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Chat with Databases using RAG

Welcome to Chat with Databases using RAG, a revolutionary project that enables seamless interaction with databases using natural language inputs. This README.md file provides an overview of the project, its features, and instructions on how to use it.

Streamlit UI:

LangSmith Monitoring:

Overview

Chat with Databases using RAG leverages advanced techniques such as RAG (Retrieve, Aggregate, Generate) and few-shot learning to bridge the gap between human language and database interactions. It allows users to input queries in plain text, automatically generates corresponding SQL queries, and retrieves human-like answers from the database.

Tech Stack

The project utilizes the following technologies and libraries:

  • Langchain & Langsmith: Powerful frameworks to create and monitor AI powered applications.
  • GooglePalm & GooglePalmEmbeddings: State-of-the-art language models for enhanced comprehension.
  • ChromaDb: Provides a rich palette of database interactions.
  • FewShotPromptTemplate: Optimizes query generation with few-shot learning techniques.
  • create_sql_query_chain: Streamlines the process of generating SQL queries.
  • Streamlit: For seamless user interaction.

How it Works

  1. Input Query: Users input their query in natural language.
  2. Query Translation: The system translates the query into an SQL query using advanced language processing techniques.
  3. Database Interaction: The SQL query is executed against the database, retrieving the relevant results.
  4. Response Generation: Human-like answers are generated based on the retrieved data.
  5. Future Roadmap: Integration of memory and dynamic table selection for enhanced performance and capabilities.

Usage

To use Chat with Databases using RAG, follow these steps:

  1. Install the necessary dependencies and libraries listed in the requirements.txt file.
  2. Run the application.
  3. Input your query in natural language when prompted.
  4. The system will automatically generate an SQL query and retrieve the results from the database.
  5. Enjoy the seamless interaction between human language and database queries!

Contributions

Contributions to the project are welcome! If you have ideas for improvements, new features, or bug fixes, feel free to submit a pull request or open an issue on the GitHub repository.

License

This project is licensed under the MIT License.

Acknowledgments

Special thanks to the developers and contributors of the libraries and technologies used in this project, as well as the open-source community for their continuous support and contributions.

Contact

For inquiries or support, please contact harshnkgupta@email.com.

Stay tuned for updates and let's revolutionize the way we interact with databases! #ChatWithDatabases #RAG #TechInnovation #DataScience #AIRevolution