如何将 LangGraph（函数式 API）与 AutoGen、CrewAI 及其他框架集成¶
LangGraph 是一个用于构建智能体和多智能体应用程序的框架。LangGraph 可以轻松地与其他智能体框架集成。
你可能希望将 LangGraph 与其他智能体框架集成的主要原因
将其他框架中的智能体集成的最简单方法是在 LangGraph 的节点内调用这些智能体
import autogen
from langgraph.func import entrypoint, task
autogen_agent = autogen.AssistantAgent(name="assistant", ...)
user_proxy = autogen.UserProxyAgent(name="user_proxy", ...)
@task
def call_autogen_agent(messages):
response = user_proxy.initiate_chat(
autogen_agent,
message=messages[-1],
...
)
...
@entrypoint()
def workflow(messages):
response = call_autogen_agent(messages).result()
return response
workflow.invoke(
[
{
"role": "user",
"content": "Find numbers between 10 and 30 in fibonacci sequence",
}
]
)
在本指南中，我们将展示如何构建一个与 AutoGen 集成的 LangGraph 聊天机器人，但你也可以对其他框架采用相同的方法。
设置¶
import getpass
import os
def _set_env(var: str):
if not os.environ.get(var):
os.environ[var] = getpass.getpass(f"{var}: ")
_set_env("OPENAI_API_KEY")
定义 AutoGen 智能体¶
在这里我们定义了 AutoGen 智能体。改编自这里的官方教程。
import autogen
import os
config_list = [{"model": "gpt-4o", "api_key": os.environ["OPENAI_API_KEY"]}]
llm_config = {
"timeout": 600,
"cache_seed": 42,
"config_list": config_list,
"temperature": 0,
}
autogen_agent = autogen.AssistantAgent(
name="assistant",
llm_config=llm_config,
)
user_proxy = autogen.UserProxyAgent(
name="user_proxy",
human_input_mode="NEVER",
max_consecutive_auto_reply=10,
is_termination_msg=lambda x: x.get("content", "").rstrip().endswith("TERMINATE"),
code_execution_config={
"work_dir": "web",
"use_docker": False,
}, # Please set use_docker=True if docker is available to run the generated code. Using docker is safer than running the generated code directly.
llm_config=llm_config,
system_message="Reply TERMINATE if the task has been solved at full satisfaction. Otherwise, reply CONTINUE, or the reason why the task is not solved yet.",
)
创建工作流¶
现在我们将创建一个调用 AutoGen 智能体的 LangGraph 聊天机器人图。
API 参考：convert_to_openai_messages | BaseMessage | entrypoint | task | add_messages | MemorySaver
from langchain_core.messages import convert_to_openai_messages, BaseMessage
from langgraph.func import entrypoint, task
from langgraph.graph import add_messages
from langgraph.checkpoint.memory import MemorySaver
@task
def call_autogen_agent(messages: list[BaseMessage]):
# convert to openai-style messages
messages = convert_to_openai_messages(messages)
response = user_proxy.initiate_chat(
autogen_agent,
message=messages[-1],
# pass previous message history as context
carryover=messages[:-1],
)
# get the final response from the agent
content = response.chat_history[-1]["content"]
return {"role": "assistant", "content": content}
# add short-term memory for storing conversation history
checkpointer = MemorySaver()
@entrypoint(checkpointer=checkpointer)
def workflow(messages: list[BaseMessage], previous: list[BaseMessage]):
messages = add_messages(previous or [], messages)
response = call_autogen_agent(messages).result()
return entrypoint.final(value=response, save=add_messages(messages, response))
运行图¶
我们现在可以运行这个图了。
# pass the thread ID to persist agent outputs for future interactions
config = {"configurable": {"thread_id": "1"}}
for chunk in workflow.stream(
[
{
"role": "user",
"content": "Find numbers between 10 and 30 in fibonacci sequence",
}
],
config,
):
print(chunk)
user_proxy (to assistant):
Find numbers between 10 and 30 in fibonacci sequence
--------------------------------------------------------------------------------
assistant (to user_proxy):
To find numbers between 10 and 30 in the Fibonacci sequence, we can generate the Fibonacci sequence and check which numbers fall within this range. Here's a plan:
1. Generate Fibonacci numbers starting from 0.
2. Continue generating until the numbers exceed 30.
3. Collect and print the numbers that are between 10 and 30.
Let's implement this in Python:
\`\`\`python
# filename: fibonacci_range.py
def fibonacci_sequence():
a, b = 0, 1
while a <= 30:
if 10 <= a <= 30:
print(a)
a, b = b, a + b
fibonacci_sequence()
\`\`\`
This script will print the Fibonacci numbers between 10 and 30. Please execute the code to see the result.
--------------------------------------------------------------------------------
>>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is python)...
user_proxy (to assistant):
exitcode: 0 (execution succeeded)
Code output:
13
21
--------------------------------------------------------------------------------
assistant (to user_proxy):
The Fibonacci numbers between 10 and 30 are 13 and 21.
These numbers are part of the Fibonacci sequence, which is generated by adding the two preceding numbers to get the next number, starting from 0 and 1.
The sequence goes: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, ...
As you can see, 13 and 21 are the only numbers in this sequence that fall between 10 and 30.
TERMINATE
--------------------------------------------------------------------------------
{'call_autogen_agent': {'role': 'assistant', 'content': 'The Fibonacci numbers between 10 and 30 are 13 and 21. \n\nThese numbers are part of the Fibonacci sequence, which is generated by adding the two preceding numbers to get the next number, starting from 0 and 1. \n\nThe sequence goes: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, ...\n\nAs you can see, 13 and 21 are the only numbers in this sequence that fall between 10 and 30.\n\nTERMINATE'}}
{'workflow': {'role': 'assistant', 'content': 'The Fibonacci numbers between 10 and 30 are 13 and 21. \n\nThese numbers are part of the Fibonacci sequence, which is generated by adding the two preceding numbers to get the next number, starting from 0 and 1. \n\nThe sequence goes: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, ...\n\nAs you can see, 13 and 21 are the only numbers in this sequence that fall between 10 and 30.\n\nTERMINATE'}}
for chunk in workflow.stream(
[
{
"role": "user",
"content": "Multiply the last number by 3",
}
],
config,
):
print(chunk)
user_proxy (to assistant):
Multiply the last number by 3
Context:
Find numbers between 10 and 30 in fibonacci sequence
The Fibonacci numbers between 10 and 30 are 13 and 21.
These numbers are part of the Fibonacci sequence, which is generated by adding the two preceding numbers to get the next number, starting from 0 and 1.
The sequence goes: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, ...
As you can see, 13 and 21 are the only numbers in this sequence that fall between 10 and 30.
TERMINATE
--------------------------------------------------------------------------------
assistant (to user_proxy):
The last number in the Fibonacci sequence between 10 and 30 is 21. Multiplying 21 by 3 gives:
21 * 3 = 63
TERMINATE
--------------------------------------------------------------------------------
{'call_autogen_agent': {'role': 'assistant', 'content': 'The last number in the Fibonacci sequence between 10 and 30 is 21. Multiplying 21 by 3 gives:\n\n21 * 3 = 63\n\nTERMINATE'}}
{'workflow': {'role': 'assistant', 'content': 'The last number in the Fibonacci sequence between 10 and 30 is 21. Multiplying 21 by 3 gives:\n\n21 * 3 = 63\n\nTERMINATE'}}