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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 groq-api real-time-interaction sentiment-analysis streamlit
Last synced: 13 days 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 (3 months ago)
- Default Branch: main
- Last Pushed: 2025-01-17T19:19:37.000Z (25 days ago)
- Last Synced: 2025-01-17T20:19:34.234Z (25 days ago)
- Topics: ai-assistant, groq-api, real-time-interaction, sentiment-analysis, streamlit
- Language: Python
- Homepage: https://ask-aura.streamlit.app/
- Size: 73.2 KB
- Stars: 1
- Watchers: 2
- 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!_
## 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. [Conclusion](#conclusion)
8. [Future Enhancements](#future-enhancements)
9. [License](#license)
10. [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
```
2. **Install dependencies**:
```bash
pip install -r requirements.txt
```
3. **Setup environment variables**:
- Create a `.env` file in the root directory and add the following:
```env
GROQ_API_KEY=your_groq_api_key
```
- Replace `your_groq_api_key` with your actual **GroQ API Key**.
## Usage🚀
1. **Run the Streamlit App**:
```bash
streamlit run app.py
```
2. **Interact with Aura**: Type any question or statement, and Aura will respond instantly, offering insights based on its contextual knowledge.
## Technologies Used💻
- **Programming Language**: Python
- **Libraries**:
- `streamlit` — For creating the user interface.
- `langchain` — For managing the chain of conversation and data processing.
- `vaderSentiment` — Sentiment analysis for tone detection.
- `groq` — For intelligent query answering.
- `python-dotenv` — To manage environment variables.
- **API**:
- **GroQ API** — Powers contextual and intelligent responses.
## 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.
## Conclusion📚
The **Aura Smart Assistant** project demonstrates how deep learning, natural language processing, and intelligent APIs can be combined to create a powerful and interactive virtual assistant. It showcases the use of **GroQ**, **VaderSentiment**, and **LangChain** in a real-world application, offering a practical solution for engaging, context-aware conversations.
Real-world applications of Aura include **customer support**, where it provides real-time solutions to user queries; as a **personal assistant** for task management; offering **mental health support** with emotionally intelligent conversations; serving as an **educational tool** for interactive learning; and enhancing **business productivity** by facilitating quick information retrieval and team collaboration. This makes Aura a versatile assistant for both personal and professional use.
## Future Enhancements🚀
1. **Multi-turn Conversation**: Enhance the assistant to remember the context over multiple interactions for deeper conversations.
2. **Emotionally Intelligent Responses**: Expand sentiment analysis to detect a broader range of emotions (e.g., joy, anger, surprise).
3. **Real-world Integration**: Integrate with external services (e.g., calendars, reminders, news, etc.) to make Aura more functional.
4. **Voice Integration**: Enable Aura to understand and respond via voice, making it more interactive.
## 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 exploring Aura's world! 🌍🤖 We hope you had a great time! 🎉💫**
> "An assistant's true power is in its ability to make your life easier, one conversation at a time." - Harshal Kumawat