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DeepKnowledge.net is an advanced Q&A chatbot leveraging Retrieval-Augmented Generation (RAG) to deliver precise, source-grounded responses. It integrates DeepSeek-V3 for chat interactions and OpenAI's text-embedding-ada-002 for embeddings, utilizing Streamlit for a seamless web interface.

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ErnestAroozoo/DeepKnowledge.net

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DeepKnowledge.net

Python License: MIT

An intelligent Q&A system powered by Retrieval-Augmented Generation (RAG).

Demo Screenshot

Project Overview

DeepKnowledge.net is an advanced chatbot that integrates large language models with your private data sources using Retrieval-Augmented Generation (RAG). This approach provides precise, source-grounded answers while ensuring data privacy.

Key Features

  • Multi-source Integration: Seamlessly process content from websites and documents (PDF/DOCX).
  • Source Citation: Offers transparent references to original data sources for every response.
  • Relevance Scoring: Efficiently ranks information based on query relevance.
  • Conversational Memory: Supports context-aware follow-up questions to maintain dialogue continuity.

Technical Specifications

  • Language Models: Utilizes DeepSeek-V3 for chat interactions and OpenAI's text-embedding-ada-002 for embeddings.
  • RAG Framework: Powered by LlamaIndex.
  • Vector Store: Employs LlamaIndex In-Memory Vector Store for efficient data retrieval.
  • User Interface: Built with Streamlit for a seamless web experience.

Installation Instructions

  1. Clone the repository:

    git clone https://github.com/ErnestAroozoo/DeepKnowledge.net.git
    cd DeepKnowledge.net
  2. Install necessary dependencies:

    pip install -r requirements.txt
  3. Set up environment variables:

    cp .env.example .env

Configuration

Update the .env file with your API credentials:

# OpenAI Embeddings Configuration
OPENAI_API_KEY=your-openai-key
OPENAI_API_HOST=https://api.openai.com/v1

# DeepSeek Chat Configuration
DEEPSEEK_API_KEY=your-deepseek-key
DEEPSEEK_API_HOST=https://api.deepseek.com/v1

Note: API keys can be obtained from:

Usage Guide

  1. Launch the application:

    streamlit run app.py
  2. Add data sources:

    • Websites: Input valid URLs for content parsing.
    • Documents: Upload PDF/DOCX files for text extraction.
  3. Engage with the chatbot by:

    • Asking natural language queries.
    • Following up with questions using chat history.
    • Requesting source verification for responses.

Supported Data Sources

Type Formats Processing Method
Web Content URLs Web page parsing
Documents PDF, DOCX Text extraction

About

DeepKnowledge.net is an advanced Q&A chatbot leveraging Retrieval-Augmented Generation (RAG) to deliver precise, source-grounded responses. It integrates DeepSeek-V3 for chat interactions and OpenAI's text-embedding-ada-002 for embeddings, utilizing Streamlit for a seamless web interface.

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