Unified AI Assist

Description

Our project, Unified AI Assist, offers a comprehensive solution for users seeking to streamline their workflow across various platforms such as Google Workspace, HubSpot, Zendesk, Salesforce, Google Analytics, databases, and more. Our platform empowers users to create their own AI assistants tailored to them, integrating seamlessly with their existing tools and services.

Through an intuitive chat interface, users can interact with their AI assistant to perform a wide range of tasks, from managing customer inquiries and updating sales records to analyzing data trends and generating reports. The AI assistant utilizes natural language processing and machine learning algorithms to understand user queries and execute actions across multiple platforms efficiently.

Moreover, our platform offers flexibility by allowing users to communicate with their AI assistant through popular chat platforms like Slack, Discord, Notion, WhatsApp, and more. Whether at their desk or on the go, users can access their AI assistant from any device or chat application, ensuring seamless communication and productivity.

AI Assist as a Service revolutionizes the way users manage their workflows by providing a centralized and intelligent assistant capable of handling tasks across various platforms with ease. With our platform, users can boost efficiency, save time, and enhance collaboration across their organization.

Table of Contents

• Installation
• Usage
• To-do
• Contributing
• License

Installation

Backend (Python/Django)

1. Clone the repository:

   git clone https://github.com/Oseni03/Unified-AI-Assist.git

2. Navigate to the backend directory:

   cd Unified-AI-Assist/backend

3. Install dependencies:

   pip install -r requirements.txt

4. Set up environment variables:

   • Create a .env file in the backend directory.
   • Add necessary environment variables such as API keys, database credentials, etc.

5. Run migrations:

   python manage.py migrate

6. Start the Django server:

   python manage.py runserver

Frontend (JavaScript/React)

1. Navigate to the frontend directory:

   cd ../frontend

2. Install dependencies:

   npm install

3. Set up environment variables:

   • Create a .env file in the frontend directory.
   • Add necessary environment variables such as API endpoints, chat platform tokens, etc.

4. Start the React development server:

   npm start

5. Access the application at http://localhost:3000 in your browser.

Usage

Coming soon...

To-do

The following are tasks that need to be completed or features that need to be implemented in the project. Contributions are welcome from the community to help address these items:

1. Frontend Setup:

   • Set up the frontend environment using JavaScript/React to create a user-friendly interface for interacting with the AI assistant.

2. Dynamic AI Assistant Configuration:

   • Implement functionality to dynamically configure AI assistants using CrewAI, Gemini AI, and Langchain to perform various tasks and integrations.

3. Assistant Memory Setup:

   • Set up memory capabilities for the AI assistant to retain context and information across interactions with users.

4. Platform OAuth Authentication and Integration:

   • Implement OAuth authentication and integration with platforms like Google Workspace, HubSpot, Zendesk, etc., to enable secure user authentication and access control.

5. Chat Interface with AI:

   • Develop a chat interface for seamless communication with the AI assistant, allowing users to interact with it using natural language.

6. Error Handling and Logging:

   • Implement robust error handling mechanisms and logging functionality to track and troubleshoot issues encountered by the AI assistant during execution.

7. Documentation and Tutorial:

   • Create comprehensive documentation and tutorials to guide users through the process of setting up, configuring, and using the AI assistant.

8. Performance Optimization:

   • Optimize the performance of the AI assistant, including response time, resource utilization, scalability, etc., to ensure smooth and efficient operation under varying workloads.

9. Enhance Cross-platform Communication with AI Assistant:

   • Improve integration with external chat platforms like Slack, Discord, Notion, WhatsApp, etc., to facilitate seamless communication and interaction with the AI assistant.

Feel free to pick any task from the list above or suggest new ideas for improving the project. Contributions in the form of code, documentation, testing, or feedback are highly appreciated!

Contributing

We welcome contributions from the community to enhance the features and functionality of Unified AI Assist. Here's how you can contribute:

1. Fork the Repository: Start by forking the project repository to your GitHub account.

2. Clone the Repository: Clone the forked repository to your local machine using the git clone command.

3. Create a Branch: Create a new branch for your contribution using a descriptive branch name.

4. Make Changes: Implement your changes or additions to the project.

5. Test Your Changes: Ensure that your changes are properly tested and do not introduce any regressions.

6. Commit Changes: Commit your changes with clear and concise commit messages.

7. Push Changes: Push your changes to your forked repository on GitHub.

8. Submit a Pull Request: Submit a pull request from your forked repository to the main project repository. Provide a detailed description of your changes in the pull request.

9. Review and Collaboration: Participate in the review process, address any feedback or comments, and collaborate with project maintainers to finalize your contribution.

10. Stay Engaged: Stay engaged with the project community, participate in discussions, and contribute to ongoing development efforts.

By contributing to Unified AI Assist, you're helping to improve the functionality and usability of the platform for users worldwide. Thank you for your valuable contributions!

License

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