llm/tests/test_llm.py
2023-07-05 18:31:38 -07:00

139 lines
4.2 KiB
Python

from click.testing import CliRunner
from llm.cli import cli
from llm.migrations import migrate
import json
import os
import pytest
import sqlite_utils
from unittest import mock
def test_version():
runner = CliRunner()
with runner.isolated_filesystem():
result = runner.invoke(cli, ["--version"])
assert result.exit_code == 0
assert result.output.startswith("cli, version ")
@pytest.mark.parametrize("n", (None, 0, 2))
def test_logs(n, user_path):
log_path = str(user_path / "logs.db")
db = sqlite_utils.Database(log_path)
migrate(db)
db["logs"].insert_all(
{
"system": "system",
"prompt": "prompt",
"response": "response",
"model": "davinci",
}
for i in range(100)
)
runner = CliRunner()
args = ["logs", "-p", str(log_path)]
if n is not None:
args.extend(["-n", str(n)])
result = runner.invoke(cli, args, catch_exceptions=False)
assert result.exit_code == 0
logs = json.loads(result.output)
expected_length = 3
if n is not None:
if n == 0:
expected_length = 100
else:
expected_length = n
assert len(logs) == expected_length
@pytest.mark.parametrize("env", ({}, {"LLM_USER_PATH": "/tmp/llm-user-path"}))
def test_logs_path(monkeypatch, env, user_path):
for key, value in env.items():
monkeypatch.setenv(key, value)
runner = CliRunner()
result = runner.invoke(cli, ["logs", "path"])
assert result.exit_code == 0
if env:
expected = env["LLM_USER_PATH"] + "/logs.db"
else:
expected = str(user_path) + "/logs.db"
assert result.output.strip() == expected
@mock.patch.dict(os.environ, {"OPENAI_API_KEY": "X"})
@pytest.mark.parametrize("use_stdin", (True, False))
def test_llm_default_prompt(mocked_openai, use_stdin, user_path):
# Reset the log_path database
log_path = user_path / "logs.db"
log_db = sqlite_utils.Database(str(log_path))
log_db["logs"].delete_where()
runner = CliRunner()
prompt = "three names for a pet pelican"
input = None
args = ["--no-stream"]
if use_stdin:
input = prompt
else:
args.append(prompt)
result = runner.invoke(cli, args, input=input, catch_exceptions=False)
assert result.exit_code == 0
assert result.output == "Bob, Alice, Eve\n"
assert mocked_openai.last_request.headers["Authorization"] == "Bearer X"
# Was it logged?
rows = list(log_db["logs"].rows)
assert len(rows) == 1
expected = {
"model": "gpt-3.5-turbo",
"prompt": "three names for a pet pelican",
"system": None,
"response": "Bob, Alice, Eve",
"chat_id": None,
}
expected = {
"model": "gpt-3.5-turbo",
"prompt": "three names for a pet pelican",
"system": None,
"options_json": "{}",
"response": "Bob, Alice, Eve",
"reply_to_id": None,
"chat_id": None,
}
row = rows[0]
assert expected.items() <= row.items()
assert isinstance(row["duration_ms"], int)
assert isinstance(row["datetime_utc"], str)
assert json.loads(row["prompt_json"]) == {
"messages": [{"role": "user", "content": "three names for a pet pelican"}]
}
assert json.loads(row["response_json"]) == {
"model": "gpt-3.5-turbo",
"usage": {},
"choices": [{"message": {"content": "Bob, Alice, Eve"}}],
}
# Test "llm logs"
log_result = runner.invoke(cli, ["logs", "-n", "1"], catch_exceptions=False)
log_json = json.loads(log_result.output)
assert (
log_json[0].items()
>= {
"model": "gpt-3.5-turbo",
"prompt": "three names for a pet pelican",
"system": None,
"prompt_json": {
"messages": [
{"role": "user", "content": "three names for a pet pelican"}
]
},
"options_json": {},
"response": "Bob, Alice, Eve",
"response_json": {
"model": "gpt-3.5-turbo",
"usage": {},
"choices": [{"message": {"content": "Bob, Alice, Eve"}}],
},
"reply_to_id": None,
"chat_id": None,
}.items()
)