151 lines
4.7 KiB
Python
151 lines
4.7 KiB
Python
import pytest
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import json
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from text_generation.types import GrammarType
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@pytest.fixture(scope="module")
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def flash_llama_grammar_handle(launcher):
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with launcher(
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"TinyLlama/TinyLlama-1.1B-Chat-v1.0", num_shard=2, disable_grammar_support=False
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) as handle:
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yield handle
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@pytest.fixture(scope="module")
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async def flash_llama_grammar(flash_llama_grammar_handle):
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await flash_llama_grammar_handle.health(300)
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return flash_llama_grammar_handle.client
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@pytest.mark.asyncio
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async def test_flash_llama_grammar(flash_llama_grammar, response_snapshot):
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response = await flash_llama_grammar.generate(
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"Test request", max_new_tokens=10, decoder_input_details=True
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)
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assert response.details.generated_tokens == 10
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assert response == response_snapshot
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@pytest.mark.skip
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@pytest.mark.asyncio
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async def test_flash_llama_grammar_regex(flash_llama_grammar, response_snapshot):
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response = await flash_llama_grammar.generate(
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"Whats Googles DNS",
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max_new_tokens=10,
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decoder_input_details=True,
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seed=0,
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grammar={
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"type": GrammarType.Regex, # "regex"
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"value": "((25[0-5]|2[0-4]\\d|[01]?\\d\\d?)\\.){3}(25[0-5]|2[0-4]\\d|[01]?\\d\\d?)",
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},
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)
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assert response.details.generated_tokens == 10
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assert response.generated_text == "42.1.1.101"
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assert response == response_snapshot
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@pytest.mark.skip
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@pytest.mark.asyncio
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async def test_flash_llama_grammar_json(flash_llama_grammar, response_snapshot):
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response = await flash_llama_grammar.generate(
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"info: david holtz like trees and has two cats. ",
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max_new_tokens=100,
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decoder_input_details=True,
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seed=0,
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grammar={
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"type": GrammarType.Json, # "json"
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"value": json.dumps(
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{
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"type": "object",
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"$id": "https://example.com/person.schema.json",
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"$schema": "https://json-schema.org/draft/2020-12/schema",
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"title": "Person",
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"properties": {
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"firstName": {
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"type": "string",
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"description": "The person'''s first name.",
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},
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"lastName": {
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"type": "string",
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"description": "The person'''s last name.",
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},
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"hobby": {
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"description": "The person'''s hobby.",
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"type": "string",
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},
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"numCats": {
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"description": "The number of cats the person has.",
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"type": "integer",
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"minimum": 0,
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},
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},
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"required": ["firstName", "lastName", "hobby", "numCats"],
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}
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),
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},
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)
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assert response.details.generated_tokens == 30
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assert (
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response.generated_text
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== '{"firstName":"David","hobby":"Trees","lastName":"Holtz","numCats":2}'
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)
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assert response == response_snapshot
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@pytest.mark.skip
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@pytest.mark.asyncio
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async def test_flash_llama_grammar_load(
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flash_llama_grammar, generate_load, response_snapshot
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):
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responses = await generate_load(
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flash_llama_grammar,
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"name: david. email: ",
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max_new_tokens=10,
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n=4,
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stop_sequences=[".com"],
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seed=0,
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grammar={
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"type": GrammarType.Regex, # "regex"
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"value": "[\\w-]+@([\\w-]+\\.)+[\\w-]+", # email regex
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},
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)
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assert len(responses) == 4
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expected = "123456@gmail.com"
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for response in responses:
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assert response.generated_text == expected
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assert all([r.generated_text == responses[0].generated_text for r in responses])
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assert responses == response_snapshot
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# this is the same as the above test, but only fires off a single request
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# this is only to ensure that the parallel and single inference produce the same result
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@pytest.mark.skip
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@pytest.mark.asyncio
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async def test_flash_llama_grammar_single_load_instance(
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flash_llama_grammar, generate_load, response_snapshot
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):
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response = await flash_llama_grammar.generate(
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"name: david. email: ",
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max_new_tokens=10,
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stop_sequences=[".com"],
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seed=0,
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grammar={
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"type": GrammarType.Regex, # "regex"
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"value": "[\\w-]+@([\\w-]+\\.)+[\\w-]+", # email regex
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},
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)
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# assert response.details.generated_tokens == 30
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assert response.generated_text == "123456@gmail.com"
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assert response == response_snapshot
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