feat: add stateful responses API
This commit is contained in:
Xin Wang
@@ -315,6 +315,35 @@ class DifyLLMServiceTests(unittest.IsolatedAsyncioTestCase):
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class PromptBrainTests(unittest.IsolatedAsyncioTestCase):
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async def test_responses_state_skips_completed_prompt_startup(self):
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cfg = AssistantConfig(type="prompt")
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brain = build_brain(cfg)
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brain.restore_text_state(
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{
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"type": "prompt",
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"preflight_finished": True,
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"opening_finished": True,
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"entry_dispatched": True,
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}
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)
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await brain.setup(
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cfg,
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BrainRuntime(
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context=LLMContext(messages=[]),
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llm=FakeLLM(),
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queue_frame=noop_queue_frame,
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set_system_prompt=lambda _prompt: None,
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set_tools=lambda _tools: None,
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call_end=FakeCallEnd(),
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),
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)
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self.assertTrue(brain._preflight_finished)
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self.assertTrue(brain._opening_finished)
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self.assertTrue(brain._entry_dispatched)
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self.assertEqual(brain.text_state_snapshot()["type"], "prompt")
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async def test_startup_only_tool_is_not_registered_with_llm(self):
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startup_tool = RuntimeTool(
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id="opening_message",
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@@ -0,0 +1,355 @@
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from __future__ import annotations
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import asyncio
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import unittest
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from datetime import UTC, datetime
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from types import SimpleNamespace
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from unittest.mock import AsyncMock, patch
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from models import AssistantConfig
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from pipecat.frames.frames import (
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LLMContextFrame,
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LLMFullResponseEndFrame,
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LLMFullResponseStartFrame,
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LLMTextFrame,
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)
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from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
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from services.brains.base import BaseBrain, BrainSpec
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from services.openai_responses.protocol import ResponsesAPIError, parse_request
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from services.openai_responses.runner import (
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ResponsesClientToolPort,
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ResponsesTextRunner,
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_context_snapshot,
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)
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from services.openai_responses.state import _validate_tool_outputs, items_to_messages
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from routes.openai_responses import _stream_response
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class ResponsesProtocolTests(unittest.TestCase):
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def test_first_turn_requires_model_and_normalizes_text(self):
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request = parse_request(
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{
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"model": "assistant:asst_1",
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"input": "你好",
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"x_interactive_media": {"variables": {"customer": "王女士"}},
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}
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)
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self.assertEqual(request.model, "assistant:asst_1")
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self.assertFalse(request.stream)
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self.assertEqual(request.dynamic_variables, {"customer": "王女士"})
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self.assertEqual(request.input_items[0]["role"], "user")
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self.assertEqual(request.input_items[0]["content"][0]["text"], "你好")
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def test_continuation_can_inherit_model(self):
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request = parse_request(
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{
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"previous_response_id": "resp_parent",
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"input": [
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{
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"type": "function_call_output",
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"call_id": "call_1",
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"output": {"ok": True},
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}
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],
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"stream": True,
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}
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)
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self.assertIsNone(request.model)
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self.assertTrue(request.stream)
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self.assertEqual(request.input_items[0]["output"], '{"ok": true}')
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def test_rejects_stateless_and_assistant_owned_options(self):
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with self.assertRaisesRegex(ResponsesAPIError, "store must be true"):
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parse_request(
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{"model": "assistant:asst_1", "input": "hi", "store": False}
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)
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with self.assertRaisesRegex(ResponsesAPIError, "store must be true"):
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parse_request(
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{"model": "assistant:asst_1", "input": "hi", "store": None}
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)
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with self.assertRaisesRegex(ResponsesAPIError, "owned"):
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parse_request(
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{
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"model": "assistant:asst_1",
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"input": "hi",
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"instructions": "override",
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}
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)
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def test_rejects_unknown_top_level_parameters(self):
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with self.assertRaises(ResponsesAPIError) as raised:
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parse_request(
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{"model": "assistant:asst_1", "input": "hi", "metadata": {}}
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)
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self.assertEqual(raised.exception.code, "unsupported_parameter")
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self.assertEqual(raised.exception.param, "metadata")
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def test_rejects_images_and_unknown_items(self):
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with self.assertRaises(ResponsesAPIError) as raised:
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parse_request(
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{
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"model": "assistant:asst_1",
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"input": [
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{
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"type": "message",
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"role": "user",
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"content": [{"type": "input_image", "image_url": "x"}],
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}
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],
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}
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)
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self.assertEqual(raised.exception.code, "invalid_request_error")
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class ResponsesStateTests(unittest.TestCase):
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def test_context_items_become_llm_messages(self):
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messages = items_to_messages(
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[
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{
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"type": "message",
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"role": "user",
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"content": [{"type": "input_text", "text": "查订单"}],
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},
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{
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"type": "function_call",
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"call_id": "call_1",
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"name": "lookup_order",
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"arguments": '{"id":"A1"}',
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},
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{
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"type": "function_call_output",
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"call_id": "call_1",
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"output": '{"status":"ok"}',
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},
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]
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)
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self.assertEqual(messages[0], {"role": "user", "content": "查订单"})
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self.assertEqual(messages[1]["tool_calls"][0]["id"], "call_1")
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self.assertEqual(messages[2]["role"], "tool")
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def test_tool_output_must_resolve_parent_pending_call(self):
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parent = SimpleNamespace(
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output_items=[{"type": "function_call", "call_id": "call_1"}],
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input_items=[],
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)
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_validate_tool_outputs(
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[parent],
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[
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{
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"type": "function_call_output",
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"call_id": "call_1",
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"output": "ok",
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}
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],
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)
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with self.assertRaises(ResponsesAPIError) as raised:
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_validate_tool_outputs(
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[parent],
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[
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{
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"type": "function_call_output",
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"call_id": "call_other",
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"output": "ok",
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}
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],
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)
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self.assertEqual(raised.exception.code, "invalid_tool_output")
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def test_context_snapshot_aligns_provider_and_public_call_ids(self):
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context = SimpleNamespace(
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get_messages=lambda: [
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{
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"role": "assistant",
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"tool_calls": [
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{
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"id": "provider_call",
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"type": "function",
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"function": {"name": "show_message", "arguments": "{}"},
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}
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],
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}
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]
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)
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snapshot = _context_snapshot(
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context,
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function_calls=[
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{
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"call_id": "call_public",
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"name": "show_message",
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"arguments": "{}",
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}
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],
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)
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self.assertEqual(snapshot[0]["tool_calls"][0]["id"], "call_public")
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def test_tool_output_cannot_be_replayed(self):
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resolved = SimpleNamespace(
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output_items=[{"type": "function_call", "call_id": "call_1"}],
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input_items=[
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{
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"type": "function_call_output",
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"call_id": "call_1",
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"output": "ok",
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}
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],
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)
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with self.assertRaises(ResponsesAPIError) as raised:
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_validate_tool_outputs(
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[resolved],
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[
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{
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"type": "function_call_output",
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"call_id": "call_1",
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"output": "again",
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}
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],
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)
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self.assertEqual(raised.exception.code, "invalid_tool_output")
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class ResponsesClientToolTests(unittest.IsolatedAsyncioTestCase):
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async def test_client_tool_is_exposed_without_waiting_for_browser(self):
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port = ResponsesClientToolPort()
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task = asyncio.create_task(
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port.call("show_message", {"message": "确认"}, timeout_seconds=3)
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)
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await port.called.wait()
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self.assertEqual(port.calls[0]["type"], "function_call")
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self.assertEqual(port.calls[0]["name"], "show_message")
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self.assertIn('"message": "确认"', port.calls[0]["arguments"])
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task.cancel()
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await asyncio.gather(task, return_exceptions=True)
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async def test_persisted_result_resumes_deterministic_client_tool(self):
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port = ResponsesClientToolPort(
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[
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{
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"name": "show_message",
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"result": {"status": "ok", "data": {"action": "confirmed"}},
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}
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]
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)
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result = await port.call(
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"show_message",
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{"message": "确认"},
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timeout_seconds=3,
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)
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self.assertEqual(result["data"]["action"], "confirmed")
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self.assertFalse(port.called.is_set())
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class _FakeTextLLM(FrameProcessor):
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async def process_frame(self, frame, direction: FrameDirection):
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await super().process_frame(frame, direction)
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if not isinstance(frame, LLMContextFrame):
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await self.push_frame(frame, direction)
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return
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await self.push_frame(LLMFullResponseStartFrame())
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await self.push_frame(LLMTextFrame("状态已恢复"))
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await self.push_frame(LLMFullResponseEndFrame())
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class _FakeBrain(BaseBrain):
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spec = BrainSpec(
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type="dify",
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supported_runtime_modes=frozenset({"pipeline"}),
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owns_context=False,
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)
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def build_llm(self, _cfg, _context):
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return _FakeTextLLM()
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class ResponsesTextRunnerTests(unittest.IsolatedAsyncioTestCase):
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async def test_transportless_runner_streams_and_finishes_text(self):
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deltas: list[str] = []
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async def on_delta(value: str) -> None:
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deltas.append(value)
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with patch(
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"services.openai_responses.runner.build_brain",
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return_value=_FakeBrain(),
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):
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result = await asyncio.wait_for(
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ResponsesTextRunner().run(
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AssistantConfig(
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type="dify",
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runtimeMode="pipeline",
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greeting="",
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),
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history_messages=[{"role": "user", "content": "上一轮"}],
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current_messages=[{"role": "user", "content": "继续"}],
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on_delta=on_delta,
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),
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timeout=3,
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)
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self.assertEqual(result.text, "状态已恢复")
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self.assertEqual(deltas, ["状态已恢复"])
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class ResponsesStreamingTests(unittest.IsolatedAsyncioTestCase):
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async def test_stream_uses_responses_event_lifecycle(self):
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now = datetime.now(UTC)
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row = SimpleNamespace(
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id="resp_1",
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api_key_id="rtkey_1",
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assistant_id="asst_1",
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previous_response_id=None,
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status="completed",
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error=None,
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output_items=[
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{
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"id": "msg_1",
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"type": "message",
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"status": "completed",
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"role": "assistant",
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"content": [
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{
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"type": "output_text",
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"text": "完成",
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"annotations": [],
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}
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],
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}
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],
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created_at=now,
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completed_at=now,
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)
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prepared = SimpleNamespace(row=row)
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async def run_prepared(_prepared, *, on_delta, text_item_id):
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self.assertEqual(text_item_id, "msg_1")
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await on_delta("完")
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await on_delta("成")
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return row
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with patch(
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"routes.openai_responses._run_prepared",
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new=AsyncMock(side_effect=run_prepared),
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):
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chunks = [
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chunk.decode("utf-8")
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async for chunk in _stream_response(prepared, text_item_id="msg_1")
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]
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body = "".join(chunks)
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self.assertIn("event: response.created", body)
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self.assertIn("event: response.output_text.delta", body)
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self.assertIn("event: response.output_text.done", body)
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self.assertIn("event: response.completed", body)
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if __name__ == "__main__":
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unittest.main()
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