patchy631/ai-engineering-hub
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
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Build applications that make decisions (chatbots, agents, simulations, etc...). Monitor, trace, persist, and execute on your own infrastructure.
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Latest capture 2026-07-17 04:41
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pyproject.toml
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website/package.json
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examples/adaptive-crag/requirements.txt
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examples/custom-serde/requirements.txt
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examples/deep-researcher/requirements.txt
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examples/email-assistant/requirements.txt
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In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
AI agents, automations and apps that run your operations. Model agnostic.
🧊 Open source LLM observability platform. One line of code to monitor, evaluate, and experiment. YC W23 🍓
Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
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, and conversational systems.
Production-grade platform for building agentic IM bots - 生产级多平台智能机器人开发平台/ Agent、知识库编排、插件系统 / Bots for Discord / Slack / LINE / Telegram / WeChat(企业微信, 企微智能机器人, 公众号) / 飞书 / 钉钉 / QQ / Matrix e.g. Integrated with ChatGPT(GPT), DeepSeek, Dify, n8n, Langflow, Coze, Claude, Gemini, GLM, Ollama, SiliconFlow, Moonshot, openclaw / hermes agent, deerflow
https://burr.apache.org/
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