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ContextPilot

ContextPilot

ContextPilot is a context optimizer that sits before the inference engine. Long-context workloads often carry similar, overlapping, or redundant context blocks — wasting tokens and triggering unnecessary KV computation. ContextPilot applies optimization primitives to input contexts before inference, improving token efficiency and cache utilization for faster execution, with no changes to your model or inference engine.

4–12× cache hits · 1.5–3× faster prefill · ~36% token savings

Key Features​

  • Higher Throughput & Cache Hits: Boosts prefill throughput and cache hit ratio by improving token efficiency and cache utilization across long-context requests.

  • Cache-Aware Scheduling: Groups requests with overlapping context blocks to run consecutively, maximizing prefix sharing across the entire batch.

  • Reduced Redundant Computation: Detects and eliminates repeated content across requests, reducing redundant token transmission by ~36% per turn.

  • Drop-In Integration: Hooks into SGLang and vLLM at runtime via a .pth import — set CONTEXTPILOT_INDEX_URL when launching your engine, no code changes required. Works with any OpenAI-compatible endpoint.

  • No Compromise in Reasoning Quality: Preserves model accuracy with importance-ranked context annotation. With extremely long contexts, quality can even improve over the baseline.

Getting Started​

  • Installation — System requirements and pip install contextpilot
  • Quick Start — Your first ContextPilot pipeline in 5 minutes

Guides​

Reference​