From 252fff3b282442ebc1472e63ded679604eedd823 Mon Sep 17 00:00:00 2001
From: Zain Hoda <7146154+zainhoda@users.noreply.github.com>
Date: Sat, 29 Jul 2023 17:58:06 -0400
Subject: [PATCH] notebooks
---
docs/notebooks/vn-ask.md | 179 ++++++--
docs/notebooks/vn-ask_files/vn-ask_10_2.png | Bin 0 -> 125336 bytes
docs/notebooks/vn-ask_files/vn-ask_11_2.png | Bin 0 -> 78743 bytes
docs/notebooks/vn-ask_files/vn-ask_12_2.png | Bin 0 -> 142409 bytes
docs/notebooks/vn-train.md | 266 ++++++++++++
mkdocs.yml | 6 +-
notebooks/vn-train.ipynb | 452 +++++++++++++++++++-
src/vanna/__init__.py | 2 +-
8 files changed, 855 insertions(+), 50 deletions(-)
create mode 100644 docs/notebooks/vn-ask_files/vn-ask_10_2.png
create mode 100644 docs/notebooks/vn-ask_files/vn-ask_11_2.png
create mode 100644 docs/notebooks/vn-ask_files/vn-ask_12_2.png
diff --git a/docs/notebooks/vn-ask.md b/docs/notebooks/vn-ask.md
index 1249c16d..f6f4bd90 100644
--- a/docs/notebooks/vn-ask.md
+++ b/docs/notebooks/vn-ask.md
@@ -1,10 +1,10 @@
-
+
-This notebook will help you unleash the full potential of AI-powered data analysis at your organization. We'll go through how to "bulk train" Vanna and generate SQL, tables, charts, and explanations, all with minimal code and effort. For more about Vanna, see our [intro blog post](https://medium.com/vanna-ai/intro-to-vanna-a-python-based-ai-sql-co-pilot-218c25b19c6a).
+The following notebook goes through the process of asking questions from your data using Vanna AI. Here we use a demo model that is pre-trained on the [TPC-H dataset](https://docs.snowflake.com/en/user-guide/sample-data-tpch.html) that is available in Snowflake.
-[](https://colab.research.google.com/github/vanna-ai/vanna-py/blob/main/notebooks/vn-full.ipynb)
+[](https://colab.research.google.com/github/vanna-ai/vanna-py/blob/main/notebooks/vn-ask.ipynb)
-[](https://github.com/vanna-ai/vanna-py/blob/main/notebooks/vn-full.ipynb)
+[](https://github.com/vanna-ai/vanna-py/blob/main/notebooks/vn-ask.ipynb)
# Install Vanna
First we install Vanna from [PyPI](https://pypi.org/project/vanna/) and import it.
@@ -20,7 +20,6 @@ Here, we'll also install the Snowflake connector. If you're using a different da
```python
import vanna as vn
import snowflake.connector
-import pandas as pd
```
# Login
@@ -37,7 +36,7 @@ You need to choose a globally unique model name. Try using your company name or
```python
-vn.set_model('my-model') # Enter your dataset name here. This is a globally unique identifier for your dataset.
+vn.set_model('tpc') # Enter your model name here. This is a globally unique identifier for your model.
```
# Set Database Connection
@@ -64,20 +63,105 @@ vn.ask("What are the top 10 customers by sales?")
GROUP BY customer_name
ORDER BY total_sales desc limit 10;
-
- AI-generated follow-up questions:
- What are the countries of the top 10 customers by sales?
- How many orders did each of the top 10 customers place?
- What is the average sales amount per customer in the top 10?
- Can you provide a breakdown of the sales by country for the top 10 customers?
- Who are the top 10 customers in terms of returned parts gross value?
- What are the total sales for each customer in the top 3?
- Can you provide a breakdown of the sales by region for the top customers?
- How many customers are there in each country?
- What is the total revenue for the top 5 countries?
- Can you provide a breakdown of the sales by customer for the top 5 countries?
+
+
+
+
+
+ |
+ CUSTOMER_NAME |
+ TOTAL_SALES |
+
+
+
+
+ | 0 |
+ Customer#000143500 |
+ 6757566.0218 |
+
+
+ | 1 |
+ Customer#000095257 |
+ 6294115.3340 |
+
+
+ | 2 |
+ Customer#000087115 |
+ 6184649.5176 |
+
+
+ | 3 |
+ Customer#000131113 |
+ 6080943.8305 |
+
+
+ | 4 |
+ Customer#000134380 |
+ 6075141.9635 |
+
+
+ | 5 |
+ Customer#000103834 |
+ 6059770.3232 |
+
+
+ | 6 |
+ Customer#000069682 |
+ 6057779.0348 |
+
+
+ | 7 |
+ Customer#000102022 |
+ 6039653.6335 |
+
+
+ | 8 |
+ Customer#000098587 |
+ 6027021.5855 |
+
+
+ | 9 |
+ Customer#000064660 |
+ 5905659.6159 |
+
+
+
+