LiteLLM | Stop Over Spending on LLMs | Build Smart AI Gateway | Demo - LiteLLM & OpenCode

Stop burning your API budget on basic questions—learn how to build a production-grade AI Gateway that chooses the best model for every request.

Github - https://github.com/kamalkrbh/litellm-setup.git

In this video, we move beyond basic API calls to real AI Infrastructure. I’ll show you how to integrate LiteLLM with OpenCode to create a "Universal Switch" that intelligently routes traffic. We’ll cover why hardcoding GPT-4 is a "Junior" mistake and how to implement QoS (Quality of Service) for your AI agents to optimize for both cost and latency.

What you’ll learn:
Setting up LiteLLM as a central gateway.
Connecting OpenCode to multiple providers (NVIDIA, OpenAI, Gemini).
Implementing automatic routing policies to save 90% on simple requests.

Timeline -
00:00 – The Problem: Stop wasting budget on high-end LLMs
01:41 – LiteLLM Overview: SDK vs. Proxy Server
03:10 – Deployment: Docker Compose & Configuration setup
04:14 – Admin Panel: Managing models, logs, and telemetry
05:54 – Routing Triggers: Tags, Content, Health, and Latency
10:04 – Demo Case: Complexity Routing with OpenCode
13:08 – The "Free Tier" Hack: Maxing out multiple providers
16:45 – Virtual Keys: Connecting your apps to the Gateway
19:44 – Live Testing: Routing verification & Log tracing
24:45 – Conclusion: Achieving better AI performance

#SoftwareEngineering #AIGateway #LiteLLM #DevOps2026 #OpenCode #AIInfrastructure #SystemArchitecture #LLMOps

Видео LiteLLM | Stop Over Spending on LLMs | Build Smart AI Gateway | Demo - LiteLLM & OpenCode канала Kamal Krishna Bhatt