GitHub topic

serverless GitHub repositories

Explore 11 tracked GitHub repositories tagged serverless. Compare their recorded star activity and implementation languages, then follow related topics to find other projects.

Snapshot: 2026-10-28. The collection gained 14 stars since the previous daily snapshot.

Tracked repositories: 11
Total stars: 25,077
Stars gained · 7 days: +149
Stars gained · 30 days: +632

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Star activity for serverless repositories on this page
Repository	Total stars	Today	7 days	30 days
2FastLabs/agent-squad	7.8K	+1	+2	+21
ml-tooling/opyrator	3.1K	+0	+2	+5
pingcap/autoflow	3.0K	+0	+0	+0
ovg-project/kvcached	2.0K	+3	+122	+503
yomorun/yomo	1.9K	+0	+0	+2

Explore repositories

Showing 1–11 of 11 tracked repositories.

2FastLabs/agent-squad

Flexible and powerful framework for managing multiple AI agents and handling complex conversations

ml-tooling/opyrator

🪄 Turns your machine learning code into microservices with web API, interactive GUI, and more.

★ 3.1K+0 todayPython

machine-learning fastapi

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pingcap/autoflow

pingcap/autoflow is a Graph RAG based and conversational knowledge base tool built with TiDB Serverless Vector Storage. Demo: https://tidb.ai

★ 3.0K+0 todayTypeScript

rag chatbot

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ovg-project/kvcached

Virtualized Elastic KV Cache for Dynamic GPU Sharing and Beyond

★ 2.0K+3 todayPython

llm ollama

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yomorun/yomo

🦖 Serverless AI Agent Framework with Geo-distributed Edge AI Infra.

★ 1.9K+0 todayRust

mcp claude-code

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beam-cloud/beta9

Ultrafast serverless GPU inference, sandboxes, and background jobs

★ 1.8K+3 todayGo

llm self-hosted

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golemcloud/golem

Golem Cloud is the agent-native platform for building AI agents and distributed applications that never lose state, never duplicate work, and never require you to build infrastructure.

★ 1.5K+1 todayRust

ai agents

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modal-labs/modal-examples

Examples of programs built using Modal

★ 1.3K+2 todayPython

machine-learning pytorch

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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.