wehub-resource-sync
127 lines
4.0 KiB
Python
127 lines
4.0 KiB
Python
from unittest.mock import Mock
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from aisuite import Agent, Client, Runner
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from tests.agents.helpers import chat_response
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def test_run_sync_builds_user_message_and_returns_result():
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client = Client()
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client.chat.completions.create = Mock(return_value=chat_response("hello"))
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agent = Agent(name="assistant", model="openai:gpt-4o")
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result = Runner.run_sync(agent, "Say hi", client=client)
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client.chat.completions.create.assert_called_once_with(
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model="openai:gpt-4o",
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messages=[{"role": "user", "content": "Say hi"}],
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)
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assert result.final_output == "hello"
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assert result.status == "completed"
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assert result.agent is agent
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assert result.last_agent is agent
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assert result.messages == [
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{"role": "user", "content": "Say hi"},
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{"role": "assistant", "content": "hello"},
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]
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assert result.new_items == [{"role": "assistant", "content": "hello"}]
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assert result.raw_responses
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def test_run_sync_prepends_instructions():
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client = Client()
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client.chat.completions.create = Mock(return_value=chat_response("ok"))
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agent = Agent(
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name="assistant",
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model="openai:gpt-4o",
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instructions="Answer briefly.",
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)
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Runner.run_sync(agent, "Hi", client=client)
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assert client.chat.completions.create.call_args.kwargs["messages"] == [
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{"role": "system", "content": "Answer briefly."},
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{"role": "user", "content": "Hi"},
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]
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def test_run_sync_preserves_existing_system_message():
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client = Client()
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client.chat.completions.create = Mock(return_value=chat_response("ok"))
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agent = Agent(
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name="assistant",
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model="openai:gpt-4o",
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instructions="Do not duplicate.",
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)
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messages = [
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{"role": "system", "content": "Existing."},
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{"role": "user", "content": "Hi"},
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]
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Runner.run_sync(agent, messages, client=client)
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assert client.chat.completions.create.call_args.kwargs["messages"] == messages
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def test_run_sync_passes_model_settings_and_runtime_overrides():
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client = Client()
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client.chat.completions.create = Mock(return_value=chat_response("ok"))
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agent = Agent(
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name="assistant",
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model="openai:gpt-4o",
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model_settings={"temperature": 0.2, "max_tokens": 100},
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)
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Runner.run_sync(agent, "Hi", client=client, temperature=0.7)
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assert client.chat.completions.create.call_args.kwargs["temperature"] == 0.7
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assert client.chat.completions.create.call_args.kwargs["max_tokens"] == 100
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def test_run_sync_enables_tool_loop_when_agent_has_tools():
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client = Client()
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client.chat.completions.create = Mock(return_value=chat_response("ok"))
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def lookup(city: str) -> str:
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"""Lookup a city."""
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return city
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agent = Agent(name="assistant", model="openai:gpt-4o", tools=[lookup])
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Runner.run_sync(agent, "Hi", client=client, max_turns=3)
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assert client.chat.completions.create.call_args.kwargs["tools"] == [lookup]
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assert client.chat.completions.create.call_args.kwargs["max_turns"] == 3
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def test_run_sync_merges_tags_metadata_and_observability_fields():
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client = Client()
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client.chat.completions.create = Mock(return_value=chat_response("ok"))
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agent = Agent(
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name="assistant",
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model="openai:gpt-4o",
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tags=["agent", "shared"],
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metadata={"team": "growth", "env": "dev"},
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)
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result = Runner.run_sync(
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agent,
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"Hi",
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client=client,
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run_name="support_reply",
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group_id="conversation_1",
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tags=["run", "shared"],
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metadata={"request_id": "req_1", "env": "prod"},
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)
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assert result.run_name == "support_reply"
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assert result.group_id == "conversation_1"
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assert result.tags == ["agent", "shared", "run"]
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assert result.metadata == {
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"team": "growth",
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"env": "prod",
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"request_id": "req_1",
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}
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assert result.trace_id.startswith("trace_")
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assert [step.type for step in result.steps] == ["agent", "model_response"]
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assert result.steps[0].name == "assistant"
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