# flake8: noqa """Test Llama.cpp wrapper.""" import os from typing import Generator from urllib.request import urlretrieve from langchain.llms import LlamaCpp from langchain.callbacks.base import CallbackManager from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler def get_model() -> str: """Download model. f From https://huggingface.co/Sosaka/Alpaca-native-4bit-ggml/, convert to new ggml format and return model path.""" model_url = "https://huggingface.co/Sosaka/Alpaca-native-4bit-ggml/resolve/main/ggml-alpaca-7b-q4.bin" tokenizer_url = "https://huggingface.co/decapoda-research/llama-7b-hf/resolve/main/tokenizer.model" conversion_script = "https://github.com/ggerganov/llama.cpp/raw/master/convert-unversioned-ggml-to-ggml.py" local_filename = model_url.split("/")[-1] if not os.path.exists("convert-unversioned-ggml-to-ggml.py"): urlretrieve(conversion_script, "convert-unversioned-ggml-to-ggml.py") if not os.path.exists("tokenizer.model"): urlretrieve(tokenizer_url, "tokenizer.model") if not os.path.exists(local_filename): urlretrieve(model_url, local_filename) os.system(f"python convert-unversioned-ggml-to-ggml.py . tokenizer.model") return local_filename def test_llamacpp_inference() -> None: """Test valid llama.cpp inference.""" model_path = get_model() llm = LlamaCpp(model_path=model_path) output = llm("Say foo:") assert isinstance(output, str) assert len(output) > 1 def test_llamacpp_streaming() -> None: """Test streaming tokens from LlamaCpp.""" model_path = get_model() llm = LlamaCpp(model_path=model_path, max_tokens=10) generator = llm.stream("Q: How do you say 'hello' in German? A:'", stop=["'"]) stream_results_string = "" assert isinstance(generator, Generator) for chunk in generator: assert not isinstance(chunk, str) # Note that this matches the OpenAI format: assert isinstance(chunk["choices"][0]["text"], str) stream_results_string += chunk["choices"][0]["text"] assert len(stream_results_string.strip()) > 1 def test_llamacpp_streaming_callback() -> None: """Test that streaming correctly invokes on_llm_new_token callback.""" MAX_TOKENS = 5 OFF_BY_ONE = 1 # There may be an off by one error in the upstream code! callback_handler = FakeCallbackHandler() callback_manager = CallbackManager([callback_handler]) llm = LlamaCpp( model_path=get_model(), callback_manager=callback_manager, verbose=True, max_tokens=MAX_TOKENS, ) llm("Q: Can you count to 10? A:'1, ") assert callback_handler.llm_streams <= MAX_TOKENS + OFF_BY_ONE