"""Test TritonTensorRTLLM llm.""" import pytest from langchain_nvidia_trt.llms import TritonTensorRTLLM _MODEL_NAME = "ensemble" @pytest.mark.skip(reason="Need a working Triton server") def test_stream() -> None: """Test streaming tokens from NVIDIA TRT.""" llm = TritonTensorRTLLM(model_name=_MODEL_NAME) for token in llm.stream("I'm Pickle Rick"): assert isinstance(token, str) @pytest.mark.skip(reason="Need a working Triton server") async def test_astream() -> None: """Test streaming tokens from NVIDIA TRT.""" llm = TritonTensorRTLLM(model_name=_MODEL_NAME) async for token in llm.astream("I'm Pickle Rick"): assert isinstance(token, str) @pytest.mark.skip(reason="Need a working Triton server") async def test_abatch() -> None: """Test streaming tokens from TritonTensorRTLLM.""" llm = TritonTensorRTLLM(model_name=_MODEL_NAME) result = await llm.abatch(["I'm Pickle Rick", "I'm not Pickle Rick"]) for token in result: assert isinstance(token, str) @pytest.mark.skip(reason="Need a working Triton server") async def test_abatch_tags() -> None: """Test batch tokens from TritonTensorRTLLM.""" llm = TritonTensorRTLLM(model_name=_MODEL_NAME) result = await llm.abatch( ["I'm Pickle Rick", "I'm not Pickle Rick"], config={"tags": ["foo"]} ) for token in result: assert isinstance(token, str) @pytest.mark.skip(reason="Need a working Triton server") def test_batch() -> None: """Test batch tokens from TritonTensorRTLLM.""" llm = TritonTensorRTLLM(model_name=_MODEL_NAME) result = llm.batch(["I'm Pickle Rick", "I'm not Pickle Rick"]) for token in result: assert isinstance(token, str) @pytest.mark.skip(reason="Need a working Triton server") async def test_ainvoke() -> None: """Test invoke tokens from TritonTensorRTLLM.""" llm = TritonTensorRTLLM(model_name=_MODEL_NAME) result = await llm.ainvoke("I'm Pickle Rick", config={"tags": ["foo"]}) assert isinstance(result, str) @pytest.mark.skip(reason="Need a working Triton server") def test_invoke() -> None: """Test invoke tokens from TritonTensorRTLLM.""" llm = TritonTensorRTLLM(model_name=_MODEL_NAME) result = llm.invoke("I'm Pickle Rick", config=dict(tags=["foo"])) assert isinstance(result, str)