Speak Your Queries: How Langchain Lets You Chat with Your Database

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  • langchain

    Discontinued ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain] (by hwchase17)

  • Imagine effortlessly conversing with your database as if it were a close friend, asking questions and receiving instant, accurate responses. Welcome to the world of Langchain, a groundbreaking package that harnesses the power of LLMs(Large Language Models) to redefine the way you interact with your databases. In this tutorial, we'll explore how to seamlessly connect to a PostgreSQL database and start chatting with it using Langchain. Say goodbye to complex queries and embrace the future of database management – let's dive into the realm of conversational AI and revolutionize your data-driven tasks today!

  • langchain_todo

  • I have included all the code for this project on my github. Lets start by installing all the required packages first. Install langchain, openai, psycopg2 and python-environ with pip:

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

    InfluxDB logo
  • PostgreSQL

    Mirror of the official PostgreSQL GIT repository. Note that this is just a *mirror* - we don't work with pull requests on github. To contribute, please see https://wiki.postgresql.org/wiki/Submitting_a_Patch

  • We are going to be using a postgresql database in this tutorial hence we're installing psycopg2. I am already assuming that you have postgresql installed on your device and have an open ai account. We are going to use the python-environ module to manage the API keys and database password.

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