In today's fast-paced digital communication landscape, WhatsApp has become a central hub for group discussions, brainstorming sessions, and knowledge sharing. However, the transient nature of these conversations often leads to valuable insights being lost amidst the chat clutter. Enter the WhatsApp Knowledge Miner, a tool designed to extract, organize, and transform your WhatsApp group chats into a structured, searchable knowledge base.
Project Overview
The WhatsApp Knowledge Miner is an open-source application that bridges the gap between unstructured WhatsApp group chats and structured knowledge management. By leveraging the WhatsApp Business API and advanced natural language processing (NLP) techniques, the application captures messages, analyzes their content, and converts them into question-answer pairs that can be easily searched and referenced.
🧩 Core Components
1. WhatsApp Bridge
The WhatsApp Bridge serves as the interface between your WhatsApp account and the application. It connects to your WhatsApp account and securely stores messages in a local SQLite database.
Setup:
cd whatsapp-bridge
go run main.go
Upon running, scan the QR code displayed to log in (similar to WhatsApp Web). The application will then begin capturing messages from your WhatsApp groups.
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- Message Capture and Storage**
Captured messages are stored in a local SQLite database, ensuring that all data remains secure and accessible. This local storage approach facilitates easy retrieval and analysis of messages without relying on external servers.
*3. Message Processing Server
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The message processing server analyzes the captured messages to identify key information, such as questions and answers. Using NLP techniques, it extracts relevant content and organizes it into structured data.
*4. Streamlit Web Interface
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The Streamlit web interface provides a user-friendly platform to interact with the processed data. Users can search for specific questions and view the corresponding answers, making it easy to access valuable information from past discussions.
🔧 Technical Highlights
Go (Golang): Used for building the WhatsApp Bridge, ensuring efficient and concurrent message capturing.
SQLite: Provides a lightweight and reliable local database for storing messages.
Natural Language Processing: Employed to analyze and extract meaningful information from unstructured messages.
Streamlit: Facilitates the creation of an interactive web interface for users to search and view Q&A pairs.
🧪 Installation and Usage
Clone the Repository:
git clone https://github.com/BigAchiever/whatsapp-knowledge-miner.git
cd whatsapp-knowledge-miner
Set Up the WhatsApp Bridge:
cd whatsapp-bridge
go run main.go
Scan the QR code to log in to your WhatsApp account.
Run the Message Processing Server:
Navigate to the whatsapp-mcp-server directory and start the server to begin processing captured messages.
Launch the Streamlit Web Interface:
In the streamlit-app directory, run the following command to start the web interface:
streamlit run app.py
Access the interface through your web browser to search and view Q&A pairs.
🌟 Key Features
Seamless Integration: Effortlessly connects to your WhatsApp account to capture messages.
Automated Q&A Extraction: Utilizes NLP to automatically generate question-answer pairs from conversations.
Local Data Storage: Ensures data privacy by storing messages in a local SQLite database.
Interactive Search Interface: Provides a user-friendly web interface for searching and viewing Q&A pairs.
Open Source: Freely available for modification and enhancement.
💡 Use Cases
Team Collaboration: Easily reference past discussions and decisions made in group chats.
Knowledge Management: Organize and access valuable information shared within WhatsApp groups.
Educational Purposes: Create a repository of questions and answers for study groups or tutoring sessions.
Customer Support: Analyze customer inquiries and responses to improve support services.
🔗 Explore the Project
To delve deeper into the WhatsApp Knowledge Miner, explore the Github Repository
. Here, you'll find comprehensive documentation, installation instructions, and the complete source code.
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🧠 Conclusion
The WhatsApp Knowledge Miner exemplifies the power of combining messaging platforms with advanced data processing techniques. By transforming unstructured group chats into a searchable knowledge base, it enhances collaboration, preserves valuable information, and streamlines access to past discussions. Whether for personal use, team collaboration, or educational purposes, this tool offers a practical solution to manage and utilize the wealth of information shared within WhatsApp groups.
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