A practical guide to reducing LLM token costs in RAG and agentic pipelines using two context compression strategies: extraction-based (LLMChainExtractor) and selection-based (LLMChainFilter) via LangChain. Covers precise token counting with TikToken, implementing both approaches against the same FAISS-backed retrieval pipeline,
Table of contents
How to Optimize Token Usage with Context CompressionTable of ContentsWhy Token Optimization Matters NowHow Context Windows Drain Your BudgetExtraction vs. Selection: When to Use WhichImplementing Context Compression with LangChainMeasuring Real-Dollar SavingsBest Practices and PitfallsNext StepsSort: