Conversational Memory
Retains long-term context and learns your habits and preferences over time. Semantic retrieval powered by a vector database ensures every conversation picks up right where you left off.
Your Personal AI Assistant & Intelligent Companion
BetaRetains long-term context and learns your habits and preferences over time. Semantic retrieval powered by a vector database ensures every conversation picks up right where you left off.
Built-in search engine, calculator, database query, and more. The Agent architecture automatically selects the right tool to get the job done.
Supports voice, text, and image input. Real-time voice transcription and automatic image understanding included.
WebSocket-based streaming output with visible reasoning and tool-call steps. Watch the AI generate its response word by word for a more natural conversational feel.
Fully self-hosted — your data stays completely under your control. Supports on-premises or private enterprise network deployment with no data-leakage concerns.
Customize system prompts, tune model parameters, and plug in your own tools. Build an AI assistant that is truly yours.
Demonstrates Jarvis's core capabilities: natural-language conversation, real-time streaming responses, and intelligent tool calling (search engine, calculator, knowledge-base queries, etc.). Watch how the AI understands your intent and automatically selects the right tool — with the full reasoning and execution process visualized.
A deep dive into Jarvis's long-term memory: how it remembers multi-turn context, extracts and stores your personal habits, preferences, and key events. Vector-database semantic retrieval lets the AI proactively recall relevant information at just the right moment — it genuinely gets to know you over time.
Showcases practical tool features: intelligent calendar management (add, query, remind) and personal item inventory tracking (record locations, quantities, expiry reminders). See how natural-language conversation can handle complex data-management tasks — your AI life assistant in action.






Built on a LangChain Agent architecture using the ReAct (Reasoning + Acting) pattern, combining Chain-of-Thought reasoning with tool-calling capabilities. Qdrant vector database stores long-term memory; semantic retrieval enables deep context understanding. The frontend uses React + WebSocket for streaming responses; the backend is a high-performance FastAPI service.

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