A LLM semantic caching system aiming to enhance user experience by reducing response time via cached query-result pairs.
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Updated
Jun 30, 2025 - Python
A LLM semantic caching system aiming to enhance user experience by reducing response time via cached query-result pairs.
Redis Vector Library. The AI-native Python client for Redis.
SmarterRouter: An intelligent LLM gateway and VRAM-aware router for Ollama, llama.cpp, and OpenAI. Features semantic caching, model profiling, and automatic failover for local AI labs.
Drop-in AI memory layer with 2x faster retrieval and 10x lower cost. Fully compatible with Mem0 API. Migrate in 5 minutes without any code changes. Self-host for free.
Reliable and Efficient Semantic Prompt Caching with vCache
Own your LLM's web search: a local search->fetch->rank pipeline that replaces hosted web-search tools. Measured: matches hosted accuracy at 66% lower cost and up to 88% fewer tokens, plus a precision-tuned semantic caching with query-dependant TTL that no API offers.
Transparent, transport-layer semantic cache for LLM API calls, powered by Redis 8 Vector Sets.
Unified multi-layer caching library for AI/agent pipelines — LangChain, LangGraph, AutoGen, CrewAI, Agno, A2A
Redis integration for Google Agent Development Kit (ADK) - Memory, Sessions, Search Tools, MCP
Semantic caching layer for LLM apps: serves cached answers for paraphrased prompts, with pluggable vector stores and streaming support.
High-performance LLM query cache with semantic search. Reduce API costs 80% and latency from 8.5s to 1ms using Redis + Qdrant vector DB. Multi-provider support (OpenAI, Anthropic).
AI real-estate automation platform: Telegram bot, RAG, apartment search, CRM workflows, voice agent, Langfuse observability, and Dockerized AI runtime.
ToolOps is a framework-agnostic middleware SDK that treats every tool call as a first-class operation. By wrapping your tools in a single decorator, you instantly upgrade them with industrial-grade caching, resilience, and observability.
GenPark AI Agent Skill - Semantic prompt cache, cosine similarity threshold lookup, hit/miss metrics, and TTL cache expiration.
GenPark AI Agent Skill - Semantic prompt cache, cosine similarity threshold lookup, hit/miss metrics, and TTL cache expiration.
Entity-relation-object triplet extractor and multi-hop path reasoning kernel with Cypher and JSON-LD graph generation.
Context window attention optimizer reordering retrieved documents to place critical evidence at prompt boundaries, mitigating lost-in-the-middle degradation.
Zero-dependency hybrid retrieval engine fusing sparse lexical BM25 Okapi and dense Cosine vector similarities via Reciprocal Rank Fusion.
Cognitive multi-tier memory kernel managing working scratchpad, sliding dialogue buffer, and episodic memories with exponential recency decay.
High-throughput semantic query cache and approximate deduplicator combining exact SHA-256 and cosine similarity threshold matching with LRU eviction.
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