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88c0e85 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 | """Streaming contract tests for OpenAI-compatible SSE endpoints."""
from __future__ import annotations
import asyncio
import json
from collections import deque
import pytest
from fastapi.responses import StreamingResponse
from app.core.model_registry import ModelSpec
from app.routers import chat, completions, responses
from app.schemas.chat import ChatCompletionRequest
from app.schemas.completions import CompletionRequest
from app.schemas.responses import ResponseRequest
class DummyStream:
def __init__(
self,
*,
tokens: list[str],
prompt_tokens: int,
completion_tokens: int,
finish_reason: str = "stop",
) -> None:
self._tokens = tokens
self.prompt_tokens = prompt_tokens
self.completion_tokens = completion_tokens
self.finish_reason = finish_reason
def iter_tokens(self):
for token in self._tokens:
yield token
async def _read_stream_body(response: StreamingResponse) -> str:
chunks: list[str] = []
async for chunk in response.body_iterator:
if isinstance(chunk, bytes):
chunks.append(chunk.decode("utf-8"))
else:
chunks.append(chunk)
return "".join(chunks)
def _parse_sse_data_frames(raw_body: str) -> list[str]:
frames = [frame.strip() for frame in raw_body.split("\n\n") if frame.strip()]
data_frames: list[str] = []
for frame in frames:
assert frame.startswith("data: ")
data_frames.append(frame[len("data: ") :])
return data_frames
def test_completions_stream_emits_sse_chunks_usage_and_done(
monkeypatch: pytest.MonkeyPatch,
) -> None:
monkeypatch.setattr("app.routers.completions.get_model_spec", lambda _: None)
monkeypatch.setattr(
"app.routers.completions.engine.create_stream",
lambda *_, **__: DummyStream(
tokens=["Hel", "lo"],
prompt_tokens=3,
completion_tokens=2,
finish_reason="stop",
),
)
payload = CompletionRequest.model_validate(
{
"model": "GPT3-dev",
"prompt": "Hello",
"stream": True,
}
)
response = asyncio.run(completions.create_completion(payload))
assert isinstance(response, StreamingResponse)
body = asyncio.run(_read_stream_body(response))
data_frames = _parse_sse_data_frames(body)
assert data_frames[-1] == "[DONE]"
chunks = [json.loads(frame) for frame in data_frames[:-1]]
assert chunks[0]["object"] == "text_completion.chunk"
assert chunks[0]["choices"][0]["text"] == "Hel"
assert chunks[1]["choices"][0]["text"] == "lo"
assert chunks[2]["choices"][0]["finish_reason"] == "stop"
tail = chunks[-1]
assert tail["choices"] == []
assert tail["usage"] == {
"prompt_tokens": 3,
"completion_tokens": 2,
"total_tokens": 5,
}
def test_chat_stream_emits_initial_role_delta_and_done(
monkeypatch: pytest.MonkeyPatch,
) -> None:
monkeypatch.setattr(
"app.routers.chat.get_model_spec",
lambda model: ModelSpec(name=model, hf_repo="dummy/instruct", is_instruct=True),
)
monkeypatch.setattr("app.routers.chat.engine.apply_chat_template", lambda *_: "formatted")
monkeypatch.setattr(
"app.routers.chat.engine.create_stream",
lambda *_, **__: DummyStream(
tokens=["Hi", " there"],
prompt_tokens=4,
completion_tokens=2,
finish_reason="stop",
),
)
payload = ChatCompletionRequest.model_validate(
{
"model": "GPT4-dev-177M-1511-Instruct",
"messages": [{"role": "user", "content": "hello"}],
"stream": True,
}
)
response = asyncio.run(chat.create_chat_completion(payload))
assert isinstance(response, StreamingResponse)
body = asyncio.run(_read_stream_body(response))
data_frames = _parse_sse_data_frames(body)
assert data_frames[-1] == "[DONE]"
chunks = [json.loads(frame) for frame in data_frames[:-1]]
assert chunks[0]["choices"][0]["delta"]["role"] == "assistant"
assert chunks[1]["choices"][0]["delta"]["content"] == "Hi"
assert chunks[2]["choices"][0]["delta"]["content"] == " there"
assert chunks[3]["choices"][0]["finish_reason"] == "stop"
def test_responses_stream_emits_created_delta_completed_done(
monkeypatch: pytest.MonkeyPatch,
) -> None:
monkeypatch.setattr(
"app.routers.responses.get_model_spec",
lambda model: ModelSpec(name=model, hf_repo="dummy/base", is_instruct=False),
)
monkeypatch.setattr(
"app.routers.responses.engine.create_stream",
lambda *_, **__: DummyStream(
tokens=["Hi", " there"],
prompt_tokens=5,
completion_tokens=2,
finish_reason="stop",
),
)
payload = ResponseRequest.model_validate(
{
"model": "GPT3-dev",
"input": "Say hi",
"stream": True,
}
)
response = asyncio.run(responses.create_response(payload))
assert isinstance(response, StreamingResponse)
body = asyncio.run(_read_stream_body(response))
data_frames = _parse_sse_data_frames(body)
assert data_frames[-1] == "[DONE]"
events = [json.loads(frame) for frame in data_frames[:-1]]
assert events[0]["type"] == "response.created"
assert events[1]["type"] == "response.output_text.delta"
assert events[1]["delta"] == "Hi"
assert events[2]["type"] == "response.output_text.delta"
assert events[2]["delta"] == " there"
assert events[3]["type"] == "response.completed"
assert events[3]["response"]["output"][0]["content"][0]["text"] == "Hi there"
assert events[3]["response"]["usage"] == {
"input_tokens": 5,
"output_tokens": 2,
"total_tokens": 7,
}
def test_completions_stream_usage_aggregates_prompt_and_completion_tokens(
monkeypatch: pytest.MonkeyPatch,
) -> None:
calls: list[str] = []
streams = deque(
[
DummyStream(tokens=["a1"], prompt_tokens=10, completion_tokens=1),
DummyStream(tokens=["a2"], prompt_tokens=999, completion_tokens=2),
DummyStream(tokens=["b1"], prompt_tokens=20, completion_tokens=3),
DummyStream(tokens=["b2"], prompt_tokens=888, completion_tokens=4),
]
)
def fake_create_stream(model: str, prompt: str, **_: object) -> DummyStream:
calls.append(prompt)
return streams.popleft()
monkeypatch.setattr("app.routers.completions.get_model_spec", lambda _: None)
monkeypatch.setattr("app.routers.completions.engine.create_stream", fake_create_stream)
payload = CompletionRequest.model_validate(
{
"model": "GPT3-dev",
"prompt": ["alpha", "beta"],
"n": 2,
"stream": True,
}
)
response = asyncio.run(completions.create_completion(payload))
body = asyncio.run(_read_stream_body(response))
data_frames = _parse_sse_data_frames(body)
assert data_frames[-1] == "[DONE]"
chunks = [json.loads(frame) for frame in data_frames[:-1]]
tail = chunks[-1]
assert calls == ["alpha", "alpha", "beta", "beta"]
assert tail["usage"] == {
"prompt_tokens": 30,
"completion_tokens": 10,
"total_tokens": 40,
}
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