LICENSE and README.md files
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Eng. Elias
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LICENSE
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MIT License
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Copyright (c) 2024 Eng. Elias
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Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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README.md
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README.md
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This is a [Next.js](https://nextjs.org/) project bootstrapped with [`create-next-app`](https://github.com/vercel/next.js/tree/canary/packages/create-next-app).
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# CrewAI Simplified App
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This application provides a simplified user interface for leveraging the power of CrewAI, a cutting-edge framework for orchestrating role-playing autonomous AI agents. With this app, users can streamline the process of creating and managing AI crews without the need for coding.
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## Features
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- **Intuitive UI**: The app offers a user-friendly interface, allowing users to easily create and manage AI crews.
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- **Role-Based Agent Design**: Customize agents with specific roles, goals, and tools through a simple form-based approach.
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- **Task Management**: Define tasks and assign them to agents dynamically.
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- **Sequential and Hierarchical Processes**: Choose between sequential or hierarchical processes for task execution, depending on your workflow needs.
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- **Save Output**: Save the output for future reference or analysis.
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- **Connection to LLM model**: for this version I used Gemini model and I plan to add more models in the future.
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## Getting Started
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First, run the development server:
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To get started with the CrewAI Simplified App, follow these simple steps:
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```bash
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npm run dev
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# or
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yarn dev
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# or
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pnpm dev
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# or
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bun dev
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```
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1. **Installation**: Clone the repository and install dependencies using npm or yarn:
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Open [http://localhost:3000](http://localhost:3000) with your browser to see the result.
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```bash
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git clone https://github.com/Eng-Elias/CrewAI-Visualizer.git
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cd crewai-simplified-app
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npm install
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```
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You can start editing the page by modifying `app/page.tsx`. The page auto-updates as you edit the file.
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2. **Create Python Virtual Enviroment**: create Python venv, activate the venv and install the requirements.
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This project uses [`next/font`](https://nextjs.org/docs/basic-features/font-optimization) to automatically optimize and load Inter, a custom Google Font.
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Create venv:
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## Learn More
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```bash
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python -m venv venv
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```
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To learn more about Next.js, take a look at the following resources:
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To activate the virtual environment on Windows:
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- [Next.js Documentation](https://nextjs.org/docs) - learn about Next.js features and API.
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- [Learn Next.js](https://nextjs.org/learn) - an interactive Next.js tutorial.
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```bash
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.\venv\Scripts\activate
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```
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You can check out [the Next.js GitHub repository](https://github.com/vercel/next.js/) - your feedback and contributions are welcome!
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To activate the virtual environment on Linux or Mac:
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## Deploy on Vercel
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```bash
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source venv/bin/activate
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```
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The easiest way to deploy your Next.js app is to use the [Vercel Platform](https://vercel.com/new?utm_medium=default-template&filter=next.js&utm_source=create-next-app&utm_campaign=create-next-app-readme) from the creators of Next.js.
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Install the requirements:
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Check out our [Next.js deployment documentation](https://nextjs.org/docs/deployment) for more details.
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```bash
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pip install -r requirements.txt
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```
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3. **Configuration**: Set up your environment variables in a `.env` file:
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Just rename .env.template to .env and set your values:
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```plaintext
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DATABASE_URL="postgresql://postgres:postgres@localhost:5432/ crew_ai_visualizer?schema=public"
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GEMINI_API_KEY=""
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PYTHON_SITE_PACKAGES="<The path of site packages folder in the venv you created in the previous step>"
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CREW_AI_PY_FILE="<the path of my crew_ai.py file in on your system. you can find it in src/app/api/graphql/crew_ai.py>"
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```
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4. **Start the Development Server**: Run the following command to start the development server:
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```bash
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npm run dev
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```
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5. **Access the App**: Once the development server is running, access the app in your browser at `http://localhost:3000`.
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## Usage
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1. **Create a New Crew**: By adding agents.
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2. **Customize Agents**: Fill in the information for each agent, including role, goal, backstory, tools, allow_deligation, and verbose.
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3. **Define Missions**: Fill mission information including name, crew, verbose, process and add tasks with their details (name, description, agent).
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4. **Execute Mission**: Once your mission is set up, execute it to start the execution process.
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5. **View Results**: View the output of completed missions within the app.
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## Contributing
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We welcome contributions to the CrewAI Simplified App. If you'd like to contribute, please follow these steps:
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1. Fork the repository.
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2. Create a new branch for your feature or improvement.
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3. Add your feature or improvement.
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4. Submit a pull request.
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## Tech Stack
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This app is built using TypeScript, Prisma, GraphQL, Next.js, and node-calls-python to execute Python code from Node.js and get the result in addition to use Gemini as LLM.
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## License
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This application is open-source and is released under the MIT License. See the [LICENSE](LICENSE) file for details.
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## To Do
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- [ ] Add more tools for agents either from LangChain community or create new useful tools.
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- [ ] Add more LLM options like ChatGPT and local LLMs.
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## Credits
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Special thanks to [João Moura](https://github.com/joaomdmoura) the creator of [CrewAI](https://github.com/joaomdmoura/crewAI) for providing the underlying framework for AI crew orchestration.
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