docs: Update langchain_quick_start.ipynb (#81)

* docs: Update langchain_quick_start.ipynb Tweak into to match memory store + AlloyDB's introductions * docs: Update langchain_quick_start.ipynb changes gcs bucket names --------- Co-authored-by: Averi Kitsch <akitsch@google.com>
googleapis · Mar 6, 2024 · 5e79043 · 5e79043
1 parent caadf4d
commit 5e79043
Showing 1 changed file with 3 additions and 3 deletions.
diff --git a/samples/langchain_quick_start.ipynb b/samples/langchain_quick_start.ipynb
@@ -34,7 +34,7 @@
                 "---\n",
                 "# **Introduction**\n",
                 "\n",
-                "In this codelab you will learn how to create an interactive generative AI application with Retrieval Augmented Generation using [Cloud SQL for PostgreSQL](https://cloud.google.com/sql/docs/postgres) and [LangChain](https://www.langchain.com/). We will be creating an application grounded in a [Netflix Movie dataset](https://www.kaggle.com/datasets/shivamb/netflix-shows)."
+                "In this codelab, you'll learn how to create a powerful interactive generative AI application using Retrieval Augmented Generation powered by [Cloud SQL for PostgreSQL](https://cloud.google.com/sql/docs/postgres) and [LangChain](https://www.langchain.com/). We will be creating an application grounded in a [Netflix Movie dataset](https://www.kaggle.com/datasets/shivamb/netflix-shows), allowing you to interact with movie data in exciting new ways."
             ]
         },
         {
@@ -341,7 +341,7 @@
             "outputs": [],
             "source": [
                 "# Import the Netflix titles table using gcloud command\n",
-                "import_command_output = !gcloud sql import sql {instance_name} gs://cloud-samples-data/langchain/postgres/langchain_postgres_netflix_titles.sql --database={database_name} --quiet\n",
+                "import_command_output = !gcloud sql import sql {instance_name} gs://cloud-samples-data/langchain/cloud-sql/postgres/first_five_netflix_titles.sql --database={database_name} --quiet\n",
                 "\n",
                 "if \"Imported data\" in str(import_command_output):\n",
                 "    print(import_command_output)\n",
@@ -608,7 +608,7 @@
             "outputs": [],
             "source": [
                 "# Import the netflix titles with vector table using gcloud command\n",
-                "import_command_output = !gcloud sql import sql {instance_name} gs://cloud-samples-data/langchain/postgres/netflix_titles_vector_table.sql --database={database_name} --quiet\n",
+                "import_command_output = !gcloud sql import sql {instance_name} gs://cloud-samples-data/langchain/cloud-sql/postgres/netflix_titles_vector_table.sql --database={database_name} --quiet\n",
                 "\n",
                 "if \"Imported data\" in str(import_command_output):\n",
                 "    print(import_command_output)\n",