text2sql | Convert natural language query to appropriate SQL | SQL Database library

by yashbonde Python Version: 0.1.1 License: MIT

X-Ray Key Features Code Snippets(3)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | text2sql Summary

text2sql is a Python library typically used in Database, SQL Database applications. text2sql has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install text2sql' or download it from GitHub, PyPI.

How many times have you pulled your hair apart writing a SQL query, now use natural language to convert to appropriate SQL and save your precious hair. Though this can be used as a standalone package, I highly recommend that you use streamlit to play with the model interactively, to run it interactively.

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Quality

Security

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Support

text2sql has a low active ecosystem.

It has 39 star(s) with 9 fork(s). There are 4 watchers for this library.

It had no major release in the last 12 months.

There are 1 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of text2sql is 0.1.1

Quality

text2sql has 0 bugs and 0 code smells.

Security

text2sql has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

text2sql code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

text2sql is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

text2sql releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed text2sql and discovered the below as its top functions. This is intended to give you an instant insight into text2sql implemented functionality, and help decide if they suit your requirements.

Train the model
Evaluate a model
Configure optimizers
The encoder function
Return the SQL output
Computes the top k logits of the given logits
Save the checkpoint
Compute forward attention
Layer attention
Split the input tensors
Merge the head of x
Get a random database
Convert a database to a networkx graph
Convert db to networkx graph
Formats the SQL

Get all kandi verified functions for this library.

text2sql Key Features

No Key Features are available at this moment for text2sql.

text2sql Examples and Code Snippets

Text2SQL,Model

Python

Lines of Code : 14

License : Permissive (MIT)

Copy

[TRAIN] GS: 2568, Epoch: 5, Loss: 0.34184: 100%|██████████████████| 428/428 [05:05<00:00,  1.40it/s]
[VAL] Epoch: 5: : 46it [00:16,  2.87it/s]
Generating Samples ...
--> atsuhiro patients H 8.5canadagames expenses debatescore cinemastestlingsan

Text2SQL,Training

Python

Lines of Code : 2

License : Permissive (MIT)

Copy

python parse_to_lm.py

python train.py

Text2SQL

Python

Lines of Code : 1

License : Permissive (MIT)

Copy

streamlit run t2s.py (not updated currently)

Community Discussions

Trending Discussions on text2sql

How to deploy a Question Answering BERT Model as a chat bot on MS Teams

QUESTION

How to deploy a Question Answering BERT Model as a chat bot on MS Teams

Asked 2022-Mar-30 at 18:51

I have a Text2SQL model (EditSQL: https://github.com/ryanzhumich/editsql) which I have configured to take a sentence as input and return a SQL query as output.

Now, I want to deploy this program as a chat bot application in Microsoft Teams.

I understand there's Microsoft bot framework that enables publishing a bot and the 3 options are described here. https://docs.microsoft.com/en-us/learn/modules/choose-bot-building-tool/

However, I am not finding any of them suitable for my use case since I need to deploy a Question-Answering Bot where the Questions from users need to be sent to an external server like AWS and the response from AWS (could be an excel file) needs to be sent back to the user. Multiple questions can be the part of a conversation, so the chat client should be able to mark start and end of a conversation.

My problem:

What are the basic steps of exposing a ml model via a server so that it can be queried in production.
What are the tools that will allow me to make a client on Teams and a server for this model on AWS?

Please let me know if I should add more information on this.

Thanks

...

ANSWER

Answered 2022-Mar-30 at 18:51

As you've seen, there are a bunch of tools/approaches to creating bots in the Microsoft world, for Teams or otherwise. Underneath, these all use the Bot Framework, but you can develop directly (i.e. write code), or use a higher-level tool like Bot Framework Composer - the choice is yours depending on your own internal skills. If you want to work with code directly, here are a bunch of bot samples, in multiple languages: https://github.com/microsoft/BotBuilder-Samples/tree/main/samples . For isntance, here is an example of integrating the Microsoft QnAMaker service into your bot: https://github.com/microsoft/BotBuilder-Samples/tree/main/samples/python/49.qnamaker-all-features

Basically, if you go the development approach, your bot is just a web service. Once it receives the message, it can call out to any other service behind the scenes. That means it can receive a message, call out to an AWS service, receive the response, and send a reply to the user.

For multiple questions as part of a 'set' of chats, Bot Framework provides an idea called "dialogs" that should work for you.

Source https://stackoverflow.com/questions/71680285

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install text2sql

You can install using 'pip install text2sql' or download it from GitHub, PyPI.
You can use text2sql like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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