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# Copyright 2025 the LlamaFactory team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import sys
import pytest
from llamafactory.chat import ChatModel
from llamafactory.extras.packages import is_sglang_available
MODEL_NAME = "meta-llama/Llama-3.2-1B-Instruct"
INFER_ARGS = {
"model_name_or_path": MODEL_NAME,
"finetuning_type": "lora",
"template": "llama3",
"infer_dtype": "float16",
"infer_backend": "sglang",
"do_sample": False,
"max_new_tokens": 1,
}
MESSAGES = [
{"role": "user", "content": "Hi"},
]
@pytest.mark.skipif(not is_sglang_available(), reason="SGLang is not installed")
def test_chat():
r"""Test the SGLang engine's basic chat functionality."""
chat_model = ChatModel(INFER_ARGS)
response = chat_model.chat(MESSAGES)[0]
# TODO: Change to EXPECTED_RESPONSE
print(response.response_text)
@pytest.mark.skipif(not is_sglang_available(), reason="SGLang is not installed")
def test_stream_chat():
r"""Test the SGLang engine's streaming chat functionality."""
chat_model = ChatModel(INFER_ARGS)
response = ""
for token in chat_model.stream_chat(MESSAGES):
response += token
print("Complete response:", response)
assert response, "Should receive a non-empty response"
# Run tests if executed directly
if __name__ == "__main__":
if not is_sglang_available():
print("SGLang is not available. Please install it.")
sys.exit(1)
test_chat()
test_stream_chat()
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