| layout | default |
|---|---|
| title | Chapter 2: Framework Architecture and Core Modules |
| nav_order | 2 |
| parent | Qwen-Agent Tutorial |
Welcome to Chapter 2: Framework Architecture and Core Modules. In this part of Qwen-Agent Tutorial: Tool-Enabled Agent Framework with MCP, RAG, and Multi-Modal Workflows, you will build an intuitive mental model first, then move into concrete implementation details and practical production tradeoffs.
This chapter explains the internal framework layers and extension surfaces.
- understand agent, llm, tool, and context module boundaries
- identify extension points for custom agents/tools
- map high-level assistants to low-level primitives
- reason about framework composition for real applications
- agent orchestration
- llm wrappers and generation config
- tools/function calling interfaces
- context/memory and retrieval layers
You now have a reliable mental model for Qwen-Agent framework internals.
Next: Chapter 3: Model Service and Runtime Strategy
The init_agent_service_create function in examples/group_chat_demo.py handles a key part of this chapter's functionality:
def init_agent_service_create():
llm_cfg = {'model': 'qwen-max'}
bot = GroupChatCreator(llm=llm_cfg)
return bot
# =========================================================
# Below is the gradio service: front-end and back-end logic
# =========================================================
app_global_para = {
'messages': [],
'messages_create': [],
'is_first_upload': False,
'uploaded_file': '',
'user_interrupt': True
}
# Initialized group chat configuration
CFGS = {
'background':
'一个陌生人互帮互助群聊',
'agents': [
{
'name': '小塘',
'description': '一个勤劳的打工人，每天沉迷工作，日渐消瘦。（这是一个真实用户）',
'is_human': True # mark this as a real person
},
{
'name': '甄嬛',This function is important because it defines how Qwen-Agent Tutorial: Tool-Enabled Agent Framework with MCP, RAG, and Multi-Modal Workflows implements the patterns covered in this chapter.
The app function in examples/group_chat_demo.py handles a key part of this chapter's functionality:
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""A group chat gradio demo"""
import json
import json5
from qwen_agent.agents import GroupChat, GroupChatCreator
from qwen_agent.agents.user_agent import PENDING_USER_INPUT
from qwen_agent.gui.gradio_dep import gr, mgr, ms
from qwen_agent.llm.schema import ContentItem, Message
def init_agent_service(cfgs):
llm_cfg = {'model': 'qwen-max'}
bot = GroupChat(agents=cfgs, llm=llm_cfg)
return bot
def init_agent_service_create():
llm_cfg = {'model': 'qwen-max'}
bot = GroupChatCreator(llm=llm_cfg)
return bot
# =========================================================This function is important because it defines how Qwen-Agent Tutorial: Tool-Enabled Agent Framework with MCP, RAG, and Multi-Modal Workflows implements the patterns covered in this chapter.
The test function in examples/group_chat_demo.py handles a key part of this chapter's functionality:
def test():
app(cfgs=CFGS)
def app_create(history, now_cfgs):
now_cfgs = json5.loads(now_cfgs)
if not history:
yield history, json.dumps(now_cfgs, indent=4, ensure_ascii=False)
else:
if len(history) == 1:
new_cfgs = {'background': '', 'agents': []}
# The first time to create grouchat
exist_cfgs = now_cfgs['agents']
for cfg in exist_cfgs:
if 'is_human' in cfg and cfg['is_human']:
new_cfgs['agents'].append(cfg)
else:
new_cfgs = now_cfgs
app_global_para['messages_create'].append(Message('user', history[-1][0].text))
response = []
try:
agent = init_agent_service_create()
for response in agent.run(messages=app_global_para['messages_create']):
display_content = ''
for rsp in response:
if rsp.name == 'role_config':
cfg = json5.loads(rsp.content)
old_pos = -1
for i, x in enumerate(new_cfgs['agents']):This function is important because it defines how Qwen-Agent Tutorial: Tool-Enabled Agent Framework with MCP, RAG, and Multi-Modal Workflows implements the patterns covered in this chapter.
The app_create function in examples/group_chat_demo.py handles a key part of this chapter's functionality:
def app_create(history, now_cfgs):
now_cfgs = json5.loads(now_cfgs)
if not history:
yield history, json.dumps(now_cfgs, indent=4, ensure_ascii=False)
else:
if len(history) == 1:
new_cfgs = {'background': '', 'agents': []}
# The first time to create grouchat
exist_cfgs = now_cfgs['agents']
for cfg in exist_cfgs:
if 'is_human' in cfg and cfg['is_human']:
new_cfgs['agents'].append(cfg)
else:
new_cfgs = now_cfgs
app_global_para['messages_create'].append(Message('user', history[-1][0].text))
response = []
try:
agent = init_agent_service_create()
for response in agent.run(messages=app_global_para['messages_create']):
display_content = ''
for rsp in response:
if rsp.name == 'role_config':
cfg = json5.loads(rsp.content)
old_pos = -1
for i, x in enumerate(new_cfgs['agents']):
if x['name'] == cfg['name']:
old_pos = i
break
if old_pos > -1:This function is important because it defines how Qwen-Agent Tutorial: Tool-Enabled Agent Framework with MCP, RAG, and Multi-Modal Workflows implements the patterns covered in this chapter.
flowchart TD
A[init_agent_service_create]
B[app]
C[test]
D[app_create]
E[get_name_of_current_user]
A --> B
B --> C
C --> D
D --> E