hf_text-generation-inference/integration-tests/models/test_flash_grammar_llama.py

151 lines
4.7 KiB
Python

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