Files
vllm/tests/entrypoints/test_chat_utils.py
Russell Bryant 04c2b26972 Add filtering for chat template kwargs (#25794)
Signed-off-by: Isotr0py <mozf@mail2.sysu.edu.cn>
Co-authored-by: Isotr0py <mozf@mail2.sysu.edu.cn>
Signed-off-by: simon-mo <simon.mo@hey.com>
2025-09-27 23:32:55 -07:00

2752 lines
78 KiB
Python

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import warnings
from collections.abc import Mapping
from typing import Literal, Optional
import pytest
from mistral_common.tokens.tokenizers.base import (SpecialTokenPolicy,
SpecialTokens)
from mistral_common.tokens.tokenizers.tekken import (SpecialTokenInfo,
Tekkenizer)
from vllm.assets.audio import AudioAsset
from vllm.assets.image import ImageAsset
from vllm.assets.video import VideoAsset
from vllm.config import ModelConfig
from vllm.entrypoints.chat_utils import (_try_extract_ast, load_chat_template,
parse_chat_messages,
parse_chat_messages_futures,
resolve_chat_template_content_format,
resolve_chat_template_kwargs,
resolve_hf_chat_template)
from vllm.multimodal import MultiModalDataDict, MultiModalUUIDDict
from vllm.multimodal.utils import (encode_audio_base64, encode_image_base64,
encode_video_base64)
from vllm.transformers_utils.tokenizer import get_tokenizer
from vllm.transformers_utils.tokenizers.mistral import MistralTokenizer
from ..models.registry import HF_EXAMPLE_MODELS
from ..utils import VLLM_PATH
EXAMPLES_DIR = VLLM_PATH / "examples"
PHI3V_MODEL_ID = "microsoft/Phi-3.5-vision-instruct"
ULTRAVOX_MODEL_ID = "fixie-ai/ultravox-v0_5-llama-3_2-1b"
QWEN2AUDIO_MODEL_ID = "Qwen/Qwen2-Audio-7B-Instruct"
QWEN2VL_MODEL_ID = "Qwen/Qwen2-VL-2B-Instruct"
QWEN25VL_MODEL_ID = "Qwen/Qwen2.5-VL-3B-Instruct"
QWEN25OMNI_MODEL_ID = "Qwen/Qwen2.5-Omni-7B"
QWEN3_MODEL_ID = "Qwen/Qwen3-8B"
LLAMA_GUARD_MODEL_ID = "meta-llama/Llama-Guard-3-1B"
HERMES_MODEL_ID = "NousResearch/Hermes-3-Llama-3.1-8B"
MISTRAL_MODEL_ID = "mistralai/Mistral-Small-3.1-24B-Instruct-2503"
@pytest.fixture(scope="function")
def phi3v_model_config():
return ModelConfig(
PHI3V_MODEL_ID,
runner="generate",
trust_remote_code=True,
limit_mm_per_prompt={
"image": 2,
},
)
@pytest.fixture(scope="function")
def phi3v_model_config_mm_interleaved():
return ModelConfig(
PHI3V_MODEL_ID,
runner="generate",
trust_remote_code=True,
interleave_mm_strings=True,
limit_mm_per_prompt={
"image": 2,
},
)
@pytest.fixture(scope="module")
def phi3v_tokenizer():
return get_tokenizer(PHI3V_MODEL_ID)
@pytest.fixture(scope="function")
def qwen2_audio_model_config():
return ModelConfig(
QWEN2AUDIO_MODEL_ID,
runner="generate",
trust_remote_code=True,
limit_mm_per_prompt={
"audio": 1,
},
)
@pytest.fixture(scope="module")
def qwen2_audio_tokenizer():
return get_tokenizer(QWEN2AUDIO_MODEL_ID)
@pytest.fixture(scope="function")
def qwen25omni_model_config_mm_interleaved():
return ModelConfig(
QWEN25OMNI_MODEL_ID,
runner="generate",
interleave_mm_strings=True,
limit_mm_per_prompt={
"image": 2,
"audio": 1,
"video": 1,
},
)
@pytest.fixture(scope="module")
def qwen25omni_tokenizer():
return get_tokenizer(QWEN25OMNI_MODEL_ID)
@pytest.fixture(scope="function")
def mistral_model_config():
return ModelConfig(
MISTRAL_MODEL_ID,
runner="generate",
limit_mm_per_prompt={
"image": 2,
},
)
@pytest.fixture(scope="module")
def mistral_tokenizer():
return get_tokenizer(MISTRAL_MODEL_ID)
@pytest.fixture(scope="module")
def image_url():
image = ImageAsset("cherry_blossom")
base64 = encode_image_base64(image.pil_image)
return f"data:image/jpeg;base64,{base64}"
@pytest.fixture(scope="module")
def video_url():
video = VideoAsset("baby_reading", 1)
base64 = encode_video_base64(video.np_ndarrays)
return f"data:video/jpeg;base64,{base64}"
@pytest.fixture(scope="module")
def audio_url():
audio = AudioAsset("mary_had_lamb")
base64 = encode_audio_base64(*audio.audio_and_sample_rate)
return f"data:audio/ogg;base64,{base64}"
def _assert_mm_data_is_image_input(
mm_data: Optional[MultiModalDataDict],
image_count: int,
skipped_image_indices: Optional[list] = None,
) -> None:
assert mm_data is not None
assert set(mm_data.keys()) == {"image"}
image_data = mm_data.get("image")
assert image_data is not None
assert isinstance(image_data, list) and len(image_data) == image_count
if skipped_image_indices is not None:
for i in skipped_image_indices:
assert image_data[i] is None
def _assert_mm_uuids(
mm_uuids: Optional[MultiModalUUIDDict],
media_count: int,
expected_uuids: list[Optional[str]],
modality: str = "image",
) -> None:
if len(expected_uuids) > 0:
assert mm_uuids is not None
assert modality in mm_uuids
image_uuids = mm_uuids.get(modality)
assert image_uuids is not None
assert isinstance(image_uuids,
list) and len(image_uuids) == media_count
assert image_uuids == expected_uuids
else:
assert mm_uuids is None
ModalityType = Literal["image", "video", "audio"]
MultiModalDataCounts = Mapping[ModalityType, int]
def _assert_mm_data_inputs(
mm_data: Optional[MultiModalDataDict],
data_count: MultiModalDataCounts,
skipped_media_indices: Optional[dict[
str, list]] = None, # modality -> list[int]
) -> None:
assert mm_data is not None
assert set(data_count.keys()) == (set(mm_data.keys()))
for modality, n in data_count.items():
modality_data = mm_data.get(modality)
assert modality_data is not None
assert isinstance(modality_data, list) and len(modality_data) == n
if skipped_media_indices is not None:
skipped_media_indices_for_modality = skipped_media_indices.get(
modality)
assert skipped_media_indices_for_modality is not None
for i in skipped_media_indices_for_modality:
assert modality_data[i] is None
def test_parse_chat_messages_single_image(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
conversation, mm_data, mm_uuids = parse_chat_messages(
[{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type": "text",
"text": "What's in the image?"
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role": "user",
"content": "<|image_1|>\nWhat's in the image?"
}]
_assert_mm_data_is_image_input(mm_data, 1)
_assert_mm_uuids(mm_uuids, 1, expected_uuids=[None])
def test_parse_chat_messages_single_image_with_uuid(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
image_uuid = str(hash(image_url))
conversation, mm_data, mm_uuids = parse_chat_messages(
[{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url,
},
"uuid": image_uuid,
},
{
"type": "text",
"text": "What's in the image?"
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role": "user",
"content": "<|image_1|>\nWhat's in the image?"
}]
_assert_mm_data_is_image_input(mm_data, 1)
_assert_mm_uuids(mm_uuids, 1, expected_uuids=[image_uuid])
def test_parse_chat_messages_single_empty_image_with_uuid(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
image_uuid = str(hash(image_url))
conversation, mm_data, mm_uuids = parse_chat_messages(
[{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": None,
"uuid": image_uuid,
},
{
"type": "text",
"text": "What's in the image?"
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role": "user",
"content": "<|image_1|>\nWhat's in the image?"
}]
_assert_mm_data_is_image_input(mm_data, 1, skipped_image_indices=[0])
_assert_mm_uuids(mm_uuids, 1, expected_uuids=[image_uuid])
def test_parse_chat_messages_single_image_with_bad_uuid_format(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
image_uuid = str(hash(image_url))
conversation, mm_data, mm_uuids = parse_chat_messages(
[{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url,
"uuid": image_uuid,
},
"bad_uuid_key": image_uuid,
},
{
"type": "text",
"text": "What's in the image?"
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role": "user",
"content": "<|image_1|>\nWhat's in the image?"
}]
_assert_mm_data_is_image_input(mm_data, 1)
_assert_mm_uuids(mm_uuids, 1, expected_uuids=[None])
def test_parse_chat_messages_multiple_images_with_uuids(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
image_uuid1 = "my_uuid_1"
image_uuid2 = "my_uuid_2"
conversation, mm_data, mm_uuids = parse_chat_messages(
[{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url,
},
"uuid": image_uuid1,
},
{
"type": "image_url",
"image_url": {
"url": image_url,
},
"uuid": image_uuid2,
},
{
"type": "text",
"text": "What's in the image?"
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role":
"user",
"content":
"<|image_1|>\n<|image_2|>\nWhat's in the image?",
}]
_assert_mm_data_is_image_input(mm_data, 2)
_assert_mm_uuids(mm_uuids, 2, expected_uuids=[image_uuid1, image_uuid2])
def test_parse_chat_messages_multiple_empty_images_with_uuids(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
image_uuid1 = "my_uuid_1"
image_uuid2 = "my_uuid_2"
conversation, mm_data, mm_uuids = parse_chat_messages(
[{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": None,
"uuid": image_uuid1,
},
{
"type": "image_url",
"image_url": None,
"uuid": image_uuid2,
},
{
"type": "text",
"text": "What's in the image?"
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role":
"user",
"content":
"<|image_1|>\n<|image_2|>\nWhat's in the image?",
}]
_assert_mm_data_is_image_input(mm_data, 2, skipped_image_indices=[0, 1])
_assert_mm_uuids(mm_uuids, 2, expected_uuids=[image_uuid1, image_uuid2])
def test_parse_chat_messages_mixed_empty_images_with_uuids(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
image_uuid1 = "my_uuid_1"
image_uuid2 = "my_uuid_2"
conversation, mm_data, mm_uuids = parse_chat_messages(
[{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url,
},
"uuid": image_uuid1,
},
{
"type": "image_url",
"image_url": None,
"uuid": image_uuid2,
},
{
"type": "text",
"text": "What's in the image?"
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role":
"user",
"content":
"<|image_1|>\n<|image_2|>\nWhat's in the image?",
}]
_assert_mm_data_is_image_input(mm_data, 2, skipped_image_indices=[1])
_assert_mm_uuids(mm_uuids, 2, expected_uuids=[image_uuid1, image_uuid2])
@pytest.mark.asyncio
async def test_parse_chat_messages_single_image_with_uuid_async(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
image_uuid = str(hash(image_url))
conversation, mm_future, mm_uuids = parse_chat_messages_futures(
[{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url
},
"uuid": image_uuid,
},
{
"type": "text",
"text": "What's in the image?"
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role": "user",
"content": "<|image_1|>\nWhat's in the image?"
}]
_assert_mm_data_is_image_input(await mm_future, 1)
_assert_mm_uuids(mm_uuids, 1, expected_uuids=[image_uuid])
@pytest.mark.asyncio
async def test_parse_chat_messages_empty_image_with_uuid_async(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
image_uuid = str(hash(image_url))
conversation, mm_future, mm_uuids = parse_chat_messages_futures(
[{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": None,
"uuid": image_uuid,
},
{
"type": "text",
"text": "What's in the image?"
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role": "user",
"content": "<|image_1|>\nWhat's in the image?"
}]
_assert_mm_data_is_image_input(await mm_future,
1,
skipped_image_indices=[0])
_assert_mm_uuids(mm_uuids, 1, expected_uuids=[image_uuid])
@pytest.mark.asyncio
async def test_parse_chat_messages_multiple_images_with_uuids_async(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
image_uuid1 = "my_uuid_1"
image_uuid2 = "my_uuid_2"
conversation, mm_future, mm_uuids = parse_chat_messages_futures(
[{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url
},
"uuid": image_uuid1,
},
{
"type": "image_pil",
"image_pil": ImageAsset("cherry_blossom").pil_image,
"uuid": image_uuid2,
},
{
"type": "text",
"text": "What's in these images?"
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role":
"user",
"content":
"<|image_1|>\n<|image_2|>\nWhat's in these images?",
}]
_assert_mm_data_is_image_input(await mm_future, 2)
_assert_mm_uuids(mm_uuids, 2, expected_uuids=[image_uuid1, image_uuid2])
@pytest.mark.asyncio
async def test_parse_chat_messages_multiple_empty_images_with_uuids_async(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
image_uuid1 = "my_uuid_1"
image_uuid2 = "my_uuid_2"
conversation, mm_future, mm_uuids = parse_chat_messages_futures(
[{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": None,
"uuid": image_uuid1,
},
{
"type": "image_pil",
"image_pil": None,
"uuid": image_uuid2,
},
{
"type": "text",
"text": "What's in these images?"
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role":
"user",
"content":
"<|image_1|>\n<|image_2|>\nWhat's in these images?",
}]
_assert_mm_data_is_image_input(await mm_future,
2,
skipped_image_indices=[0, 1])
_assert_mm_uuids(mm_uuids, 2, expected_uuids=[image_uuid1, image_uuid2])
@pytest.mark.asyncio
async def test_parse_chat_messages_multiple_images_with_partial_uuids_async(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
image_uuid2 = "my_uuid_2"
conversation, mm_future, mm_uuids = parse_chat_messages_futures(
[{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url
},
},
{
"type": "image_pil",
"image_pil": ImageAsset("cherry_blossom").pil_image,
"uuid": image_uuid2,
},
{
"type": "text",
"text": "What's in these images?"
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role":
"user",
"content":
"<|image_1|>\n<|image_2|>\nWhat's in these images?",
}]
_assert_mm_data_is_image_input(await mm_future, 2)
_assert_mm_uuids(mm_uuids, 2, expected_uuids=[None, image_uuid2])
def test_parse_chat_messages_empty_system(
mistral_model_config,
mistral_tokenizer,
):
# Test string format
conversation, _, _ = parse_chat_messages(
[
{
"role": "system",
"content": ""
},
{
"role": "user",
"content": [{
"type": "text",
"text": "Who are you?"
}],
},
],
mistral_model_config,
mistral_tokenizer,
content_format="string",
)
assert conversation == [
{
"role": "system",
"content": ""
},
{
"role": "user",
"content": "Who are you?"
},
]
# Test openai format
conversation, _, _ = parse_chat_messages(
[
{
"role": "system",
"content": ""
},
{
"role": "user",
"content": [{
"type": "text",
"text": "Who are you?"
}],
},
],
mistral_model_config,
mistral_tokenizer,
content_format="openai",
)
assert conversation == [
{
"role": "system",
"content": [{
"type": "text",
"text": ""
}]
},
{
"role": "user",
"content": [{
"type": "text",
"text": "Who are you?"
}]
},
]
@pytest.mark.asyncio
async def test_parse_chat_messages_single_image_async(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
conversation, mm_future, mm_uuids = parse_chat_messages_futures(
[{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type": "text",
"text": "What's in the image?"
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role": "user",
"content": "<|image_1|>\nWhat's in the image?"
}]
_assert_mm_data_is_image_input(await mm_future, 1)
_assert_mm_uuids(mm_uuids, 1, expected_uuids=[None])
def test_parse_chat_messages_multiple_images(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
conversation, mm_data, mm_uuids = parse_chat_messages(
[{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type": "image_pil",
"image_pil": ImageAsset("cherry_blossom").pil_image,
},
{
"type": "text",
"text": "What's in these images?"
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role":
"user",
"content":
"<|image_1|>\n<|image_2|>\nWhat's in these images?",
}]
_assert_mm_data_is_image_input(mm_data, 2)
_assert_mm_uuids(mm_uuids, 2, expected_uuids=[None, None])
def test_parse_chat_messages_empty_pil_image_with_uuid(
phi3v_model_config,
phi3v_tokenizer,
):
uuid = "abcd"
conversation, mm_data, mm_uuids = parse_chat_messages(
[{
"role":
"user",
"content": [
{
"type": "image_pil",
"image_pil": None,
"uuid": uuid
},
{
"type": "text",
"text": "What's in this image?"
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role": "user",
"content": "<|image_1|>\nWhat's in this image?",
}]
_assert_mm_data_is_image_input(mm_data, 1, skipped_image_indices=[0])
_assert_mm_uuids(mm_uuids, 1, expected_uuids=[uuid])
def test_parse_chat_messages_empty_image_embeds_with_uuid(
phi3v_model_config,
phi3v_tokenizer,
):
uuid = "abcd"
conversation, mm_data, mm_uuids = parse_chat_messages(
[{
"role":
"user",
"content": [
{
"type": "image_embeds",
"image_embeds": None,
"uuid": uuid
},
{
"type": "text",
"text": "What's in this image?"
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role": "user",
"content": "<|image_1|>\nWhat's in this image?",
}]
assert mm_data is not None
assert "image" in mm_data
assert mm_data["image"] is None
_assert_mm_uuids(mm_uuids, 1, expected_uuids=[uuid])
@pytest.mark.asyncio
async def test_parse_chat_messages_empty_image_embeds_with_uuid_async(
phi3v_model_config,
phi3v_tokenizer,
):
uuid = "abcd"
conversation, mm_future, mm_uuids = parse_chat_messages_futures(
[{
"role":
"user",
"content": [
{
"type": "image_embeds",
"image_embeds": None,
"uuid": uuid
},
{
"type": "text",
"text": "What's in this image?"
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role": "user",
"content": "<|image_1|>\nWhat's in this image?",
}]
mm_data = await mm_future
assert mm_data is not None
assert "image" in mm_data
assert mm_data["image"] is None
_assert_mm_uuids(mm_uuids, 1, expected_uuids=[uuid])
@pytest.mark.asyncio
async def test_parse_chat_messages_multiple_images_async(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
conversation, mm_future, mm_uuids = parse_chat_messages_futures(
[{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type": "image_pil",
"image_pil": ImageAsset("cherry_blossom").pil_image,
},
{
"type": "text",
"text": "What's in these images?"
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role":
"user",
"content":
"<|image_1|>\n<|image_2|>\nWhat's in these images?",
}]
_assert_mm_data_is_image_input(await mm_future, 2)
_assert_mm_uuids(mm_uuids, 2, expected_uuids=[None, None])
def test_parse_chat_messages_placeholder_already_in_prompt(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
conversation, mm_data, mm_uuids = parse_chat_messages(
[{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type":
"text",
"text":
"What's in <|image_1|> and how does it compare to <|image_2|>?", # noqa: E501
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role":
"user",
"content":
"What's in <|image_1|> and how does it compare to <|image_2|>?",
}]
_assert_mm_data_is_image_input(mm_data, 2)
_assert_mm_uuids(mm_uuids, 2, expected_uuids=[None, None])
def test_parse_chat_messages_placeholder_one_already_in_prompt(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
conversation, mm_data, mm_uuids = parse_chat_messages(
[{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type":
"text",
"text":
"What's in <|image_1|> and how does it compare to the other one?", # noqa: E501
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role":
"user",
"content":
"<|image_2|>\nWhat's in <|image_1|> and how does it compare to the "
"other one?",
}]
_assert_mm_data_is_image_input(mm_data, 2)
_assert_mm_uuids(mm_uuids, 2, expected_uuids=[None, None])
def test_parse_chat_messages_multiple_images_across_messages(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
conversation, mm_data, mm_uuids = parse_chat_messages(
[
{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type": "text",
"text": "What's in this image?"
},
],
},
{
"role": "assistant",
"content": "Some stuff."
},
{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type": "text",
"text": "What about this one?"
},
],
},
],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [
{
"role": "user",
"content": "<|image_1|>\nWhat's in this image?"
},
{
"role": "assistant",
"content": "Some stuff."
},
{
"role": "user",
"content": "<|image_2|>\nWhat about this one?"
},
]
_assert_mm_data_is_image_input(mm_data, 2)
_assert_mm_uuids(mm_uuids, 2, expected_uuids=[None, None])
def test_parse_chat_messages_multiple_images_with_uuids_across_messages(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
image_uuid = str(hash(image_url))
conversation, mm_data, mm_uuids = parse_chat_messages(
[
{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url
},
"uuid": image_uuid,
},
{
"type": "text",
"text": "What's in this image?"
},
],
},
{
"role": "assistant",
"content": "Some stuff."
},
{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url
},
"uuid": image_uuid,
},
{
"type": "text",
"text": "What about this one?"
},
],
},
],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [
{
"role": "user",
"content": "<|image_1|>\nWhat's in this image?"
},
{
"role": "assistant",
"content": "Some stuff."
},
{
"role": "user",
"content": "<|image_2|>\nWhat about this one?"
},
]
_assert_mm_data_is_image_input(mm_data, 2)
_assert_mm_uuids(mm_uuids, 2, expected_uuids=[image_uuid, image_uuid])
def test_parse_chat_messages_context_text_format(
phi3v_model_config,
phi3v_tokenizer,
):
conversation, mm_data, mm_uuids = parse_chat_messages(
[
{
"role": "user",
"content": [{
"type": "text",
"text": "What's in this text?"
}],
},
{
"role": "assistant",
"content": "Some stuff."
},
{
"role": "user",
"content": "What about this one?"
},
],
phi3v_model_config,
phi3v_tokenizer,
content_format="openai",
)
assert conversation == [
{
"role": "user",
"content": [{
"type": "text",
"text": "What's in this text?"
}],
},
{
"role": "assistant",
"content": [{
"type": "text",
"text": "Some stuff."
}],
},
{
"role": "user",
"content": [{
"type": "text",
"text": "What about this one?"
}],
},
]
assert mm_data is None
assert mm_uuids is None
def test_parse_chat_messages_rejects_too_many_images_in_one_message(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
with warnings.catch_warnings():
warnings.filterwarnings(
"ignore",
message="coroutine 'async_get_and_parse_image' was never awaited",
)
with pytest.raises(ValueError, match="At most"):
parse_chat_messages(
[{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url
},
},
{
"type": "image_url",
"image_url": {
"url": image_url
},
},
{
"type": "image_url",
"image_url": {
"url": image_url
},
},
{
"type": "text",
"text": "What's in these images?"
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
def test_parse_chat_messages_rejects_too_many_images_across_messages(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
with warnings.catch_warnings():
warnings.filterwarnings(
"ignore",
message="coroutine 'async_get_and_parse_image' was never awaited",
)
with pytest.raises(ValueError, match="At most"):
parse_chat_messages(
[
{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url
},
},
{
"type": "text",
"text": "What's in this image?"
},
],
},
{
"role": "assistant",
"content": "Some stuff."
},
{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url
},
},
{
"type": "image_url",
"image_url": {
"url": image_url
},
},
{
"type": "text",
"text": "What about these two?"
},
],
},
],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
def test_parse_chat_messages_multiple_images_uncommon_input(
phi3v_model_config,
phi3v_tokenizer,
image_url,
):
conversation, mm_data, mm_uuids = parse_chat_messages(
[{
"role":
"user",
"content": [
"What's in these images?",
{
"image_url": image_url
},
{
"image_url": image_url
},
],
}],
phi3v_model_config,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role":
"user",
"content":
"<|image_1|>\n<|image_2|>\nWhat's in these images?",
}]
_assert_mm_data_is_image_input(mm_data, 2)
_assert_mm_uuids(mm_uuids, 2, expected_uuids=[None, None])
def test_parse_chat_messages_multiple_images_interleave(
phi3v_model_config_mm_interleaved,
phi3v_tokenizer,
image_url,
):
conversation, mm_data, mm_uuids = parse_chat_messages(
[{
"role":
"user",
"content": [
{
"type": "text",
"text": "I need you to compare this image",
},
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type": "text",
"text": "and this one"
},
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type": "text",
"text": "Do they have differences?"
},
],
}],
phi3v_model_config_mm_interleaved,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role":
"user",
"content":
"I need you to compare this image\n<|image_1|>\nand this one\n<|image_2|>\n" # noqa: E501
"Do they have differences?",
}]
_assert_mm_data_is_image_input(mm_data, 2)
_assert_mm_uuids(mm_uuids, 2, expected_uuids=[None, None])
@pytest.mark.asyncio
async def test_parse_chat_messages_multiple_images_interleave_async(
phi3v_model_config_mm_interleaved,
phi3v_tokenizer,
image_url,
):
conversation, mm_data, mm_uuids = parse_chat_messages_futures(
[{
"role":
"user",
"content": [
{
"type": "text",
"text": "I need you to compare this image",
},
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type": "text",
"text": "and this one"
},
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type": "text",
"text": "Do they have differences?"
},
],
}],
phi3v_model_config_mm_interleaved,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role":
"user",
"content":
"I need you to compare this image\n<|image_1|>\nand this one\n<|image_2|>\n" # noqa: E501
"Do they have differences?",
}]
_assert_mm_data_is_image_input(await mm_data, 2)
_assert_mm_uuids(mm_uuids, 2, expected_uuids=[None, None])
@pytest.mark.asyncio
async def test_parse_chat_messages_multiple_images_with_uuids_interleave_async(
phi3v_model_config_mm_interleaved,
phi3v_tokenizer,
image_url,
):
image_uuid = str(hash(image_url))
conversation, mm_data, mm_uuids = parse_chat_messages_futures(
[{
"role":
"user",
"content": [
{
"type": "text",
"text": "I need you to compare this image",
},
{
"type": "image_url",
"image_url": {
"url": image_url
},
"uuid": image_uuid,
},
{
"type": "text",
"text": "and this one"
},
{
"type": "image_url",
"image_url": {
"url": image_url
},
"uuid": image_uuid,
},
{
"type": "text",
"text": "Do they have differences?"
},
],
}],
phi3v_model_config_mm_interleaved,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [{
"role":
"user",
"content":
"I need you to compare this image\n<|image_1|>\nand this one\n<|image_2|>\n" # noqa: E501
"Do they have differences?",
}]
_assert_mm_data_is_image_input(await mm_data, 2)
_assert_mm_uuids(mm_uuids, 2, expected_uuids=[image_uuid, image_uuid])
def test_parse_chat_messages_multiple_images_multiple_messages_interleave(
phi3v_model_config_mm_interleaved,
phi3v_tokenizer,
image_url,
):
conversation, mm_data, mm_uuids = parse_chat_messages(
[
{
"role":
"user",
"content": [
{
"type": "text",
"text": "What's on this image?"
},
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type": "text",
"text": "Be accurate."
},
],
},
{
"role": "assistant",
"content": "Some stuff."
},
{
"role":
"user",
"content": [
{
"type": "text",
"text": "What's on this image?"
},
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
],
},
],
phi3v_model_config_mm_interleaved,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [
{
"role": "user",
"content": "What's on this image?\n<|image_1|>\nBe accurate.",
},
{
"role": "assistant",
"content": "Some stuff."
},
{
"role": "user",
"content": "What's on this image?\n<|image_2|>"
},
]
_assert_mm_data_is_image_input(mm_data, 2)
_assert_mm_uuids(mm_uuids, 2, expected_uuids=[None, None])
def test_parse_chat_messages_multiple_images_with_uuids_multiple_messages_interleave( # noqa: E501
phi3v_model_config_mm_interleaved,
phi3v_tokenizer,
image_url,
):
image_uuid = str(hash(image_url))
conversation, mm_data, mm_uuids = parse_chat_messages(
[
{
"role":
"user",
"content": [
{
"type": "text",
"text": "What's on this image?"
},
{
"type": "image_url",
"image_url": {
"url": image_url
},
"uuid": image_uuid,
},
{
"type": "text",
"text": "Be accurate."
},
],
},
{
"role": "assistant",
"content": "Some stuff."
},
{
"role":
"user",
"content": [
{
"type": "text",
"text": "What's on this image?"
},
{
"type": "image_url",
"image_url": {
"url": image_url
},
"uuid": image_uuid,
},
],
},
],
phi3v_model_config_mm_interleaved,
phi3v_tokenizer,
content_format="string",
)
assert conversation == [
{
"role": "user",
"content": "What's on this image?\n<|image_1|>\nBe accurate.",
},
{
"role": "assistant",
"content": "Some stuff."
},
{
"role": "user",
"content": "What's on this image?\n<|image_2|>"
},
]
_assert_mm_data_is_image_input(mm_data, 2)
_assert_mm_uuids(mm_uuids, 2, expected_uuids=[image_uuid, image_uuid])
def test_parse_chat_messages_multiple_modals_multiple_messages_interleave(
qwen25omni_model_config_mm_interleaved,
qwen25omni_tokenizer,
image_url,
video_url,
audio_url,
):
conversation, mm_data, mm_uuids = parse_chat_messages(
[
{
"role":
"user",
"content": [
{
"type": "text",
"text": "What's on this image?"
},
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type": "text",
"text": "Now listen to this audio"
},
{
"type": "audio_url",
"audio_url": {
"url": audio_url
}
},
],
},
{
"role": "assistant",
"content": "Some stuff."
},
{
"role":
"user",
"content": [
{
"type": "text",
"text": "What's on this image?"
},
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type": "text",
"text": "And what's in the video?"
},
{
"type": "video_url",
"video_url": {
"url": video_url
}
},
],
},
],
qwen25omni_model_config_mm_interleaved,
qwen25omni_tokenizer,
content_format="string",
)
assert conversation == [
{
"role":
"user",
"content":
"What's on this image?\n<|vision_start|><|IMAGE|><|vision_end|>\n"
"Now listen to this audio\nAudio 1: <|audio_bos|><|AUDIO|><|audio_eos|>", # noqa: E501
},
{
"role": "assistant",
"content": "Some stuff."
},
{
"role":
"user",
"content":
"What's on this image?\n<|vision_start|><|IMAGE|><|vision_end|>\n"
"And what's in the video?\n<|vision_start|><|VIDEO|><|vision_end|>",
},
]
_assert_mm_data_inputs(mm_data, {"image": 2, "video": 1, "audio": 1})
_assert_mm_uuids(mm_uuids,
2,
modality="image",
expected_uuids=[None, None])
_assert_mm_uuids(mm_uuids, 1, modality="video", expected_uuids=[None])
_assert_mm_uuids(mm_uuids, 1, modality="audio", expected_uuids=[None])
def test_parse_chat_messages_multiple_modals_with_uuids_multiple_messages_interleave( # noqa: E501
qwen25omni_model_config_mm_interleaved,
qwen25omni_tokenizer,
image_url,
video_url,
audio_url,
):
conversation, mm_data, mm_uuids = parse_chat_messages(
[
{
"role":
"user",
"content": [
{
"type": "text",
"text": "What's on this image?"
},
{
"type": "image_url",
"image_url": {
"url": image_url
},
"uuid": "image_123",
},
{
"type": "text",
"text": "Now listen to this audio"
},
{
"type": "audio_url",
"audio_url": {
"url": audio_url
},
"uuid": "audio_123",
},
],
},
{
"role": "assistant",
"content": "Some stuff."
},
{
"role":
"user",
"content": [
{
"type": "text",
"text": "What's on this image?"
},
{
"type": "image_url",
"image_url": {
"url": image_url
},
"uuid": "image_123",
},
{
"type": "text",
"text": "And what's in the video?"
},
{
"type": "video_url",
"video_url": {
"url": video_url
},
"uuid": "video_123",
},
],
},
],
qwen25omni_model_config_mm_interleaved,
qwen25omni_tokenizer,
content_format="string",
)
assert conversation == [
{
"role":
"user",
"content":
"What's on this image?\n<|vision_start|><|IMAGE|><|vision_end|>\n"
"Now listen to this audio\nAudio 1: <|audio_bos|><|AUDIO|><|audio_eos|>", # noqa: E501
},
{
"role": "assistant",
"content": "Some stuff."
},
{
"role":
"user",
"content":
"What's on this image?\n<|vision_start|><|IMAGE|><|vision_end|>\n"
"And what's in the video?\n<|vision_start|><|VIDEO|><|vision_end|>",
},
]
_assert_mm_data_inputs(mm_data, {"image": 2, "video": 1, "audio": 1})
_assert_mm_uuids(mm_uuids,
2,
modality="image",
expected_uuids=["image_123", "image_123"])
_assert_mm_uuids(mm_uuids,
1,
modality="video",
expected_uuids=["video_123"])
_assert_mm_uuids(mm_uuids,
1,
modality="audio",
expected_uuids=["audio_123"])
def test_parse_chat_messages_multiple_modals_with_uuids_multiple_empty_media_messages_interleave( # noqa: E501
qwen25omni_model_config_mm_interleaved,
qwen25omni_tokenizer,
image_url,
video_url,
audio_url,
):
conversation, mm_data, mm_uuids = parse_chat_messages(
[
{
"role":
"user",
"content": [
{
"type": "text",
"text": "What's on this image?"
},
{
"type": "image_url",
"image_url": None,
"uuid": "image_123",
},
{
"type": "text",
"text": "Now listen to this audio"
},
{
"type": "audio_url",
"audio_url": None,
"uuid": "audio_123",
},
],
},
{
"role": "assistant",
"content": "Some stuff."
},
{
"role":
"user",
"content": [
{
"type": "text",
"text": "What's on this image?"
},
{
"type": "image_url",
"image_url": None,
"uuid": "image_123",
},
{
"type": "text",
"text": "And what's in the video?"
},
{
"type": "video_url",
"video_url": None,
"uuid": "video_123",
},
],
},
],
qwen25omni_model_config_mm_interleaved,
qwen25omni_tokenizer,
content_format="string",
)
assert conversation == [
{
"role":
"user",
"content":
"What's on this image?\n<|vision_start|><|IMAGE|><|vision_end|>\n"
"Now listen to this audio\nAudio 1: <|audio_bos|><|AUDIO|><|audio_eos|>", # noqa: E501
},
{
"role": "assistant",
"content": "Some stuff."
},
{
"role":
"user",
"content":
"What's on this image?\n<|vision_start|><|IMAGE|><|vision_end|>\n"
"And what's in the video?\n<|vision_start|><|VIDEO|><|vision_end|>",
},
]
_assert_mm_data_inputs(mm_data, {
"image": 2,
"video": 1,
"audio": 1
},
skipped_media_indices={
"image": [0, 1],
"video": [0],
"audio": [0]
})
_assert_mm_uuids(mm_uuids,
2,
modality="image",
expected_uuids=["image_123", "image_123"])
_assert_mm_uuids(mm_uuids,
1,
modality="video",
expected_uuids=["video_123"])
_assert_mm_uuids(mm_uuids,
1,
modality="audio",
expected_uuids=["audio_123"])
def test_parse_chat_messages_multiple_modals_with_partial_uuids_multiple_messages_interleave( # noqa: E501
qwen25omni_model_config_mm_interleaved,
qwen25omni_tokenizer,
image_url,
video_url,
audio_url,
):
conversation, mm_data, mm_uuids = parse_chat_messages(
[
{
"role":
"user",
"content": [
{
"type": "text",
"text": "What's on this image?"
},
{
"type": "image_url",
"image_url": {
"url": image_url
},
"uuid": "image_123",
},
{
"type": "text",
"text": "Now listen to this audio"
},
{
"type": "audio_url",
"audio_url": {
"url": audio_url
}
},
],
},
{
"role": "assistant",
"content": "Some stuff."
},
{
"role":
"user",
"content": [
{
"type": "text",
"text": "What's on this image?"
},
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type": "text",
"text": "And what's in the video?"
},
{
"type": "video_url",
"video_url": {
"url": video_url
},
"uuid": "video_123",
},
],
},
],
qwen25omni_model_config_mm_interleaved,
qwen25omni_tokenizer,
content_format="string",
)
assert conversation == [
{
"role":
"user",
"content":
"What's on this image?\n<|vision_start|><|IMAGE|><|vision_end|>\n"
"Now listen to this audio\nAudio 1: <|audio_bos|><|AUDIO|><|audio_eos|>", # noqa: E501
},
{
"role": "assistant",
"content": "Some stuff."
},
{
"role":
"user",
"content":
"What's on this image?\n<|vision_start|><|IMAGE|><|vision_end|>\n"
"And what's in the video?\n<|vision_start|><|VIDEO|><|vision_end|>",
},
]
_assert_mm_data_inputs(mm_data, {"image": 2, "video": 1, "audio": 1})
_assert_mm_uuids(mm_uuids,
2,
modality="image",
expected_uuids=["image_123", None])
_assert_mm_uuids(mm_uuids,
1,
modality="video",
expected_uuids=["video_123"])
_assert_mm_uuids(mm_uuids, 1, modality="audio", expected_uuids=[None])
def test_parse_chat_messages_multiple_images_interleave_with_placeholders(
phi3v_model_config_mm_interleaved,
phi3v_tokenizer,
image_url,
):
with pytest.raises(
ValueError,
match=r"Found more '<|image_1|>' placeholders in input prompt "
"than actual multimodal data items.",
):
parse_chat_messages(
[{
"role":
"user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type": "image_url",
"image_url": {
"url": image_url
}
},
{
"type":
"text",
"text":
"I need you to compare this image\n<|image_1|>\nand this one\n<|image_2|>\n" # noqa: E501
"Do they have differences?",
},
],
}],
phi3v_model_config_mm_interleaved,
phi3v_tokenizer,
content_format="string",
)
@pytest.mark.parametrize(
"model",
[
QWEN2VL_MODEL_ID, # tokenizer.chat_template is of type str
HERMES_MODEL_ID, # tokenizer.chat_template is of type dict
],
)
@pytest.mark.parametrize("use_tools", [True, False])
def test_resolve_hf_chat_template(sample_json_schema, model, use_tools):
"""checks that chat_template is a dict type for HF models."""
model_info = HF_EXAMPLE_MODELS.find_hf_info(model)
model_info.check_available_online(on_fail="skip")
model_config = ModelConfig(
model,
tokenizer=model_info.tokenizer or model,
tokenizer_mode=model_info.tokenizer_mode,
revision=model_info.revision,
trust_remote_code=model_info.trust_remote_code,
hf_overrides=model_info.hf_overrides,
skip_tokenizer_init=model_info.skip_tokenizer_init,
enforce_eager=model_info.enforce_eager,
dtype=model_info.dtype)
# Build the tokenizer
tokenizer = get_tokenizer(
model,
trust_remote_code=model_config.trust_remote_code,
)
tools = ([{
"type": "function",
"function": {
"name": "dummy_function_name",
"description": "This is a dummy function",
"parameters": sample_json_schema,
},
}] if use_tools else None)
# Test detecting the tokenizer's chat_template
chat_template = resolve_hf_chat_template(
tokenizer,
chat_template=None,
tools=tools,
model_config=model_config,
)
assert isinstance(chat_template, str)
@pytest.mark.parametrize(
"model, expected_kwargs",
[
(
QWEN2VL_MODEL_ID,
{
"add_vision_id", "add_generation_prompt",
"continue_final_message", "tools"
},
),
(
QWEN3_MODEL_ID,
{
"enable_thinking", "add_generation_prompt",
"continue_final_message", "tools"
},
),
],
)
def test_resolve_hf_chat_template_kwargs(sample_json_schema, model,
expected_kwargs):
"""checks that chat_template is a dict type for HF models."""
model_info = HF_EXAMPLE_MODELS.find_hf_info(model)
model_info.check_available_online(on_fail="skip")
tools = ([{
"type": "function",
"function": {
"name": "dummy_function_name",
"description": "This is a dummy function",
"parameters": sample_json_schema,
},
}])
chat_template_kwargs = {
# both unused
"unsed_kwargs_1": 123,
"unsed_kwargs_2": "abc",
# should not appear
"chat_template": "{% Hello world! %}",
# used by tokenizer
"continue_final_message": True,
"tools": tools,
# both used by Qwen2-VL and Qwen3
"add_generation_prompt": True,
# only used by Qwen2-VL
"add_vision_id": True,
# only used by Qwen3
"enable_thinking": True,
}
model_config = ModelConfig(
model,
tokenizer=model_info.tokenizer or model,
tokenizer_mode=model_info.tokenizer_mode,
revision=model_info.revision,
trust_remote_code=model_info.trust_remote_code,
hf_overrides=model_info.hf_overrides,
skip_tokenizer_init=model_info.skip_tokenizer_init,
enforce_eager=model_info.enforce_eager,
dtype=model_info.dtype)
# Build the tokenizer
tokenizer = get_tokenizer(
model,
trust_remote_code=model_config.trust_remote_code,
)
# Test detecting the tokenizer's chat_template
chat_template = resolve_hf_chat_template(
tokenizer,
chat_template=None,
tools=tools,
model_config=model_config,
)
resolved_chat_template_kwargs = resolve_chat_template_kwargs(
tokenizer,
chat_template=chat_template,
chat_template_kwargs=chat_template_kwargs,
)
assert set(resolved_chat_template_kwargs.keys()) == expected_kwargs
# NOTE: Qwen2-Audio default chat template is specially defined inside
# processor class instead of using `tokenizer_config.json`
# yapf: disable
@pytest.mark.parametrize(
("model", "expected_format"),
[(PHI3V_MODEL_ID, "string"),
(QWEN2VL_MODEL_ID, "openai"),
(QWEN25VL_MODEL_ID, "openai"),
(ULTRAVOX_MODEL_ID, "string"),
(QWEN2AUDIO_MODEL_ID, "openai"),
(LLAMA_GUARD_MODEL_ID, "openai")],
)
# yapf: enable
def test_resolve_content_format_hf_defined(model, expected_format):
model_info = HF_EXAMPLE_MODELS.find_hf_info(model)
model_info.check_available_online(on_fail="skip")
model_config = ModelConfig(
model,
tokenizer=model_info.tokenizer or model,
tokenizer_mode=model_info.tokenizer_mode,
revision=model_info.revision,
trust_remote_code=model_info.trust_remote_code,
hf_overrides=model_info.hf_overrides,
skip_tokenizer_init=model_info.skip_tokenizer_init,
enforce_eager=model_info.enforce_eager,
dtype=model_info.dtype)
tokenizer = get_tokenizer(
model,
trust_remote_code=model_config.trust_remote_code,
)
# Test detecting the tokenizer's chat_template
chat_template = resolve_hf_chat_template(
tokenizer,
chat_template=None,
tools=None,
model_config=model_config,
)
assert isinstance(chat_template, str)
print("[TEXT]")
print(chat_template)
print("[AST]")
print(_try_extract_ast(chat_template))
resolved_format = resolve_chat_template_content_format(
None, # Test detecting the tokenizer's chat_template
None,
"auto",
tokenizer,
model_config=model_config,
)
assert resolved_format == expected_format
# yapf: disable
@pytest.mark.parametrize(
("model", "expected_format"),
[("Salesforce/blip2-opt-2.7b", "string"),
("facebook/chameleon-7b", "string"),
("deepseek-ai/deepseek-vl2-tiny", "string"),
("adept/fuyu-8b", "string"),
("google/paligemma-3b-mix-224", "string"),
("Qwen/Qwen-VL", "string"),
("Qwen/Qwen-VL-Chat", "string")],
)
# yapf: enable
def test_resolve_content_format_fallbacks(model, expected_format):
model_info = HF_EXAMPLE_MODELS.find_hf_info(model)
model_info.check_available_online(on_fail="skip")
model_config = ModelConfig(
model,
tokenizer=model_info.tokenizer or model,
tokenizer_mode=model_info.tokenizer_mode,
revision=model_info.revision,
trust_remote_code=model_info.trust_remote_code,
hf_overrides=model_info.hf_overrides,
skip_tokenizer_init=model_info.skip_tokenizer_init,
enforce_eager=model_info.enforce_eager,
dtype=model_info.dtype)
tokenizer = get_tokenizer(
model_config.tokenizer,
trust_remote_code=model_config.trust_remote_code,
)
# Test detecting the tokenizer's chat_template
chat_template = resolve_hf_chat_template(
tokenizer,
chat_template=None,
tools=None,
model_config=model_config,
)
assert isinstance(chat_template, str)
print("[TEXT]")
print(chat_template)
print("[AST]")
print(_try_extract_ast(chat_template))
resolved_format = resolve_chat_template_content_format(
None, # Test detecting the tokenizer's chat_template
None,
"auto",
tokenizer,
model_config=model_config,
)
assert resolved_format == expected_format
# yapf: disable
@pytest.mark.parametrize(
("template_path", "expected_format"),
[("template_alpaca.jinja", "string"),
("template_baichuan.jinja", "string"),
("template_chatglm.jinja", "string"),
("template_chatglm2.jinja", "string"),
("template_chatml.jinja", "string"),
("template_dse_qwen2_vl.jinja", "openai"),
("template_falcon_180b.jinja", "string"),
("template_falcon.jinja", "string"),
("template_inkbot.jinja", "string"),
("template_teleflm.jinja", "string"),
("template_vlm2vec.jinja", "openai"),
("tool_chat_template_granite_20b_fc.jinja", "string"),
("tool_chat_template_hermes.jinja", "string"),
("tool_chat_template_internlm2_tool.jinja", "string"),
("tool_chat_template_llama3.1_json.jinja", "openai"),
("tool_chat_template_llama3.2_json.jinja", "openai"),
("tool_chat_template_mistral_parallel.jinja", "string"),
("tool_chat_template_mistral.jinja", "string")],
)
# yapf: enable
def test_resolve_content_format_examples(template_path, expected_format):
model_config = ModelConfig(
PHI3V_MODEL_ID, # Dummy
tokenizer=PHI3V_MODEL_ID, # Dummy
trust_remote_code=True,
)
dummy_tokenizer = get_tokenizer(
PHI3V_MODEL_ID, # Dummy
trust_remote_code=model_config.trust_remote_code,
)
dummy_tokenizer.chat_template = None
chat_template = load_chat_template(EXAMPLES_DIR / template_path)
assert isinstance(chat_template, str)
print("[TEXT]")
print(chat_template)
print("[AST]")
print(_try_extract_ast(chat_template))
resolved_format = resolve_chat_template_content_format(
chat_template,
None,
"auto",
dummy_tokenizer,
model_config=model_config,
)
assert resolved_format == expected_format
def test_parse_chat_messages_include_thinking_chunk(mistral_model_config,
mistral_tokenizer):
messages = [{
"role":
"system",
"content": [{
"type": "text",
"text": "You are a helpful assistant."
}, {
"type":
"thinking",
"closed":
True,
"thinking":
"Only return the answer when you are confident."
}]
}, {
"role": "user",
"content": "What is 2+2?"
}, {
"role":
"assistant",
"content": [{
"type": "text",
"text": "Let me think about it."
}, {
"type": "thinking",
"closed": True,
"thinking": "2+2 = 4"
}, {
"type": "text",
"text": "The answer is 4.",
}],
}]
conversation_with_thinking, _, _ = parse_chat_messages(
messages,
mistral_model_config,
mistral_tokenizer,
content_format="openai",
)
expected_conversation = [{
"role":
"system",
"content": [{
"type": "text",
"text": "You are a helpful assistant."
}, {
"type": "text",
"text": "Only return the answer when you are confident."
}],
}, {
"role":
"user",
"content": [{
"type": "text",
"text": "What is 2+2?"
}],
}, {
"role":
"assistant",
"content": [
{
"type": "text",
"text": "Let me think about it."
},
{
"type": "text",
"text": "2+2 = 4"
},
{
"type": "text",
"text": "The answer is 4."
},
]
}]
assert conversation_with_thinking == expected_conversation
def test_apply_mistral_chat_template_thinking_chunk():
# Moved import here to avoid yapf and isort conflicts
from vllm.entrypoints.chat_utils import apply_mistral_chat_template
messages = [{
"role":
"system",
"content": [{
"type": "text",
"text": "You are a helpful assistant."
}, {
"type":
"thinking",
"closed":
True,
"thinking":
"Only return the answer when you are confident."
}]
}, {
"role": "user",
"content": "What is 2+2?"
}, {
"role":
"assistant",
"content": [{
"type": "text",
"text": "Let me think about it."
}, {
"type": "thinking",
"closed": True,
"thinking": "2+2 = 4"
}, {
"type": "text",
"text": "The answer is 4.",
}],
}, {
"role": "user",
"content": "Thanks, what is 3+3?"
}]
# TODO(Julien): upon model release change to a tokenizer already configured.
# =================================================================
mistral_tokenizer = MistralTokenizer.from_pretrained(
"mistralai/Devstral-Small-2507")
assert isinstance(mistral_tokenizer.tokenizer, Tekkenizer)
# Add think special tokens to the tokenizer
mistral_tokenizer.tokenizer._all_special_tokens[35] = SpecialTokenInfo(
rank=35, is_control=True, token_str=SpecialTokens.begin_think.value)
mistral_tokenizer.tokenizer._all_special_tokens[36] = SpecialTokenInfo(
rank=36, is_control=True, token_str=SpecialTokens.end_think.value)
mistral_tokenizer.tokenizer._special_tokens_reverse_vocab = {
k: v
for k, v in
mistral_tokenizer.tokenizer._special_tokens_reverse_vocab.items()
if v not in {35, 36}
}
mistral_tokenizer.tokenizer._special_tokens_reverse_vocab[
SpecialTokens.begin_think.value] = 35
mistral_tokenizer.tokenizer._special_tokens_reverse_vocab[
SpecialTokens.end_think.value] = 36
mistral_tokenizer.instruct.BEGIN_THINK = 35
mistral_tokenizer.instruct.END_THINK = 36
# =================================================================
tokens_ids = apply_mistral_chat_template(mistral_tokenizer,
messages,
chat_template=None,
tools=None)
string_tokens = mistral_tokenizer.mistral.decode(
tokens_ids, special_token_policy=SpecialTokenPolicy.KEEP)
expected_tokens = (
r"<s>[SYSTEM_PROMPT]You are a helpful assistant.[THINK]Only return the"
r" answer when you are confident.[/THINK][/SYSTEM_PROMPT]"
r"[INST]What is 2+2?[/INST]"
r"Let me think about it.[THINK]2+2 = 4[/THINK]The answer is 4.</s>"
r"[INST]Thanks, what is 3+3?[/INST]")
assert string_tokens == expected_tokens
def test_parse_chat_messages_single_empty_audio_with_uuid(
qwen2_audio_model_config,
qwen2_audio_tokenizer,
):
audio_uuid = "abcd"
conversation, mm_data, mm_uuids = parse_chat_messages(
[{
"role":
"user",
"content": [
{
"type": "input_audio",
"input_audio": {},
"uuid": audio_uuid,
},
{
"type": "text",
"text": "What does the audio say?"
},
],
}],
qwen2_audio_model_config,
qwen2_audio_tokenizer,
content_format="string",
)
assert conversation == [{
"role":
"user",
"content":
"Audio 1: <|audio_bos|><|AUDIO|><|audio_eos|>\nWhat does the audio say?"
}]
_assert_mm_data_inputs(mm_data, {"audio": 1})
_assert_mm_uuids(mm_uuids,
1,
modality="audio",
expected_uuids=[audio_uuid])
@pytest.mark.asyncio
async def test_parse_chat_messages_single_empty_audio_with_uuid_async(
qwen2_audio_model_config,
qwen2_audio_tokenizer,
):
audio_uuid = "abcd"
conversation, mm_future, mm_uuids = parse_chat_messages_futures(
[{
"role":
"user",
"content": [
{
"type": "input_audio",
"input_audio": {},
"uuid": audio_uuid,
},
{
"type": "text",
"text": "What does the audio say?"
},
],
}],
qwen2_audio_model_config,
qwen2_audio_tokenizer,
content_format="string",
)
assert conversation == [{
"role":
"user",
"content":
"Audio 1: <|audio_bos|><|AUDIO|><|audio_eos|>\nWhat does the audio say?"
}]
_assert_mm_data_inputs(await mm_future, {"audio": 1})
_assert_mm_uuids(mm_uuids,
1,
modality="audio",
expected_uuids=[audio_uuid])