Sold by: MphasisÂ
Deployed on AWS
It is a Generative AI (LLM) based offering which can generate SQL query given a table schema and meta data and validate it through a dry run
Overview
The solution uses Generative AI to generate complex SQL queries leveraging bedrock claude(LLM) modelgiven a question prompt. The solution also validates the generated queries by testing them with sample data to ensure a smooth run without any errors. The solution requires only two input files containing questions in the English language and a data schema with metadata in JSON format. The output file contains the SQL queries perfectly ready to run. If the asked question is too complex the GenAI-based solution also suggests changes that get generated along with the query.
The offering requires an AWS bedrock anthropic Claude Instant model subscription.
Highlights
- The solution can be useful to analyze the multi-tabular data without giving the actual data to the LLM. It generates complex SQL queries given appropriate prompts on one table schema at a time and up to 4 questions in a single inference. It also validates the queries for a smooth run and returns the error or warning if any.
- It can be used for data analysis tasks, to extract information from tabular data, and does not require any expertise in SQL or GenAI. The users required only the AWS credentials of an account that has an LLM (bedrock anthropic-claude-instant-v1) model subscription.
- Mphasis DeepInsights is a cloud-based cognitive computing platform that offers data extraction & predictive analytics capabilities. Need customized Machine Learning and Deep Learning solutions? Get in touch!
Details
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Delivery method
Latest version
Deployed on AWS
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost |
|---|---|---|
ml.m5.large Inference (Batch) Recommended | Model inference on the ml.m5.large instance type, batch mode | $5.00/host/hour |
ml.m4.xlarge Inference (Batch) | Model inference on the ml.m4.xlarge instance type, batch mode | $5.00/host/hour |
inference.count.m.i.c Inference Pricing | inference.count.m.i.c Inference Pricing | $3.00/request |
Vendor refund policy
Currently, we do not support refunds, but you can cancel your subscription to the service at any time.
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
first version
Additional details
Inputs
- Summary
Usage Methodology for the algorithm:
- The input must be 'Input.zip' file.
- The zip file should contain three files 'credentials', 'input-question' and 'input' in .json format.
- The credentials file includes the aws access keys with region of the account which has a subscription of anthripic Claude Instant bedrock model.
- Name of the folder inside the zip file should be “input” which is case-sensitive
- check the instructions and sample endpoint in the sample jupyter file provided.
- Limitations for input type
- cant not input more than 4 questions at time for inferencing.
- Input MIME type
- application/zip, text/plain
https://github.com/Mphasis-ML-Marketplace/Text-to-SQL-using-LLM/blob/main/input.zip
https://github.com/Mphasis-ML-Marketplace/Text-to-SQL-using-LLM/blob/main/input.zip
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