安装其他依赖包
pip install termcolor==2.4.0
pip install lmdeploy==0.5.2
#安装 lagent
# 创建目录以存放代码
mkdir -p /root/agent_camp3
cd /root/agent_camp3
git clone https://github.com/InternLM/lagent.git
cd lagent && git checkout 81e7ace && pip install -e . && cd ..
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
# 1.3 Lagent Web Demo
conda activate agent_camp3
# 窗口1
lmdeploy serve api_server /share/new_models/Shanghai_AI_Laboratory/internlm2_5-7b-chat --model-name internlm2_5-7b-chat
# 窗口2
cd /root/agent_camp3/lagent
streamlit run examples/internlm2_agent_web_demo.py
1
2
3
4
5
6
7
2
3
4
5
6
7
两个都启动好之后，浏览器访问 http://localhost:8501，测试功能。
# 1.4 自定义智能体
修改如下2个文件，并重启启动，验证自定义智能体。 /root/agent_camp3/lagent/lagent/actions/magicmaker.py
import json
import requests
from lagent.actions.base_action import BaseAction, tool_api
from lagent.actions.parser import BaseParser, JsonParser
from lagent.schema import ActionReturn, ActionStatusCode
class MagicMaker(BaseAction):
styles_option = [
"dongman", # 动漫
"guofeng", # 国风
"xieshi", # 写实
"youhua", # 油画
"manghe", # 盲盒
]
aspect_ratio_options = ["16:9", "4:3", "3:2", "1:1", "2:3", "3:4", "9:16"]
def __init__(self, style="guofeng", aspect_ratio="4:3"):
super().__init__()
if style in self.styles_option:
self.style = style
else:
raise ValueError(f"The style must be one of {self.styles_option}")
if aspect_ratio in self.aspect_ratio_options:
self.aspect_ratio = aspect_ratio
else:
raise ValueError(f"The aspect ratio must be one of {aspect_ratio}")
@tool_api
def generate_image(self, keywords: str) -> dict:
"""Run magicmaker and get the generated image according to the keywords.
Args:
keywords (:class:`str`): the keywords to generate image
Returns:
:class:`dict`: the generated image
* image (str): path to the generated image
"""
try:
response = requests.post(
url="https://magicmaker.openxlab.org.cn/gw/edit-anything/api/v1/bff/sd/generate",
data=json.dumps(
{
"official": True,
"prompt": keywords,
"style": self.style,
"poseT": False,
"aspectRatio": self.aspect_ratio,
}
),
headers={"content-type": "application/json"},
)
except Exception as exc:
return ActionReturn(
errmsg=f"MagicMaker exception: {exc}", state=ActionStatusCode.HTTP_ERROR
)
image_url = response.json()["data"]["imgUrl"]
return {"image": image_url}
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
/root/agent_camp3/lagent/examples/internlm2_agent_web_demo.py
import copy
import hashlib
import json
import os
import streamlit as st
from lagent.actions import ActionExecutor, ArxivSearch, IPythonInterpreter
from lagent.actions.magicmaker import MagicMaker
from lagent.agents.internlm2_agent import INTERPRETER_CN, META_CN, PLUGIN_CN, Internlm2Agent, Internlm2Protocol
from lagent.llms.lmdeploy_wrapper import LMDeployClient
from lagent.llms.meta_template import INTERNLM2_META as META
from lagent.schema import AgentStatusCode
# from streamlit.logger import get_logger
class SessionState:
def init_state(self):
"""Initialize session state variables."""
st.session_state['assistant'] = []
st.session_state['user'] = []
action_list = [
ArxivSearch(),
MagicMaker()
]
st.session_state['plugin_map'] = {
action.name: action
for action in action_list
}
st.session_state['model_map'] = {}
st.session_state['model_selected'] = None
st.session_state['plugin_actions'] = set()
st.session_state['history'] = []
def clear_state(self):
"""Clear the existing session state."""
st.session_state['assistant'] = []
st.session_state['user'] = []
st.session_state['model_selected'] = None
st.session_state['file'] = set()
if 'chatbot' in st.session_state:
st.session_state['chatbot']._session_history = []
class StreamlitUI:
def __init__(self, session_state: SessionState):
self.init_streamlit()
self.session_state = session_state
def init_streamlit(self):
"""Initialize Streamlit's UI settings."""
st.set_page_config(
layout='wide',
page_title='lagent-web',
page_icon='./docs/imgs/lagent_icon.png')
st.header(':robot_face: :blue[Lagent] Web Demo ', divider='rainbow')
st.sidebar.title('模型控制')
st.session_state['file'] = set()
st.session_state['ip'] = None
def setup_sidebar(self):
"""Setup the sidebar for model and plugin selection."""
# model_name = st.sidebar.selectbox('模型选择：', options=['internlm'])
model_name = st.sidebar.text_input('模型名称：', value='internlm2-chat-7b')
meta_prompt = st.sidebar.text_area('系统提示词', value=META_CN)
da_prompt = st.sidebar.text_area('数据分析提示词', value=INTERPRETER_CN)
plugin_prompt = st.sidebar.text_area('插件提示词', value=PLUGIN_CN)
model_ip = st.sidebar.text_input('模型IP：', value='10.140.0.220:23333')
if model_name != st.session_state[
'model_selected'] or st.session_state['ip'] != model_ip:
st.session_state['ip'] = model_ip
model = self.init_model(model_name, model_ip)
self.session_state.clear_state()
st.session_state['model_selected'] = model_name
if 'chatbot' in st.session_state:
del st.session_state['chatbot']
else:
model = st.session_state['model_map'][model_name]
plugin_name = st.sidebar.multiselect(
'插件选择',
options=list(st.session_state['plugin_map'].keys()),
default=[],
)
da_flag = st.sidebar.checkbox(
'数据分析',
value=False,
)
plugin_action = [
st.session_state['plugin_map'][name] for name in plugin_name
]
if 'chatbot' in st.session_state:
if len(plugin_action) > 0:
st.session_state['chatbot']._action_executor = ActionExecutor(
actions=plugin_action)
else:
st.session_state['chatbot']._action_executor = None
if da_flag:
st.session_state[
'chatbot']._interpreter_executor = ActionExecutor(
actions=[IPythonInterpreter()])
else:
st.session_state['chatbot']._interpreter_executor = None
st.session_state['chatbot']._protocol._meta_template = meta_prompt
st.session_state['chatbot']._protocol.plugin_prompt = plugin_prompt
st.session_state[
'chatbot']._protocol.interpreter_prompt = da_prompt
if st.sidebar.button('清空对话', key='clear'):
self.session_state.clear_state()
uploaded_file = st.sidebar.file_uploader('上传文件')
return model_name, model, plugin_action, uploaded_file, model_ip
def init_model(self, model_name, ip=None):
"""Initialize the model based on the input model name."""
model_url = f'http://{ip}'
st.session_state['model_map'][model_name] = LMDeployClient(
model_name=model_name,
url=model_url,
meta_template=META,
max_new_tokens=1024,
top_p=0.8,
top_k=100,
temperature=0,
repetition_penalty=1.0,
stop_words=['<|im_end|>'])
return st.session_state['model_map'][model_name]
def initialize_chatbot(self, model, plugin_action):
"""Initialize the chatbot with the given model and plugin actions."""
return Internlm2Agent(
llm=model,
protocol=Internlm2Protocol(
tool=dict(
begin='{start_token}{name}\n',
start_token='<|action_start|>',
name_map=dict(
plugin='<|plugin|>', interpreter='<|interpreter|>'),
belong='assistant',
end='<|action_end|>\n',
), ),
max_turn=7)
def render_user(self, prompt: str):
with st.chat_message('user'):
st.markdown(prompt)
def render_assistant(self, agent_return):
with st.chat_message('assistant'):
for action in agent_return.actions:
if (action) and (action.type != 'FinishAction'):
self.render_action(action)
st.markdown(agent_return.response)
def render_plugin_args(self, action):
action_name = action.type
args = action.args
import json
parameter_dict = dict(name=action_name, parameters=args)
parameter_str = '```json\n' + json.dumps(
parameter_dict, indent=4, ensure_ascii=False) + '\n```'
st.markdown(parameter_str)
def render_interpreter_args(self, action):
st.info(action.type)
st.markdown(action.args['text'])
def render_action(self, action):
st.markdown(action.thought)
if action.type == 'IPythonInterpreter':
self.render_interpreter_args(action)
elif action.type == 'FinishAction':
pass
else:
self.render_plugin_args(action)
self.render_action_results(action)
def render_action_results(self, action):
"""Render the results of action, including text, images, videos, and
audios."""
if (isinstance(action.result, dict)):
if 'text' in action.result:
st.markdown('```\n' + action.result['text'] + '\n```')
if 'image' in action.result:
# image_path = action.result['image']
for image_path in action.result['image']:
image_data = open(image_path, 'rb').read()
st.image(image_data, caption='Generated Image')
if 'video' in action.result:
video_data = action.result['video']
video_data = open(video_data, 'rb').read()
st.video(video_data)
if 'audio' in action.result:
audio_data = action.result['audio']
audio_data = open(audio_data, 'rb').read()
st.audio(audio_data)
elif isinstance(action.result, list):
for item in action.result:
if item['type'] == 'text':
st.markdown('```\n' + item['content'] + '\n```')
elif item['type'] == 'image':
image_data = open(item['content'], 'rb').read()
st.image(image_data, caption='Generated Image')
elif item['type'] == 'video':
video_data = open(item['content'], 'rb').read()
st.video(video_data)
elif item['type'] == 'audio':
audio_data = open(item['content'], 'rb').read()
st.audio(audio_data)
if action.errmsg:
st.error(action.errmsg)
def main():
# logger = get_logger(__name__)
# Initialize Streamlit UI and setup sidebar
if 'ui' not in st.session_state:
session_state = SessionState()
session_state.init_state()
st.session_state['ui'] = StreamlitUI(session_state)
else:
st.set_page_config(
layout='wide',
page_title='lagent-web',
page_icon='./docs/imgs/lagent_icon.png')
st.header(':robot_face: :blue[Lagent] Web Demo ', divider='rainbow')
_, model, plugin_action, uploaded_file, _ = st.session_state[
'ui'].setup_sidebar()
# Initialize chatbot if it is not already initialized
# or if the model has changed
if 'chatbot' not in st.session_state or model != st.session_state[
'chatbot']._llm:
st.session_state['chatbot'] = st.session_state[
'ui'].initialize_chatbot(model, plugin_action)
st.session_state['session_history'] = []
for prompt, agent_return in zip(st.session_state['user'],
st.session_state['assistant']):
st.session_state['ui'].render_user(prompt)
st.session_state['ui'].render_assistant(agent_return)
if user_input := st.chat_input(''):
with st.container():
st.session_state['ui'].render_user(user_input)
st.session_state['user'].append(user_input)
# Add file uploader to sidebar
if (uploaded_file
and uploaded_file.name not in st.session_state['file']):
st.session_state['file'].add(uploaded_file.name)
file_bytes = uploaded_file.read()
file_type = uploaded_file.type
if 'image' in file_type:
st.image(file_bytes, caption='Uploaded Image')
elif 'video' in file_type:
st.video(file_bytes, caption='Uploaded Video')
elif 'audio' in file_type:
st.audio(file_bytes, caption='Uploaded Audio')
# Save the file to a temporary location and get the path
postfix = uploaded_file.name.split('.')[-1]
# prefix = str(uuid.uuid4())
prefix = hashlib.md5(file_bytes).hexdigest()
filename = f'{prefix}.{postfix}'
file_path = os.path.join(root_dir, filename)
with open(file_path, 'wb') as tmpfile:
tmpfile.write(file_bytes)
file_size = os.stat(file_path).st_size / 1024 / 1024
file_size = f'{round(file_size, 2)} MB'
# st.write(f'File saved at: {file_path}')
user_input = [
dict(role='user', content=user_input),
dict(
role='user',
content=json.dumps(dict(path=file_path, size=file_size)),
name='file')
]
if isinstance(user_input, str):
user_input = [dict(role='user', content=user_input)]
st.session_state['last_status'] = AgentStatusCode.SESSION_READY
for agent_return in st.session_state['chatbot'].stream_chat(
st.session_state['session_history'] + user_input):
if agent_return.state == AgentStatusCode.PLUGIN_RETURN:
with st.container():
st.session_state['ui'].render_plugin_args(
agent_return.actions[-1])
st.session_state['ui'].render_action_results(
agent_return.actions[-1])
elif agent_return.state == AgentStatusCode.CODE_RETURN:
with st.container():
st.session_state['ui'].render_action_results(
agent_return.actions[-1])
elif (agent_return.state == AgentStatusCode.STREAM_ING
or agent_return.state == AgentStatusCode.CODING):
# st.markdown(agent_return.response)
# 清除占位符的当前内容，并显示新内容
with st.container():
if agent_return.state != st.session_state['last_status']:
st.session_state['temp'] = ''
placeholder = st.empty()
st.session_state['placeholder'] = placeholder
if isinstance(agent_return.response, dict):
action = f"\n\n {agent_return.response['name']}: \n\n"
action_input = agent_return.response['parameters']
if agent_return.response[
'name'] == 'IPythonInterpreter':
action_input = action_input['command']
response = action + action_input
else:
response = agent_return.response
st.session_state['temp'] = response
st.session_state['placeholder'].markdown(
st.session_state['temp'])
elif agent_return.state == AgentStatusCode.END:
st.session_state['session_history'] += (
user_input + agent_return.inner_steps)
agent_return = copy.deepcopy(agent_return)
agent_return.response = st.session_state['temp']
st.session_state['assistant'].append(
copy.deepcopy(agent_return))
st.session_state['last_status'] = agent_return.state
if __name__ == '__main__':
root_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
root_dir = os.path.join(root_dir, 'tmp_dir')
os.makedirs(root_dir, exist_ok=True)
main()
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
Apache License 2.0 | Copyright © 2022 by xueliang.wu 苏ICP备15016087号