111 lines
3.9 KiB
Markdown
111 lines
3.9 KiB
Markdown
# 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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To get started with the CrewAI Simplified App, follow these simple steps:
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1. **Installation**: Clone the repository and install dependencies using npm or yarn:
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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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2. **Create Python Virtual Enviroment**: create Python venv, activate the venv and install the requirements.
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Create venv:
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```bash
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python -m venv venv
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```
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To activate the virtual environment on Windows:
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```bash
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.\venv\Scripts\activate
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```
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To activate the virtual environment on Linux or Mac:
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```bash
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source venv/bin/activate
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```
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Install the requirements:
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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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