What is a Local AI Research Gateway? Building a local research stack gives you total privacy by keeping your data and LLM execution entirely on your hardware. By combining Ollama with Open WebUI and SearXNG, you can create a localized version of modern chat interfaces capable of real-time web search. Key Components: Ollama: The backend engine handling model execution locally. Open WebUI: The interface for chat and agent orchestration. SearXNG: A self-hosted metasearch engine that feeds real-time web data directly to the LLM. How to get started: Host Ollama: Run Ollama natively on your Ubuntu host to maximize GPU access for your local models (like gemma2:2b). Deploy via Docker: Use a docker-compose.yml to spin up Open WebUI and SearXNG containers. Bridge the Connection: In Open WebUI, navigate to Admin Panel > Settings > Web Search and set the Query URL to http://host.docker.internal:8080/search?q=<query>. Configure Search: Set the “Search Result Count” to 3 to ensure memory usage stays within the limits of constrained hardware. ...

The Challenge: The 4GB VRAM Wall Running modern LLMs like Phi-4 or Qwen3 on local hardware is becoming a necessity as cloud AI costs continue to add up for power users. However, OpenClaw 2026 now requires a large context window (minimum 12k-16k) to handle its agentic workflows and tool-calling capabilities. On an entry-level NVIDIA T500 (4GB), these large windows usually force the system to spill over into System RAM (CPU mode). When this happens, generation speed drops from sluggish to 5+ minutes per response, making the bot unresponsive. ...