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Treat empty prompts and responses as empty strings #100

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merged 1 commit into from
Oct 3, 2024
Merged

Treat empty prompts and responses as empty strings #100

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5 changes: 1 addition & 4 deletions autoarena/service/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -96,13 +96,10 @@ def upload_responses(project_slug: str, model_name: str, df_response: pd.DataFra
raise BadRequestError(str(e))
if len(df_response) == 0:
raise BadRequestError("Responses must not be empty")
df_response = df_response.copy().replace({np.nan: ""})
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If we ever make use of columns beyond prompt or response, we may want to restrict it to df_response[["prompt", "response"]].

n_duplicate_prompts = len(df_response) - len(set(df_response["prompt"]))
if n_duplicate_prompts > 0:
raise BadRequestError(f"Each 'prompt' value must be unique (received {n_duplicate_prompts} duplicate(s))")
n_input = len(df_response)
df_response = df_response.copy().dropna(subset=["prompt", "response"])
if len(df_response) != n_input:
logger.warning(f"Dropped {n_input - len(df_response)} responses with empty prompt or response values")
logger.info(f"Uploading {len(df_response)} responses from model '{model_name}'")
with ProjectService.connect(project_slug, commit=True) as conn:
cur = conn.cursor()
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25 changes: 18 additions & 7 deletions tests/integration/api/test_models.py
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Original file line number Diff line number Diff line change
Expand Up @@ -54,19 +54,30 @@ def test__models__upload__missing_columns(project_client: TestClient, df_bad: pd


@pytest.mark.parametrize(
"df,n_dropped",
"df",
[
(pd.DataFrame([("p", "r"), ("p2", "")], columns=["prompt", "response"]), 1),
(pd.DataFrame([("p", "r"), ("", "r")], columns=["prompt", "response"]), 1),
(pd.DataFrame([("p", ""), ("p2", "")], columns=["prompt", "response"]), 2),
(pd.DataFrame([("", "r"), ("p2", "")], columns=["prompt", "response"]), 2),
# many empty responses are fine
pd.DataFrame([("p", "r"), ("p2", ""), ("p3", None), ("p4", pd.NA)], columns=["prompt", "response"]),
# empty prompts are fine, treated as empty strings
pd.DataFrame([("p", "r"), (None, "r")], columns=["prompt", "response"]),
pd.DataFrame([("p", "r"), (pd.NA, "r")], columns=["prompt", "response"]),
pd.DataFrame([("p", "r"), ("", "r")], columns=["prompt", "response"]),
],
)
def test__models__upload__missing_values(project_client: TestClient, df: pd.DataFrame, n_dropped: int) -> None:
def test__models__upload__missing_values(project_client: TestClient, df: pd.DataFrame) -> None:
body = construct_upload_model_body(dict(example=df))
models = project_client.post("/model", data=body.data, files=body.files).json()
assert len(models) == 1
assert models[0]["n_responses"] == len(df) - n_dropped
assert models[0]["n_responses"] == len(df)


def test__models__upload__missing_multiple_prompts(project_client: TestClient) -> None:
# empty prompts are treated as empty strings -- should fail due to duplicates
df = pd.DataFrame([(None, "r"), ("", "r2")], columns=["prompt", "response"])
body = construct_upload_model_body(dict(example=df))
response = project_client.post("/model", data=body.data, files=body.files)
assert response.status_code == 400
assert "Each 'prompt' value must be unique" in response.json()["detail"]


def test__models__upload__duplicate_prompts(project_client: TestClient) -> None:
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