Ultra-low-latency LLM gateway with microsecond caching, dynamic routing, budgets, analytics, and forecasting.

Official implementation of "SentenceKV: Efficient LLM Inference via Sentence-Level Semantic KV Caching" (COLM 2025). A novel KV cache compression method that organizes cache at sentence level using semantic similarity.

This app leverages Semantic Caching to minimize inference latency and reduce API costs by reusing semantically similar prompt responses.

Semantic caching demo with real-time streaming and a cost & sizing calculator, powered by Azure Managed Redis and Azure OpenAI.

Semantic caching system using Meta Llama 3.3, Groq, FAISS, and Sentence Transformers to reduce LLM latency and API costs through meaning-based query matching.

Evaluate how a semantic cache performs on your dataset by computing key KPIs over a threshold sweep and producing plots/CSVs:

Rust Local Token Compression Proxy for coding agents, built solo for GenAI Genesis 2026. 🏆 1st Google Sustainability Hack

Implemented an LLM observability and evaluation submodule featuring automated instrumentation and tracing, stateful chat orchestration, semantic vector-memory caching, and scheduled Temporal workers for cost anomaly detection. (Tracep api only link : https://tracep-go.onrender.com/)

Semantic caching for LLM responses using Redis Vector DB, LangChain, and HuggingFace embeddings, parses PDFs, generates FAQs with Groq, and serves similarity-based answers without redundant LLM calls.

Python library for the Semcache API

A retrieval-augmented generation pipeline in Python with a rigorous offline evaluation harness. Chunks and embeds documents, retrieves by vector similarity, and generates grounded answers — with pluggable LLM providers (including a deterministic local fake for tests) and metrics for retrieval quality and answer faithfulness. No API key required.

An intelligent gateway for Claude APIs that dynamically routes requests to the most cost-efficient model, caches responses, and escalates based on confidence signals — reducing LLM spend without sacrificing quality.

Semantic memory and caching for LLM agents with classifier-validated equivalence instead of naive cosine thresholds.

Terraform module for a production-hardened Azure AI gateway: APIM in front of Azure AI Foundry with tiered JWT auth, token quotas, content safety, semantic caching, and private networking

Surgical middleware for LLMs. Reduces token waste by 40-60% using Triple-Tier Memory (Anchor + Fact Sheet + Buffer) and Semantic Caching. Built for production-grade branding & cost-recovery.

Semantic LLM Gateway featuring intelligent prompt routing (basic MoE), L1/L2 semantic caching (Redis + pgvector), fault-tolerant model fallbacks, and real-time streaming telemetry. Built to reduce AI inference latency and optimize API compute costs.

A systems research platform for semantic KV-cache orchestration, topology-aware memory placement, distributed prefix reuse, and rack-scale inference memory simulation.

Node SDK for the Semcache API

Production-ready enterprise chatbot starter — RAG, declarative tool calling + MCP, layered memory, semantic caching, guardrails and evals. LangGraph · FastAPI · LiteLLM · pgvector · Redis · Langfuse.

Production-grade Java 25 Virtual Thread inference gateway bridging NVIDIA Triton → Dynamo with Earliest Deadline First (EDF) priority queuing, adaptive batching, and async shadow validation.