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Python: [BREAKING]: Introducing Options as TypedDict and Generic (#3140)

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* WIP typeddict for options

* updated all clients and ChatAgents

* updated everything

* added ADR

* fix mypy

* proper typevar imports

* fixed import

* fixed other imports

* slight update in the sample

* updated from feedback

* fixes

* fixed missing covariants and test fixes

* fixed typing

* updated anthropic thinking config

* ruff fixes

* fixed int tests

* fix tests and mypy

* updated integration tests

* updated docstring and test fix

* improved options handling in obser

* mypy fix

* updated a host of integration tests

* fix tests

* bedrock fix
This commit is contained in:
Eduard van Valkenburg
2026-01-13 17:41:05 +01:00
committed by GitHub
Unverified
parent 5faa2851bb
commit 3e97425245
111 changed files with 6141 additions and 4715 deletions
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python/packages/lab/tau2/agent_framework_lab_tau2/runner.py
+13 -11
View File
@@ -3,18 +3,20 @@
import uuid
from typing import cast
from agent_framework._agents import ChatAgent
from agent_framework._types import AgentRunResponse, ChatMessage, Role
from agent_framework._workflows import (
from agent_framework import (
AgentExecutor,
AgentExecutorRequest,
AgentExecutorResponse,
AgentRunResponse,
ChatAgent,
ChatClientProtocol,
ChatMessage,
FunctionExecutor,
Role,
Workflow,
WorkflowBuilder,
WorkflowContext,
)
from agent_framework.openai import OpenAIChatClient
from loguru import logger
from tau2.data_model.simulation import SimulationRun, TerminationReason # type: ignore[import-untyped]
from tau2.data_model.tasks import Task # type: ignore[import-untyped]
@@ -156,7 +158,7 @@ class TaskRunner:
"""Check if user wants to stop the conversation."""
return STOP in text or TRANSFER in text or OUT_OF_SCOPE in text
def assistant_agent(self, assistant_chat_client: OpenAIChatClient) -> ChatAgent:
def assistant_agent(self, assistant_chat_client: ChatClientProtocol) -> ChatAgent:
"""Create an assistant agent.
Users can override this method to provide a custom assistant agent.
@@ -205,7 +207,7 @@ class TaskRunner:
),
)
def user_simulator(self, user_simuator_chat_client: OpenAIChatClient, task: Task) -> ChatAgent:
def user_simulator(self, user_simuator_chat_client: ChatClientProtocol, task: Task) -> ChatAgent:
"""Create a user simulator agent.
Users can override this method to provide a custom user simulator agent.
@@ -301,8 +303,8 @@ class TaskRunner:
async def run(
self,
task: Task,
assistant_chat_client: OpenAIChatClient,
user_simuator_chat_client: OpenAIChatClient,
assistant_chat_client: ChatClientProtocol,
user_simulator_chat_client: ChatClientProtocol,
) -> list[ChatMessage]:
"""Run a tau2 task using workflow-based agent orchestration.
@@ -317,18 +319,18 @@ class TaskRunner:
Args:
task: Tau2 task containing scenario, policy, and evaluation criteria
assistant_chat_client: LLM client for the assistant agent
user_simuator_chat_client: LLM client for the user simulator
user_simulator_chat_client: LLM client for the user simulator
Returns:
Complete conversation history as ChatMessage list for evaluation
"""
logger.info(f"Starting workflow agent for task {task.id}: {task.description.purpose}") # type: ignore[unused-ignore]
logger.info(f"Assistant chat client: {assistant_chat_client}")
logger.info(f"User simulator chat client: {user_simuator_chat_client}")
logger.info(f"User simulator chat client: {user_simulator_chat_client}")
# STEP 1: Create agents
assistant_agent = self.assistant_agent(assistant_chat_client)
user_simulator_agent = self.user_simulator(user_simuator_chat_client, task)
user_simulator_agent = self.user_simulator(user_simulator_chat_client, task)
# STEP 2: Create the conversation workflow
workflow = self.build_conversation_workflow(assistant_agent, user_simulator_agent)