Brunobkr/llama.cpp_AlgMor24_github

1import pytest2from utils import *3 4server = ServerPreset.jina_reranker_tiny()5 6 7@pytest.fixture(autouse=True)8def create_server():9    global server10    server = ServerPreset.jina_reranker_tiny()11 12 13TEST_DOCUMENTS = [14    "A machine is a physical system that uses power to apply forces and control movement to perform an action. The term is commonly applied to artificial devices, such as those employing engines or motors, but also to natural biological macromolecules, such as molecular machines.",15    "Learning is the process of acquiring new understanding, knowledge, behaviors, skills, values, attitudes, and preferences. The ability to learn is possessed by humans, non-human animals, and some machines; there is also evidence for some kind of learning in certain plants.",16    "Machine learning is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions.",17    "Paris, capitale de la France, est une grande ville européenne et un centre mondial de l'art, de la mode, de la gastronomie et de la culture. Son paysage urbain du XIXe siècle est traversé par de larges boulevards et la Seine."18]19 20 21def test_rerank():22    global server23    server.start()24    res = server.make_request("POST", "/rerank", data={25        "query": "Machine learning is",26        "documents": TEST_DOCUMENTS,27    })28    assert res.status_code == 20029    assert len(res.body["results"]) == 430 31    most_relevant = res.body["results"][0]32    least_relevant = res.body["results"][0]33    for doc in res.body["results"]:34        if doc["relevance_score"] > most_relevant["relevance_score"]:35            most_relevant = doc36        if doc["relevance_score"] < least_relevant["relevance_score"]:37            least_relevant = doc38 39    assert most_relevant["relevance_score"] > least_relevant["relevance_score"]40    assert most_relevant["index"] == 241    assert least_relevant["index"] == 342 43 44def test_rerank_tei_format():45    global server46    server.start()47    res = server.make_request("POST", "/rerank", data={48        "query": "Machine learning is",49        "texts": TEST_DOCUMENTS,50    })51    assert res.status_code == 20052    assert len(res.body) == 453 54    most_relevant = res.body[0]55    least_relevant = res.body[0]56    for doc in res.body:57        if doc["score"] > most_relevant["score"]:58            most_relevant = doc59        if doc["score"] < least_relevant["score"]:60            least_relevant = doc61 62    assert most_relevant["score"] > least_relevant["score"]63    assert most_relevant["index"] == 264    assert least_relevant["index"] == 365 66 67@pytest.mark.parametrize("documents", [68    [],69    None,70    123,71    [1, 2, 3],72])73def test_invalid_rerank_req(documents):74    global server75    server.start()76    res = server.make_request("POST", "/rerank", data={77        "query": "Machine learning is",78        "documents": documents,79    })80    assert res.status_code == 40081    assert "error" in res.body82 83 84@pytest.mark.parametrize(85    "query,doc1,doc2,n_tokens",86    [87        ("Machine learning is", "A machine", "Learning is", 19),88        ("Which city?", "Machine learning is ", "Paris, capitale de la", 26),89    ]90)91def test_rerank_usage(query, doc1, doc2, n_tokens):92    global server93    server.start()94 95    res = server.make_request("POST", "/rerank", data={96        "query": query,97        "documents": [98            doc1,99            doc2,100        ]101    })102    assert res.status_code == 200103    assert res.body['usage']['prompt_tokens'] == res.body['usage']['total_tokens']104    assert res.body['usage']['prompt_tokens'] == n_tokens105 106 107@pytest.mark.parametrize("top_n,expected_len", [108    (None, len(TEST_DOCUMENTS)),  # no top_n parameter109    (2, 2),110    (4, 4),111    (99, len(TEST_DOCUMENTS)),    # higher than available docs112])113def test_rerank_top_n(top_n, expected_len):114    global server115    server.start()116    data = {117        "query": "Machine learning is",118        "documents": TEST_DOCUMENTS,119    }120    if top_n is not None:121        data["top_n"] = top_n122 123    res = server.make_request("POST", "/rerank", data=data)124    assert res.status_code == 200125    assert len(res.body["results"]) == expected_len126 127 128@pytest.mark.parametrize("top_n,expected_len", [129    (None, len(TEST_DOCUMENTS)),  # no top_n parameter130    (2, 2),131    (4, 4),132    (99, len(TEST_DOCUMENTS)),    # higher than available docs133])134def test_rerank_tei_top_n(top_n, expected_len):135    global server136    server.start()137    data = {138        "query": "Machine learning is",139        "texts": TEST_DOCUMENTS,140    }141    if top_n is not None:142        data["top_n"] = top_n143 144    res = server.make_request("POST", "/rerank", data=data)145    assert res.status_code == 200146    assert len(res.body) == expected_len147