241 lines
7.4 KiB
Python
241 lines
7.4 KiB
Python
import ctypes
|
|
|
|
import pytest
|
|
|
|
import llama_cpp
|
|
|
|
MODEL = "./vendor/llama.cpp/models/ggml-vocab-llama.gguf"
|
|
|
|
|
|
def test_llama_cpp_tokenization():
|
|
llama = llama_cpp.Llama(model_path=MODEL, vocab_only=True, verbose=False)
|
|
|
|
assert llama
|
|
assert llama._ctx.ctx is not None
|
|
|
|
text = b"Hello World"
|
|
|
|
tokens = llama.tokenize(text)
|
|
assert tokens[0] == llama.token_bos()
|
|
assert tokens == [1, 15043, 2787]
|
|
detokenized = llama.detokenize(tokens)
|
|
assert detokenized == text
|
|
|
|
tokens = llama.tokenize(text, add_bos=False)
|
|
assert tokens[0] != llama.token_bos()
|
|
assert tokens == [15043, 2787]
|
|
|
|
detokenized = llama.detokenize(tokens)
|
|
assert detokenized != text
|
|
|
|
text = b"Hello World</s>"
|
|
tokens = llama.tokenize(text)
|
|
assert tokens[-1] != llama.token_eos()
|
|
assert tokens == [1, 15043, 2787, 829, 29879, 29958]
|
|
|
|
tokens = llama.tokenize(text, special=True)
|
|
assert tokens[-1] == llama.token_eos()
|
|
assert tokens == [1, 15043, 2787, 2]
|
|
|
|
text = b""
|
|
tokens = llama.tokenize(text, add_bos=True, special=True)
|
|
assert tokens[-1] != llama.token_eos()
|
|
assert tokens == [llama.token_bos()]
|
|
assert text == llama.detokenize(tokens)
|
|
|
|
|
|
@pytest.fixture
|
|
def mock_llama(monkeypatch):
|
|
def setup_mock(llama: llama_cpp.Llama, output_text: str):
|
|
llama.reset()
|
|
n_vocab = llama.n_vocab()
|
|
output_tokens = llama.tokenize(
|
|
output_text.encode("utf-8"), add_bos=True, special=True
|
|
)
|
|
n = 0
|
|
last_n_tokens = 0
|
|
|
|
def mock_decode(ctx: llama_cpp.llama_context_p, batch: llama_cpp.llama_batch):
|
|
nonlocal n
|
|
nonlocal last_n_tokens
|
|
# Test some basic invariants of this mocking technique
|
|
assert ctx == llama._ctx.ctx
|
|
assert llama.n_tokens == n
|
|
assert batch.n_tokens > 0
|
|
n += batch.n_tokens
|
|
last_n_tokens = batch.n_tokens
|
|
return 0
|
|
|
|
def mock_get_logits(*args, **kwargs):
|
|
nonlocal last_n_tokens
|
|
size = n_vocab * last_n_tokens
|
|
return (llama_cpp.c_float * size)()
|
|
|
|
def mock_sample(*args, **kwargs):
|
|
nonlocal n
|
|
if n < len(output_tokens):
|
|
return output_tokens[n]
|
|
else:
|
|
return llama.token_eos()
|
|
|
|
monkeypatch.setattr("llama_cpp.llama_cpp.llama_decode", mock_decode)
|
|
monkeypatch.setattr("llama_cpp.llama_cpp.llama_get_logits", mock_get_logits)
|
|
monkeypatch.setattr("llama_cpp.llama_cpp.llama_sample_token", mock_sample)
|
|
|
|
return setup_mock
|
|
|
|
|
|
def test_llama_patch(mock_llama):
|
|
n_ctx = 128
|
|
llama = llama_cpp.Llama(model_path=MODEL, vocab_only=True, n_ctx=n_ctx)
|
|
n_vocab = llama_cpp.llama_n_vocab(llama._model.model)
|
|
assert n_vocab == 32000
|
|
|
|
text = "The quick brown fox"
|
|
output_text = " jumps over the lazy dog."
|
|
all_text = text + output_text
|
|
|
|
## Test basic completion from bos until eos
|
|
mock_llama(llama, all_text)
|
|
completion = llama.create_completion("", max_tokens=36)
|
|
assert completion["choices"][0]["text"] == all_text
|
|
assert completion["choices"][0]["finish_reason"] == "stop"
|
|
|
|
## Test basic completion until eos
|
|
mock_llama(llama, all_text)
|
|
completion = llama.create_completion(text, max_tokens=20)
|
|
assert completion["choices"][0]["text"] == output_text
|
|
assert completion["choices"][0]["finish_reason"] == "stop"
|
|
|
|
## Test streaming completion until eos
|
|
mock_llama(llama, all_text)
|
|
chunks = list(llama.create_completion(text, max_tokens=20, stream=True))
|
|
assert "".join(chunk["choices"][0]["text"] for chunk in chunks) == output_text
|
|
assert chunks[-1]["choices"][0]["finish_reason"] == "stop"
|
|
|
|
## Test basic completion until stop sequence
|
|
mock_llama(llama, all_text)
|
|
completion = llama.create_completion(text, max_tokens=20, stop=["lazy"])
|
|
assert completion["choices"][0]["text"] == " jumps over the "
|
|
assert completion["choices"][0]["finish_reason"] == "stop"
|
|
|
|
## Test streaming completion until stop sequence
|
|
mock_llama(llama, all_text)
|
|
chunks = list(
|
|
llama.create_completion(text, max_tokens=20, stream=True, stop=["lazy"])
|
|
)
|
|
assert (
|
|
"".join(chunk["choices"][0]["text"] for chunk in chunks) == " jumps over the "
|
|
)
|
|
assert chunks[-1]["choices"][0]["finish_reason"] == "stop"
|
|
|
|
## Test basic completion until length
|
|
mock_llama(llama, all_text)
|
|
completion = llama.create_completion(text, max_tokens=2)
|
|
assert completion["choices"][0]["text"] == " jumps"
|
|
assert completion["choices"][0]["finish_reason"] == "length"
|
|
|
|
## Test streaming completion until length
|
|
mock_llama(llama, all_text)
|
|
chunks = list(llama.create_completion(text, max_tokens=2, stream=True))
|
|
assert "".join(chunk["choices"][0]["text"] for chunk in chunks) == " jumps"
|
|
assert chunks[-1]["choices"][0]["finish_reason"] == "length"
|
|
|
|
|
|
def test_llama_pickle():
|
|
import pickle
|
|
import tempfile
|
|
|
|
fp = tempfile.TemporaryFile()
|
|
llama = llama_cpp.Llama(model_path=MODEL, vocab_only=True)
|
|
pickle.dump(llama, fp)
|
|
fp.seek(0)
|
|
llama = pickle.load(fp)
|
|
|
|
assert llama
|
|
assert llama.ctx is not None
|
|
|
|
text = b"Hello World"
|
|
|
|
assert llama.detokenize(llama.tokenize(text)) == text
|
|
|
|
|
|
def test_utf8(mock_llama, monkeypatch):
|
|
llama = llama_cpp.Llama(model_path=MODEL, vocab_only=True, logits_all=True)
|
|
n_ctx = llama.n_ctx()
|
|
n_vocab = llama.n_vocab()
|
|
|
|
output_text = "😀"
|
|
output_tokens = llama.tokenize(
|
|
output_text.encode("utf-8"), add_bos=True, special=True
|
|
)
|
|
token_eos = llama.token_eos()
|
|
n = 0
|
|
|
|
def reset():
|
|
nonlocal n
|
|
llama.reset()
|
|
n = 0
|
|
|
|
## Set up mock function
|
|
def mock_decode(ctx: llama_cpp.llama_context_p, batch: llama_cpp.llama_batch):
|
|
nonlocal n
|
|
assert batch.n_tokens > 0
|
|
assert llama.n_tokens == n
|
|
n += batch.n_tokens
|
|
return 0
|
|
|
|
def mock_get_logits(*args, **kwargs):
|
|
size = n_vocab * n_ctx
|
|
return (llama_cpp.c_float * size)()
|
|
|
|
def mock_sample(*args, **kwargs):
|
|
nonlocal n
|
|
if n <= len(output_tokens):
|
|
return output_tokens[n - 1]
|
|
else:
|
|
return token_eos
|
|
|
|
monkeypatch.setattr("llama_cpp.llama_cpp.llama_decode", mock_decode)
|
|
monkeypatch.setattr("llama_cpp.llama_cpp.llama_get_logits", mock_get_logits)
|
|
monkeypatch.setattr("llama_cpp.llama_cpp.llama_sample_token", mock_sample)
|
|
|
|
## Test basic completion with utf8 multibyte
|
|
# mock_llama(llama, output_text)
|
|
reset()
|
|
completion = llama.create_completion("", max_tokens=4)
|
|
assert completion["choices"][0]["text"] == output_text
|
|
|
|
## Test basic completion with incomplete utf8 multibyte
|
|
# mock_llama(llama, output_text)
|
|
reset()
|
|
completion = llama.create_completion("", max_tokens=1)
|
|
assert completion["choices"][0]["text"] == ""
|
|
|
|
|
|
def test_llama_server():
|
|
from fastapi.testclient import TestClient
|
|
from llama_cpp.server.app import create_app, Settings
|
|
|
|
settings = Settings(
|
|
model=MODEL,
|
|
vocab_only=True,
|
|
)
|
|
app = create_app(settings)
|
|
client = TestClient(app)
|
|
response = client.get("/v1/models")
|
|
assert response.json() == {
|
|
"object": "list",
|
|
"data": [
|
|
{
|
|
"id": MODEL,
|
|
"object": "model",
|
|
"owned_by": "me",
|
|
"permissions": [],
|
|
}
|
|
],
|
|
}
|
|
|
|
|
|
def test_llama_cpp_version():
|
|
assert llama_cpp.__version__
|