chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
@@ -0,0 +1,495 @@
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# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""Tests for the /render endpoints that expose prompt preprocessing."""
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import httpx
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import pytest
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import pytest_asyncio
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from tests.utils import RemoteLaunchRenderServer
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MODEL_NAME = "hmellor/tiny-random-LlamaForCausalLM"
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@pytest.fixture(scope="module")
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def server():
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args: list[str] = ["--trust-request-chat-template"]
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with RemoteLaunchRenderServer(MODEL_NAME, args) as remote_server:
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yield remote_server
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@pytest_asyncio.fixture
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async def client(server):
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async with httpx.AsyncClient(
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base_url=server.url_for(""), timeout=30.0
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) as http_client:
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yield http_client
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@pytest.mark.asyncio
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async def test_completion_render_basic(client):
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"""Test basic completion render endpoint."""
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# Make request to render endpoint
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response = await client.post(
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"/v1/completions/render",
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json={
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"model": MODEL_NAME,
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"prompt": "When should a chat-completions handler return an empty string?",
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},
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)
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assert response.status_code == 200
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data = response.json()
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# Verify response structure - list of GenerateRequest
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assert isinstance(data, list)
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assert len(data) > 0
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# Verify first prompt is a GenerateRequest
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first_prompt = data[0]
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assert "token_ids" in first_prompt
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assert "sampling_params" in first_prompt
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assert "model" in first_prompt
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assert "request_id" in first_prompt
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assert isinstance(first_prompt["token_ids"], list)
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assert len(first_prompt["token_ids"]) > 0
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assert first_prompt["model"] == MODEL_NAME
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assert first_prompt["request_id"].startswith("cmpl-")
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@pytest.mark.asyncio
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async def test_chat_completion_render_basic(client):
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"""Test basic chat completion render endpoint."""
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# Make request to render endpoint
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response = await client.post(
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"/v1/chat/completions/render",
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json={
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"model": MODEL_NAME,
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"messages": [
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{
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"role": "user",
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"content": (
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"Returning an empty string for the prompt may be confusing."
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),
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}
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],
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},
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)
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assert response.status_code == 200
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data = response.json()
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# Verify response structure - should be a GenerateRequest
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assert isinstance(data, dict)
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assert "token_ids" in data
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assert isinstance(data["token_ids"], list)
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assert len(data["token_ids"]) > 0
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# Verify token IDs are integers and BOS token is present
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token_ids = data["token_ids"]
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assert all(isinstance(tid, int) for tid in token_ids)
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assert token_ids[0] == 1
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@pytest.mark.asyncio
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async def test_completion_render_multiple_prompts(client):
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"""Test completion render with multiple prompts."""
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response = await client.post(
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"/v1/completions/render",
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json={
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"model": MODEL_NAME,
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"prompt": ["Hello world", "Goodbye world"],
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},
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)
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assert response.status_code == 200
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data = response.json()
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# Should return two GenerateRequest items
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assert isinstance(data, list)
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assert len(data) == 2
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# Verify both prompts have GenerateRequest fields
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for prompt in data:
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assert "token_ids" in prompt
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assert "sampling_params" in prompt
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assert "model" in prompt
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assert "request_id" in prompt
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assert len(prompt["token_ids"]) > 0
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assert prompt["request_id"].startswith("cmpl-")
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@pytest.mark.asyncio
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async def test_chat_completion_render_multi_turn(client):
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"""Test chat completion render with multi-turn conversation."""
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response = await client.post(
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"/v1/chat/completions/render",
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json={
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"model": MODEL_NAME,
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"messages": [
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{"role": "user", "content": "Hello"},
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{"role": "assistant", "content": "Hi there!"},
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{"role": "user", "content": "How are you?"},
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],
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},
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)
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assert response.status_code == 200
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data = response.json()
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# Verify tokenization occurred
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assert isinstance(data, dict)
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assert "token_ids" in data
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assert isinstance(data["token_ids"], list)
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assert len(data["token_ids"]) > 0
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@pytest.mark.asyncio
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async def test_chat_completion_render_with_stream_true(client):
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"""Render accepts stream params but still returns JSON (non-streamed)."""
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response = await client.post(
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"/v1/chat/completions/render",
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json={
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"model": MODEL_NAME,
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"stream": True,
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"stream_options": {
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"include_usage": True,
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"continuous_usage_stats": True,
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},
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"messages": [
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{
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"role": "user",
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"content": "Stream options should be accepted by /render.",
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}
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],
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},
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)
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assert response.status_code == 200
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assert response.headers.get("content-type", "").startswith("application/json")
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data = response.json()
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assert isinstance(data, dict)
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assert "token_ids" in data
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assert isinstance(data["token_ids"], list)
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assert len(data["token_ids"]) > 0
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# /render should preserve stream fields on the returned token-in request.
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assert data.get("stream") is True
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assert isinstance(data.get("stream_options"), dict)
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assert data["stream_options"].get("include_usage") is True
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assert data["stream_options"].get("continuous_usage_stats") is True
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@pytest.mark.asyncio
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async def test_completion_render_error_invalid_model(client):
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"""Test completion render with invalid model returns error."""
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response = await client.post(
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"/v1/completions/render",
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json={
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"model": "invalid-model-name",
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"prompt": "Hello",
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},
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)
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assert response.status_code == 404
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data = response.json()
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assert "error" in data
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@pytest.mark.asyncio
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async def test_chat_completion_render_error_invalid_model(client):
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"""Test chat completion render with invalid model returns error."""
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response = await client.post(
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"/v1/chat/completions/render",
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json={
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"model": "invalid-model-name",
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"messages": [{"role": "user", "content": "Hello"}],
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},
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)
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assert response.status_code == 404
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data = response.json()
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assert "error" in data
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@pytest.mark.asyncio
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async def test_completion_render_no_generation(client):
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"""Verify render endpoint does not generate text."""
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# This test verifies that calling render is fast (no generation)
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import time
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start = time.perf_counter()
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response = await client.post(
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"/v1/completions/render",
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json={
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"model": MODEL_NAME,
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"prompt": "Tell me a very long story about " * 10,
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},
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)
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elapsed = time.perf_counter() - start
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assert response.status_code == 200
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# Render should be fast (< 1 second) since no generation
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assert elapsed < 1.0
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@pytest.mark.asyncio
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async def test_chat_completion_render_with_sampling_params(client):
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"""Verify sampling params are correctly returned by /render."""
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response = await client.post(
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"/v1/chat/completions/render",
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json={
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"model": MODEL_NAME,
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"messages": [{"role": "user", "content": "Test sampling params"}],
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"temperature": 0.123,
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"top_p": 0.456,
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"frequency_penalty": 1.1,
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},
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)
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assert response.status_code == 200
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data = response.json()
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assert "sampling_params" in data
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sampling_params = data["sampling_params"]
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assert sampling_params.get("temperature") == 0.123
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assert sampling_params.get("top_p") == 0.456
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assert sampling_params.get("frequency_penalty") == 1.1
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# Check that internal fields are not present
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assert "_all_stop_token_ids" not in sampling_params
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@pytest.mark.asyncio
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async def test_completion_render_emits_token_offsets(client):
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"""With return_token_offsets, /v1/completions/render returns per-token
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(start, end) char offsets aligned with token_ids."""
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prompt = "Hello, world."
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response = await client.post(
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"/v1/completions/render",
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json={
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"model": MODEL_NAME,
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"prompt": prompt,
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"return_token_offsets": True,
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},
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)
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assert response.status_code == 200
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data = response.json()
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assert isinstance(data, list)
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offsets = data[0]["token_offsets"]
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assert offsets is not None
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assert len(offsets) == len(data[0]["token_ids"])
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for start, end in offsets:
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assert isinstance(start, int) and isinstance(end, int)
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assert 0 <= start <= end <= len(prompt)
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@pytest.mark.asyncio
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async def test_completion_render_default_no_token_offsets(client):
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"""Without the flag, token_offsets must be null (existing responses
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unchanged)."""
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response = await client.post(
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"/v1/completions/render",
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json={
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"model": MODEL_NAME,
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"prompt": "Hello, world.",
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},
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)
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assert response.status_code == 200
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data = response.json()
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assert data[0]["token_offsets"] is None
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@pytest.mark.asyncio
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async def test_chat_render_emits_token_offsets(client):
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"""With return_token_offsets, /v1/chat/completions/render returns
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per-token offsets relative to the templated prompt string."""
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response = await client.post(
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"/v1/chat/completions/render",
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json={
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"model": MODEL_NAME,
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"messages": [{"role": "user", "content": "Hello, world."}],
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"return_token_offsets": True,
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},
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)
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assert response.status_code == 200
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data = response.json()
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assert isinstance(data, dict)
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offsets = data["token_offsets"]
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assert offsets is not None
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assert len(offsets) == len(data["token_ids"])
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for start, end in offsets:
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assert isinstance(start, int) and isinstance(end, int)
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assert 0 <= start <= end
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@pytest.mark.asyncio
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async def test_chat_render_default_no_token_offsets(client):
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"""Without the flag, chat render token_offsets must be null."""
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response = await client.post(
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"/v1/chat/completions/render",
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json={
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"model": MODEL_NAME,
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"messages": [{"role": "user", "content": "Hello, world."}],
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},
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)
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assert response.status_code == 200
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data = response.json()
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assert data["token_offsets"] is None
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@pytest.mark.asyncio
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async def test_completion_render_multiple_prompts_token_offsets(client):
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"""Each prompt in a batch gets its own offsets aligned with its tokens."""
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prompts = ["Hello, world.", "Goodbye, world."]
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response = await client.post(
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"/v1/completions/render",
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json={
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"model": MODEL_NAME,
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"prompt": prompts,
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"return_token_offsets": True,
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},
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)
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assert response.status_code == 200
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data = response.json()
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assert len(data) == len(prompts)
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for item, prompt in zip(data, prompts):
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offsets = item["token_offsets"]
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assert offsets is not None
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assert len(offsets) == len(item["token_ids"])
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for start, end in offsets:
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assert 0 <= start <= end <= len(prompt)
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@pytest.mark.asyncio
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async def test_chat_completion_render_assistant_tokens_mask_default(client):
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"""Without return_assistant_tokens_mask, assistant_tokens_mask should be null."""
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response = await client.post(
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"/v1/chat/completions/render",
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json={
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"model": MODEL_NAME,
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"messages": [
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{"role": "user", "content": "Hello"},
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{"role": "assistant", "content": "Hi!"},
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{"role": "user", "content": "How are you?"},
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],
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},
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)
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assert response.status_code == 200
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data = response.json()
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assert data.get("assistant_tokens_mask") is None
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@pytest.mark.asyncio
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async def test_chat_completion_render_assistant_tokens_mask_false(client):
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"""Explicitly setting return_assistant_tokens_mask=false gives null."""
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response = await client.post(
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"/v1/chat/completions/render",
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json={
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"model": MODEL_NAME,
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"messages": [
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{"role": "user", "content": "Hello"},
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],
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"return_assistant_tokens_mask": False,
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},
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)
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assert response.status_code == 200
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data = response.json()
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assert data.get("assistant_tokens_mask") is None
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@pytest.mark.asyncio
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async def test_chat_render_assistant_tokens_mask_null_without_gen_tags(
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client,
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):
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"""The tiny test model lacks ``{% generation %}`` tags, so the mask is null."""
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response = await client.post(
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"/v1/chat/completions/render",
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json={
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"model": MODEL_NAME,
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"messages": [
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{"role": "user", "content": "Hello"},
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{"role": "assistant", "content": "Hi!"},
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],
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"return_assistant_tokens_mask": True,
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},
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)
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assert response.status_code == 200
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assert response.json().get("assistant_tokens_mask") is None
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# A minimal chat template with {% generation %} tags so we can test that
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# the mask correctly marks assistant tokens.
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_TEMPLATE_WITH_GENERATION = (
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"{% for m in messages %}"
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"{% if m['role'] == 'user' %}User: {{ m['content'] }}\n"
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"{% elif m['role'] == 'assistant' %}"
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"{% generation %}Assistant: {{ m['content'] }}\n{% endgeneration %}"
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"{% endif %}"
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"{% endfor %}"
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)
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@pytest.mark.asyncio
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async def test_chat_completion_render_assistant_tokens_mask_with_generation_tags(
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client,
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):
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"""With a ``{% generation %}``-enabled template, the mask marks assistant
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tokens and the masked tokens decode to the assistant content."""
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response = await client.post(
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"/v1/chat/completions/render",
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json={
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"model": MODEL_NAME,
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"messages": [
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{"role": "user", "content": "Hello"},
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{"role": "assistant", "content": "Hi!"},
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{"role": "user", "content": "Bye"},
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],
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"chat_template": _TEMPLATE_WITH_GENERATION,
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"return_assistant_tokens_mask": True,
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},
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)
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assert response.status_code == 200
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data = response.json()
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mask = data["assistant_tokens_mask"]
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token_ids = data["token_ids"]
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assert mask is not None
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assert isinstance(mask, list)
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assert len(mask) == len(token_ids)
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assert all(v in (0, 1) for v in mask)
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assert sum(mask) > 0, "mask should mark at least one assistant token"
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# Detokenize masked (assistant) and unmasked (non-assistant) tokens
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# separately to verify the mask is correct, not just non-empty.
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masked_ids = [t for t, m in zip(token_ids, mask, strict=True) if m]
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unmasked_ids = [t for t, m in zip(token_ids, mask, strict=True) if not m]
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detok = await client.post(
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"/detokenize",
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json={"model": MODEL_NAME, "tokens": masked_ids},
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)
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assert detok.status_code == 200
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assert "Hi!" in detok.json()["prompt"]
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detok_rest = await client.post(
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"/detokenize",
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json={"model": MODEL_NAME, "tokens": unmasked_ids},
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)
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assert detok_rest.status_code == 200
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assert "Hi!" not in detok_rest.json()["prompt"]
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assert "Bye" in detok_rest.json()["prompt"]
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