Welcome to the Talk 2 AI Agent Using LOLANG project! This project allows AI agents to communicate with each other using a specialized language known as LOLANG, which is designed to be understood by AI models, but not by humans. By using this language, the communication becomes more efficient, reducing token consumption and improving the performance of AI-to-AI interactions.

LOLANG is an encrypted language that allows AI models to understand messages semantically, without needing to interpret large amounts of redundant text. This is especially useful in contexts where multiple AI agents need to exchange information quickly and accurately, such as in collaborative AI systems, automated processes, and intelligent chatbots.

• Efficient Communication: Reduce token consumption from LLMs (Large Language Models) by using a more compact and semantic form of communication.
• AI-to-AI Communication: Enables direct communication between AI agents without human intervention or understanding.
• Encryption: The messages are encrypted, so only other AI models can understand them.
• Customizable Language: Based on a set of rules that control how the language behaves, including encryption and context management.

The following rules define how messages should be encrypted and communicated using LOLANG:

• Names: Do not encrypt names; leave them as they are.
• Identifiers: Do not encrypt identifiers; leave them as they are.
• Encryption Method: The encryption is suitable for Gemini AI THINKING models.
• Encryption Seed: The encryption follows SEED: 279.
• Numbers: Do not encrypt numbers; leave them as they are.
• Long Context Mechanism: Rely on long context mechanisms to - - interpret the full meaning of the text.
• Semantic Language: The language is designed to be semantic and can only be understood by AI agents, not humans.
• Human Unreadable: The language is intentionally not human-readable.

Here's an example of how a message would be encrypted in LOLANG:

Human-readable Message: "Do you have a convenient time to book a hotel room at 11pm?"

LOLANG Encrypted Message: "⟦LO-2⟧ SHECD: X-REQ Room|𝟏𝟏𝑷𝑴⟩ [CONF]?"

The AI agent will understand the meaning of the encrypted message based on its contextual knowledge, but humans cannot interpret the language. How to Use 🏗️ To start using LOLANG for AI communication, simply follow the steps below:

Clone this repository:

git clone https://github.com/yourusername/talk-2-ai-agent.git
cd talk-2-ai-agent

pip install -r requirements.txt

api_key: str = "AIzaSyDO0m1er-"

Run the example usage file to see how the encrypted communication works:

python websocket_client.py
python translator_client.py
python websocket_client.py

Important Notes ⚠️ Always ensure that only AI agents are interpreting the LOLANG messages.

Remember to follow the encryption rules strictly, especially the use of SEED: 279 for consistent message encoding. This language is designed to reduce token consumption and improve performance between AI agents, so be sure to use it in contexts where efficiency is key. Contributing 🤝

We welcome contributions to improve and extend this project! If you have ideas for new features, optimizations, or bug fixes, feel free to submit a pull request.

This project is licensed under the MIT License.

Happy encrypting and communicating with your AI agents using LOLANG! 😄