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| # flake8: noqa | |
| """Test Llama.cpp wrapper.""" | |
| import os | |
| from typing import Generator | |
| from urllib.request import urlretrieve | |
| from langchain.llms import LlamaCpp | |
| 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() | |
| llm = LlamaCpp( | |
| model_path=get_model(), | |
| callbacks=[callback_handler], | |
| 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 | |