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import hashlib
import json
import os
import pickle
import unittest
from unittest.mock import patch
from lm_eval.api.instance import Instance
from lm_eval.models.gguf import GGUFLM
base_url = "https://matthoffner-ggml-llm-api.hf.space"
def gguf_completion_mock(base_url=None, **kwargs):
# Generate a hash from the parameters
hash_kwargs = {"base_url": base_url, **kwargs}
hash = hashlib.sha256(
json.dumps(hash_kwargs, sort_keys=True).encode("utf-8")
).hexdigest()
fname = f"./tests/testdata/gguf_test_{hash}.pkl"
if os.path.exists(fname):
with open(fname, "rb") as fh:
return pickle.load(fh)
else:
print("The file does not exist, attempting to write...")
if "stop" in kwargs:
result = {
"choices": [
{
"text": f"generated text until {kwargs['stop']}",
"logprobs": {"token_logprobs": [-1.2345], "text_offset": 0},
"finish_reason": "length",
}
]
}
else:
# generated with # curl -X 'POST' 'http://localhost:8000/v1/completions' -H 'accept: application/json' -H 'Content-Type: application/json' -d '{"prompt": "string", "logprobs": 10, "temperature": 0.0, "max_tokens": 1, "echo": true}'
result = {
"id": "cmpl-4023976b-bc6a-43b0-a5a9-629f4216c7f3",
"object": "text_completion",
"created": 1700511361,
"model": "../llama-2-7b.Q8_0.gguf",
"choices": [
{
"text": "string(",
"index": 0,
"logprobs": {
"text_offset": [0, 7],
"token_logprobs": [None, -1.033263319857306],
"tokens": [" string", "("],
"top_logprobs": [
None,
{
"(": -1.033263319857306,
"[]": -2.6530743779017394,
".": -3.0377145947291324,
"\n": -3.0399156750513976,
"_": -3.510376089937872,
" =": -3.6957918347193663,
",": -3.9309459866358702,
" of": -4.2834550083949035,
'("': -4.322762841112799,
"()": -4.426229113466925,
},
],
},
"finish_reason": "length",
}
],
"usage": {
"prompt_tokens": 2,
"completion_tokens": 1,
"total_tokens": 3,
},
}
try:
os.makedirs(os.path.dirname(fname), exist_ok=True)
print("Writing file at", fname)
with open(fname, "wb") as fh:
pickle.dump(result, fh)
print("File written successfully")
except Exception as e:
print("File writing failed:", e)
return result
class GGUFLMTest(unittest.TestCase):
@patch(
"lm_eval.models.gguf.GGUFLM.gguf_completion", side_effect=gguf_completion_mock
)
def test_loglikelihood(self, gguf_completion_mock):
lm = GGUFLM(base_url)
# Test loglikelihood
requests = [
Instance(
request_type="loglikelihood",
doc=args,
arguments=args,
idx=i,
)
for i, args in enumerate([("str", "ing"), ("str", "ing")])
]
res = lm.loglikelihood(requests)
# Assert the loglikelihood response is correct
expected_res = [(logprob, True) for logprob in [0, 0]]
self.assertEqual(res, expected_res)
@patch(
"lm_eval.models.gguf.GGUFLM.gguf_completion", side_effect=gguf_completion_mock
)
def test_generate_until(self, gguf_completion_mock):
lm = GGUFLM(base_url)
# Test generate_until
requests = [
Instance(
request_type="generate_until",
doc={"input": doc},
arguments=(doc, {"until": stop}),
idx=i,
)
for i, (doc, stop) in enumerate([("input1", "stop1"), ("input2", "stop2")])
]
res = lm.generate_until(requests)
# Assert the generate_until response is correct
expected_res = ["generated text until stop1", "generated text until stop2"]
self.assertEqual(res, expected_res)
# @patch('lm_eval.models.gguf.GGUFLM.gguf_completion', side_effect=gguf_completion_mock)
# def test_loglikelihood_rolling(self, gguf_completion_mock):
# lm = GGUFLM(base_url)
# # Test loglikelihood_rolling
# requests = ["input1", "input2"]
# res = lm.loglikelihood_rolling(requests)
# # Assert the loglikelihood_rolling response is correct
# expected_res = [(-1.2345, True), (-1.2345, True)]
# self.assertEqual(res, expected_res)
if __name__ == "__main__":
unittest.main()
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