가입 후 초대 링크를 공유하면 동영상 재생 및 초대 보상을 받을 수 있습니다.

cv usk
@cv_usk
AI / Software Research Notes AI Agent, LLMOps, MLOps, Software Architecture 投稿は個人の意見です。
가입 May 2026
284 팔로잉 중    449 팬
# Useful but Little-Known Features of ADK 2.0 🌍 Want to build AI agents that run entirely on your own hardware, with no cloud API dependency? ADK 2.0 supports local and self-hosted model serving through LiteRT-LM, vLLM, and Ollama — enabling fully cloud-independent agent development. 📌 Title: Local & Self-Hosting with LiteRT-LM / vLLM / Ollama 🔗 URL: 🧩 Overview LiteRT-LM is a C++-based inference library optimized for edge platforms. Simply download a model with `lit pull` and start a local server with `lit serve` — then point your ADK agent to the local endpoint via the `base_url` parameter. The same pattern works with vLLM and Ollama-hosted models, giving you flexibility across different hosting environments. 🛠 How to use it With LiteRT-LM, first download the model and start the server. ```bash # Download the model lit pull gemma3n-e2b # Start local server lit serve --port 8001 ``` Then connect your ADK agent by specifying the `base_url`. ```python from google.adk.agents import Agent from google.adk.models import Gemini agent = Agent( name="local_agent", model=Gemini( model="gemma3n-e2b", base_url="http://localhost:8001", ), instruction="Process tasks using the local model", ) ``` Use the `--verbose` flag during debugging to inspect request/response details. 🏗 Building it into production ・Use LiteRT-LM on edge devices for optimized latency and data privacy ・Leverage vLLM on GPU servers for high-throughput inference ・Use Ollama for rapid development and prototyping ・Implement health checks and resource monitoring for local servers to ensure stable operations 💡 Use cases 🏥 On-premises AI in healthcare where patient data cannot leave the facility 🏭 Real-time quality inspection on factory edge devices 🔐 Data sovereignty compliance in environments handling classified information ✈️ Offline-capable agents in environments with unreliable network connectivity ⚠️ Watch out Local models may underperform compared to large cloud-hosted models. On edge devices, pay attention to memory and compute constraints when choosing model sizes. LiteRT-LM is a C++ library, so verify platform-specific build compatibility beforehand. Model updates and version management must be handled manually, unlike cloud APIs that manage this transparently. ✨ Local hosting lets you build agents that satisfy privacy, latency, and offline requirements all at once. Choose between LiteRT-LM, vLLM, and Ollama based on your deployment needs. #ADK# #AIAgent#
더 보기