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test_group_chat.py 47 kB

Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
fix: Update SKChatCompletionAdapter message conversion (#5749) <!-- Thank you for your contribution! Please review https://microsoft.github.io/autogen/docs/Contribute before opening a pull request. --> <!-- Please add a reviewer to the assignee section when you create a PR. If you don't have the access to it, we will shortly find a reviewer and assign them to your PR. --> ## Why are these changes needed? <!-- Please give a short summary of the change and the problem this solves. --> The PR introduces two changes. The first change is adding a name attribute to `FunctionExecutionResult`. The motivation is that semantic kernel requires it for their function result interface and it seemed like a easy modification as `FunctionExecutionResult` is always created in the context of a `FunctionCall` which will contain the name. I'm unsure if there was a motivation to keep it out but this change makes it easier to trace which tool the result refers to and also increases api compatibility with SK. The second change is an update to how messages are mapped from autogen to semantic kernel, which includes an update/fix in the processing of function results. ## Related issue number <!-- For example: "Closes #1234" --> Related to #5675 but wont fix the underlying issue of anthropic requiring tools during AssistantAgent reflection. ## Checks - [ ] I've included any doc changes needed for <https://microsoft.github.io/autogen/>. See <https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to build and test documentation locally. - [ ] I've added tests (if relevant) corresponding to the changes introduced in this PR. - [ ] I've made sure all auto checks have passed. --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
1 year ago
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  1. import asyncio
  2. import json
  3. import logging
  4. import tempfile
  5. from typing import AsyncGenerator, List, Sequence
  6. import pytest
  7. import pytest_asyncio
  8. from autogen_agentchat import EVENT_LOGGER_NAME
  9. from autogen_agentchat.agents import (
  10. AssistantAgent,
  11. BaseChatAgent,
  12. CodeExecutorAgent,
  13. )
  14. from autogen_agentchat.base import Handoff, Response, TaskResult
  15. from autogen_agentchat.conditions import HandoffTermination, MaxMessageTermination, TextMentionTermination
  16. from autogen_agentchat.messages import (
  17. AgentEvent,
  18. ChatMessage,
  19. HandoffMessage,
  20. MultiModalMessage,
  21. StopMessage,
  22. TextMessage,
  23. ToolCallExecutionEvent,
  24. ToolCallRequestEvent,
  25. ToolCallSummaryMessage,
  26. )
  27. from autogen_agentchat.teams import MagenticOneGroupChat, RoundRobinGroupChat, SelectorGroupChat, Swarm
  28. from autogen_agentchat.teams._group_chat._round_robin_group_chat import RoundRobinGroupChatManager
  29. from autogen_agentchat.teams._group_chat._selector_group_chat import SelectorGroupChatManager
  30. from autogen_agentchat.teams._group_chat._swarm_group_chat import SwarmGroupChatManager
  31. from autogen_agentchat.ui import Console
  32. from autogen_core import AgentId, AgentRuntime, CancellationToken, FunctionCall, SingleThreadedAgentRuntime
  33. from autogen_core.models import (
  34. AssistantMessage,
  35. CreateResult,
  36. FunctionExecutionResult,
  37. FunctionExecutionResultMessage,
  38. LLMMessage,
  39. RequestUsage,
  40. UserMessage,
  41. )
  42. from autogen_core.tools import FunctionTool
  43. from autogen_ext.code_executors.local import LocalCommandLineCodeExecutor
  44. from autogen_ext.models.openai import OpenAIChatCompletionClient
  45. from autogen_ext.models.replay import ReplayChatCompletionClient
  46. from utils import FileLogHandler
  47. logger = logging.getLogger(EVENT_LOGGER_NAME)
  48. logger.setLevel(logging.DEBUG)
  49. logger.addHandler(FileLogHandler("test_group_chat.log"))
  50. class _EchoAgent(BaseChatAgent):
  51. def __init__(self, name: str, description: str) -> None:
  52. super().__init__(name, description)
  53. self._last_message: str | None = None
  54. self._total_messages = 0
  55. @property
  56. def produced_message_types(self) -> Sequence[type[ChatMessage]]:
  57. return (TextMessage,)
  58. @property
  59. def total_messages(self) -> int:
  60. return self._total_messages
  61. async def on_messages(self, messages: Sequence[ChatMessage], cancellation_token: CancellationToken) -> Response:
  62. if len(messages) > 0:
  63. assert isinstance(messages[0], TextMessage)
  64. self._last_message = messages[0].content
  65. self._total_messages += 1
  66. return Response(chat_message=TextMessage(content=messages[0].content, source=self.name))
  67. else:
  68. assert self._last_message is not None
  69. self._total_messages += 1
  70. return Response(chat_message=TextMessage(content=self._last_message, source=self.name))
  71. async def on_reset(self, cancellation_token: CancellationToken) -> None:
  72. self._last_message = None
  73. class _FlakyAgent(BaseChatAgent):
  74. def __init__(self, name: str, description: str) -> None:
  75. super().__init__(name, description)
  76. self._last_message: str | None = None
  77. self._total_messages = 0
  78. @property
  79. def produced_message_types(self) -> Sequence[type[ChatMessage]]:
  80. return (TextMessage,)
  81. @property
  82. def total_messages(self) -> int:
  83. return self._total_messages
  84. async def on_messages(self, messages: Sequence[ChatMessage], cancellation_token: CancellationToken) -> Response:
  85. raise ValueError("I am a flaky agent...")
  86. async def on_reset(self, cancellation_token: CancellationToken) -> None:
  87. self._last_message = None
  88. class _StopAgent(_EchoAgent):
  89. def __init__(self, name: str, description: str, *, stop_at: int = 1) -> None:
  90. super().__init__(name, description)
  91. self._count = 0
  92. self._stop_at = stop_at
  93. @property
  94. def produced_message_types(self) -> Sequence[type[ChatMessage]]:
  95. return (TextMessage, StopMessage)
  96. async def on_messages(self, messages: Sequence[ChatMessage], cancellation_token: CancellationToken) -> Response:
  97. self._count += 1
  98. if self._count < self._stop_at:
  99. return await super().on_messages(messages, cancellation_token)
  100. return Response(chat_message=StopMessage(content="TERMINATE", source=self.name))
  101. def _pass_function(input: str) -> str:
  102. return "pass"
  103. @pytest_asyncio.fixture(params=["single_threaded", "embedded"]) # type: ignore
  104. async def runtime(request: pytest.FixtureRequest) -> AsyncGenerator[AgentRuntime | None, None]:
  105. if request.param == "single_threaded":
  106. runtime = SingleThreadedAgentRuntime()
  107. runtime.start()
  108. yield runtime
  109. await runtime.stop()
  110. elif request.param == "embedded":
  111. yield None
  112. @pytest.mark.asyncio
  113. async def test_round_robin_group_chat(runtime: AgentRuntime | None) -> None:
  114. model_client = ReplayChatCompletionClient(
  115. [
  116. 'Here is the program\n ```python\nprint("Hello, world!")\n```',
  117. "TERMINATE",
  118. ],
  119. )
  120. with tempfile.TemporaryDirectory() as temp_dir:
  121. code_executor_agent = CodeExecutorAgent(
  122. "code_executor", code_executor=LocalCommandLineCodeExecutor(work_dir=temp_dir)
  123. )
  124. coding_assistant_agent = AssistantAgent(
  125. "coding_assistant",
  126. model_client=model_client,
  127. )
  128. termination = TextMentionTermination("TERMINATE")
  129. team = RoundRobinGroupChat(
  130. participants=[coding_assistant_agent, code_executor_agent],
  131. termination_condition=termination,
  132. runtime=runtime,
  133. )
  134. result = await team.run(
  135. task="Write a program that prints 'Hello, world!'",
  136. )
  137. expected_messages = [
  138. "Write a program that prints 'Hello, world!'",
  139. 'Here is the program\n ```python\nprint("Hello, world!")\n```',
  140. "Hello, world!",
  141. "TERMINATE",
  142. ]
  143. # Normalize the messages to remove \r\n and any leading/trailing whitespace.
  144. normalized_messages = [
  145. msg.content.replace("\r\n", "\n").rstrip("\n") if isinstance(msg.content, str) else msg.content
  146. for msg in result.messages
  147. ]
  148. # Assert that all expected messages are in the collected messages
  149. assert normalized_messages == expected_messages
  150. assert result.stop_reason is not None and result.stop_reason == "Text 'TERMINATE' mentioned"
  151. # Test streaming.
  152. model_client.reset()
  153. index = 0
  154. await team.reset()
  155. async for message in team.run_stream(
  156. task="Write a program that prints 'Hello, world!'",
  157. ):
  158. if isinstance(message, TaskResult):
  159. assert message == result
  160. else:
  161. assert message == result.messages[index]
  162. index += 1
  163. # Test message input.
  164. # Text message.
  165. model_client.reset()
  166. index = 0
  167. await team.reset()
  168. result_2 = await team.run(
  169. task=TextMessage(content="Write a program that prints 'Hello, world!'", source="user")
  170. )
  171. assert result == result_2
  172. # Test multi-modal message.
  173. model_client.reset()
  174. index = 0
  175. await team.reset()
  176. result_2 = await team.run(
  177. task=MultiModalMessage(content=["Write a program that prints 'Hello, world!'"], source="user")
  178. )
  179. assert result.messages[0].content == result_2.messages[0].content[0]
  180. assert result.messages[1:] == result_2.messages[1:]
  181. @pytest.mark.asyncio
  182. async def test_round_robin_group_chat_state(runtime: AgentRuntime | None) -> None:
  183. model_client = ReplayChatCompletionClient(
  184. ["No facts", "No plan", "print('Hello, world!')", "TERMINATE"],
  185. )
  186. agent1 = AssistantAgent("agent1", model_client=model_client)
  187. agent2 = AssistantAgent("agent2", model_client=model_client)
  188. termination = TextMentionTermination("TERMINATE")
  189. team1 = RoundRobinGroupChat(participants=[agent1, agent2], termination_condition=termination, runtime=runtime)
  190. await team1.run(task="Write a program that prints 'Hello, world!'")
  191. state = await team1.save_state()
  192. agent3 = AssistantAgent("agent1", model_client=model_client)
  193. agent4 = AssistantAgent("agent2", model_client=model_client)
  194. team2 = RoundRobinGroupChat(participants=[agent3, agent4], termination_condition=termination, runtime=runtime)
  195. await team2.load_state(state)
  196. state2 = await team2.save_state()
  197. assert state == state2
  198. agent1_model_ctx_messages = await agent1._model_context.get_messages() # pyright: ignore
  199. agent2_model_ctx_messages = await agent2._model_context.get_messages() # pyright: ignore
  200. agent3_model_ctx_messages = await agent3._model_context.get_messages() # pyright: ignore
  201. agent4_model_ctx_messages = await agent4._model_context.get_messages() # pyright: ignore
  202. assert agent3_model_ctx_messages == agent1_model_ctx_messages
  203. assert agent4_model_ctx_messages == agent2_model_ctx_messages
  204. manager_1 = await team1._runtime.try_get_underlying_agent_instance( # pyright: ignore
  205. AgentId(f"{team1._group_chat_manager_name}_{team1._team_id}", team1._team_id), # pyright: ignore
  206. RoundRobinGroupChatManager, # pyright: ignore
  207. ) # pyright: ignore
  208. manager_2 = await team2._runtime.try_get_underlying_agent_instance( # pyright: ignore
  209. AgentId(f"{team2._group_chat_manager_name}_{team2._team_id}", team2._team_id), # pyright: ignore
  210. RoundRobinGroupChatManager, # pyright: ignore
  211. ) # pyright: ignore
  212. assert manager_1._current_turn == manager_2._current_turn # pyright: ignore
  213. assert manager_1._message_thread == manager_2._message_thread # pyright: ignore
  214. @pytest.mark.asyncio
  215. async def test_round_robin_group_chat_with_tools(runtime: AgentRuntime | None) -> None:
  216. model_client = ReplayChatCompletionClient(
  217. chat_completions=[
  218. CreateResult(
  219. finish_reason="function_calls",
  220. content=[FunctionCall(id="1", name="pass", arguments=json.dumps({"input": "pass"}))],
  221. usage=RequestUsage(prompt_tokens=0, completion_tokens=0),
  222. cached=False,
  223. ),
  224. "Hello",
  225. "TERMINATE",
  226. ],
  227. model_info={"family": "gpt-4o", "function_calling": True, "json_output": True, "vision": True},
  228. )
  229. tool = FunctionTool(_pass_function, name="pass", description="pass function")
  230. tool_use_agent = AssistantAgent("tool_use_agent", model_client=model_client, tools=[tool])
  231. echo_agent = _EchoAgent("echo_agent", description="echo agent")
  232. termination = TextMentionTermination("TERMINATE")
  233. team = RoundRobinGroupChat(
  234. participants=[tool_use_agent, echo_agent], termination_condition=termination, runtime=runtime
  235. )
  236. result = await team.run(
  237. task="Write a program that prints 'Hello, world!'",
  238. )
  239. assert len(result.messages) == 8
  240. assert isinstance(result.messages[0], TextMessage) # task
  241. assert isinstance(result.messages[1], ToolCallRequestEvent) # tool call
  242. assert isinstance(result.messages[2], ToolCallExecutionEvent) # tool call result
  243. assert isinstance(result.messages[3], ToolCallSummaryMessage) # tool use agent response
  244. assert result.messages[3].content == "pass" # ensure the tool call was executed
  245. assert isinstance(result.messages[4], TextMessage) # echo agent response
  246. assert isinstance(result.messages[5], TextMessage) # tool use agent response
  247. assert isinstance(result.messages[6], TextMessage) # echo agent response
  248. assert isinstance(result.messages[7], TextMessage) # tool use agent response, that has TERMINATE
  249. assert result.messages[7].content == "TERMINATE"
  250. assert result.stop_reason is not None and result.stop_reason == "Text 'TERMINATE' mentioned"
  251. # Test streaming.
  252. await tool_use_agent._model_context.clear() # pyright: ignore
  253. model_client.reset()
  254. index = 0
  255. await team.reset()
  256. async for message in team.run_stream(
  257. task="Write a program that prints 'Hello, world!'",
  258. ):
  259. if isinstance(message, TaskResult):
  260. assert message == result
  261. else:
  262. assert message == result.messages[index]
  263. index += 1
  264. # Test Console.
  265. await tool_use_agent._model_context.clear() # pyright: ignore
  266. model_client.reset()
  267. index = 0
  268. await team.reset()
  269. result2 = await Console(team.run_stream(task="Write a program that prints 'Hello, world!'"))
  270. assert result2 == result
  271. @pytest.mark.asyncio
  272. async def test_round_robin_group_chat_with_resume_and_reset(runtime: AgentRuntime | None) -> None:
  273. agent_1 = _EchoAgent("agent_1", description="echo agent 1")
  274. agent_2 = _EchoAgent("agent_2", description="echo agent 2")
  275. agent_3 = _EchoAgent("agent_3", description="echo agent 3")
  276. agent_4 = _EchoAgent("agent_4", description="echo agent 4")
  277. termination = MaxMessageTermination(3)
  278. team = RoundRobinGroupChat(
  279. participants=[agent_1, agent_2, agent_3, agent_4], termination_condition=termination, runtime=runtime
  280. )
  281. result = await team.run(
  282. task="Write a program that prints 'Hello, world!'",
  283. )
  284. assert len(result.messages) == 3
  285. assert result.messages[1].source == "agent_1"
  286. assert result.messages[2].source == "agent_2"
  287. assert result.stop_reason is not None
  288. # Resume.
  289. result = await team.run()
  290. assert len(result.messages) == 3
  291. assert result.messages[0].source == "agent_3"
  292. assert result.messages[1].source == "agent_4"
  293. assert result.messages[2].source == "agent_1"
  294. assert result.stop_reason is not None
  295. # Reset.
  296. await team.reset()
  297. result = await team.run(task="Write a program that prints 'Hello, world!'")
  298. assert len(result.messages) == 3
  299. assert result.messages[1].source == "agent_1"
  300. assert result.messages[2].source == "agent_2"
  301. assert result.stop_reason is not None
  302. # TODO: add runtime fixture for testing with custom runtime once the issue regarding
  303. # hanging on exception is resolved.
  304. @pytest.mark.asyncio
  305. async def test_round_robin_group_chat_with_exception_raised() -> None:
  306. agent_1 = _EchoAgent("agent_1", description="echo agent 1")
  307. agent_2 = _FlakyAgent("agent_2", description="echo agent 2")
  308. agent_3 = _EchoAgent("agent_3", description="echo agent 3")
  309. termination = MaxMessageTermination(3)
  310. team = RoundRobinGroupChat(
  311. participants=[agent_1, agent_2, agent_3],
  312. termination_condition=termination,
  313. )
  314. with pytest.raises(ValueError, match="I am a flaky agent..."):
  315. await team.run(
  316. task="Write a program that prints 'Hello, world!'",
  317. )
  318. @pytest.mark.asyncio
  319. async def test_round_robin_group_chat_max_turn(runtime: AgentRuntime | None) -> None:
  320. agent_1 = _EchoAgent("agent_1", description="echo agent 1")
  321. agent_2 = _EchoAgent("agent_2", description="echo agent 2")
  322. agent_3 = _EchoAgent("agent_3", description="echo agent 3")
  323. agent_4 = _EchoAgent("agent_4", description="echo agent 4")
  324. team = RoundRobinGroupChat(participants=[agent_1, agent_2, agent_3, agent_4], max_turns=3, runtime=runtime)
  325. result = await team.run(
  326. task="Write a program that prints 'Hello, world!'",
  327. )
  328. assert len(result.messages) == 4
  329. assert result.messages[1].source == "agent_1"
  330. assert result.messages[2].source == "agent_2"
  331. assert result.messages[3].source == "agent_3"
  332. assert result.stop_reason is not None
  333. # Resume.
  334. result = await team.run()
  335. assert len(result.messages) == 3
  336. assert result.messages[0].source == "agent_4"
  337. assert result.messages[1].source == "agent_1"
  338. assert result.messages[2].source == "agent_2"
  339. assert result.stop_reason is not None
  340. # Reset.
  341. await team.reset()
  342. result = await team.run(task="Write a program that prints 'Hello, world!'")
  343. assert len(result.messages) == 4
  344. assert result.messages[1].source == "agent_1"
  345. assert result.messages[2].source == "agent_2"
  346. assert result.messages[3].source == "agent_3"
  347. assert result.stop_reason is not None
  348. @pytest.mark.asyncio
  349. async def test_round_robin_group_chat_cancellation(runtime: AgentRuntime | None) -> None:
  350. agent_1 = _EchoAgent("agent_1", description="echo agent 1")
  351. agent_2 = _EchoAgent("agent_2", description="echo agent 2")
  352. agent_3 = _EchoAgent("agent_3", description="echo agent 3")
  353. agent_4 = _EchoAgent("agent_4", description="echo agent 4")
  354. # Set max_turns to a large number to avoid stopping due to max_turns before cancellation.
  355. team = RoundRobinGroupChat(participants=[agent_1, agent_2, agent_3, agent_4], max_turns=1000, runtime=runtime)
  356. cancellation_token = CancellationToken()
  357. run_task = asyncio.create_task(
  358. team.run(
  359. task="Write a program that prints 'Hello, world!'",
  360. cancellation_token=cancellation_token,
  361. )
  362. )
  363. await asyncio.sleep(0.1)
  364. # Cancel the task.
  365. cancellation_token.cancel()
  366. with pytest.raises(asyncio.CancelledError):
  367. await run_task
  368. # Still can run again and finish the task.
  369. result = await team.run()
  370. assert result.stop_reason is not None and result.stop_reason == "Maximum number of turns 1000 reached."
  371. @pytest.mark.asyncio
  372. async def test_selector_group_chat(runtime: AgentRuntime | None) -> None:
  373. model_client = ReplayChatCompletionClient(
  374. chat_completions=[
  375. "agent3",
  376. "agent2",
  377. "agent1",
  378. "agent2",
  379. "agent1",
  380. ]
  381. )
  382. agent1 = _StopAgent("agent1", description="echo agent 1", stop_at=2)
  383. agent2 = _EchoAgent("agent2", description="echo agent 2")
  384. agent3 = _EchoAgent("agent3", description="echo agent 3")
  385. termination = TextMentionTermination("TERMINATE")
  386. team = SelectorGroupChat(
  387. participants=[agent1, agent2, agent3],
  388. model_client=model_client,
  389. termination_condition=termination,
  390. runtime=runtime,
  391. )
  392. result = await team.run(
  393. task="Write a program that prints 'Hello, world!'",
  394. )
  395. assert len(result.messages) == 6
  396. assert result.messages[0].content == "Write a program that prints 'Hello, world!'"
  397. assert result.messages[1].source == "agent3"
  398. assert result.messages[2].source == "agent2"
  399. assert result.messages[3].source == "agent1"
  400. assert result.messages[4].source == "agent2"
  401. assert result.messages[5].source == "agent1"
  402. assert result.stop_reason is not None and result.stop_reason == "Text 'TERMINATE' mentioned"
  403. # Test streaming.
  404. model_client.reset()
  405. agent1._count = 0 # pyright: ignore
  406. index = 0
  407. await team.reset()
  408. async for message in team.run_stream(
  409. task="Write a program that prints 'Hello, world!'",
  410. ):
  411. if isinstance(message, TaskResult):
  412. assert message == result
  413. else:
  414. assert message == result.messages[index]
  415. index += 1
  416. # Test Console.
  417. model_client.reset()
  418. agent1._count = 0 # pyright: ignore
  419. index = 0
  420. await team.reset()
  421. result2 = await Console(team.run_stream(task="Write a program that prints 'Hello, world!'"))
  422. assert result2 == result
  423. @pytest.mark.asyncio
  424. async def test_selector_group_chat_state(runtime: AgentRuntime | None) -> None:
  425. model_client = ReplayChatCompletionClient(
  426. ["agent1", "No facts", "agent2", "No plan", "agent1", "print('Hello, world!')", "agent2", "TERMINATE"],
  427. )
  428. agent1 = AssistantAgent("agent1", model_client=model_client)
  429. agent2 = AssistantAgent("agent2", model_client=model_client)
  430. termination = TextMentionTermination("TERMINATE")
  431. team1 = SelectorGroupChat(
  432. participants=[agent1, agent2],
  433. termination_condition=termination,
  434. model_client=model_client,
  435. runtime=runtime,
  436. )
  437. await team1.run(task="Write a program that prints 'Hello, world!'")
  438. state = await team1.save_state()
  439. agent3 = AssistantAgent("agent1", model_client=model_client)
  440. agent4 = AssistantAgent("agent2", model_client=model_client)
  441. team2 = SelectorGroupChat(
  442. participants=[agent3, agent4], termination_condition=termination, model_client=model_client
  443. )
  444. await team2.load_state(state)
  445. state2 = await team2.save_state()
  446. assert state == state2
  447. agent1_model_ctx_messages = await agent1._model_context.get_messages() # pyright: ignore
  448. agent2_model_ctx_messages = await agent2._model_context.get_messages() # pyright: ignore
  449. agent3_model_ctx_messages = await agent3._model_context.get_messages() # pyright: ignore
  450. agent4_model_ctx_messages = await agent4._model_context.get_messages() # pyright: ignore
  451. assert agent3_model_ctx_messages == agent1_model_ctx_messages
  452. assert agent4_model_ctx_messages == agent2_model_ctx_messages
  453. manager_1 = await team1._runtime.try_get_underlying_agent_instance( # pyright: ignore
  454. AgentId(f"{team1._group_chat_manager_name}_{team1._team_id}", team1._team_id), # pyright: ignore
  455. SelectorGroupChatManager, # pyright: ignore
  456. ) # pyright: ignore
  457. manager_2 = await team2._runtime.try_get_underlying_agent_instance( # pyright: ignore
  458. AgentId(f"{team2._group_chat_manager_name}_{team2._team_id}", team2._team_id), # pyright: ignore
  459. SelectorGroupChatManager, # pyright: ignore
  460. ) # pyright: ignore
  461. assert manager_1._message_thread == manager_2._message_thread # pyright: ignore
  462. assert manager_1._previous_speaker == manager_2._previous_speaker # pyright: ignore
  463. @pytest.mark.asyncio
  464. async def test_selector_group_chat_two_speakers(runtime: AgentRuntime | None) -> None:
  465. model_client = ReplayChatCompletionClient(["agent2"])
  466. agent1 = _StopAgent("agent1", description="echo agent 1", stop_at=2)
  467. agent2 = _EchoAgent("agent2", description="echo agent 2")
  468. termination = TextMentionTermination("TERMINATE")
  469. team = SelectorGroupChat(
  470. participants=[agent1, agent2],
  471. termination_condition=termination,
  472. model_client=model_client,
  473. runtime=runtime,
  474. )
  475. result = await team.run(
  476. task="Write a program that prints 'Hello, world!'",
  477. )
  478. assert len(result.messages) == 5
  479. assert result.messages[0].content == "Write a program that prints 'Hello, world!'"
  480. assert result.messages[1].source == "agent2"
  481. assert result.messages[2].source == "agent1"
  482. assert result.messages[3].source == "agent2"
  483. assert result.messages[4].source == "agent1"
  484. assert result.stop_reason is not None and result.stop_reason == "Text 'TERMINATE' mentioned"
  485. # Test streaming.
  486. model_client.reset()
  487. agent1._count = 0 # pyright: ignore
  488. index = 0
  489. await team.reset()
  490. async for message in team.run_stream(task="Write a program that prints 'Hello, world!'"):
  491. if isinstance(message, TaskResult):
  492. assert message == result
  493. else:
  494. assert message == result.messages[index]
  495. index += 1
  496. # Test Console.
  497. model_client.reset()
  498. agent1._count = 0 # pyright: ignore
  499. index = 0
  500. await team.reset()
  501. result2 = await Console(team.run_stream(task="Write a program that prints 'Hello, world!'"))
  502. assert result2 == result
  503. @pytest.mark.asyncio
  504. async def test_selector_group_chat_two_speakers_allow_repeated(runtime: AgentRuntime | None) -> None:
  505. model_client = ReplayChatCompletionClient(
  506. [
  507. "agent2",
  508. "agent2",
  509. "agent1",
  510. ]
  511. )
  512. agent1 = _StopAgent("agent1", description="echo agent 1", stop_at=1)
  513. agent2 = _EchoAgent("agent2", description="echo agent 2")
  514. termination = TextMentionTermination("TERMINATE")
  515. team = SelectorGroupChat(
  516. participants=[agent1, agent2],
  517. model_client=model_client,
  518. termination_condition=termination,
  519. allow_repeated_speaker=True,
  520. runtime=runtime,
  521. )
  522. result = await team.run(task="Write a program that prints 'Hello, world!'")
  523. assert len(result.messages) == 4
  524. assert result.messages[0].content == "Write a program that prints 'Hello, world!'"
  525. assert result.messages[1].source == "agent2"
  526. assert result.messages[2].source == "agent2"
  527. assert result.messages[3].source == "agent1"
  528. assert result.stop_reason is not None and result.stop_reason == "Text 'TERMINATE' mentioned"
  529. # Test streaming.
  530. model_client.reset()
  531. index = 0
  532. await team.reset()
  533. async for message in team.run_stream(task="Write a program that prints 'Hello, world!'"):
  534. if isinstance(message, TaskResult):
  535. assert message == result
  536. else:
  537. assert message == result.messages[index]
  538. index += 1
  539. # Test Console.
  540. model_client.reset()
  541. index = 0
  542. await team.reset()
  543. result2 = await Console(team.run_stream(task="Write a program that prints 'Hello, world!'"))
  544. assert result2 == result
  545. @pytest.mark.asyncio
  546. async def test_selector_group_chat_succcess_after_2_attempts(runtime: AgentRuntime | None) -> None:
  547. model_client = ReplayChatCompletionClient(
  548. ["agent2, agent3", "agent2"],
  549. )
  550. agent1 = _StopAgent("agent1", description="echo agent 1", stop_at=1)
  551. agent2 = _EchoAgent("agent2", description="echo agent 2")
  552. agent3 = _EchoAgent("agent3", description="echo agent 3")
  553. team = SelectorGroupChat(
  554. participants=[agent1, agent2, agent3],
  555. model_client=model_client,
  556. max_turns=1,
  557. runtime=runtime,
  558. )
  559. result = await team.run(task="Write a program that prints 'Hello, world!'")
  560. assert len(result.messages) == 2
  561. assert result.messages[0].content == "Write a program that prints 'Hello, world!'"
  562. assert result.messages[1].source == "agent2"
  563. @pytest.mark.asyncio
  564. async def test_selector_group_chat_fall_back_to_first_after_3_attempts(runtime: AgentRuntime | None) -> None:
  565. model_client = ReplayChatCompletionClient(
  566. [
  567. "agent2, agent3", # Multiple speakers
  568. "agent5", # Non-existent speaker
  569. "agent3, agent1", # Multiple speakers
  570. ]
  571. )
  572. agent1 = _StopAgent("agent1", description="echo agent 1", stop_at=1)
  573. agent2 = _EchoAgent("agent2", description="echo agent 2")
  574. agent3 = _EchoAgent("agent3", description="echo agent 3")
  575. team = SelectorGroupChat(
  576. participants=[agent1, agent2, agent3],
  577. model_client=model_client,
  578. max_turns=1,
  579. runtime=runtime,
  580. )
  581. result = await team.run(task="Write a program that prints 'Hello, world!'")
  582. assert len(result.messages) == 2
  583. assert result.messages[0].content == "Write a program that prints 'Hello, world!'"
  584. assert result.messages[1].source == "agent1"
  585. @pytest.mark.asyncio
  586. async def test_selector_group_chat_fall_back_to_previous_after_3_attempts(runtime: AgentRuntime | None) -> None:
  587. model_client = ReplayChatCompletionClient(
  588. ["agent2", "agent2", "agent2", "agent2"],
  589. )
  590. agent1 = _StopAgent("agent1", description="echo agent 1", stop_at=1)
  591. agent2 = _EchoAgent("agent2", description="echo agent 2")
  592. agent3 = _EchoAgent("agent3", description="echo agent 3")
  593. team = SelectorGroupChat(
  594. participants=[agent1, agent2, agent3],
  595. model_client=model_client,
  596. max_turns=2,
  597. runtime=runtime,
  598. )
  599. result = await team.run(task="Write a program that prints 'Hello, world!'")
  600. assert len(result.messages) == 3
  601. assert result.messages[0].content == "Write a program that prints 'Hello, world!'"
  602. assert result.messages[1].source == "agent2"
  603. assert result.messages[2].source == "agent2"
  604. @pytest.mark.asyncio
  605. async def test_selector_group_chat_custom_selector(runtime: AgentRuntime | None) -> None:
  606. model_client = ReplayChatCompletionClient(["agent3"])
  607. agent1 = _EchoAgent("agent1", description="echo agent 1")
  608. agent2 = _EchoAgent("agent2", description="echo agent 2")
  609. agent3 = _EchoAgent("agent3", description="echo agent 3")
  610. agent4 = _EchoAgent("agent4", description="echo agent 4")
  611. def _select_agent(messages: Sequence[AgentEvent | ChatMessage]) -> str | None:
  612. if len(messages) == 0:
  613. return "agent1"
  614. elif messages[-1].source == "agent1":
  615. return "agent2"
  616. elif messages[-1].source == "agent2":
  617. return None
  618. elif messages[-1].source == "agent3":
  619. return "agent4"
  620. else:
  621. return "agent1"
  622. termination = MaxMessageTermination(6)
  623. team = SelectorGroupChat(
  624. participants=[agent1, agent2, agent3, agent4],
  625. model_client=model_client,
  626. selector_func=_select_agent,
  627. termination_condition=termination,
  628. runtime=runtime,
  629. )
  630. result = await team.run(task="task")
  631. assert len(result.messages) == 6
  632. assert result.messages[1].source == "agent1"
  633. assert result.messages[2].source == "agent2"
  634. assert result.messages[3].source == "agent3"
  635. assert result.messages[4].source == "agent4"
  636. assert result.messages[5].source == "agent1"
  637. assert (
  638. result.stop_reason is not None
  639. and result.stop_reason == "Maximum number of messages 6 reached, current message count: 6"
  640. )
  641. class _HandOffAgent(BaseChatAgent):
  642. def __init__(self, name: str, description: str, next_agent: str) -> None:
  643. super().__init__(name, description)
  644. self._next_agent = next_agent
  645. @property
  646. def produced_message_types(self) -> Sequence[type[ChatMessage]]:
  647. return (HandoffMessage,)
  648. async def on_messages(self, messages: Sequence[ChatMessage], cancellation_token: CancellationToken) -> Response:
  649. return Response(
  650. chat_message=HandoffMessage(
  651. content=f"Transferred to {self._next_agent}.", target=self._next_agent, source=self.name
  652. )
  653. )
  654. async def on_reset(self, cancellation_token: CancellationToken) -> None:
  655. pass
  656. @pytest.mark.asyncio
  657. async def test_swarm_handoff(runtime: AgentRuntime | None) -> None:
  658. first_agent = _HandOffAgent("first_agent", description="first agent", next_agent="second_agent")
  659. second_agent = _HandOffAgent("second_agent", description="second agent", next_agent="third_agent")
  660. third_agent = _HandOffAgent("third_agent", description="third agent", next_agent="first_agent")
  661. termination = MaxMessageTermination(6)
  662. team = Swarm([second_agent, first_agent, third_agent], termination_condition=termination, runtime=runtime)
  663. result = await team.run(task="task")
  664. assert len(result.messages) == 6
  665. assert result.messages[0].content == "task"
  666. assert result.messages[1].content == "Transferred to third_agent."
  667. assert result.messages[2].content == "Transferred to first_agent."
  668. assert result.messages[3].content == "Transferred to second_agent."
  669. assert result.messages[4].content == "Transferred to third_agent."
  670. assert result.messages[5].content == "Transferred to first_agent."
  671. assert (
  672. result.stop_reason is not None
  673. and result.stop_reason == "Maximum number of messages 6 reached, current message count: 6"
  674. )
  675. # Test streaming.
  676. index = 0
  677. await team.reset()
  678. stream = team.run_stream(task="task")
  679. async for message in stream:
  680. if isinstance(message, TaskResult):
  681. assert message == result
  682. else:
  683. assert message == result.messages[index]
  684. index += 1
  685. # Test save and load.
  686. state = await team.save_state()
  687. first_agent2 = _HandOffAgent("first_agent", description="first agent", next_agent="second_agent")
  688. second_agent2 = _HandOffAgent("second_agent", description="second agent", next_agent="third_agent")
  689. third_agent2 = _HandOffAgent("third_agent", description="third agent", next_agent="first_agent")
  690. team2 = Swarm([second_agent2, first_agent2, third_agent2], termination_condition=termination, runtime=runtime)
  691. await team2.load_state(state)
  692. state2 = await team2.save_state()
  693. assert state == state2
  694. manager_1 = await team._runtime.try_get_underlying_agent_instance( # pyright: ignore
  695. AgentId(f"{team._group_chat_manager_name}_{team._team_id}", team._team_id), # pyright: ignore
  696. SwarmGroupChatManager, # pyright: ignore
  697. ) # pyright: ignore
  698. manager_2 = await team2._runtime.try_get_underlying_agent_instance( # pyright: ignore
  699. AgentId(f"{team2._group_chat_manager_name}_{team2._team_id}", team2._team_id), # pyright: ignore
  700. SwarmGroupChatManager, # pyright: ignore
  701. ) # pyright: ignore
  702. assert manager_1._message_thread == manager_2._message_thread # pyright: ignore
  703. assert manager_1._current_speaker == manager_2._current_speaker # pyright: ignore
  704. @pytest.mark.asyncio
  705. async def test_swarm_handoff_using_tool_calls(runtime: AgentRuntime | None) -> None:
  706. model_client = ReplayChatCompletionClient(
  707. chat_completions=[
  708. CreateResult(
  709. finish_reason="function_calls",
  710. content=[FunctionCall(id="1", name="handoff_to_agent2", arguments=json.dumps({}))],
  711. usage=RequestUsage(prompt_tokens=0, completion_tokens=0),
  712. cached=False,
  713. ),
  714. "Hello",
  715. "TERMINATE",
  716. ],
  717. model_info={"family": "gpt-4o", "function_calling": True, "json_output": True, "vision": True},
  718. )
  719. agent1 = AssistantAgent(
  720. "agent1",
  721. model_client=model_client,
  722. handoffs=[Handoff(target="agent2", name="handoff_to_agent2", message="handoff to agent2")],
  723. )
  724. agent2 = _HandOffAgent("agent2", description="agent 2", next_agent="agent1")
  725. termination = TextMentionTermination("TERMINATE")
  726. team = Swarm([agent1, agent2], termination_condition=termination, runtime=runtime)
  727. result = await team.run(task="task")
  728. assert len(result.messages) == 7
  729. assert result.messages[0].content == "task"
  730. assert isinstance(result.messages[1], ToolCallRequestEvent)
  731. assert isinstance(result.messages[2], ToolCallExecutionEvent)
  732. assert result.messages[3].content == "handoff to agent2"
  733. assert result.messages[4].content == "Transferred to agent1."
  734. assert result.messages[5].content == "Hello"
  735. assert result.messages[6].content == "TERMINATE"
  736. assert result.stop_reason is not None and result.stop_reason == "Text 'TERMINATE' mentioned"
  737. # Test streaming.
  738. await agent1._model_context.clear() # pyright: ignore
  739. model_client.reset()
  740. index = 0
  741. await team.reset()
  742. stream = team.run_stream(task="task")
  743. async for message in stream:
  744. if isinstance(message, TaskResult):
  745. assert message == result
  746. else:
  747. assert message == result.messages[index]
  748. index += 1
  749. # Test Console
  750. await agent1._model_context.clear() # pyright: ignore
  751. model_client.reset()
  752. index = 0
  753. await team.reset()
  754. result2 = await Console(team.run_stream(task="task"))
  755. assert result2 == result
  756. @pytest.mark.asyncio
  757. async def test_swarm_pause_and_resume(runtime: AgentRuntime | None) -> None:
  758. first_agent = _HandOffAgent("first_agent", description="first agent", next_agent="second_agent")
  759. second_agent = _HandOffAgent("second_agent", description="second agent", next_agent="third_agent")
  760. third_agent = _HandOffAgent("third_agent", description="third agent", next_agent="first_agent")
  761. team = Swarm([second_agent, first_agent, third_agent], max_turns=1, runtime=runtime)
  762. result = await team.run(task="task")
  763. assert len(result.messages) == 2
  764. assert result.messages[0].content == "task"
  765. assert result.messages[1].content == "Transferred to third_agent."
  766. # Resume with a new task.
  767. result = await team.run(task="new task")
  768. assert len(result.messages) == 2
  769. assert result.messages[0].content == "new task"
  770. assert result.messages[1].content == "Transferred to first_agent."
  771. # Resume with the same task.
  772. result = await team.run()
  773. assert len(result.messages) == 1
  774. assert result.messages[0].content == "Transferred to second_agent."
  775. @pytest.mark.asyncio
  776. async def test_swarm_with_parallel_tool_calls(runtime: AgentRuntime | None) -> None:
  777. model_client = ReplayChatCompletionClient(
  778. [
  779. CreateResult(
  780. finish_reason="function_calls",
  781. content=[
  782. FunctionCall(id="1", name="tool1", arguments="{}"),
  783. FunctionCall(id="2", name="tool2", arguments="{}"),
  784. FunctionCall(id="3", name="handoff_to_agent2", arguments=json.dumps({})),
  785. ],
  786. usage=RequestUsage(prompt_tokens=0, completion_tokens=0),
  787. cached=False,
  788. ),
  789. "Hello",
  790. "TERMINATE",
  791. ],
  792. model_info={"family": "gpt-4o", "function_calling": True, "json_output": True, "vision": True},
  793. )
  794. expected_handoff_context: List[LLMMessage] = [
  795. AssistantMessage(
  796. source="agent1",
  797. content=[
  798. FunctionCall(id="1", name="tool1", arguments="{}"),
  799. FunctionCall(id="2", name="tool2", arguments="{}"),
  800. ],
  801. ),
  802. FunctionExecutionResultMessage(
  803. content=[
  804. FunctionExecutionResult(content="tool1", call_id="1", is_error=False, name="tool1"),
  805. FunctionExecutionResult(content="tool2", call_id="2", is_error=False, name="tool2"),
  806. ]
  807. ),
  808. ]
  809. def tool1() -> str:
  810. return "tool1"
  811. def tool2() -> str:
  812. return "tool2"
  813. agent1 = AssistantAgent(
  814. "agent1",
  815. model_client=model_client,
  816. handoffs=[Handoff(target="agent2", name="handoff_to_agent2", message="handoff to agent2")],
  817. tools=[tool1, tool2],
  818. )
  819. agent2 = AssistantAgent(
  820. "agent2",
  821. model_client=model_client,
  822. )
  823. termination = TextMentionTermination("TERMINATE")
  824. team = Swarm([agent1, agent2], termination_condition=termination, runtime=runtime)
  825. result = await team.run(task="task")
  826. assert len(result.messages) == 6
  827. assert result.messages[0] == TextMessage(content="task", source="user")
  828. assert isinstance(result.messages[1], ToolCallRequestEvent)
  829. assert isinstance(result.messages[2], ToolCallExecutionEvent)
  830. assert result.messages[3] == HandoffMessage(
  831. content="handoff to agent2",
  832. target="agent2",
  833. source="agent1",
  834. context=expected_handoff_context,
  835. )
  836. assert result.messages[4].content == "Hello"
  837. assert result.messages[4].source == "agent2"
  838. assert result.messages[5].content == "TERMINATE"
  839. assert result.messages[5].source == "agent2"
  840. # Verify the tool calls are in agent2's context.
  841. agent2_model_ctx_messages = await agent2._model_context.get_messages() # pyright: ignore
  842. assert agent2_model_ctx_messages[0] == UserMessage(content="task", source="user")
  843. assert agent2_model_ctx_messages[1] == expected_handoff_context[0]
  844. assert agent2_model_ctx_messages[2] == expected_handoff_context[1]
  845. @pytest.mark.asyncio
  846. async def test_swarm_with_handoff_termination(runtime: AgentRuntime | None) -> None:
  847. first_agent = _HandOffAgent("first_agent", description="first agent", next_agent="second_agent")
  848. second_agent = _HandOffAgent("second_agent", description="second agent", next_agent="third_agent")
  849. third_agent = _HandOffAgent("third_agent", description="third agent", next_agent="first_agent")
  850. # Handoff to an existing agent.
  851. termination = HandoffTermination(target="third_agent")
  852. team = Swarm([second_agent, first_agent, third_agent], termination_condition=termination, runtime=runtime)
  853. # Start
  854. result = await team.run(task="task")
  855. assert len(result.messages) == 2
  856. assert result.messages[0].content == "task"
  857. assert result.messages[1].content == "Transferred to third_agent."
  858. # Resume existing.
  859. result = await team.run()
  860. assert len(result.messages) == 3
  861. assert result.messages[0].content == "Transferred to first_agent."
  862. assert result.messages[1].content == "Transferred to second_agent."
  863. assert result.messages[2].content == "Transferred to third_agent."
  864. # Resume new task.
  865. result = await team.run(task="new task")
  866. assert len(result.messages) == 4
  867. assert result.messages[0].content == "new task"
  868. assert result.messages[1].content == "Transferred to first_agent."
  869. assert result.messages[2].content == "Transferred to second_agent."
  870. assert result.messages[3].content == "Transferred to third_agent."
  871. # Handoff to a non-existing agent.
  872. third_agent = _HandOffAgent("third_agent", description="third agent", next_agent="non_existing_agent")
  873. termination = HandoffTermination(target="non_existing_agent")
  874. team = Swarm([second_agent, first_agent, third_agent], termination_condition=termination, runtime=runtime)
  875. # Start
  876. result = await team.run(task="task")
  877. assert len(result.messages) == 3
  878. assert result.messages[0].content == "task"
  879. assert result.messages[1].content == "Transferred to third_agent."
  880. assert result.messages[2].content == "Transferred to non_existing_agent."
  881. # Attempt to resume.
  882. with pytest.raises(ValueError):
  883. await team.run()
  884. # Attempt to resume with a new task.
  885. with pytest.raises(ValueError):
  886. await team.run(task="new task")
  887. # Resume with a HandoffMessage
  888. result = await team.run(task=HandoffMessage(content="Handoff to first_agent.", target="first_agent", source="user"))
  889. assert len(result.messages) == 4
  890. assert result.messages[0].content == "Handoff to first_agent."
  891. assert result.messages[1].content == "Transferred to second_agent."
  892. assert result.messages[2].content == "Transferred to third_agent."
  893. assert result.messages[3].content == "Transferred to non_existing_agent."
  894. @pytest.mark.asyncio
  895. async def test_round_robin_group_chat_with_message_list(runtime: AgentRuntime | None) -> None:
  896. # Create a simple team with echo agents
  897. agent1 = _EchoAgent("Agent1", "First agent")
  898. agent2 = _EchoAgent("Agent2", "Second agent")
  899. termination = MaxMessageTermination(4) # Stop after 4 messages
  900. team = RoundRobinGroupChat([agent1, agent2], termination_condition=termination, runtime=runtime)
  901. # Create a list of messages
  902. messages: List[ChatMessage] = [
  903. TextMessage(content="Message 1", source="user"),
  904. TextMessage(content="Message 2", source="user"),
  905. TextMessage(content="Message 3", source="user"),
  906. ]
  907. # Run the team with the message list
  908. result = await team.run(task=messages)
  909. # Verify the messages were processed in order
  910. assert len(result.messages) == 4 # Initial messages + echo until termination
  911. assert result.messages[0].content == "Message 1" # First message
  912. assert result.messages[1].content == "Message 2" # Second message
  913. assert result.messages[2].content == "Message 3" # Third message
  914. assert result.messages[3].content == "Message 1" # Echo from first agent
  915. assert result.stop_reason == "Maximum number of messages 4 reached, current message count: 4"
  916. # Test with streaming
  917. await team.reset()
  918. index = 0
  919. async for message in team.run_stream(task=messages):
  920. if isinstance(message, TaskResult):
  921. assert message == result
  922. else:
  923. assert message == result.messages[index]
  924. index += 1
  925. # Test with invalid message list
  926. with pytest.raises(ValueError, match="All messages in task list must be valid ChatMessage types"):
  927. await team.run(task=["not a message"]) # type: ignore[list-item, arg-type] # intentionally testing invalid input
  928. # Test with empty message list
  929. with pytest.raises(ValueError, match="Task list cannot be empty"):
  930. await team.run(task=[])
  931. @pytest.mark.asyncio
  932. async def test_declarative_groupchats_with_config(runtime: AgentRuntime | None) -> None:
  933. # Create basic agents and components for testing
  934. agent1 = AssistantAgent(
  935. "agent_1",
  936. model_client=OpenAIChatCompletionClient(model="gpt-4o-2024-05-13", api_key=""),
  937. handoffs=["agent_2"],
  938. )
  939. agent2 = AssistantAgent("agent_2", model_client=OpenAIChatCompletionClient(model="gpt-4o-2024-05-13", api_key=""))
  940. termination = MaxMessageTermination(4)
  941. model_client = OpenAIChatCompletionClient(model="gpt-4o-2024-05-13", api_key="")
  942. # Test round robin - verify config is preserved
  943. round_robin = RoundRobinGroupChat(participants=[agent1, agent2], termination_condition=termination, max_turns=5)
  944. config = round_robin.dump_component()
  945. loaded = RoundRobinGroupChat.load_component(config)
  946. assert loaded.dump_component() == config
  947. # Test selector group chat - verify config is preserved
  948. selector_prompt = "Custom selector prompt with {roles}, {participants}, {history}"
  949. selector = SelectorGroupChat(
  950. participants=[agent1, agent2],
  951. model_client=model_client,
  952. termination_condition=termination,
  953. max_turns=10,
  954. selector_prompt=selector_prompt,
  955. allow_repeated_speaker=True,
  956. runtime=runtime,
  957. )
  958. selector_config = selector.dump_component()
  959. selector_loaded = SelectorGroupChat.load_component(selector_config)
  960. assert selector_loaded.dump_component() == selector_config
  961. # Test swarm with handoff termination
  962. handoff_termination = HandoffTermination(target="Agent2")
  963. swarm = Swarm(
  964. participants=[agent1, agent2], termination_condition=handoff_termination, max_turns=5, runtime=runtime
  965. )
  966. swarm_config = swarm.dump_component()
  967. swarm_loaded = Swarm.load_component(swarm_config)
  968. assert swarm_loaded.dump_component() == swarm_config
  969. # Test MagenticOne with custom parameters
  970. magentic = MagenticOneGroupChat(
  971. participants=[agent1],
  972. model_client=model_client,
  973. max_turns=15,
  974. max_stalls=5,
  975. final_answer_prompt="Custom prompt",
  976. runtime=runtime,
  977. )
  978. magentic_config = magentic.dump_component()
  979. magentic_loaded = MagenticOneGroupChat.load_component(magentic_config)
  980. assert magentic_loaded.dump_component() == magentic_config
  981. # Verify component types are correctly set for each
  982. for team in [loaded, selector, swarm, magentic]:
  983. assert team.component_type == "team"
  984. # Verify provider strings are correctly set
  985. assert round_robin.dump_component().provider == "autogen_agentchat.teams.RoundRobinGroupChat"
  986. assert selector.dump_component().provider == "autogen_agentchat.teams.SelectorGroupChat"
  987. assert swarm.dump_component().provider == "autogen_agentchat.teams.Swarm"
  988. assert magentic.dump_component().provider == "autogen_agentchat.teams.MagenticOneGroupChat"