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Awesome GitHub RepositoriesLLM Token Compression

Techniques to reduce the number of billed tokens in LLM requests through deduplication and minification.

Distinct from Visual Token Compression: Focuses on textual LLM prompt tokens and message deduplication rather than visual or security token compression.

Explore 3 awesome GitHub repositories matching data & databases · LLM Token Compression. Refine with filters or upvote what's useful.

Awesome LLM Token Compression GitHub Repositories

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  • diegosouzapw/omniroutediegosouzapw 的头像

    diegosouzapw/OmniRoute

    6,391在 GitHub 上查看↗

    OmniRoute is a unified LLM API gateway that connects multiple AI providers to a single endpoint. Its primary purpose is to simplify the integration of various AI models into tools and agents by translating different provider formats into a standardized API. The project distinguishes itself through a multi-strategy request routing system that optimizes for cost, speed, and availability, including automatic model fallbacks and a circuit-breaker resilience model to isolate provider failures. It employs a local-first security posture, using AES-256-GCM encryption to store API keys and conversatio

    Reduces billed token usage through semantic pruning and deduplication of prompts to maximize the context window.

    TypeScript
    在 GitHub 上查看↗6,391
  • blockrunai/clawrouterBlockRunAI 的头像

    BlockRunAI/ClawRouter

    3,020在 GitHub 上查看↗

    ClawRouter is an AI model router and API gateway designed to classify query complexity and assign prompts to the most efficient model tier. It operates as a multi-model AI proxy that orchestrates traffic between various large language models and AI media generators through a unified interface. The project distinguishes itself by integrating a non-custodial micropayment processor using the x402 protocol. This allows for per-request API access and USDC settlement on Base and Solana chains, replacing static API keys with wallet-based authentication and real-time budget enforcement. The system c

    Reduces billed token counts by deduplicating messages and minifying data before sending requests.

    TypeScriptaiai-agentsanthropic
    在 GitHub 上查看↗3,020
  • aiming-lab/simplememaiming-lab 的头像

    aiming-lab/SimpleMem

    2,972在 GitHub 上查看↗

    SimpleMem is a persistent memory system for AI assistants designed to maintain context across different user chat sessions. It functions as a memory server and multimodal vector database that stores and retrieves information from text, images, audio, and video. The project features a context compression engine that distills interaction histories into compact units to reduce token consumption. It utilizes a distributed memory orchestrator and worker-thread parallel processing to reduce latency when querying large-scale dialogue datasets. The system implements a hybrid indexing approach combin

    Reduces token consumption by compressing interaction histories into compact, non-redundant units.

    Python
    在 GitHub 上查看↗2,972
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  3. Data Compression Algorithms
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