QA With Any URL

👋 Introduction 👋

Hello! I am a beginner developer who is greatly interested in the rapidly emerging field of LLMs.

This is my another basic starter project, created for the purpose of studying LLM prompting, Python and RAG for my own study.

You can revise this project your own style.

Thank you for coming by, and please keep an eye out for future updates!

🌠 OverView 🌠

This project is a simple starter project that demonstrates how you can utilize LangChain and LLM model to perform Q&A on given URL.

Also, this project is very simple and easy to build or customize it.

🚀 HOW TO START 🚀

1. Clone this repository

git clone https://github.com/MIRACLE-cowf/QA-With-URL.git

2. Move to the cloned repository

ca RAG_URL

3. Inside the RAG_URL, fill the necessary API keys in the .env file.

   • Anthropic
   • OpenAI

4. Install the required libraries

pip install -r requirements.txt 

5. Run main.py

python3 -m main

✅ Check Out My Other Project ✅

🔥 PAR(Powerful-Agent-Researcher) 🔥

This project is an Agent Assistant that aims to automatically generate high-quality documents in response to user question. It conducts its own web searches and creates documents to provide answers.

Main Features

• THLO(Think-High-Level-Outline) : It deeply 'think' and 'inner monologue' to understands user question and automatically generates high-level-outline or plan for document creation.
• Utilization of Various Information Sources : It integrates multiple search engines, including Tavily, YouTube, arXiv, and Wikipedia, to gather comprehensive and intelligent information.
• Intelligent Information Summarization and Integration : It intelligently summarizes and integrates the collected information to automatically generate documents that are not only optimized for the user's question but also contain richer and high-quality information.

If you're interested, Check it out
I'm actively seeking feedback and discussions in this project!

🔥 QA-With-Jupyter 🔥

The QA-With-Jupyter project is similarly as this QA-With-Url project.

Main Features

• You can Q&A with your own Jupyter Notebook(.ipynb) file.
• Use chat history, so that you can interact like Claude.ai

If you're interested, Check it out

🔥 A-SQL-A 🔥

This A-SQL-A project is similarly as the QA-With-Jupyter.

Main Features

• You can Q&A with your own CSV file.
• Automatically transform .csv to .db.
• Generate SQL query by LLM.

If you're interested, Check it out