Llm Ops Collection

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🌑Dark

★★★★

“🦍 The API and AI Gateway”

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🔮Psychic

★★★

“Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.”

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⚡Thunder

★★★

“Enterprise-grade, commercial-friendly agentic workflow platform for building next-generation SuperAgents.”

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📦Normal

★★★

“Firebase for AI agents”

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🔮Psychic

★★

“AutoRAG: An Open-Source Framework for Retrieval-Augmented Generation (RAG) Evaluation & Optimization with AutoML-Style Automation”

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🔮Psychic

★★

“RAG (Retrieval Augmented Generation) Framework for building modular, open source applications for production by TrueFoundry ”

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💎Aqua

★★

“The platform for LLM evaluations and AI agent testing”

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🔮Psychic

★★

“The collaborative spreadsheet for AI. Chain cells into powerful pipelines, experiment with prompts and models, and evaluate LLM responses in real-time. Work together seamlessly to build and iterate on AI applications.”

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🔮Psychic

★★

“AIConfig is a config-based framework to build generative AI applications.”

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🔮Psychic

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“Python SDK for running evaluations on LLM generated responses”

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🔮Psychic

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“An end-to-end LLM reference implementation providing a Q&A interface for Airflow and Astronomer”

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💎Aqua

★

“国内首个企业级 IT 运维多 Agent 自动化平台 — 基于大语言模型的智能运维解决方案。ITOps Agent Platform通过可视化工作流编排，将多个AI Agent组合成智能运维自动化流水线，实现服务器管理、告警处理、故障诊断、日志分析、脚本管理、定时运维任务的自动化执行， 支持国内外主流大模型，旨在 Zabbix/Prometheus 告警自动修复闭环，Docker 一键部署”

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⚡Electric

★

“Open Source Context infrastructure for AI agents. Auto-capture and share your agents' context everywhere.”

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⚙️Steel

★

“High-performance Ollama & LM Studio proxy with per-user fair-share queuing, round-robin scheduling, and a real-time TUI dashboard. Built in Rust.”

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🔮Psychic

★

“[DEPRECATED] Moved to microsoft/agent-governance-toolkit”

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🔮Psychic

★

“A production-grade control layer that sits between your application logic and any LLM — input validation, schema enforcement, circuit breaking, targeted retry, and audit logging in one composable pipeline.”

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⚡Electric

★

“Anthropic API reverse proxy with prompt-cache injection and request body transforms”