You should add @nebiusaistudio for Open Source LLMS and @heygibsonai Memori for Memory!
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Sounds like you're diving into some complex stuff! Keep pushing those boundaries.
You missed @AgoraIO in the Level 0 infrastructure. Their Conversational AI Engine makes it so easy to orchestrate voice-to-voice AI, whether you’re running OpenAI realtime or cascading with specific STT/LLM/TTS components.
Once you have cognee, it’s so simple to build on the rest! cognee ships with native connectors/adapters for at least one tool in every layer. Try it! github.com/topoteretes/co…
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Comprehensive visualization! The layered architecture shows how modern RAG systems need both solid infrastructure (Modal, Fireworks) and smart orchestration (LangChain, AutoGen). The key is choosing the right combination for your specific use case.
This is a comprehensive stack overview! How would you recommend balancing tool selection across these layers for a startup vs. enterprise deployment? Which combinations have you found most effective for real-world applications?
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