https://github.com/hk-kumawat/aura-smart-assistant
🤖 Aura: An AI-powered assistant that provides rapid, intuitive, and personalized responses. It uses advanced sentiment analysis and Groq for efficient conversation, offering instant replies for smooth user interaction. 💬
https://github.com/hk-kumawat/aura-smart-assistant
ai-assistant chatbot conversational-ai groq-api langchain machine-learning nlp python real-time-interaction sentiment-analysis streamlit
Last synced: about 2 months ago
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🤖 Aura: An AI-powered assistant that provides rapid, intuitive, and personalized responses. It uses advanced sentiment analysis and Groq for efficient conversation, offering instant replies for smooth user interaction. 💬
- Host: GitHub
- URL: https://github.com/hk-kumawat/aura-smart-assistant
- Owner: hk-kumawat
- License: mit
- Created: 2024-11-10T20:38:57.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2025-02-14T20:58:46.000Z (3 months ago)
- Last Synced: 2025-02-14T21:33:16.862Z (3 months ago)
- Topics: ai-assistant, chatbot, conversational-ai, groq-api, langchain, machine-learning, nlp, python, real-time-interaction, sentiment-analysis, streamlit
- Language: Python
- Homepage: https://ask-aura.streamlit.app/
- Size: 73.2 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# **Aura Smart Assistant 🤖**
## Overview
**Aura Smart Assistant** is an AI-powered conversational assistant designed to engage in meaningful, context-aware interactions with users. Built using **LangChain**, **VaderSentiment**, and **GroQ**, Aura can respond to text-based queries and provide insightful answers in real-time.
Whether you're seeking **quick information**, **exploring ideas**, or having a **casual chat**, **Aura** understands and generates **context-aware** responses tailored to your needs. It uses **sentiment analysis** for emotionally intelligent replies and leverages **GroQ's powerful backend** for fast, reliable, and rich responses.
## Live Demo
Explore Aura in action! 👉🏻 [](https://ask-aura.streamlit.app/)
_Aura, your friendly assistant, is here to chat and answer your questions! 👇🏻_
## Learning Journey 🗺️
I developed Aura to merge my passion for conversational AI with my desire to create highly responsive applications. Here’s a snapshot of my journey:
- **Inspiration:**
Inspired by the need for smarter, faster AI assistants, I wanted to create an assistant that not only responds accurately but also adapts its tone based on your sentiment.
- **Why I Made It:**
Aura was built to provide instant answers with a personalized touch. By integrating Groq Chat with LangChain and using sentiment analysis, I aimed to deliver fast responses that feel both human and efficient.
- **Challenges Faced:**
- **API & Environment Management:** Handling API keys securely with Streamlit’s secrets management and dotenv.
- **Conversational Memory:** Implementing session-based conversation history for continuous dialogue.
- **Dynamic UI:** Creating an engaging UI with animations and custom CSS for a smooth chat experience.
- **What I Learned:**
- Mastery of **Streamlit** for interactive web apps.
- Leveraging **LangChain** and **Groq Chat** for building conversational agents.
- Integrating sentiment analysis using **VADER** to tailor responses.
- Best practices for session management and responsive design.
Every step of this project has enriched my understanding of AI-powered conversations and reinforced my commitment to creating user-friendly solutions.
## Table of Contents
1. [Features](#features)
2. [How It Works](#how-it-works)
3. [Installation](#installation)
4. [Usage](#usage)
5. [Technologies Used](#technologies-used)
6. [Results](#results)
7. [Directory Structure](#directory-structure)
8. [Future Enhancements](#future-enhancements)
9. [Contributing](#contributing)
10. [License](#license)
11. [Contact](#contact)
## Features🌟
- **Context-Aware Conversations**:
Responds to a wide range of questions with personalized, instant answers.
- **Sentiment Analysis**:
Analyzes the sentiment of user inputs using **VaderSentiment** to provide tone-appropriate responses.
- **Real-time Responses**:
Powered by **GroQ API**, ensuring a fast response time.
- **Streamlit Interface**:
Interactive and user-friendly interface for seamless interaction with Aura.
- **Temporary Memory**:
Remembers user inputs (such as name or preferences) temporarily during a session, so Aura can provide more personalized responses. Once the tab is refreshed, all memory is cleared to protect privacy.
## How It Works🧠
1. **User Input**: The user types a message or question into the chat interface.
2. **Sentiment Analysis**: The text is processed by **VaderSentiment** to detect the sentiment and adjust the tone of Aura's response accordingly.
3. **GroQ API**: The input is sent to the **GroQ API**, which handles intelligent query answering and provides a context-aware response.
4. **Response**: Aura generates an instant response, displayed to the user through the Streamlit interface.
## Installation🛠
1. **Clone the repository:**
```bash
git clone https://github.com/hk-kumawat/Aura-Smart-Assistant.git
cd Aura-Smart-Assistant
```
2. **Create & Activate a Virtual Environment (optional but recommended):**
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
3. **Install Required Packages:**
```bash
pip install -r requirements.txt
```
4. **Set Up Your API Key:**
- Create a `.env` file or use Streamlit's secrets management.
- For Streamlit, create a `.streamlit/secrets.toml` file and add:
```toml
[GROQ]
GROQ_API_KEY = "your_groq_api_key_here"
```
- Alternatively, set the environment variable as needed.
## Usage🚀
### Running the Aura Smart Assistant
Start the smart assistant with:
```bash
Streamlight run app.py
```
**Features include:**
- **Conversational Interface:** Chat with Aura by typing your questions.
- **Sentiment-Based Responses:** Aura adjusts its replies based on your emotional tone.
- **Dynamic Conversation Memory:** Enjoy continuous and coherent interactions.
## Technologies Used💻
- **Programming Language:**
- `Python`
- **Web Framework:**
- `Streamlit`
- **Conversational AI:**
- `LangChain`
- `ChatGroq` (for LLM-based chat)
- **Sentiment Analysis:**
- `VADER SentimentIntensityAnalyzer`
- **Environment Management:**
- `python-dotenv`
- **Other:**
- Standard libraries like `os`, `time`
## Results🏆
The **Aura Smart Assistant** is able to provide meaningful, real-time answers to various types of questions. It successfully understands and responds in a contextually relevant manner based on sentiment analysis and intelligent querying through the **GroQ API**.
In the example above, Aura correctly analyzes the input, adjusts its tone based on sentiment, and generates an appropriate response.
## Directory Structure📁
```plaintext
hk-kumawat-aura-smart-assistant/
├── README.md # Project documentation
├── LICENSE # License information
├── app.py # Streamlit application for Aura Smart Assistant
└── requirements.txt # List of dependencies
```
## Future Enhancements🚀
1. **Multi-turn Conversation**:
Enhance the assistant to remember the context over multiple interactions for deeper conversations.
3. **Emotionally Intelligent Responses**:
Expand sentiment analysis to detect a broader range of emotions (e.g., joy, anger, surprise).
5. **Real-world Integration**:
Integrate with external services (e.g., calendars, reminders, news, etc.) to make Aura more functional.
7. **Voice Integration**:
Enable Aura to understand and respond via voice, making it more interactive.
## Contributing🤝
Contributions make the open source community such an amazing place to learn, inspire, and create. 🙌 Any contributions you make are greatly appreciated! 😊
Have an idea to improve this project? Go ahead and fork the repo to create a pull request, or open an issue with the tag **"enhancement"**. Don't forget to give the project a star! ⭐ Thanks again! 🙏
1. **Fork** the repository.
2. **Create** a new branch:
```bash
git checkout -b feature/YourFeatureName
```
3. **Commit** your changes with a descriptive message.
4. **Push** to your branch:
```bash
git push origin feature/YourFeatureName
```
5. **Open** a Pull Request detailing your enhancements or bug fixes.
## License📝
This project is licensed under the **MIT License** — see the [LICENSE](./LICENSE) file for details.
## Contact
### 📬 Get in Touch!
Feel free to reach out for collaborations or questions:
- [](https://github.com/hk-kumawat) 💻 — Explore my projects and contributions.
- [](https://www.linkedin.com/in/harshal-kumawat/) 🌐 — Let's connect professionally.
- [](mailto:[email protected]) 📧 — Send me an email for discussions and queries.
## Thanks for chatting—enjoy your conversation with Aura! 🤖💬
> "Smart conversations start with a single question." – Anonymous