mirror of
https://github.com/hwchase17/langchain.git
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docs: fix errors and table formatting in notebook (#21696)
There are 2 issues fixed here: * In the notebook pandas dataframes are formatted as HTML in the cells. On the documentation site the renderer that converts notebooks incorrectly displays the raw HTML. I can't find any examples of where this is working and so I am formatting the dataframes as text. * Some incorrect table names were referenced resulting in errors.
This commit is contained in:
Chad Juliano
GitHub
parent
f3289b898c
commit
685c13e157
@ -54,18 +54,9 @@
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": null,
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"metadata": {},
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"metadata": {},
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"outputs": [
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"outputs": [],
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Note: you may need to restart the kernel to use updated packages.\n",
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"Note: you may need to restart the kernel to use updated packages.\n"
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]
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}
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],
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"source": [
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"source": [
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"# Install Langchain community and core packages\n",
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"# Install Langchain community and core packages\n",
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"%pip install --upgrade --quiet langchain-core langchain-community\n",
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"%pip install --upgrade --quiet langchain-core langchain-community\n",
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@ -123,98 +114,13 @@
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 2,
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"metadata": {},
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"metadata": {},
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"outputs": [
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"outputs": [
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{
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"data": {
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"name": "stdout",
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"text/html": [
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"output_type": "stream",
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"<div>\n",
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"text": [
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>username</th>\n",
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" <th>name</th>\n",
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" <th>sex</th>\n",
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" <th>address</th>\n",
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" <th>mail</th>\n",
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" <th>birthdate</th>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>id</th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>eduardo69</td>\n",
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" <td>Haley Beck</td>\n",
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" <td>F</td>\n",
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" <td>59836 Carla Causeway Suite 939\\nPort Eugene, I...</td>\n",
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" <td>meltondenise@yahoo.com</td>\n",
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" <td>1997-11-23</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>lbarrera</td>\n",
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" <td>Joshua Stephens</td>\n",
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" <td>M</td>\n",
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" <td>3108 Christina Forges\\nPort Timothychester, KY...</td>\n",
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" <td>erica80@hotmail.com</td>\n",
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" <td>1924-07-19</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>bburton</td>\n",
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" <td>Paula Kaiser</td>\n",
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" <td>F</td>\n",
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" <td>Unit 7405 Box 3052\\nDPO AE 09858</td>\n",
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" <td>timothypotts@gmail.com</td>\n",
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" <td>1933-11-20</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>melissa49</td>\n",
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" <td>Wendy Reese</td>\n",
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" <td>F</td>\n",
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" <td>6408 Christopher Hill Apt. 459\\nNew Benjamin, ...</td>\n",
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" <td>dadams@gmail.com</td>\n",
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" <td>1988-10-11</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>melissacarter</td>\n",
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" <td>Manuel Rios</td>\n",
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" <td>M</td>\n",
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" <td>2241 Bell Gardens Suite 723\\nScottside, CA 38463</td>\n",
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" <td>williamayala@gmail.com</td>\n",
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" <td>1931-03-04</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" username name sex \\\n",
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" username name sex \\\n",
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"id \n",
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"id \n",
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"0 eduardo69 Haley Beck F \n",
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"0 eduardo69 Haley Beck F \n",
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@ -233,16 +139,12 @@
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"\n",
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"\n",
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" birthdate \n",
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" birthdate \n",
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"id \n",
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"id \n",
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"0 1997-11-23 \n",
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"0 1997-12-01 \n",
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"1 1924-07-19 \n",
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"1 1924-07-27 \n",
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"2 1933-11-20 \n",
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"2 1933-11-28 \n",
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"3 1988-10-11 \n",
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"3 1988-10-19 \n",
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"4 1931-03-04 "
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"4 1931-03-12 \n"
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]
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]
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},
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"execution_count": 1,
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"metadata": {},
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"output_type": "execute_result"
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}
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}
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],
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],
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"source": [
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"source": [
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@ -263,7 +165,7 @@
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"\n",
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"\n",
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"\n",
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"\n",
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"load_df = pd.DataFrame.from_records(data=profile_gen(100), index=\"id\")\n",
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"load_df = pd.DataFrame.from_records(data=profile_gen(100), index=\"id\")\n",
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"load_df.head()"
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"print(load_df.head())"
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]
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]
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},
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{
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@ -279,85 +181,17 @@
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"metadata": {},
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"metadata": {},
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"outputs": [
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"outputs": [
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{
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{
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"data": {
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"name": "stdout",
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"text/html": [
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"output_type": "stream",
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"<div>\n",
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"text": [
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>name</th>\n",
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" <th>type</th>\n",
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" <th>properties</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>username</td>\n",
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" <td>string</td>\n",
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" <td>[char32]</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>name</td>\n",
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" <td>string</td>\n",
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" <td>[char32]</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>sex</td>\n",
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" <td>string</td>\n",
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" <td>[char1]</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>address</td>\n",
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" <td>string</td>\n",
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" <td>[char64]</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>mail</td>\n",
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" <td>string</td>\n",
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" <td>[char32]</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>5</th>\n",
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" <td>birthdate</td>\n",
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" <td>long</td>\n",
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" <td>[timestamp]</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" name type properties\n",
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" name type properties\n",
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"0 username string [char32]\n",
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"0 username string [char32]\n",
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"1 name string [char32]\n",
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"1 name string [char32]\n",
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"2 sex string [char1]\n",
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"2 sex string [char2]\n",
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"3 address string [char64]\n",
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"3 address string [char64]\n",
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"4 mail string [char32]\n",
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"4 mail string [char32]\n",
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"5 birthdate long [timestamp]"
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"5 birthdate long [timestamp]\n"
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]
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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}
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],
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],
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"source": [
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"source": [
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@ -372,7 +206,7 @@
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")\n",
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")\n",
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"\n",
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"\n",
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"# See the Kinetica column types\n",
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"# See the Kinetica column types\n",
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"gpudb_table.type_as_df()"
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"print(gpudb_table.type_as_df())"
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]
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]
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},
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{
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{
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@ -394,10 +228,7 @@
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{
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{
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"data": {
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"data": {
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"text/plain": [
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"text/plain": [
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"{'status': 'OK',\n",
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"1"
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" 'message': '',\n",
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" 'data_type': 'execute_sql_response',\n",
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" 'response_time': 0.0148}"
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]
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]
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},
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},
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"execution_count": 4,
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"execution_count": 4,
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@ -408,34 +239,23 @@
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"source": [
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"source": [
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"# create an LLM context for the table.\n",
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"# create an LLM context for the table.\n",
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"\n",
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"\n",
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"from gpudb import GPUdbException\n",
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"\n",
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"sql = f\"\"\"\n",
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"sql = f\"\"\"\n",
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"CREATE OR REPLACE CONTEXT {kinetica_ctx}\n",
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"CREATE OR REPLACE CONTEXT {kinetica_ctx}\n",
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"(\n",
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"(\n",
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" TABLE = demo.test_profiles\n",
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" TABLE = {table_name}\n",
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" COMMENT = 'Contains user profiles.'\n",
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" COMMENT = 'Contains user profiles.'\n",
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"),\n",
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"),\n",
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"(\n",
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"(\n",
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" SAMPLES = (\n",
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" SAMPLES = (\n",
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" 'How many male users are there?' = \n",
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" 'How many male users are there?' = \n",
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" 'select count(1) as num_users\n",
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" 'select count(1) as num_users\n",
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" from demo.test_profiles\n",
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" from {table_name}\n",
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" where sex = ''M'';')\n",
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" where sex = ''M'';')\n",
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")\n",
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")\n",
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"\"\"\"\n",
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"\"\"\"\n",
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"\n",
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"\n",
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"\n",
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"count_affected = kinetica_llm.kdbc.execute(sql)\n",
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"def _check_error(response: dict) -> None:\n",
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"count_affected"
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" status = response[\"status_info\"][\"status\"]\n",
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" if status != \"OK\":\n",
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" message = response[\"status_info\"][\"message\"]\n",
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" raise GPUdbException(\"[%s]: %s\" % (status, message))\n",
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"\n",
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"\n",
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"response = kinetica_llm.kdbc.execute_sql(sql)\n",
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"_check_error(response)\n",
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"response[\"status_info\"]"
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]
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]
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},
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"text": [
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"text": [
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"================================\u001b[1m System Message \u001b[0m================================\n",
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"================================\u001b[1m System Message \u001b[0m================================\n",
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"\n",
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"\n",
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"CREATE TABLE demo.test_profiles AS\n",
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"CREATE TABLE demo.user_profiles AS\n",
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"(\n",
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"(\n",
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" username VARCHAR (32) NOT NULL,\n",
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" username VARCHAR (32) NOT NULL,\n",
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" name VARCHAR (32) NOT NULL,\n",
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" name VARCHAR (32) NOT NULL,\n",
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" sex VARCHAR (1) NOT NULL,\n",
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" sex VARCHAR (2) NOT NULL,\n",
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" address VARCHAR (64) NOT NULL,\n",
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" address VARCHAR (64) NOT NULL,\n",
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" mail VARCHAR (32) NOT NULL,\n",
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" mail VARCHAR (32) NOT NULL,\n",
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" birthdate TIMESTAMP NOT NULL\n",
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" birthdate TIMESTAMP NOT NULL\n",
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");\n",
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");\n",
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"COMMENT ON TABLE demo.test_profiles IS 'Contains user profiles.';\n",
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"COMMENT ON TABLE demo.user_profiles IS 'Contains user profiles.';\n",
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"\n",
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"\n",
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"================================\u001b[1m Human Message \u001b[0m=================================\n",
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"================================\u001b[1m Human Message \u001b[0m=================================\n",
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"\n",
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"\n",
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"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
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"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
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"\n",
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"\n",
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"select count(1) as num_users\n",
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"select count(1) as num_users\n",
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" from demo.test_profiles\n",
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" from demo.user_profiles\n",
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" where sex = 'M';\n",
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" where sex = 'M';\n",
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"\n",
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"\n",
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"================================\u001b[1m Human Message \u001b[0m=================================\n",
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"================================\u001b[1m Human Message \u001b[0m=================================\n",
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"output_type": "stream",
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"output_type": "stream",
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"text": [
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"text": [
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"SQL: SELECT username, name\n",
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"SQL: SELECT username, name\n",
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" FROM demo.test_profiles\n",
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" FROM demo.user_profiles\n",
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" WHERE sex = 'F'\n",
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" WHERE sex = 'F'\n",
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" ORDER BY username;\n"
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" ORDER BY username;\n",
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},
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{
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"data": {
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"text/html": [
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"<style scoped>\n",
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" vertical-align: middle;\n",
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||||||
" }\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>username</th>\n",
|
|
||||||
" <th>name</th>\n",
|
|
||||||
" </tr>\n",
|
|
||||||
" </thead>\n",
|
|
||||||
" <tbody>\n",
|
|
||||||
" <tr>\n",
|
|
||||||
" <th>0</th>\n",
|
|
||||||
" <td>alexander40</td>\n",
|
|
||||||
" <td>Tina Ramirez</td>\n",
|
|
||||||
" </tr>\n",
|
|
||||||
" <tr>\n",
|
|
||||||
" <th>1</th>\n",
|
|
||||||
" <td>bburton</td>\n",
|
|
||||||
" <td>Paula Kaiser</td>\n",
|
|
||||||
" </tr>\n",
|
|
||||||
" <tr>\n",
|
|
||||||
" <th>2</th>\n",
|
|
||||||
" <td>brian12</td>\n",
|
|
||||||
" <td>Stefanie Williams</td>\n",
|
|
||||||
" </tr>\n",
|
|
||||||
" <tr>\n",
|
|
||||||
" <th>3</th>\n",
|
|
||||||
" <td>brownanna</td>\n",
|
|
||||||
" <td>Jennifer Rowe</td>\n",
|
|
||||||
" </tr>\n",
|
|
||||||
" <tr>\n",
|
|
||||||
" <th>4</th>\n",
|
|
||||||
" <td>carl19</td>\n",
|
|
||||||
" <td>Amanda Potts</td>\n",
|
|
||||||
" </tr>\n",
|
|
||||||
" </tbody>\n",
|
|
||||||
"</table>\n",
|
|
||||||
"</div>"
|
|
||||||
],
|
|
||||||
"text/plain": [
|
|
||||||
" username name\n",
|
" username name\n",
|
||||||
"0 alexander40 Tina Ramirez\n",
|
"0 alexander40 Tina Ramirez\n",
|
||||||
"1 bburton Paula Kaiser\n",
|
"1 bburton Paula Kaiser\n",
|
||||||
"2 brian12 Stefanie Williams\n",
|
"2 brian12 Stefanie Williams\n",
|
||||||
"3 brownanna Jennifer Rowe\n",
|
"3 brownanna Jennifer Rowe\n",
|
||||||
"4 carl19 Amanda Potts"
|
"4 carl19 Amanda Potts\n"
|
||||||
]
|
]
|
||||||
},
|
|
||||||
"execution_count": 7,
|
|
||||||
"metadata": {},
|
|
||||||
"output_type": "execute_result"
|
|
||||||
}
|
}
|
||||||
],
|
],
|
||||||
"source": [
|
"source": [
|
||||||
@ -626,7 +384,7 @@
|
|||||||
")\n",
|
")\n",
|
||||||
"\n",
|
"\n",
|
||||||
"print(f\"SQL: {response.sql}\")\n",
|
"print(f\"SQL: {response.sql}\")\n",
|
||||||
"response.dataframe.head()"
|
"print(response.dataframe.head())"
|
||||||
]
|
]
|
||||||
}
|
}
|
||||||
],
|
],
|
||||||
@ -646,7 +404,7 @@
|
|||||||
"name": "python",
|
"name": "python",
|
||||||
"nbconvert_exporter": "python",
|
"nbconvert_exporter": "python",
|
||||||
"pygments_lexer": "ipython3",
|
"pygments_lexer": "ipython3",
|
||||||
"version": "3.11.4"
|
"version": "3.8.19"
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
"nbformat": 4,
|
"nbformat": 4,
|
||||||
|
|||||||
Loading…
Reference in New Issue
Block a user