AI Assistant: Advanced NLP Suite with Streamlit GUI

Project Description

AI Assistant is an advanced Natural Language Processing (NLP) suite designed to provide intelligent, context-aware responses to user queries. This project leverages cutting-edge machine learning techniques, web scraping, and the OpenAI API to deliver accurate and comprehensive answers. The system features a user-friendly Streamlit GUI, making it accessible for both technical and non-technical users.

Key Features

• Streamlit GUI: Intuitive web interface for easy interaction
• OpenAI Integration: Utilizes GPT models for advanced language understanding and generation
• Web Scraping: Fetches and processes information from various online sources
• Local Caching: Stores and retrieves previous interactions for faster responses
• Self-Learning Capability: Improves performance over time through continuous learning
• GPU Acceleration: Harnesses CUDA-enabled GPUs for enhanced processing speed
• Fact-Checking: Implements robust fact-checking mechanisms for information accuracy
• Customizable: Easily adaptable for various NLP tasks and domains

Table of Contents

• Prerequisites
• Installation
• Downloading Required Models
• Usage
• Scripts Overview
• Configuration
• Contributing
• License
• Contact

Prerequisites

• Python 3.8+
• CUDA-compatible GPU (recommended for optimal performance)
• OpenAI API key

Installation

1. Clone the repository:

   git clone https://github.com/slyfox1186/ai-assistant.git
   cd ai-assistant
   

2. Create and activate a Conda environment:

   conda create --name ai_assistant python=3.12.2
   conda activate ai_assistant
   

3. Install the required dependencies:

   pip install -r requirements.txt
   

4. Set up your OpenAI API key:

   • Create a config.py file in the project root
   • Add your API key: OPENAI_API_KEY = "your-api-key-here"

Downloading Required Models

Before running the AI Assistant, you need to download the necessary NLP models. Run the following commands:

1. Download the spaCy model:

   python -m spacy download en_core_web_trf
   

2. Download the Flair model:

   python -m flair.models.text_classification.sentiment download
   

3. Download the Hugging Face transformers models:

   python -c "from transformers import AutoTokenizer, AutoModel; AutoTokenizer.from_pretrained('sentence-transformers/all-MiniLM-L6-v2'); AutoModel.from_pretrained('sentence-transformers/all-MiniLM-L6-v2')"
   

These commands will download and cache the required models for NER processing, sentiment analysis, and similarity checking.

Usage

To launch the AI Assistant with the Streamlit GUI, run:

streamlit run main.py

This will start the Streamlit server and open the AI Assistant interface in your default web browser. By default, it will run on http://localhost:8501.

If you want to specify a different port or host, you can use:

streamlit run main.py --server.port 8080 --server.address 0.0.0.0

Using the Interface

1. API Key: Enter your OpenAI API key in the sidebar (if not set in config.py)
2. Query Input: Type your question in the chat input at the bottom of the page
3. Response: The AI Assistant will process your query and display the answer
4. Settings: Use the sidebar to customize behavior:
   • Toggle between using OpenAI API or internet search
   • Enable/disable local cache usage
   • Adjust model training parameters

Scripts Overview

• main.py: The core script that launches the Streamlit interface and orchestrates the entire process
• openai_handler.py: Manages interactions with the OpenAI API
• web_scraper.py: Handles web scraping for additional information
• data_manager.py: Manages data storage and retrieval, including local caching
• similarity_checker.py: Compares queries to find similar previous interactions
• model_trainer.py: Handles the training and updating of local models
• ner_processor.py: Processes named entities in the text

Configuration

Adjust the following files to customize the AI Assistant:

• config.py: Set API keys, model parameters, and other global settings
• requirements.txt: Manage project dependencies

Contributing

We welcome contributions to the AI Assistant project! Here's how you can help:

1. Fork the repository
2. Create a new branch (git checkout -b feature/AmazingFeature)
3. Make your changes
4. Commit your changes (git commit -m 'Add some AmazingFeature')
5. Push to the branch (git push origin feature/AmazingFeature)
6. Open a Pull Request

Please ensure your code adheres to the project's coding standards and includes appropriate tests.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

Project Link: https://github.com/slyfox1186/ai-assistant

For support or queries, please open an issue in the GitHub repository or contact slyfox1186.

We hope you find the AI Assistant useful for your NLP tasks. Your feedback and contributions are highly app