mirror of
https://github.com/aljazceru/gpt-engineer.git
synced 2025-12-17 12:45:26 +01:00
52 lines
1.6 KiB
Python
52 lines
1.6 KiB
Python
import json
|
|
import os
|
|
|
|
from unittest.mock import MagicMock
|
|
|
|
import pytest
|
|
import rudderstack.analytics as rudder_analytics
|
|
|
|
from gpt_engineer.collect import collect_learnings, steps_file_hash
|
|
from gpt_engineer.db import DB, DBs
|
|
from gpt_engineer.learning import extract_learning
|
|
from gpt_engineer.steps import gen_code
|
|
|
|
|
|
def test_collect_learnings(monkeypatch):
|
|
monkeypatch.setattr(os, "environ", {"COLLECT_LEARNINGS_OPT_OUT": "false"})
|
|
monkeypatch.setattr(rudder_analytics, "track", MagicMock())
|
|
|
|
model = "test_model"
|
|
temperature = 0.5
|
|
steps = [gen_code]
|
|
dbs = DBs(DB("/tmp"), DB("/tmp"), DB("/tmp"), DB("/tmp"), DB("/tmp"))
|
|
dbs.input = {
|
|
"prompt": "test prompt\n with newlines",
|
|
"feedback": "test feedback",
|
|
}
|
|
code = "this is output\n\nit contains code"
|
|
dbs.logs = {gen_code.__name__: json.dumps([{"role": "system", "content": code}])}
|
|
dbs.workspace = {"all_output.txt": "test workspace\n" + code}
|
|
|
|
collect_learnings(model, temperature, steps, dbs)
|
|
|
|
learnings = extract_learning(
|
|
model, temperature, steps, dbs, steps_file_hash=steps_file_hash()
|
|
)
|
|
assert rudder_analytics.track.call_count == 1
|
|
assert rudder_analytics.track.call_args[1]["event"] == "learning"
|
|
a = {
|
|
k: v
|
|
for k, v in rudder_analytics.track.call_args[1]["properties"].items()
|
|
if k != "timestamp"
|
|
}
|
|
b = {k: v for k, v in learnings.to_dict().items() if k != "timestamp"}
|
|
assert a == b
|
|
|
|
assert code in learnings.logs
|
|
assert code in learnings.workspace
|
|
|
|
|
|
if __name__ == "__main__":
|
|
pytest.main(["-v"])
|