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#

llm-ops

Here are 96 public repositories matching this topic...

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

  • UpdatedFeb 16, 2026
  • Python

Deploy serverless AI workflows at scale. Firebase for AI agents

  • UpdatedJan 2, 2026
  • Jupyter Notebook
AutoRAG

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

  • UpdatedDec 23, 2025
  • Python
cognita

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

  • UpdatedNov 26, 2025
  • Python

The platform for LLM evaluations and AI agent testing

  • UpdatedFeb 20, 2026
  • TypeScript

Your autonomous engineering team in a CLI. Point Zeroshot at an issue, walk away, and return to production-grade code. Supports Claude Code, OpenAI Codex, OpenCode, and Gemini CLI.

  • UpdatedFeb 20, 2026
  • JavaScript
JamAIBase

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.

  • UpdatedFeb 19, 2026
  • Python
aiconfig

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

  • UpdatedFeb 10, 2026
  • Python

Python SDK for running evaluations on LLM generated responses

  • UpdatedJun 6, 2025
  • Python

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

  • UpdatedJul 15, 2025
  • Python

Operations toolkit and methodology for persistent LLM agents — watchdogs, memory reset, cost monitoring, tool proxy, Docker Compose stacks, and a cookbook of practical recipes. Framework-agnostic patterns from running 3 AI agents 24/7.

  • UpdatedFeb 17, 2026
  • Python

[⛔️ DEPRECATED] Friendli: the fastest serving engine for generative AI

  • UpdatedJun 25, 2025
  • Python

Production operations framework for AI-powered SaaS. The architectural patterns, failure modes, and operational playbooks that determine whether your AI systems scale profitably or fail expensively.

  • UpdatedFeb 3, 2026

🔍 AI observability skill for Claude Code. Debug LangChain/LangGraph agents by fetching execution traces from LangSmith Studio directly in your terminal.

  • UpdatedDec 29, 2025

[🚧🚧🚧WIP🚧🚧 🚧]Rework of webapp-conversation

  • UpdatedJul 5, 2023
  • TypeScript

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