Solace - AI-Powered Chatbot

Solace is an AI-powered chatbot designed to provide users with personalized and engaging conversations. Using a combination of advanced NLP models like Google's Gemini, emotion analysis tools (NRCLex), and speech recognition, Solace offers a seamless conversational experience with context-aware and emotion-sensitive responses. It supports both text and voice-based interactions and is fully dockerized and deployable for scalability and reliability.

Features

• Contextual Conversations: Powered by Google Gemini for intelligent response generation.
• Emotion-Aware: Detects emotions through NRCLex and adapts responses accordingly.
• Voice Interaction: Supports Speech-to-Text and Speech Recognition for voice-based interactions.
• Cloud Deployment: Dockerized and hosted on AWS for scalability and performance.
• Easy Setup: Quick setup using Docker, Python dependencies, and environment variables.

Installation

Prerequisites

Before running the project, make sure you have:

• Docker installed and running.
• Python 3.10 installed.

Local Setup

Follow the steps below to set up Solace on your local machine:

1. Clone the Repository

git clone https://github.com/dipayandas24/Solace  
cd Solace  

2. Create a Virtual Environment (optional but recommended)

On Linux/macOS

python3 -m venv venv  
source venv/bin/activate 

On Windows (Run in PowerShell)

python -m venv venv  
venv\Scripts\activate  

3. Install Dependencies

pip install -r requirements.txt  

Run the Application

1. Start the Streamlit application

streamlit run Home.py  

Access the Chatbot

Visit http://localhost:8501 to interact with the chatbot.

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Docker Setup

If you want to run the application using Docker, follow the steps below:

1. Clone the Repository

git clone https://github.com/dipayandas24/Solace  
cd Solace 

2. Build the Docker Image:

docker-compose build --no-cache

3. Run the containers:

docker-compose up --build

4. Access the app:

The app will be available at http://localhost:8501.

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NLTK Corpus Setup (for Docker)

NRCLex and TextBlob require several NLTK corpora. These are automatically downloaded at runtime, but if you encounter errors, ensure your entry files include:

import nltk
nltk.download('punkt', quiet=True)
nltk.download('averaged_perceptron_tagger', quiet=True)
nltk.download('brown', quiet=True)
nltk.download('wordnet', quiet=True)

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Tech Stack

1. Streamlit & HTML/CSS: Provides a fast and interactive web UI for chatbot interactions. Custom HTML/CSS ensures a polished user experience.

2. Google Gemini (Generative AI): Utilized for powerful NLP tasks like response generation and understanding. Configure GEMINI_API_KEY in your environment and use the google-generativeai Python client.

3. NRCLex: Detects emotions from user input to enable personalized, emotion-sensitive responses from the chatbot.

4. Speech-to-Text & Speech Recognition: Allows users to interact with the chatbot using voice commands, making it more accessible and engaging.

5. Google Gemini Model: A highly capable generative model for natural language processing, enabling context-aware, dynamic conversations with users.

6. PostgreSQL & SQLAlchemy: Used for structured storage of user data and conversation history, ensuring quick retrieval and consistency.

7. Docker: Docker ensures easy deployment and scalability.

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Contribution Guidelines

We welcome contributions to Solace! Here’s how you can contribute:

1. Fork the repository and clone it locally.

2. Create a new branch for your feature or bugfix:

   bash git checkout -b feature/your-feature-name

3. Write tests for any new functionality or fixes.

4. Ensure code follows PEP 8 guidelines. Use black for code formatting and flake8 for linting.

5. Commit changes with descriptive messages:

   bash git commit -m "feat: add new feature"

6. Push changes to your fork:

   bash git push origin feature/your-feature-name

7. Open a Pull Request to the main repository.

8. Review process: Once your PR is reviewed, be ready to make necessary changes and improvements based on feedback.

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