mirror of
https://github.com/ggml-org/llama.cpp.git
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45abe0f74e
* server : replace behave with pytest * fix test on windows * misc * add more tests * more tests * styling * log less, fix embd test * added all sequential tests * fix coding style * fix save slot test * add parallel completion test * fix parallel test * remove feature files * update test docs * no cache_prompt for some tests * add test_cache_vs_nocache_prompt
100 lines
3.1 KiB
Python
100 lines
3.1 KiB
Python
import pytest
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from openai import OpenAI
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from utils import *
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server = ServerPreset.bert_bge_small()
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EPSILON = 1e-3
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@pytest.fixture(scope="module", autouse=True)
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def create_server():
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global server
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server = ServerPreset.bert_bge_small()
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def test_embedding_single():
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global server
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server.start()
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res = server.make_request("POST", "/embeddings", data={
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"input": "I believe the meaning of life is",
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})
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assert res.status_code == 200
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assert len(res.body['data']) == 1
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assert 'embedding' in res.body['data'][0]
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assert len(res.body['data'][0]['embedding']) > 1
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# make sure embedding vector is normalized
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assert abs(sum([x ** 2 for x in res.body['data'][0]['embedding']]) - 1) < EPSILON
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def test_embedding_multiple():
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global server
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server.start()
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res = server.make_request("POST", "/embeddings", data={
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"input": [
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"I believe the meaning of life is",
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"Write a joke about AI from a very long prompt which will not be truncated",
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"This is a test",
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"This is another test",
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],
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})
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assert res.status_code == 200
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assert len(res.body['data']) == 4
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for d in res.body['data']:
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assert 'embedding' in d
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assert len(d['embedding']) > 1
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def test_embedding_openai_library_single():
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global server
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server.start()
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client = OpenAI(api_key="dummy", base_url=f"http://{server.server_host}:{server.server_port}")
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res = client.embeddings.create(model="text-embedding-3-small", input="I believe the meaning of life is")
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assert len(res.data) == 1
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assert len(res.data[0].embedding) > 1
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def test_embedding_openai_library_multiple():
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global server
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server.start()
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client = OpenAI(api_key="dummy", base_url=f"http://{server.server_host}:{server.server_port}")
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res = client.embeddings.create(model="text-embedding-3-small", input=[
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"I believe the meaning of life is",
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"Write a joke about AI from a very long prompt which will not be truncated",
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"This is a test",
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"This is another test",
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])
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assert len(res.data) == 4
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for d in res.data:
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assert len(d.embedding) > 1
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def test_embedding_error_prompt_too_long():
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global server
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server.start()
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res = server.make_request("POST", "/embeddings", data={
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"input": "This is a test " * 512,
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})
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assert res.status_code != 200
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assert "too large" in res.body["error"]["message"]
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def test_same_prompt_give_same_result():
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server.start()
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res = server.make_request("POST", "/embeddings", data={
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"input": [
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"I believe the meaning of life is",
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"I believe the meaning of life is",
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"I believe the meaning of life is",
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"I believe the meaning of life is",
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"I believe the meaning of life is",
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],
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})
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assert res.status_code == 200
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assert len(res.body['data']) == 5
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for i in range(1, len(res.body['data'])):
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v0 = res.body['data'][0]['embedding']
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vi = res.body['data'][i]['embedding']
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for x, y in zip(v0, vi):
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assert abs(x - y) < EPSILON
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