Added getting started tutorial to README. Added jupyter notebook download to tutorial.

Author: avthars

README.md

@@ -4,12 +4,16 @@
 
 PostgreSQL++ for AI Applications.
 
-- [Documentation and
-  Tutorials](https://timescale.github.io/python-vector/).
 - [Signup for Timescale
   Vector](https://console.cloud.timescale.com/signup?utm_campaign=vectorlaunch&utm_source=github&utm_medium=direct):
   Get 90 days free to try Timescale Vector on the Timescale cloud data
   platform. There is no self-managed version at this time.
+- [Documentation](https://timescale.github.io/python-vector/): Learn the
+  key features of Timescale Vector and how to use them.
+- [Getting Started
+  Tutorial](https://timescale.github.io/python-vector/tsv_python_getting_started_tutorial.html):
+  Learn how to use Timescale Vector for semantic search on a real world
+  dataset.
 - [Learn
   more](https://www.timescale.com/blog/how-we-made-postgresql-the-best-vector-database/?utm_campaign=vectorlaunch&utm_source=github&utm_medium=direct):
   Learn more about Timescale Vector, how it works and why we built it.

nbs/index.ipynb

@@ -15,8 +15,9 @@
    "source": [
     "PostgreSQL++ for AI Applications.\n",
     "\n",
-    "- [Documentation and Tutorials](https://timescale.github.io/python-vector/).\n",
     "- [Signup for Timescale Vector](https://console.cloud.timescale.com/signup?utm_campaign=vectorlaunch&utm_source=github&utm_medium=direct): Get 90 days free to try Timescale Vector on the Timescale cloud data platform. There is no self-managed version at this time.\n",
+    "- [Documentation](https://timescale.github.io/python-vector/): Learn the key features of Timescale Vector and how to use them.\n",
+    "- [Getting Started Tutorial](https://timescale.github.io/python-vector/tsv_python_getting_started_tutorial.html): Learn how to use Timescale Vector for semantic search on a real world dataset.\n",
     "- [Learn more](https://www.timescale.com/blog/how-we-made-postgresql-the-best-vector-database/?utm_campaign=vectorlaunch&utm_source=github&utm_medium=direct): Learn more about Timescale Vector, how it works and why we built it."
    ]
   },

nbs/tsv_python_getting_started_tutorial.ipynb

@@ -15,6 +15,8 @@
    "source": [
     "This notebook shows how to use the PostgreSQL vector database `Timescale Vector` via the [Timescale Vector python client library](https://github.com/timescale/python-vector). You'll learn how to use TimescaleVector for (1) semantic search, (2) time-based vector search, (3) and how to create indexes to speed up queries.\n",
     "\n",
+    "Follow along by downloading the [Jupyter notebook version of this tutorial here](https://github.com/timescale/python-vector/blob/main/nbs/tsv_python_getting_started_tutorial.ipynb).\n",
+    "\n",
     "Sample dataset: We'll analyze a gitlog dataset (git commit messages) and use the vector embeddings of the commit messages to find relevant commit messages to a given query question. Each git commit entry has a timestamp associated with it, as well as natural language message and other metadata (e.g author, commit hash etc). \n",
     "\n",
     "## What is Timescale Vector?\n",
@@ -49,6 +51,14 @@
     "## 0. Setup"
    ]
   },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Download the [Jupyter notebook version of this tutorial](https://github.com/timescale/python-vector/blob/main/nbs/tsv_python_getting_started_tutorial.ipynb)."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,