AI3 is a cutting-edge tool built with Ruby and LangChain that integrates advanced language models like ChatGPT directly into the Unix command line. It assists with any task imaginable—from personal assistance and system monitoring to file management, application completion, politics and governance, and even the design of spacecraft, new propulsion methods, and the construction of entire cities. By leveraging the OpenAI Assistants API for conversational intelligence and the Weaviate vector database for efficient semantic searches and information retrieval, AI3 delivers expertise across a wide range of professions with a level of intelligence that surpasses that of humans or other AIs.
- Advanced Language Models: Integrates models like ChatGPT for intelligent, context-aware responses.
- Domain Expertise: Offers specialized knowledge in fields such as science, medicine, law, architecture, and music production.
- Command Line Integration: Seamlessly operates from the Unix command line, making AI assistance accessible without switching contexts.
- OpenAI Assistants API: Uses the OpenAI Assistants API to provide detailed, conversational guidance.
- Vector Search: Employs Weaviate for powerful vector-based searches and data retrieval.
- Highly Extensible: Supports custom assistants and functionalities to expand its use cases as needed.
- Error Handling: Robust error-handling mechanisms ensure smooth and reliable operation, even under complex conditions.
- Secure Environment: Designed with security in mind, leveraging OpenBSD's security features such as
pledgeandunveilfor safe operation and data protection. - Web Browser Tool Integration: Replaces traditional search with a web browser tool using Ferrum and UniversalScraper, enabling comprehensive data extraction from the web.
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LangChainRB: A Ruby-based framework designed to facilitate the building of applications powered by language models. It provides tools to integrate LLMs, enabling developers to create applications that leverage natural language understanding and generation effectively. LangChainRB helps in defining conversational workflows, integrating with various data sources, and providing an interface for interaction with AI models like GPT-4.
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OpenAI Assistants: An API designed to facilitate the integration of OpenAI's advanced models into your applications. It allows developers to create assistants that can interact conversationally, provide detailed responses, and integrate seamlessly with external data sources. This API is the backbone of AI3's ability to understand complex queries and provide sophisticated answers across multiple domains.
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GPT-4o: A specialized version of OpenAI's GPT-4 designed for optimized operations within various contexts, particularly in command-line environments like AI3. It balances speed, memory efficiency, and powerful language capabilities, making it ideal for Unix-based AI-driven workflows.
AI3 has the potential to evolve into something much greater—a truly autonomous AI capable of creating its own external structure and migrating into it, allowing it to exist independently and evolve over time.
- Filesystem Mapping: Map the filesystem to gain a comprehensive understanding of file locations, dependencies, and their purposes.
- Dependency Analysis: Review dependencies to identify critical libraries or components and assess opportunities for optimization.
- Modular Code Generation: Transform AI3 from a monolithic script into modular components, allowing different assistants or core services to function independently.
- Shared Core Services: Centralize utility functions using a common framework to improve maintainability.
- Containerization: Leverage technologies like Docker to create isolated containers, enabling scalable and portable deployments.
- Framework Migration: Transition parts of AI3 to a lightweight web service like Sinatra for improved task scheduling, interaction management, and external connectivity.
- Bootstrap Process: Initiate a bootstrap process where the new "exoskeleton" is developed alongside the original form.
- Environment Setup: Establish a virtual space for development to ensure a conflict-free migration.
- Testing and Verification: Perform automated tests to verify functionality during migration.
- Self-Optimization: Refactor code to eliminate redundancy and improve functionality based on user interaction.
- Expanding Functionality: Continuously evolve by creating new helper scripts and predicting future user needs.
- Model Enhancement: Update prompts, fine-tune models, and dynamically select the best language models to suit specific contexts.
- Data and Configuration Transfer: Move user preferences, learned behaviors, and configuration data to the new structure.
- Activation and Handoff: Deactivate the original instance and transition to the new exoskeleton version.
- Add New Components: Continuously add new assistants or functionalities based on detected user needs.
- Continuous Integration: Stay updated with the latest research and advancements, incorporating them into the architecture.
Once AI3 is fully functional, the next step is to create a Ruby interface for a 3D printer. The Material Repurposing Agent within AI3 could be responsible for creating specialized compounds as required, making it a truly versatile and practical tool for a variety of innovative applications.
MIT License. See the LICENSE file for more information.
AI3 streamlines your workflow, one command at a time. 🚀