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LiteLLM

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CODING · 1 SOURCE · InfoQ AI, ML & Data Engineering

InfoQ: Platform engineering playbook for production LLMs

InfoQ publishes a platform-engineering playbook based on a retail inventory recommendation system that reduced hallucination rate from ~15% to ~1.5% without changing the foundation model by applying platform-level controls (automated retry loops, intent-validation gates, prompt registries, tool authorization, and custom instrumentation). The article links a companion GitHub repo with runnable examples that use a local llama3.1 via Ollama connected through LiteLLM and describes routing through foundation models such as Gemini and GPT under enterprise traffic.

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