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docs: add Gemini 2.0 text gen sample notebook (#1211)
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* feat: add Gemini 2.0 preview text model support

* update docs

* docs: add Gemini 2.0 text gen sample notebook
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@GarrettWu
GarrettWu authored Dec 11, 2024
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377 changes: 377 additions & 0 deletions notebooks/generative_ai/bq_dataframes_llm_gemini_2.ipynb
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{
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"source": [
"# Copyright 2024 Google LLC\n",
"#\n",
"# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
"# you may not use this file except in compliance with the License.\n",
"# You may obtain a copy of the License at\n",
"#\n",
"# https://www.apache.org/licenses/LICENSE-2.0\n",
"#\n",
"# Unless required by applicable law or agreed to in writing, software\n",
"# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
"# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
"# See the License for the specific language governing permissions and\n",
"# limitations under the License."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# BigFrames Gemini 2.0 Text Generation Simple Example"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Note: This feature is only available in bigframes >= 1.29.0"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Import packages"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"import bigframes.pandas as bpd\n",
"from bigframes.ml import llm"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Create Gemini 2.0 experimental Model with model_name as \"gemini-2.0-flash-exp\""
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/usr/local/google/home/garrettwu/src/bigframes/bigframes/ml/llm.py:803: PreviewWarning: Model gemini-2.0-flash-exp is subject to the \"Pre-GA Offerings Terms\" in the General Service Terms section of the\n",
" Service Specific Terms(https://cloud.google.com/terms/service-terms#1). Pre-GA products and features are available \"as is\"\n",
" and might have limited support. For more information, see the launch stage descriptions\n",
" (https://cloud.google.com/products#product-launch-stages).\n",
" warnings.warn(\n",
"/usr/local/google/home/garrettwu/src/bigframes/bigframes/pandas/__init__.py:435: DefaultLocationWarning: No explicit location is set, so using location US for the session.\n",
" return global_session.get_global_session()\n"
]
},
{
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"<IPython.core.display.HTML object>"
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"source": [
"model = llm.GeminiTextGenerator(model_name=\"gemini-2.0-flash-exp\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Create a simple DataFrame"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
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"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>prompt</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Tell me something about Gemini 2.0.</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1 rows × 1 columns</p>\n",
"</div>[1 rows x 1 columns in total]"
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" prompt\n",
"0 Tell me something about Gemini 2.0.\n",
"\n",
"[1 rows x 1 columns]"
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = bpd.DataFrame({\"prompt\": [\"Tell me something about Gemini 2.0.\"]})\n",
"df"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Make predictions"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
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"name": "stderr",
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"text": [
"/usr/local/google/home/garrettwu/src/bigframes/bigframes/core/__init__.py:109: PreviewWarning: Interpreting JSON column(s) as StringDtype. This behavior may change in future versions.\n",
" warnings.warn(\n"
]
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"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>ml_generate_text_llm_result</th>\n",
" <th>ml_generate_text_rai_result</th>\n",
" <th>ml_generate_text_status</th>\n",
" <th>prompt</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Alright, let's talk about Gemini 2.0! It's a b...</td>\n",
" <td>&lt;NA&gt;</td>\n",
" <td></td>\n",
" <td>Tell me something about Gemini 2.0.</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1 rows × 4 columns</p>\n",
"</div>[1 rows x 4 columns in total]"
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"text/plain": [
" ml_generate_text_llm_result \\\n",
"0 Alright, let's talk about Gemini 2.0! It's a b... \n",
"\n",
" ml_generate_text_rai_result ml_generate_text_status \\\n",
"0 <NA> \n",
"\n",
" prompt \n",
"0 Tell me something about Gemini 2.0. \n",
"\n",
"[1 rows x 4 columns]"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"result = model.predict(df)\n",
"result"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Save the model"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
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"/usr/local/google/home/garrettwu/src/bigframes/bigframes/ml/llm.py:803: PreviewWarning: Model gemini-2.0-flash-exp is subject to the \"Pre-GA Offerings Terms\" in the General Service Terms section of the\n",
" Service Specific Terms(https://cloud.google.com/terms/service-terms#1). Pre-GA products and features are available \"as is\"\n",
" and might have limited support. For more information, see the launch stage descriptions\n",
" (https://cloud.google.com/products#product-launch-stages).\n",
" warnings.warn(\n"
]
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"GeminiTextGenerator(connection_name='bigframes-dev.us.bigframes-rf-connection',\n",
" model_name='gemini-2.0-flash-exp',\n",
" session=<bigframes.session.Session object at 0x7f8210630370>)"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"model.to_gbq(\"bigframes-dev.garrettwu.gemini_2_flash\", replace=True)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "venv",
"language": "python",
"name": "python3"
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"codemirror_mode": {
"name": "ipython",
"version": 3
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"file_extension": ".py",
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"name": "python",
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"nbformat": 4,
"nbformat_minor": 2
}
1 change: 1 addition & 0 deletions noxfile.py
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Expand Up @@ -749,6 +749,7 @@ def notebook(session: nox.Session):
# bq_dataframes_llm_code_generation creates a bucket in the sample.
"notebooks/generative_ai/bq_dataframes_llm_code_generation.ipynb", # Needs BUCKET_URI.
"notebooks/generative_ai/sentiment_analysis.ipynb", # Too slow
"notebooks/generative_ai/bq_dataframes_llm_gemini_2.ipynb", # Gemini 2.0 backend hasn't ready in prod.
# TODO(b/366290533): to protect BQML quota
"notebooks/generative_ai/bq_dataframes_llm_claude3_museum_art.ipynb",
"notebooks/vertex_sdk/sdk2_bigframes_pytorch.ipynb", # Needs BUCKET_URI.
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