Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly
Appearance settings

feat: support ML.GENERATE_EMBEDDING in PaLM2TextEmbeddingGenerator #539

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We鈥檒l occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 3 commits into from
Mar 29, 2024
Merged

feat: support ML.GENERATE_EMBEDDING in PaLM2TextEmbeddingGenerator #539

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
f187841
feat: support ML.GENERATE_EMBEDDING in PaLM2TextEmbeddingGenerator
ashleyxuu Mar 28, 2024
a432b9d
fix failed test
ashleyxuu Mar 29, 2024
ea9d83c
Merge branch 'main' into ashleyxu-migrate-embedding-syntax
ashleyxuu Mar 29, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 2 additions & 2 deletions 4 bigframes/ml/core.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -152,14 +152,14 @@ def generate_text(
),
)

def generate_text_embedding(
def generate_embedding(
self,
input_data: bpd.DataFrame,
options: Mapping[str, int | float],
) -> bpd.DataFrame:
return self._apply_sql(
input_data,
lambda source_df: self._model_manipulation_sql_generator.ml_generate_text_embedding(
lambda source_df: self._model_manipulation_sql_generator.ml_generate_embedding(
source_df=source_df,
struct_options=options,
),
Expand Down
4 changes: 2 additions & 2 deletions 4 bigframes/ml/llm.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -44,7 +44,7 @@
_GEMINI_PRO_ENDPOINT = "gemini-pro"

_ML_GENERATE_TEXT_STATUS = "ml_generate_text_status"
_ML_EMBED_TEXT_STATUS = "ml_embed_text_status"
_ML_EMBED_TEXT_STATUS = "ml_generate_embedding_status"


@log_adapter.class_logger
Expand Down Expand Up @@ -389,7 +389,7 @@ def predict(self, X: Union[bpd.DataFrame, bpd.Series]) -> bpd.DataFrame:
"flatten_json_output": True,
}

df = self._bqml_model.generate_text_embedding(X, options)
df = self._bqml_model.generate_embedding(X, options)

if (df[_ML_EMBED_TEXT_STATUS] != "").any():
warnings.warn(
Expand Down
6 changes: 3 additions & 3 deletions 6 bigframes/ml/sql.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -270,12 +270,12 @@ def ml_generate_text(
return f"""SELECT * FROM ML.GENERATE_TEXT(MODEL `{self._model_name}`,
({self._source_sql(source_df)}), {struct_options_sql})"""

def ml_generate_text_embedding(
def ml_generate_embedding(
self, source_df: bpd.DataFrame, struct_options: Mapping[str, Union[int, float]]
) -> str:
"""Encode ML.GENERATE_TEXT_EMBEDDING for BQML"""
"""Encode ML.GENERATE_EMBEDDING for BQML"""
struct_options_sql = self.struct_options(**struct_options)
return f"""SELECT * FROM ML.GENERATE_TEXT_EMBEDDING(MODEL `{self._model_name}`,
return f"""SELECT * FROM ML.GENERATE_EMBEDDING(MODEL `{self._model_name}`,
({self._source_sql(source_df)}), {struct_options_sql})"""

def ml_detect_anomalies(
Expand Down
12 changes: 6 additions & 6 deletions 12 tests/system/small/ml/test_llm.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -261,8 +261,8 @@ def test_embedding_generator_predict_success(
):
df = palm2_embedding_generator_model.predict(llm_text_df).to_pandas()
assert df.shape == (3, 4)
assert "text_embedding" in df.columns
series = df["text_embedding"]
assert "ml_generate_embedding_result" in df.columns
series = df["ml_generate_embedding_result"]
value = series[0]
assert len(value) == 768

Expand All @@ -273,8 +273,8 @@ def test_embedding_generator_multilingual_predict_success(
):
df = palm2_embedding_generator_multilingual_model.predict(llm_text_df).to_pandas()
assert df.shape == (3, 4)
assert "text_embedding" in df.columns
series = df["text_embedding"]
assert "ml_generate_embedding_result" in df.columns
series = df["ml_generate_embedding_result"]
value = series[0]
assert len(value) == 768

Expand All @@ -285,8 +285,8 @@ def test_embedding_generator_predict_series_success(
):
df = palm2_embedding_generator_model.predict(llm_text_df["prompt"]).to_pandas()
assert df.shape == (3, 4)
assert "text_embedding" in df.columns
series = df["text_embedding"]
assert "ml_generate_embedding_result" in df.columns
series = df["ml_generate_embedding_result"]
value = series[0]
assert len(value) == 768

Expand Down
6 changes: 3 additions & 3 deletions 6 tests/unit/ml/test_sql.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -373,17 +373,17 @@ def test_ml_generate_text_correct(
)


def test_ml_generate_text_embedding_correct(
def test_ml_generate_embedding_correct(
model_manipulation_sql_generator: ml_sql.ModelManipulationSqlGenerator,
mock_df: bpd.DataFrame,
):
sql = model_manipulation_sql_generator.ml_generate_text_embedding(
sql = model_manipulation_sql_generator.ml_generate_embedding(
source_df=mock_df,
struct_options={"option_key1": 1, "option_key2": 2.2},
)
assert (
sql
== """SELECT * FROM ML.GENERATE_TEXT_EMBEDDING(MODEL `my_project_id.my_dataset_id.my_model_id`,
== """SELECT * FROM ML.GENERATE_EMBEDDING(MODEL `my_project_id.my_dataset_id.my_model_id`,
(input_X_sql), STRUCT(
1 AS option_key1,
2.2 AS option_key2))"""
Expand Down
Morty Proxy This is a proxified and sanitized view of the page, visit original site.