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 (RedisVL) -- 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.
Reliable and Efficient Semantic Prompt Caching with vCache
Redis integration for Google Agent Development Kit (ADK) - Memory, Sessions, Search Tools, MCP
Unified multi-layer caching library for AI/agent pipelines — LangChain, LangGraph, AutoGen, CrewAI, Agno, A2A
Transparent, transport-layer semantic cache for LLM API calls, powered by Redis 8 Vector Sets.
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.
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.
Enhance LLM retrieval performance with Azure Cosmos DB Semantic Cache. Learn how to integrate and optimize caching strategies in real-world web applications.
OpenAI-compatible LLM gateway: routes to the cheapest model meeting latency/quality targets, with SSE streaming, semantic caching, per-key rate limiting, and cost tracking.
Multi-agent LangGraph assistant for Montreal urban mobility — RAG, semantic caching, and a predictive ML collision model on FastAPI.
Redis Vector Similarity Search, Semantic Caching, Recommendation Systems and RAG
A ChatBot using Redis Vector Similarity Search, which can recommend blogs based on user prompt
Optimized RAG Retrieval with Indexing, Quantization, Hybrid Search and Caching
Semantic cache layer for LLM APIs — embed prompts locally, find near-matches, skip redundant LLM calls.
fastapi-semcache: Semantic caching for APIs & LLMs with pgvector, Redis, FastAPI middleware, and standalone proxy mode.
A universal open protocol for LLM semantic caching and cross-platform alignment (v0.1). High-efficiency semantic hashing based on S³ topology.
Enterprise RAG backend: hybrid retrieval (Qdrant + Elasticsearch), RRF fusion, cross-encoder reranking, RBAC, two-tier caching, guardrails, and grounded citations — streamed over SSE. FastAPI + Python. A prototype-scale rebuild of a real system-design case study.
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