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+OPENAI_API_KEY="sk-*********"
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 # Smart QA
 
-Application where you can upload csv/excel or any structured data and get the following features
+Smart QA is a versatile Streamlit-based web application designed for efficient data analysis and visualization. With support for various data formats such as CSV, Excel, and JSON, this tool empowers users to extract valuable insights seamlessly.
 
 ## Features
 
-- Ask any direct question based on the document
-- get direct visualisations and summaries based on the document
-- get visualisations based on the question asked
+- **Intelligent Questioning**: Interact with your data by asking direct questions and receive insightful answers.
+- **Visual Summaries**: Instantly generate visualizations and summaries based on the document, providing a quick overview of key patterns and trends.
+- **Question-specific Visualizations**: Obtain visualizations and infographics tailored to the questions you pose, enhancing your understanding of the data.
+- **Compatibility**: Smart QA is designed to seamlessly work with both OpenAI and any self-hosted Language Model.
 
+## Demo
+
+[![Demo 1](demo/output1.mp4)](demo/output1.mp4)
+[![Visualisation Demo](demo/visualisation.mp4)](demo/visualisation.mp4)
+
+<video width="320" height="240" controls>
+  <source src="demo/sql_based.mp4" type="video/mp4">
+  Your browser does not support the video tag.
+</video>
+
+<video width="320" height="240" controls>
+  <source src="demo/visualisation.mp4" type="video/mp4">
+  Your browser does not support the video tag.
+</video>
+
+## Installation
+
+To install Smart QA, follow these steps:
+
+1. Clone the repository: `git clone https://github.com/yourusername/smart-qa.git`
+2. Navigate to the project folder: `cd smart-qa`
+3. Install dependencies: `pip install -r requirements.txt`
+4. Create a .env file similar to .env.example
+
+## Usage
+
+1. Run the application: `streamlit run app.py`
+2. Access the application at [http://localhost:8501](http://localhost:8501) in your browser.
+
+## Built With
+
+Smart QA is built using [Streamlit](https://streamlit.io/) and integrates with [Microsoft LIDA](https://github.com/microsoft/lida) for enhanced functionalities.
 
 ## Todo
-[] Connect LLM to ask direct questions to data using SQL commands
-[] Add LIDA to get visualisations + summary
-[] Figure out ways to add trend analysis modules
-[] Figure out anomaly detection ways
+
+- **Trend Analysis Modules**: Enhance the application by incorporating improved trend analysis modules.
+- **Anomaly Detection**: Implement features to detect and highlight anomalies within the data.
+- **Integration with GPT-4-V**: Connect with GPT-4-V to leverage advanced inference capabilities, especially when dealing with graphical data.
+- Dockerise the application
+
+## Contributions
+
+Contributions welcome : )
+
+## License
+
+Smart QA is licensed under the [MIT License](LICENSE).
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