AI Agents
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AI Agent Assistant & development framework that integrates lots of IM platforms, LLMs, plugins and AI feature, and can be your openclaw alternative. ✨
★ 41.3k starsAGPL-3.0
View guide →Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic syst…
RagaAI-Catalyst is an open-source ai agents project by raga-ai-hub (raga-ai-hub/RagaAI-Catalyst on GitHub). It has 16,170 GitHub stars and 3,571 forks, is released under the Apache-2.0 license, and was last updated on GitHub on 11 February 2026.
Research, coding, browsing, or ops — agents work best with a clear goal.
From no-code builders to code-first SDKs, match complexity to the task.
Web search, code execution, and APIs are what make agents useful.
Watch the trace, approve consequential actions, iterate.
Swap frontier models as better ones appear.
Traces show exactly what the agent did and why.
Approval gates for actions that matter.
Long-term memory across sessions, not goldfish chat.
Specialized agents collaborate on bigger jobs.
Agents call real tools: browsers, terminals, APIs.
Download the source and move into the project folder.
git clone https://github.com/raga-ai-hub/RagaAI-Catalyst.git
cd RagaAI-CatalystEvery project documents its own setup; start with install requirements.
cat README.md | head -60Follow the project's launch command — Docker, pip, npm, or a binary release.
# see README for the exact launch commandIt is an open-source project at raga-ai-hub/RagaAI-Catalyst with 3,571 forks. Check the repo's contributors and recent commits to see how active maintenance is.
Apache 2.0 licensed — commercial use allowed with attribution.
Sandboxing, approval gates, and least-privilege credentials.
Builders exist, but code-first frameworks go further.
Model API bills dominate; self-hosted stacks cut that sharply.
AI Agent Assistant & development framework that integrates lots of IM platforms, LLMs, plugins and AI feature, and can be your openclaw alternative. ✨
AI 时代的伯克希尔：基于 Claude Code / Codex 的价值投资研究框架。巴菲特·芒格·段永平·李录四大师方法论 + 多Agent并行研究。| AI-era Berkshire: a value investing research framework built for Claude Code /…
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Free and open — grab the source, star the repo, and start creating.