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# pylint: disable=protected-access
"""Unit tests for DashScopeChatModel with mocked API responses.
Tests cover both non-streaming and streaming modes.
"""
import base64
import io
import wave
from typing import Any
import unittest
from unittest import IsolatedAsyncioTestCase
from unittest.mock import AsyncMock, MagicMock, patch
from utils import AnyString
from agentscope.message import (
TextBlock,
ToolCallBlock,
ThinkingBlock,
DataBlock,
)
from agentscope.model import DashScopeChatModel
from agentscope.credential import DashScopeCredential
from agentscope.tool import ToolChoice
A = AnyString()
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
def _make_model(stream: bool = False) -> Any:
return DashScopeChatModel(
credential=DashScopeCredential(api_key="test"),
model="qwen3-max",
stream=stream,
max_retries=3,
context_size=131_072,
parameters=DashScopeChatModel.Parameters(
max_tokens=1000,
thinking_enable=True,
thinking_budget=100,
),
)
def _mock_completion(
text: Any = None,
tool_calls: Any = None,
reasoning: Any = None,
response_id: str = "req-1",
) -> MagicMock:
"""Build a mock non-streaming ChatCompletion response."""
msg = MagicMock()
msg.content = text
msg.reasoning_content = reasoning
msg.tool_calls = None
if tool_calls:
tc_mocks = []
for tc in tool_calls:
m = MagicMock()
m.id = tc["id"]
m.function.name = tc["name"]
m.function.arguments = tc["arguments"]
tc_mocks.append(m)
msg.tool_calls = tc_mocks
choice = MagicMock()
choice.message = msg
resp = MagicMock()
resp.id = response_id
resp.choices = [choice]
resp.usage = MagicMock()
resp.usage.prompt_tokens = 10
resp.usage.completion_tokens = 5
resp.usage.prompt_tokens_details = None
return resp
def _make_stream_chunk(
delta_text: str | None = None,
delta_reasoning: str | None = None,
tool_calls: list | None = None,
delta_audio: dict | None = None,
response_id: str = "req-1",
usage: dict | None = None,
has_choices: bool = True,
) -> MagicMock:
"""Build a single mock streaming chunk."""
chunk = MagicMock()
chunk.id = response_id
if usage:
chunk.usage = MagicMock()
chunk.usage.prompt_tokens = usage.get("prompt_tokens", 0)
chunk.usage.completion_tokens = usage.get("completion_tokens", 0)
chunk.usage.prompt_tokens_details = None
else:
chunk.usage = None
if has_choices:
delta = MagicMock()
delta.content = delta_text
delta.reasoning_content = delta_reasoning
delta.tool_calls = tool_calls
delta.audio = delta_audio
choice = MagicMock()
choice.delta = delta
chunk.choices = [choice]
else:
chunk.choices = []
return chunk
def _make_tool_call_delta(
index: int,
tc_id: str | None = None,
name: str | None = None,
arguments: str | None = None,
) -> MagicMock:
tc = MagicMock()
tc.index = index
tc.id = tc_id
tc.function = MagicMock()
tc.function.name = name
tc.function.arguments = arguments
return tc
class _MockAsyncStream:
"""Mock async stream (context manager + async iterator)."""
def __init__(self, chunks: list) -> None:
self._chunks = chunks
self._index = 0
async def __aenter__(self) -> "_MockAsyncStream":
return self
async def __aexit__(self, *args: Any) -> None:
pass
def __aiter__(self) -> "_MockAsyncStream":
return self
async def __anext__(self) -> Any:
if self._index >= len(self._chunks):
raise StopAsyncIteration
chunk = self._chunks[self._index]
self._index += 1
return chunk
# ---------------------------------------------------------------------------
# Non-streaming tests
# ---------------------------------------------------------------------------
class TestDashScopeNonStream(IsolatedAsyncioTestCase):
"""Tests for DashScopeChatModel in non-streaming mode."""
def setUp(self) -> None:
self.model = _make_model(stream=False)
@patch("openai.AsyncClient")
async def test_text_response(self, mock_client_cls: MagicMock) -> None:
"""Non-stream text response returns a single ChatResponse."""
mock_create = AsyncMock(
return_value=_mock_completion(text="Hello!"),
)
mock_client_cls.return_value.chat.completions.create = mock_create
result = await self.model([])
self.assertEqual(
(result.is_last, result.content),
(True, [TextBlock.model_construct(id=A, text="Hello!")]),
)
self.assertEqual(result.id, "req-1")
@patch("openai.AsyncClient")
async def test_tool_call_response(
self,
mock_client_cls: MagicMock,
) -> None:
"""Non-stream tool call response creates ToolCallBlocks."""
mock_create = AsyncMock(
return_value=_mock_completion(
tool_calls=[
{
"id": "call-1",
"name": "get_weather",
"arguments": '{"city":"Hangzhou"}',
},
],
),
)
mock_client_cls.return_value.chat.completions.create = mock_create
result = await self.model([])
self.assertEqual(
(result.is_last, result.content),
(
True,
[
ToolCallBlock(
id="call-1",
name="get_weather",
input='{"city":"Hangzhou"}',
),
],
),
)
@patch("openai.AsyncClient")
async def test_thinking_response(
self,
mock_client_cls: MagicMock,
) -> None:
"""Non-stream response with reasoning creates ThinkingBlock."""
mock_create = AsyncMock(
return_value=_mock_completion(
text="42",
reasoning="Reasoning step...",
),
)
mock_client_cls.return_value.chat.completions.create = mock_create
result = await self.model([])
self.assertEqual(
(result.is_last, result.content),
(
True,
[
ThinkingBlock.model_construct(
id=A,
thinking="Reasoning step...",
),
TextBlock.model_construct(id=A, text="42"),
],
),
)
# ---------------------------------------------------------------------------
# Streaming tests
# ---------------------------------------------------------------------------
class TestDashScopeStream(IsolatedAsyncioTestCase):
"""Tests for DashScopeChatModel in streaming mode."""
def setUp(self) -> None:
self.model = _make_model(stream=True)
@patch("openai.AsyncClient")
async def test_stream_text(self, mock_client_cls: MagicMock) -> None:
"""Stream text yields n deltas + 1 final with full content."""
chunks = [
_make_stream_chunk(delta_text="Hello"),
_make_stream_chunk(delta_text=" world"),
_make_stream_chunk(
has_choices=False,
usage={"prompt_tokens": 10, "completion_tokens": 2},
),
]
mock_create = AsyncMock(return_value=_MockAsyncStream(chunks))
mock_client_cls.return_value.chat.completions.create = mock_create
gen = await self.model([])
responses = [r async for r in gen]
self.assertListEqual(
[(r.is_last, r.content) for r in responses],
[
(False, [TextBlock.model_construct(id=A, text="Hello")]),
(False, [TextBlock.model_construct(id=A, text=" world")]),
(True, [TextBlock.model_construct(id=A, text="Hello world")]),
],
)
@patch("openai.AsyncClient")
async def test_stream_thinking_and_text(
self,
mock_client_cls: MagicMock,
) -> None:
"""Stream reasoning + text yields deltas then accumulated final."""
chunks = [
_make_stream_chunk(delta_reasoning="Think"),
_make_stream_chunk(delta_reasoning="ing"),
_make_stream_chunk(delta_text="Answer"),
_make_stream_chunk(
has_choices=False,
usage={"prompt_tokens": 10, "completion_tokens": 5},
),
]
mock_create = AsyncMock(return_value=_MockAsyncStream(chunks))
mock_client_cls.return_value.chat.completions.create = mock_create
gen = await self.model([])
responses = [r async for r in gen]
self.assertListEqual(
[(r.is_last, r.content) for r in responses],
[
(
False,
[ThinkingBlock.model_construct(id=A, thinking="Think")],
),
(False, [ThinkingBlock.model_construct(id=A, thinking="ing")]),
(False, [TextBlock.model_construct(id=A, text="Answer")]),
(
True,
[
ThinkingBlock.model_construct(
id=A,
thinking="Thinking",
),
TextBlock.model_construct(id=A, text="Answer"),
],
),
],
)
@patch("openai.AsyncClient")
async def test_stream_tool_calls(
self,
mock_client_cls: MagicMock,
) -> None:
"""Stream tool call chunks accumulate into final ToolCallBlock."""
chunks = [
_make_stream_chunk(
tool_calls=[
_make_tool_call_delta(0, "call-1", "search", '{"q":'),
],
),
_make_stream_chunk(
tool_calls=[
_make_tool_call_delta(0, None, None, '"hello"}'),
],
),
_make_stream_chunk(
has_choices=False,
usage={"prompt_tokens": 10, "completion_tokens": 5},
),
]
mock_create = AsyncMock(return_value=_MockAsyncStream(chunks))
mock_client_cls.return_value.chat.completions.create = mock_create
gen = await self.model([])
responses = [r async for r in gen]
self.assertListEqual(
[(r.is_last, r.content) for r in responses],
[
(
False,
[
ToolCallBlock(
id="call-1",
name="search",
input='{"q":',
),
],
),
(
False,
[
ToolCallBlock(
id="call-1",
name="search",
input='"hello"}',
),
],
),
(
True,
[
ToolCallBlock(
id="call-1",
name="search",
input='{"q":"hello"}',
),
],
),
],
)
@patch("openai.AsyncClient")
async def test_stream_usage(self, mock_client_cls: MagicMock) -> None:
"""Stream usage chunk attaches token counts to final response."""
chunks = [
_make_stream_chunk(delta_text="X"),
_make_stream_chunk(
has_choices=False,
usage={"prompt_tokens": 50, "completion_tokens": 10},
),
]
mock_create = AsyncMock(return_value=_MockAsyncStream(chunks))
mock_client_cls.return_value.chat.completions.create = mock_create
gen = await self.model([])
responses = [r async for r in gen]
self.assertListEqual(
[(r.is_last, r.content) for r in responses],
[
(False, [TextBlock.model_construct(id=A, text="X")]),
(True, [TextBlock.model_construct(id=A, text="X")]),
],
)
self.assertEqual(responses[-1].usage.input_tokens, 50)
self.assertEqual(responses[-1].usage.output_tokens, 10)
@patch("openai.AsyncClient")
async def test_stream_audio_response(
self,
mock_client_cls: MagicMock,
) -> None:
"""Stream PCM deltas produce per-chunk DataBlocks (first chunk
prefixed with a streaming WAV header) sharing a stable id, plus a
final fixed-size WAV block readable by the ``wave`` module."""
pcm1 = bytes([1, 2, 3, 4])
pcm2 = bytes([5, 6, 7, 8])
pcm3 = bytes([9, 10, 11, 12])
pcm_full = pcm1 + pcm2 + pcm3
chunks = [
_make_stream_chunk(
delta_audio={"data": base64.b64encode(pcm1).decode()},
),
_make_stream_chunk(
delta_audio={"data": base64.b64encode(pcm2).decode()},
),
_make_stream_chunk(
delta_audio={"data": base64.b64encode(pcm3).decode()},
),
_make_stream_chunk(
has_choices=False,
usage={"prompt_tokens": 5, "completion_tokens": 3},
),
]
mock_create = AsyncMock(return_value=_MockAsyncStream(chunks))
mock_client_cls.return_value.chat.completions.create = mock_create
gen = await self.model([])
responses = [r async for r in gen]
self.assertEqual(len(responses), 4)
# All four chunks (3 deltas + 1 final) must share the same audio
# block id so downstream consumers stitch them as one stream.
all_audio_ids = {
block.id
for r in responses
for block in r.content
if isinstance(block, DataBlock)
}
self.assertEqual(len(all_audio_ids), 1)
# First delta: WAV header (44 bytes, "RIFF"..."WAVE") + pcm1.
first_payload = base64.b64decode(responses[0].content[0].source.data)
self.assertEqual(len(first_payload), 44 + len(pcm1))
self.assertEqual(first_payload[:4], b"RIFF")
self.assertEqual(first_payload[8:12], b"WAVE")
self.assertEqual(first_payload[44:], pcm1)
# Subsequent deltas: raw PCM only, no header.
for resp, pcm in zip(responses[1:3], [pcm2, pcm3]):
payload = base64.b64decode(resp.content[0].source.data)
self.assertEqual(payload, pcm)
# Final ``is_last`` block: a fixed-size WAV the ``wave`` module
# can parse end-to-end at 24kHz / mono / 16-bit.
final = responses[-1]
self.assertTrue(final.is_last)
final_audio = next(
b for b in final.content if isinstance(b, DataBlock)
)
wav_bytes = base64.b64decode(final_audio.source.data)
with wave.open(io.BytesIO(wav_bytes), "rb") as wav:
self.assertEqual(wav.getnchannels(), 1)
self.assertEqual(wav.getsampwidth(), 2)
self.assertEqual(wav.getframerate(), 24000)
frames = wav.readframes(wav.getnframes())
self.assertEqual(frames, pcm_full)
# ---------------------------------------------------------------------------
# _format_tools tests
# ---------------------------------------------------------------------------
_FT_TOOLS = [
{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get the weather",
"parameters": {
"type": "object",
"properties": {"city": {"type": "string"}},
"required": ["city"],
},
},
},
{
"type": "function",
"function": {
"name": "get_time",
"description": "Get the time",
"parameters": {
"type": "object",
"properties": {"timezone": {"type": "string"}},
"required": ["timezone"],
},
},
},
]
class TestDashScopeFormatTools(unittest.TestCase):
"""Tests for DashScopeChatModel._format_tools."""
def setUp(self) -> None:
"""Set up model instance."""
self.model = _make_model()
def test_auto_mode(self) -> None:
"""Auto mode returns tools unchanged and string 'auto'."""
fmt_tools, fmt_choice = self.model._format_tools(
_FT_TOOLS,
ToolChoice(mode="auto"),
)
self.assertEqual(fmt_tools, _FT_TOOLS)
self.assertEqual(fmt_choice, "auto")
def test_none_mode(self) -> None:
"""None mode returns tools unchanged and string 'none'."""
fmt_tools, fmt_choice = self.model._format_tools(
_FT_TOOLS,
ToolChoice(mode="none"),
)
self.assertEqual(fmt_tools, _FT_TOOLS)
self.assertEqual(fmt_choice, "none")
def test_required_mode_warns(self) -> None:
"""Required mode emits a DeprecationWarning and falls back to auto."""
with self.assertWarns(DeprecationWarning):
fmt_tools, fmt_choice = self.model._format_tools(
_FT_TOOLS,
ToolChoice(mode="required"),
)
self.assertEqual(fmt_tools, _FT_TOOLS)
self.assertEqual(fmt_choice, "auto")
def test_str_mode_force_call(self) -> None:
"""A specific tool name forces that tool call."""
fmt_tools, fmt_choice = self.model._format_tools(
_FT_TOOLS,
ToolChoice(mode="get_weather"),
)
self.assertEqual(fmt_tools, _FT_TOOLS)
self.assertEqual(
fmt_choice,
{"type": "function", "function": {"name": "get_weather"}},
)
def test_tools_filtered(self) -> None:
"""When tool_choice.tools is set, only those tools are included."""
fmt_tools, fmt_choice = self.model._format_tools(
_FT_TOOLS,
ToolChoice(mode="auto", tools=["get_weather"]),
)
self.assertEqual(len(fmt_tools), 1)
self.assertEqual(fmt_tools[0]["function"]["name"], "get_weather")
self.assertEqual(fmt_choice, "auto")
def test_no_tool_choice(self) -> None:
"""Without tool_choice, returns tools and None."""
fmt_tools, fmt_choice = self.model._format_tools(_FT_TOOLS, None)
self.assertEqual(fmt_tools, _FT_TOOLS)
self.assertIsNone(fmt_choice)
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