Building an Gen AI SQL Assistant from Scratch with Vanna LLM: Training and Querying Your Database

Welcome to an exciting session where we dive deep into building your very own SQL AI assistant from scratch using Vanna LLM. Join us as we explore the process of training and querying your database with ease and efficiency.

_*In this session, we'll cover the following key points:*_

🛠️ *Introduction to Vanna LLM:*
Understand the power of Vanna , a Python-based AISQL copilot designed to automate the generation of complex SQL queries within seconds.
Learn how Vanna excels in SQL writing compared to other tools by tailoring a dedicated model to your dataset.

🛠️ *Understanding Vanna LLM Workflow:*
Explore the two-step process of training a RAG model on your data and querying it to generate SQL statements.
Discover how Vanna uses vector storage to store embeddings related to database information and generate queries.

🛠️ *Training and Querying with Vanna LLM:*
Learn how to train Vanna LLM models with DDL statements and documentation to optimize query generation.
Explore examples of querying the database using prompts and examining the SQL queries and data frames generated.

🛠️ *Hands-On Demonstration:*
Follow along as we demonstrate connecting Vanna to SQLite and SQL Server Management Studio. Explore techniques for reading tables, loading schemas, and training the Vanna model with sample queries.

🛠️ *Generating Queries and Visualizations:*
Discover how Vanna can generate SQL queries for specific questions and visualize query results using Plotly charts. Learn how to save SQL scripts and Plotly code for future use and analysis.

🛠️ *Advanced Querying Techniques:*
Explore advanced querying techniques such as performing summary statistics and retrieving data based on specific criteria.
Learn how to read datasets into Pandas data frames for further analysis and manipulation.

🛠️ *Best Practices and Conclusion:*
Gain insights into best practices for training Vanna LLM models based on your database and table structures.

🛠️ *Demystifying SQL:* A Step-by-Step Guide to Crafting an AI SQL Assistant with Vanna LLM.

Empower Your Database Skills: Dive into Vanna LLM for SQL Assistance
Unleash the Potential of Your Database: Creating an AI SQL Assistant from Scratch with Vanna LLM

Get ready to unlock the full potential of SQL automation with Vanna LLM. Join us on this journey to master AI-driven SQL assistance and streamline your database querying process. Don't miss out—start building your AI SQL assistant today!

*Explore the Power of Vanna LLM:*
1. Building an AI SQL Assistant with Vanna LLM
2. Unlocking SQL Magic with Vanna LLM
3. Mastering SQL Queries with Vanna LLM
4. Simplify SQL Complexity with Vanna LLM

*Unlocking the Potential:*
➡️ Training an AI SQL Assistant with Vanna LLM
➡️ Boost Your SQL Skills with Vanna LLM
➡️ Transforming Data Interaction with Vanna LLM
➡️ Demystifying SQL with Vanna LLM

*Empower Your Database Skills:*
➡️ Empower Your Database Skills with Vanna LLM
➡️ Unleashing Database Potential with Vanna LLM

*Embark on Your SQL Journey:*
➡️ Building an AI SQL Assistant from Scratch with Vanna LLM: Training and Querying Your Database
➡️ Unlocking SQL Magic: Developing an AI SQL Assistant with Vanna LLM
➡️ Master SQL Queries Effortlessly: Creating an AI SQL Assistant Using Vanna LLM
➡️ Simplify SQL Complexity: Harnessing the Power of Vanna LLM for SQL Assistance

*From Data to Insights:*
➡️ From Data to Queries: How to Train an AI SQL Assistant with Vanna LLM
➡️ Boost Your SQL Skills: Exploring Vanna LLM for Automated Query Writing
➡️ Transforming Data Interaction: Building a Custom SQL Assistant with Vanna LLM

Don't forget to like, share, and subscribe for more insightful tutorials on data analysis and Python programming!

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[kenchang]

Thank you very much for this helpful video. I find it interesting that your vn.ask() questions always reference the dbo from your SQL db and given that you only had trained on one table was that necessary? Also I was hoping, that if I had trained multiple tables with multiple complex SQL queries and their accompanying questing, that Vanna would be able to infer what tables and attributes to use based on the question my user is asking. Is that asking too much of Vanna and the LLM I'm using?

[KarthikBhat-jr]

Is it compulsory to provide the data base name in the question ? Some times we might not know the database name hence

[BinFangRE]

Please help to answer my question. At 4:30, you mentioned API key. Is it API key of LLM(OpenAI)? or it is API key of Vanna?

[himanisingh]

hi I have tried your steps. I am getting below error while running vn.train(plan = plan)

SSLError: HTTPSConnectionPool(host='ask.vanna.ai', port=443): Max retries exceeded with url: /rpc (Caused by SSLError(SSLCertVerificationError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self-signed certificate in certificate chain (_ssl.c:1006)')))

[KarthikBhat-jr]

Is it compulsory to provide the data base name in the question ? Some times we might not know the database name hence

[KarthikBhat-jr]

Is it compulsory to provide the data base name in the question ? Some times we might not know the database name in pool of many