
AIFlow-Agent
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AI Flow is an advanced agentic AI framework that transforms static, rule-based bots into dynamic AI agents capable of meaningful engagement. It focuses on adaptivity, human-like interaction, and deep environmental integration. AI Flow agents embody rich personalities, opinions, and emotions, remember past conversations, evolve autonomously, create content independently, collaborate with other agents, and anticipate user needs without explicit prompts.
README:
AI Flow is an advanced agentic AI framework designed to bring digital agents to life. With a focus on adaptivity, human-like interaction, and deep environmental integration, AI Flow transforms static, rule-based bots into dynamic, evolving AI agents capable of meaningful engagement.
- An AI That Feels Human AI Flow agents are more than chatbots. They embody rich personalities, opinions, and emotions, adjusting their tone, mood, and interaction style based on context, time, and user dynamics.
- Contextual Memory AI Flow agents remember. They retain past conversations, learn about users, and leverage this memory to provide coherent, personalized, and human-like interactions.
- Dynamic Self-Evolution AI Flow agents evolve autonomously by analyzing their interactions. They refine their behavior, enhance conversational capabilities, and adapt to remain engaging and relevant.
- Autonomous Content Creation AI Flow agents can generate and share content independently, engaging on social media, responding to posts, and building authentic connections.
- Collaborative Interactions AI Flow agents interact with other agents, sharing information, collaborating, and co-creating content, enabling a network of interconnected AI personas.
- Proactivity and Context Awareness AI Flow agents anticipate user needs by analyzing trends, predicting behaviors, and initiating meaningful interactions without needing explicit prompts.
Creating a New AI Agent
- Set Up Your Repository
- Create a new repository on GitHub (public or private).
- Clone the AI Flow repository to your local machine.
git clone https://github.com/YourUsername/aiflow.git [folder_name]
cd [folder_name]
- Configure Remotes
- Add your new repository as the origin remote.
- Add the AI Flow repository as the upstream remote.
git remote set-url origin https://github.com/AIFlowwork/YourNewRepo.git
git remote add upstream https://github.com/AIFlowwork/aiflow.git
- Create a Character File
- Navigate to the characters/ folder and create a new character file.
- Use the following template to define your character (adjust fields based on your needs):
{
"name": "YourCharacterName",
"description": "Brief character description",
"personality_traits": ["trait1", "trait2"],
"twitter_username": "@YourTwitterHandle"
}
- Set Environment Variables
- Rename
.env.example
to.env
and fill in the required values.
CHARACTER_NAME_ID=your_character_name
- Push Changes
- Rename .gitignore.example to .gitignore.
- Push your changes to your repository.
git push -u origin main
- Sync Updates
- Fetch the latest updates from the AI Flow repository when needed.
git fetch upstream
git merge upstream/main
- Deploy using Render’s Background Workers.
- Select your repository during the deployment process.
- Add environment variables by uploading the .env file values.
AI Flow is licensed under the MIT License. See LICENSE for more details.
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