yujunjun/autogen
1
0
Fork 0
mirror of https://github.com/microsoft/autogen.git synced 2025-12-25 22:18:53 +00:00
Code Issues Packages Projects Releases Wiki Activity

Fix examples in docstrings (#4356)

Browse Source 
* Fix examples in docstrings

* formatting

* Update python/packages/autogen-ext/src/autogen_ext/models/_reply_chat_completion_client.py

Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

* Update python/packages/autogen-ext/src/autogen_ext/models/_reply_chat_completion_client.py

Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

* Update python/packages/autogen-ext/src/autogen_ext/agents/_openai_assistant_agent.py

Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

* Update python/packages/autogen-ext/src/autogen_ext/agents/_openai_assistant_agent.py

Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

* Update python/packages/autogen-ext/src/autogen_ext/models/_reply_chat_completion_client.py

Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

* Update python/packages/autogen-ext/src/autogen_ext/models/_reply_chat_completion_client.py

Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>

* Formattinggp

---------

Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
This commit is contained in:
Jack Gerrits 2024-11-25 16:07:45 -05:00 committed by GitHub
parent 8347881776
commit 6c8b656588
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
13 changed files with 149 additions and 118 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

7
python/packages/autogen-agentchat/src/autogen_agentchat/agents/_code_executor_agent.py
View File

@ -24,9 +24,11 @@ class CodeExecutorAgent(BaseChatAgent):
.. code-block:: python
import asyncio
from autogen_agentchat.agents import CodeExecutorAgent
from autogen_agentchat.messages import TextMessage
from autogen_ext.code_executors import DockerCommandLineCodeExecutor
from autogen_core.base import CancellationToken
async def run_code_executor_agent() -> None:
@ -51,8 +53,7 @@ class CodeExecutorAgent(BaseChatAgent):
await code_executor.stop()
# Use asyncio.run(run_code_executor_agent()) when running in a script.
await run_code_executor_agent()
asyncio.run(run_code_executor_agent())
"""

6
python/packages/autogen-agentchat/src/autogen_agentchat/base/_termination.py
View File

@ -23,15 +23,15 @@ class TerminationCondition(ABC):
.. code-block:: python
import asyncio
from autogen_agentchat.teams import MaxTurnsTermination, TextMentionTermination
from autogen_agentchat.task import MaxMessageTermination, TextMentionTermination
async def main() -> None:
# Terminate the conversation after 10 turns or if the text "TERMINATE" is mentioned.
cond1 = MaxTurnsTermination(10) | TextMentionTermination("TERMINATE")
cond1 = MaxMessageTermination(10) | TextMentionTermination("TERMINATE")
# Terminate the conversation after 10 turns and if the text "TERMINATE" is mentioned.
cond2 = MaxTurnsTermination(10) & TextMentionTermination("TERMINATE")
cond2 = MaxMessageTermination(10) & TextMentionTermination("TERMINATE")
# ...

2
python/packages/autogen-agentchat/src/autogen_agentchat/task/_terminations.py
View File

@ -218,6 +218,8 @@ class ExternalTermination(TerminationCondition):
.. code-block:: python
from autogen_agentchat.task import ExternalTermination
termination = ExternalTermination()
# Run the team in an asyncio task.

8
python/packages/autogen-agentchat/src/autogen_agentchat/teams/_group_chat/_selector_group_chat.py
View File

@ -257,16 +257,18 @@ class SelectorGroupChat(BaseGroupChat):
.. code-block:: python
import asyncio
from typing import Sequence
from autogen_ext.models import OpenAIChatCompletionClient
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.teams import SelectorGroupChat
from autogen_agentchat.task import TextMentionTermination, Console
from autogen_agentchat.messages import AgentMessage
async def main() -> None:
model_client = OpenAIChatCompletionClient(model="gpt-4o")
def check_caculation(x: int, y: int, answer: int) -> str:
def check_calculation(x: int, y: int, answer: int) -> str:
if x + y == answer:
return "Correct!"
else:
@ -281,12 +283,12 @@ class SelectorGroupChat(BaseGroupChat):
agent2 = AssistantAgent(
"Agent2",
model_client,
tools=[check_caculation],
tools=[check_calculation],
description="For checking calculation",
system_message="Check the answer and respond with 'Correct!' or 'Incorrect!'",
)
def selector_func(messages):
def selector_func(messages: Sequence[AgentMessage]) -> str | None:
if len(messages) == 1 or messages[-1].content == "Incorrect!":
return "Agent1"
if messages[-1].source == "Agent1":

27
python/packages/autogen-core/src/autogen_core/base/_agent_runtime.py
View File

@ -89,19 +89,6 @@ class AgentRuntime(Protocol):
agent_factory (Callable[[], T]): The factory that creates the agent, where T is a concrete Agent type. Inside the factory, use `autogen_core.base.AgentInstantiationContext` to access variables like the current runtime and agent ID.
subscriptions (Callable[[], list[Subscription]] | list[Subscription] | None, optional): The subscriptions that the agent should be subscribed to. Defaults to None.
Example:
.. code-block:: python
runtime.register(
"chat_agent",
lambda: ChatCompletionAgent(
description="A generic chat agent.",
system_messages=[SystemMessage("You are a helpful assistant")],
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
memory=BufferedChatMemory(buffer_size=10),
),
)
"""
...
@ -117,20 +104,6 @@ class AgentRuntime(Protocol):
Args:
type (str): The type of agent this factory creates. It is not the same as agent class name. The `type` parameter is used to differentiate between different factory functions rather than agent classes.
agent_factory (Callable[[], T]): The factory that creates the agent, where T is a concrete Agent type. Inside the factory, use `autogen_core.base.AgentInstantiationContext` to access variables like the current runtime and agent ID.
Example:
.. code-block:: python
runtime.register(
"chat_agent",
lambda: ChatCompletionAgent(
description="A generic chat agent.",
system_messages=[SystemMessage("You are a helpful assistant")],
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
memory=BufferedChatMemory(buffer_size=10),
),
)
"""
...

6
python/packages/autogen-core/src/autogen_core/components/_default_subscription.py
View File

@ -10,12 +10,6 @@ class DefaultSubscription(TypeSubscription):
This topic by default uses the "default" topic type and attempts to detect the agent type to use based on the instantiation context.
Example:
.. code-block:: python
await runtime.register("MyAgent", agent_factory, lambda: [DefaultSubscription()])
Args:
topic_type (str, optional): The topic type to subscribe to. Defaults to "default".
agent_type (str, optional): The agent type to use for the subscription. Defaults to None, in which case it will attempt to detect the agent type based on the instantiation context.

22
python/packages/autogen-core/src/autogen_core/components/_routed_agent.py
View File

@ -422,9 +422,24 @@ class RoutedAgent(BaseAgent):
.. code-block:: python
from dataclasses import dataclass
from autogen_core.base import MessageContext
from autogen_core.components import RoutedAgent, event, rpc
# Assume Message, MessageWithContent, and Response are defined elsewhere.
@dataclass
class Message:
pass
@dataclass
class MessageWithContent:
content: str
@dataclass
class Response:
pass
class MyAgent(RoutedAgent):
@ -433,9 +448,10 @@ class RoutedAgent(BaseAgent):
@event
async def handle_event_message(self, message: Message, ctx: MessageContext) -> None:
self.publish_message(MessageWithContent("event handled"), ctx.topic_id)
assert ctx.topic_id is not None
await self.publish_message(MessageWithContent("event handled"), ctx.topic_id)
@rpc(match=lambda message, ctx: message.content == "special")
@rpc(match=lambda message, ctx: message.content == "special") # type: ignore
async def handle_special_rpc_message(self, message: MessageWithContent, ctx: MessageContext) -> Response:
return Response()
"""

2
python/packages/autogen-core/src/autogen_core/components/_type_subscription.py
View File

@ -14,6 +14,8 @@ class TypeSubscription(Subscription):
.. code-block:: python
from autogen_core.components import TypeSubscription
subscription = TypeSubscription(topic_type="t1", agent_type="a1")
In this case:

32
python/packages/autogen-core/src/autogen_core/components/code_executor/_impl/local_commandline_code_executor.py
View File

@ -67,25 +67,31 @@ class LocalCommandLineCodeExecutor(CodeExecutor):
import venv
from pathlib import Path
import asyncio
from autogen_core.base import CancellationToken
from autogen_core.components.code_executor import CodeBlock, LocalCommandLineCodeExecutor
work_dir = Path("coding")
work_dir.mkdir(exist_ok=True)
venv_dir = work_dir / ".venv"
venv_builder = venv.EnvBuilder(with_pip=True)
venv_builder.create(venv_dir)
venv_context = venv_builder.ensure_directories(venv_dir)
async def example():
work_dir = Path("coding")
work_dir.mkdir(exist_ok=True)
local_executor = LocalCommandLineCodeExecutor(work_dir=work_dir, virtual_env_context=venv_context)
await local_executor.execute_code_blocks(
code_blocks=[
CodeBlock(language="bash", code="pip install matplotlib"),
],
cancellation_token=CancellationToken(),
)
venv_dir = work_dir / ".venv"
venv_builder = venv.EnvBuilder(with_pip=True)
venv_builder.create(venv_dir)
venv_context = venv_builder.ensure_directories(venv_dir)
local_executor = LocalCommandLineCodeExecutor(work_dir=work_dir, virtual_env_context=venv_context)
await local_executor.execute_code_blocks(
code_blocks=[
CodeBlock(language="bash", code="pip install matplotlib"),
],
cancellation_token=CancellationToken(),
)
asyncio.run(example())
"""

19
python/packages/autogen-core/src/autogen_core/components/tools/_function_tool.py
View File

@ -41,6 +41,7 @@ class FunctionTool(BaseTool[BaseModel, BaseModel]):
from autogen_core.base import CancellationToken
from autogen_core.components.tools import FunctionTool
from typing_extensions import Annotated
import asyncio
async def get_stock_price(ticker: str, date: Annotated[str, "Date in YYYY/MM/DD"]) -> float:
@ -48,15 +49,19 @@ class FunctionTool(BaseTool[BaseModel, BaseModel]):
return random.uniform(10, 200)
# Initialize a FunctionTool instance for retrieving stock prices.
stock_price_tool = FunctionTool(get_stock_price, description="Fetch the stock price for a given ticker.")
async def example():
# Initialize a FunctionTool instance for retrieving stock prices.
stock_price_tool = FunctionTool(get_stock_price, description="Fetch the stock price for a given ticker.")
# Execute the tool with cancellation support.
cancellation_token = CancellationToken()
result = await stock_price_tool.run_json({"ticker": "AAPL", "date": "2021/01/01"}, cancellation_token)
# Execute the tool with cancellation support.
cancellation_token = CancellationToken()
result = await stock_price_tool.run_json({"ticker": "AAPL", "date": "2021/01/01"}, cancellation_token)
# Output the result as a formatted string.
print(stock_price_tool.return_value_as_string(result))
# Output the result as a formatted string.
print(stock_price_tool.return_value_as_string(result))
asyncio.run(example())
"""
def __init__(self, func: Callable[..., Any], description: str, name: str | None = None) -> None:

48
python/packages/autogen-ext/src/autogen_ext/agents/_openai_assistant_agent.py
View File

@ -105,33 +105,41 @@ class OpenAIAssistantAgent(BaseChatAgent):
from openai import AsyncClient
from autogen_core.base import CancellationToken
import asyncio
from autogen_ext.agents import OpenAIAssistantAgent
from autogen_agentchat.messages import TextMessage
# Create an OpenAI client
client = AsyncClient(api_key="your-api-key", base_url="your-base-url")
# Create an assistant with code interpreter
assistant = OpenAIAssistantAgent(
name="Python Helper",
description="Helps with Python programming",
client=client,
model="gpt-4",
instructions="You are a helpful Python programming assistant.",
tools=["code_interpreter"],
)
async def example():
cancellation_token = CancellationToken()
# Upload files for the assistant to use
await assistant.on_upload_for_code_interpreter("data.csv", cancellation_token)
# Create an OpenAI client
client = AsyncClient(api_key="your-api-key", base_url="your-base-url")
# Get response from the assistant
response = await assistant.on_messages(
[TextMessage(source="user", content="Analyze the data in data.csv")], cancellation_token
)
# Create an assistant with code interpreter
assistant = OpenAIAssistantAgent(
name="Python Helper",
description="Helps with Python programming",
client=client,
model="gpt-4",
instructions="You are a helpful Python programming assistant.",
tools=["code_interpreter"],
)
# Clean up resources
await assistant.delete_uploaded_files(cancellation_token)
await assistant.delete_assistant(cancellation_token)
# Upload files for the assistant to use
await assistant.on_upload_for_code_interpreter("data.csv", cancellation_token)
# Get response from the assistant
_response = await assistant.on_messages(
[TextMessage(source="user", content="Analyze the data in data.csv")], cancellation_token
)
# Clean up resources
await assistant.delete_uploaded_files(cancellation_token)
await assistant.delete_assistant(cancellation_token)
asyncio.run(example())
Args:
name (str): Name of the assistant

5
python/packages/autogen-ext/src/autogen_ext/models/_openai/_openai_client.py
View File

@ -917,12 +917,12 @@ class OpenAIChatCompletionClient(BaseOpenAIChatCompletionClient):
from autogen_ext.models import OpenAIChatCompletionClient
from autogen_core.components.models import UserMessage
opneai_model_client = OpenAIChatCompletionClient(
openai_client = OpenAIChatCompletionClient(
model="gpt-4o-2024-08-06",
# api_key="sk-...", # Optional if you have an OPENAI_API_KEY environment variable set.
)
result = await opneai_model_client.create([UserMessage(content="What is the capital of France?", source="user")])
result = await openai_client.create([UserMessage(content="What is the capital of France?", source="user")]) # type: ignore
print(result)
@ -931,7 +931,6 @@ class OpenAIChatCompletionClient(BaseOpenAIChatCompletionClient):
.. code-block:: python
from autogen_ext.models import OpenAIChatCompletionClient
from autogen_core.components.models import UserMessage
custom_model_client = OpenAIChatCompletionClient(
model="custom-model-name",

83
python/packages/autogen-ext/src/autogen_ext/models/_reply_chat_completion_client.py
View File

@ -38,50 +38,73 @@ class ReplayChatCompletionClient:
.. code-block:: python
chat_completions = [
"Hello, how can I assist you today?",
"I'm happy to help with any questions you have.",
"Is there anything else I can assist you with?",
]
client = ReplayChatCompletionClient(chat_completions)
messages = [LLMMessage(content="What can you do?")]
response = await client.create(messages)
print(response.content) # Output: "Hello, how can I assist you today?"
from autogen_ext.models import ReplayChatCompletionClient
from autogen_core.components.models import UserMessage
async def example():
chat_completions = [
"Hello, how can I assist you today?",
"I'm happy to help with any questions you have.",
"Is there anything else I can assist you with?",
]
client = ReplayChatCompletionClient(chat_completions)
messages = [UserMessage(content="What can you do?", source="user")]
response = await client.create(messages)
print(response.content) # Output: "Hello, how can I assist you today?"
Simple streaming chat completion client to return pre-defined responses
.. code-block:: python
chat_completions = [
"Hello, how can I assist you today?",
"I'm happy to help with any questions you have.",
"Is there anything else I can assist you with?",
]
client = ReplayChatCompletionClient(chat_completions)
import asyncio
from autogen_ext.models import ReplayChatCompletionClient
from autogen_core.components.models import UserMessage
async for token in client.create_stream(messages):
print(token, end="") # Output: "Hello, how can I assist you today?"
async for token in client.create_stream(messages):
print(token, end="") # Output: "I'm happy to help with any questions you have."
async def example():
chat_completions = [
"Hello, how can I assist you today?",
"I'm happy to help with any questions you have.",
"Is there anything else I can assist you with?",
]
client = ReplayChatCompletionClient(chat_completions)
messages = [UserMessage(content="What can you do?", source="user")]
async for token in client.create_stream(messages):
print(token, end="") # Output: "Hello, how can I assist you today?"
async for token in client.create_stream(messages):
print(token, end="") # Output: "I'm happy to help with any questions you have."
asyncio.run(example())
Using `.reset` to reset the chat client state
.. code-block:: python
chat_completions = [
"Hello, how can I assist you today?",
]
client = ReplayChatCompletionClient(chat_completions)
messages = [LLMMessage(content="What can you do?")]
response = await client.create(messages)
print(response.content) # Output: "Hello, how can I assist you today?"
import asyncio
from autogen_ext.models import ReplayChatCompletionClient
from autogen_core.components.models import UserMessage
response = await client.create(messages) # Raises ValueError("No more mock responses available")
client.reset() # Reset the client state (current index of message and token usages)
response = await client.create(messages)
print(response.content) # Output: "Hello, how can I assist you today?" again
async def example():
chat_completions = [
"Hello, how can I assist you today?",
]
client = ReplayChatCompletionClient(chat_completions)
messages = [UserMessage(content="What can you do?", source="user")]
response = await client.create(messages)
print(response.content) # Output: "Hello, how can I assist you today?"
response = await client.create(messages) # Raises ValueError("No more mock responses available")
client.reset() # Reset the client state (current index of message and token usages)
response = await client.create(messages)
print(response.content) # Output: "Hello, how can I assist you today?" again
asyncio.run(example())
"""