📖Lessons
Introduction to LLM Gateways
Understand what LLM gateways are, why they matter, and how they simplify multi-model AI development
OpenRouter: Managed LLM Gateway
Access 200+ models through a single API with OpenRouter's managed gateway
LiteLLM: Self-Hosted LLM Proxy
Deploy your own LLM gateway with LiteLLM — the open-source proxy supporting 100+ providers
Advanced Gateway Patterns
Intelligent routing, semantic caching, rate limiting, and production gateway architecture
Gateway Cost Optimization
Reduce LLM costs by 60-80% with intelligent routing, caching, and model selection strategies
Multi-Provider Strategies
Build resilient AI systems with fallback chains, load balancing, and provider-agnostic architectures
Gateway Observability & Monitoring
Monitor LLM gateway health, track costs, detect anomalies, and build dashboards for production visibility
Workshop: Build a Gateway
Hands-on workshop building an LLM gateway with routing, caching, fallbacks, and cost tracking
🎯Missions
M-060Build a Semantic Cache for LLM Requests
Nebula Corp is spending too much on LLM API calls. Many requests are semantically similar — 'What is Python?' and 'Explain Python' should return the same cached response. Build a semantic cache that uses cosine similarity between embeddings to match similar prompts. If a new prompt is similar enough to a cached one (above a threshold), return the cached response instead of calling the LLM.
M-058Build an Intelligent Model Router
Nebula Corp's AI platform sends every request to GPT-4o, costing a fortune. Most requests are simple FAQ lookups that a cheaper model could handle. Build an intelligent router that classifies request complexity and routes to the appropriate model tier: 'fast' (cheap model for simple tasks), 'balanced' (mid-tier for moderate tasks), or 'powerful' (expensive model for complex reasoning). The router should analyze the user message and return the correct model name.
M-057Build Your First Model Router
Nebula Corp uses multiple LLM providers but has no way to route requests intelligently. Build a simple model router that selects the best model based on the request type (fast, cheap, or quality), handles provider fallbacks when a model is unavailable, and tracks usage costs across providers.
M-059Implement a Gateway Fallback Chain
Nebula Corp's AI service went down for 2 hours when their primary LLM provider had an outage. Build a fallback chain that tries multiple providers in order. If the primary model fails, automatically try the next one. Track which model actually served the request and whether a fallback was used. The function should try each model in the chain until one succeeds or all fail.