Jarvis Runtime

Jarvis Runtime offers an architecture-first approach to building robust, predictable applications. It separates core behavior and memory from language models, treating them as replaceable components. Key features include: • Decoupled system behavior from language generation • Persistent context and memory management • Model and provider-agnostic design • Deterministic control layers over probabilistic models This framework ensures stable performance and reliable interactions, unlike typical conversational interfaces that often exhibit random behavior shifts or simulated memory. By design, it allows developers to define explicit orchestration of roles, states, and execution flow, ensuring responses reflect input signals rather than forced personalities or over-explanations. The system focuses on achieving correctness and control, making it ideal for applications requiring consistent and predictable operation. Jarvis Runtime supports various providers, including OpenAI-compatible APIs, Anthropic, Google Gemini, and Mistral, enabling seamless model switching without requiring extensive code rewrites. This eliminates vendor lock-in and provides flexibility in choosing the best language engine for specific tasks. The operational flow involves analyzing user input, resolving context and memory, applying defined rules, executing deterministic tools, generating language via the chosen model, and updating memory. The runtime is crafted for developers constructing production-grade assistants and complex interactive systems where accuracy, stability, and long-term context continuity are paramount. It's suited for applications where minimal input should produce minimal, targeted output, avoiding the invention of intent or unnecessary verbosity often found in generic conversational agents.