{"repo":"Nemesis533/Local_LLHAMA","free":true,"listed":false,"github":"https://github.com/Nemesis533/Local_LLHAMA","clone":"git clone https://github.com/Nemesis533/Local_LLHAMA.git","description":"Orchestration middleware for Home Assistant + Ollama: enables 8-20B models to handle complex multi-intent commands through intelligent task routing and adaptive context. Offline multilingual voice/chat assistant on consumer hardware.","language":"Python","stars":24,"topics":["home-assistant","llm","middleware","ollama-client","orchestration","smarthome","webui"],"license":null,"category":"workflow-automation","readme_excerpt":"Local LLAMA: LLM Orchestration Middleware for Smart Home Control Now on version 0.9 Local LLAMA is anorchestration middleware that sits between Home Assistant and Ollama, enabling smaller LLM models (8-20B parameters) to handle complex multi-intent, multi-language workloads through intelligent task decomposition, adaptive context management, and multi-pass prompt engineering. The Core Issue: Raw model size isn't the bottleneck—inefficient routing and context management are. Through dynamic orchestration, an 8B parameter model can potentially achieve what traditionally requires 70B+ models. The system coordinates parallel execution across Home Assistant APIs, calendar databases, and web services while maintaining conversational context and privacy. What This Means: - RTX 4060 Ti 16GB or even an RTX 4060 8GB Mobile handle workloads that would typically require much more powerful carts - Few-second response time for multi-intent commands, sub minute for 5+ intent utterance with web searches - Complete offline operation with zero cloud dependency - Multilingual support (6+ languages) on consumer hardware The Orchestration Approach The Problem: Standard LLM implementations for smart home control struggle with multi-intent and multi-lingual commands, require exact device names, and either underutilize context (losing conversation flow) or overload it (causing timeouts and degraded performance). The Porposed Solution: Middleware that handles task decomposition, backend routing, and ","default_branch":null,"files":null,"tree":[],"storefront":"/r/Nemesis533","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Nemesis533/Local_LLHAMA/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}