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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
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