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chore: import upstream snapshot with attribution
2026-07-13 12:55:37 +08:00

496 lines
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Python

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""Tests for the /render endpoints that expose prompt preprocessing."""
import httpx
import pytest
import pytest_asyncio
from tests.utils import RemoteLaunchRenderServer
MODEL_NAME = "hmellor/tiny-random-LlamaForCausalLM"
@pytest.fixture(scope="module")
def server():
args: list[str] = ["--trust-request-chat-template"]
with RemoteLaunchRenderServer(MODEL_NAME, args) as remote_server:
yield remote_server
@pytest_asyncio.fixture
async def client(server):
async with httpx.AsyncClient(
base_url=server.url_for(""), timeout=30.0
) as http_client:
yield http_client
@pytest.mark.asyncio
async def test_completion_render_basic(client):
"""Test basic completion render endpoint."""
# Make request to render endpoint
response = await client.post(
"/v1/completions/render",
json={
"model": MODEL_NAME,
"prompt": "When should a chat-completions handler return an empty string?",
},
)
assert response.status_code == 200
data = response.json()
# Verify response structure - list of GenerateRequest
assert isinstance(data, list)
assert len(data) > 0
# Verify first prompt is a GenerateRequest
first_prompt = data[0]
assert "token_ids" in first_prompt
assert "sampling_params" in first_prompt
assert "model" in first_prompt
assert "request_id" in first_prompt
assert isinstance(first_prompt["token_ids"], list)
assert len(first_prompt["token_ids"]) > 0
assert first_prompt["model"] == MODEL_NAME
assert first_prompt["request_id"].startswith("cmpl-")
@pytest.mark.asyncio
async def test_chat_completion_render_basic(client):
"""Test basic chat completion render endpoint."""
# Make request to render endpoint
response = await client.post(
"/v1/chat/completions/render",
json={
"model": MODEL_NAME,
"messages": [
{
"role": "user",
"content": (
"Returning an empty string for the prompt may be confusing."
),
}
],
},
)
assert response.status_code == 200
data = response.json()
# Verify response structure - should be a GenerateRequest
assert isinstance(data, dict)
assert "token_ids" in data
assert isinstance(data["token_ids"], list)
assert len(data["token_ids"]) > 0
# Verify token IDs are integers and BOS token is present
token_ids = data["token_ids"]
assert all(isinstance(tid, int) for tid in token_ids)
assert token_ids[0] == 1
@pytest.mark.asyncio
async def test_completion_render_multiple_prompts(client):
"""Test completion render with multiple prompts."""
response = await client.post(
"/v1/completions/render",
json={
"model": MODEL_NAME,
"prompt": ["Hello world", "Goodbye world"],
},
)
assert response.status_code == 200
data = response.json()
# Should return two GenerateRequest items
assert isinstance(data, list)
assert len(data) == 2
# Verify both prompts have GenerateRequest fields
for prompt in data:
assert "token_ids" in prompt
assert "sampling_params" in prompt
assert "model" in prompt
assert "request_id" in prompt
assert len(prompt["token_ids"]) > 0
assert prompt["request_id"].startswith("cmpl-")
@pytest.mark.asyncio
async def test_chat_completion_render_multi_turn(client):
"""Test chat completion render with multi-turn conversation."""
response = await client.post(
"/v1/chat/completions/render",
json={
"model": MODEL_NAME,
"messages": [
{"role": "user", "content": "Hello"},
{"role": "assistant", "content": "Hi there!"},
{"role": "user", "content": "How are you?"},
],
},
)
assert response.status_code == 200
data = response.json()
# Verify tokenization occurred
assert isinstance(data, dict)
assert "token_ids" in data
assert isinstance(data["token_ids"], list)
assert len(data["token_ids"]) > 0
@pytest.mark.asyncio
async def test_chat_completion_render_with_stream_true(client):
"""Render accepts stream params but still returns JSON (non-streamed)."""
response = await client.post(
"/v1/chat/completions/render",
json={
"model": MODEL_NAME,
"stream": True,
"stream_options": {
"include_usage": True,
"continuous_usage_stats": True,
},
"messages": [
{
"role": "user",
"content": "Stream options should be accepted by /render.",
}
],
},
)
assert response.status_code == 200
assert response.headers.get("content-type", "").startswith("application/json")
data = response.json()
assert isinstance(data, dict)
assert "token_ids" in data
assert isinstance(data["token_ids"], list)
assert len(data["token_ids"]) > 0
# /render should preserve stream fields on the returned token-in request.
assert data.get("stream") is True
assert isinstance(data.get("stream_options"), dict)
assert data["stream_options"].get("include_usage") is True
assert data["stream_options"].get("continuous_usage_stats") is True
@pytest.mark.asyncio
async def test_completion_render_error_invalid_model(client):
"""Test completion render with invalid model returns error."""
response = await client.post(
"/v1/completions/render",
json={
"model": "invalid-model-name",
"prompt": "Hello",
},
)
assert response.status_code == 404
data = response.json()
assert "error" in data
@pytest.mark.asyncio
async def test_chat_completion_render_error_invalid_model(client):
"""Test chat completion render with invalid model returns error."""
response = await client.post(
"/v1/chat/completions/render",
json={
"model": "invalid-model-name",
"messages": [{"role": "user", "content": "Hello"}],
},
)
assert response.status_code == 404
data = response.json()
assert "error" in data
@pytest.mark.asyncio
async def test_completion_render_no_generation(client):
"""Verify render endpoint does not generate text."""
# This test verifies that calling render is fast (no generation)
import time
start = time.perf_counter()
response = await client.post(
"/v1/completions/render",
json={
"model": MODEL_NAME,
"prompt": "Tell me a very long story about " * 10,
},
)
elapsed = time.perf_counter() - start
assert response.status_code == 200
# Render should be fast (< 1 second) since no generation
assert elapsed < 1.0
@pytest.mark.asyncio
async def test_chat_completion_render_with_sampling_params(client):
"""Verify sampling params are correctly returned by /render."""
response = await client.post(
"/v1/chat/completions/render",
json={
"model": MODEL_NAME,
"messages": [{"role": "user", "content": "Test sampling params"}],
"temperature": 0.123,
"top_p": 0.456,
"frequency_penalty": 1.1,
},
)
assert response.status_code == 200
data = response.json()
assert "sampling_params" in data
sampling_params = data["sampling_params"]
assert sampling_params.get("temperature") == 0.123
assert sampling_params.get("top_p") == 0.456
assert sampling_params.get("frequency_penalty") == 1.1
# Check that internal fields are not present
assert "_all_stop_token_ids" not in sampling_params
@pytest.mark.asyncio
async def test_completion_render_emits_token_offsets(client):
"""With return_token_offsets, /v1/completions/render returns per-token
(start, end) char offsets aligned with token_ids."""
prompt = "Hello, world."
response = await client.post(
"/v1/completions/render",
json={
"model": MODEL_NAME,
"prompt": prompt,
"return_token_offsets": True,
},
)
assert response.status_code == 200
data = response.json()
assert isinstance(data, list)
offsets = data[0]["token_offsets"]
assert offsets is not None
assert len(offsets) == len(data[0]["token_ids"])
for start, end in offsets:
assert isinstance(start, int) and isinstance(end, int)
assert 0 <= start <= end <= len(prompt)
@pytest.mark.asyncio
async def test_completion_render_default_no_token_offsets(client):
"""Without the flag, token_offsets must be null (existing responses
unchanged)."""
response = await client.post(
"/v1/completions/render",
json={
"model": MODEL_NAME,
"prompt": "Hello, world.",
},
)
assert response.status_code == 200
data = response.json()
assert data[0]["token_offsets"] is None
@pytest.mark.asyncio
async def test_chat_render_emits_token_offsets(client):
"""With return_token_offsets, /v1/chat/completions/render returns
per-token offsets relative to the templated prompt string."""
response = await client.post(
"/v1/chat/completions/render",
json={
"model": MODEL_NAME,
"messages": [{"role": "user", "content": "Hello, world."}],
"return_token_offsets": True,
},
)
assert response.status_code == 200
data = response.json()
assert isinstance(data, dict)
offsets = data["token_offsets"]
assert offsets is not None
assert len(offsets) == len(data["token_ids"])
for start, end in offsets:
assert isinstance(start, int) and isinstance(end, int)
assert 0 <= start <= end
@pytest.mark.asyncio
async def test_chat_render_default_no_token_offsets(client):
"""Without the flag, chat render token_offsets must be null."""
response = await client.post(
"/v1/chat/completions/render",
json={
"model": MODEL_NAME,
"messages": [{"role": "user", "content": "Hello, world."}],
},
)
assert response.status_code == 200
data = response.json()
assert data["token_offsets"] is None
@pytest.mark.asyncio
async def test_completion_render_multiple_prompts_token_offsets(client):
"""Each prompt in a batch gets its own offsets aligned with its tokens."""
prompts = ["Hello, world.", "Goodbye, world."]
response = await client.post(
"/v1/completions/render",
json={
"model": MODEL_NAME,
"prompt": prompts,
"return_token_offsets": True,
},
)
assert response.status_code == 200
data = response.json()
assert len(data) == len(prompts)
for item, prompt in zip(data, prompts):
offsets = item["token_offsets"]
assert offsets is not None
assert len(offsets) == len(item["token_ids"])
for start, end in offsets:
assert 0 <= start <= end <= len(prompt)
@pytest.mark.asyncio
async def test_chat_completion_render_assistant_tokens_mask_default(client):
"""Without return_assistant_tokens_mask, assistant_tokens_mask should be null."""
response = await client.post(
"/v1/chat/completions/render",
json={
"model": MODEL_NAME,
"messages": [
{"role": "user", "content": "Hello"},
{"role": "assistant", "content": "Hi!"},
{"role": "user", "content": "How are you?"},
],
},
)
assert response.status_code == 200
data = response.json()
assert data.get("assistant_tokens_mask") is None
@pytest.mark.asyncio
async def test_chat_completion_render_assistant_tokens_mask_false(client):
"""Explicitly setting return_assistant_tokens_mask=false gives null."""
response = await client.post(
"/v1/chat/completions/render",
json={
"model": MODEL_NAME,
"messages": [
{"role": "user", "content": "Hello"},
],
"return_assistant_tokens_mask": False,
},
)
assert response.status_code == 200
data = response.json()
assert data.get("assistant_tokens_mask") is None
@pytest.mark.asyncio
async def test_chat_render_assistant_tokens_mask_null_without_gen_tags(
client,
):
"""The tiny test model lacks ``{% generation %}`` tags, so the mask is null."""
response = await client.post(
"/v1/chat/completions/render",
json={
"model": MODEL_NAME,
"messages": [
{"role": "user", "content": "Hello"},
{"role": "assistant", "content": "Hi!"},
],
"return_assistant_tokens_mask": True,
},
)
assert response.status_code == 200
assert response.json().get("assistant_tokens_mask") is None
# A minimal chat template with {% generation %} tags so we can test that
# the mask correctly marks assistant tokens.
_TEMPLATE_WITH_GENERATION = (
"{% for m in messages %}"
"{% if m['role'] == 'user' %}User: {{ m['content'] }}\n"
"{% elif m['role'] == 'assistant' %}"
"{% generation %}Assistant: {{ m['content'] }}\n{% endgeneration %}"
"{% endif %}"
"{% endfor %}"
)
@pytest.mark.asyncio
async def test_chat_completion_render_assistant_tokens_mask_with_generation_tags(
client,
):
"""With a ``{% generation %}``-enabled template, the mask marks assistant
tokens and the masked tokens decode to the assistant content."""
response = await client.post(
"/v1/chat/completions/render",
json={
"model": MODEL_NAME,
"messages": [
{"role": "user", "content": "Hello"},
{"role": "assistant", "content": "Hi!"},
{"role": "user", "content": "Bye"},
],
"chat_template": _TEMPLATE_WITH_GENERATION,
"return_assistant_tokens_mask": True,
},
)
assert response.status_code == 200
data = response.json()
mask = data["assistant_tokens_mask"]
token_ids = data["token_ids"]
assert mask is not None
assert isinstance(mask, list)
assert len(mask) == len(token_ids)
assert all(v in (0, 1) for v in mask)
assert sum(mask) > 0, "mask should mark at least one assistant token"
# Detokenize masked (assistant) and unmasked (non-assistant) tokens
# separately to verify the mask is correct, not just non-empty.
masked_ids = [t for t, m in zip(token_ids, mask, strict=True) if m]
unmasked_ids = [t for t, m in zip(token_ids, mask, strict=True) if not m]
detok = await client.post(
"/detokenize",
json={"model": MODEL_NAME, "tokens": masked_ids},
)
assert detok.status_code == 200
assert "Hi!" in detok.json()["prompt"]
detok_rest = await client.post(
"/detokenize",
json={"model": MODEL_NAME, "tokens": unmasked_ids},
)
assert detok_rest.status_code == 200
assert "Hi!" not in detok_rest.json()["prompt"]
assert "Bye" in detok_rest.json()["prompt"]