Awesome Generative AI
Section: LLMOps · LLM App is a Python library that helps you build real-time AI-powered data pipelines with few lines of code.
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Appears in 5 awesome lists
LLM App is a Python library that helps you build real-time LLM-enabled data pipelines with few lines of code.
Section: LLMOps · LLM App is a Python library that helps you build real-time AI-powered data pipelines with few lines of code.
Section: LLMOps · LLM App is a Python library that helps you build real-time LLM-enabled data pipelines with few lines of code.
Section: Retrieval-Augmented Generation · ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data
Section: Library
Section: Developer tools · Open-source Python library to build real-time LLM-enabled data pipeline.
Unified proxy and SDK that routes to 100+ LLM providers behind a single OpenAI-compatible interface, with a Router handling retry/fallback across deployments, per-project cost and rate-limit tracking, and OTEL callback integrations. The right infrastructure layer when your harness needs provider…
Comet's open-source AI observability and evaluation platform: deep tracing of LLM calls, conversation logging, and agent activity, plus built-in eval metrics, prompt versioning, guardrails, and the Opik Agent Optimizer. Worth including because it unifies observability, verification, and…
February 2026 release making human oversight a native workflow primitive: suspend execution at critical decision points, expose review-and-edit UI mid-flow, and route subsequent execution based on human action (approve/reject/escalate). Demonstrates how HITL transitions from bolt-on approval gates…
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search,…
Open-source AI observability & evaluation platform (Arize) — OpenTelemetry-native tracing for agents, LLM-as-judge evals, versioned datasets & experiments for prompt regression testing, prompt management with version control and replay, plus an MCP endpoint so Claude Code/Cursor can query traces…
The most widely adopted self-hostable LLM observability platform: traces every agent step, manages prompt versions, and runs evals in one tool. Preferred over cloud-only alternatives when data residency or cost control is a constraint.