96 lines
3 KiB
Python
96 lines
3 KiB
Python
import llama_cpp
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MODEL = "./vendor/llama.cpp/models/ggml-vocab.bin"
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def test_llama():
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llama = llama_cpp.Llama(model_path=MODEL, vocab_only=True)
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assert llama
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assert llama.ctx is not None
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text = b"Hello World"
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assert llama.detokenize(llama.tokenize(text)) == text
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def test_llama_patch(monkeypatch):
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llama = llama_cpp.Llama(model_path=MODEL, vocab_only=True)
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## Set up mock function
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def mock_eval(*args, **kwargs):
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return 0
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monkeypatch.setattr("llama_cpp.llama_cpp.llama_eval", mock_eval)
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output_text = " jumps over the lazy dog."
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output_tokens = llama.tokenize(output_text.encode("utf-8", errors="ignore"))
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token_eos = llama.token_eos()
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n = 0
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def mock_sample(*args, **kwargs):
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nonlocal n
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if n < len(output_tokens):
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n += 1
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return output_tokens[n - 1]
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else:
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return token_eos
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monkeypatch.setattr("llama_cpp.llama_cpp.llama_sample_top_p_top_k", mock_sample)
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text = "The quick brown fox"
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## Test basic completion until eos
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n = 0 # reset
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completion = llama.create_completion(text, max_tokens=20)
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assert completion["choices"][0]["text"] == output_text
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assert completion["choices"][0]["finish_reason"] == "stop"
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## Test streaming completion until eos
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n = 0 # reset
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chunks = llama.create_completion(text, max_tokens=20, stream=True)
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assert "".join(chunk["choices"][0]["text"] for chunk in chunks) == output_text
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assert completion["choices"][0]["finish_reason"] == "stop"
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## Test basic completion until stop sequence
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n = 0 # reset
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completion = llama.create_completion(text, max_tokens=20, stop=["lazy"])
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assert completion["choices"][0]["text"] == " jumps over the "
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assert completion["choices"][0]["finish_reason"] == "stop"
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## Test streaming completion until stop sequence
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n = 0 # reset
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chunks = llama.create_completion(text, max_tokens=20, stream=True, stop=["lazy"])
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assert (
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"".join(chunk["choices"][0]["text"] for chunk in chunks) == " jumps over the "
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)
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assert completion["choices"][0]["finish_reason"] == "stop"
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## Test basic completion until length
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n = 0 # reset
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completion = llama.create_completion(text, max_tokens=2)
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assert completion["choices"][0]["text"] == " j"
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assert completion["choices"][0]["finish_reason"] == "length"
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## Test streaming completion until length
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n = 0 # reset
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chunks = llama.create_completion(text, max_tokens=2, stream=True)
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assert "".join(chunk["choices"][0]["text"] for chunk in chunks) == " j"
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assert completion["choices"][0]["finish_reason"] == "length"
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def test_llama_pickle():
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import pickle
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import tempfile
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fp = tempfile.TemporaryFile()
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llama = llama_cpp.Llama(model_path=MODEL, vocab_only=True)
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pickle.dump(llama, fp)
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fp.seek(0)
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llama = pickle.load(fp)
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assert llama
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assert llama.ctx is not None
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text = b"Hello World"
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assert llama.detokenize(llama.tokenize(text)) == text |