Model choice tends to change faster than application boundaries, so the boundary should stay stable.
Documented goal
The resume describes a LangChain prompt-chaining chatbot with memory and a Flask API decoupled from the LangChain pipeline.
Why separation helps
The UI and API can remain stable while prompts, memory logic, or the underlying model changes.
What hot-swappable means
The external API contract stays stable; it does not mean every model is interchangeable without quality validation.
What to measure
Compare latency, quality, memory continuity, and operational cost across backends to make flexibility a measurable property.
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Related work and reading
LLM Conversational Chatbot
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AI Developer / ML Engineer building end-to-end AI systems from research to production, with a focus on multimodal AI, LLM applications, retrieval, MLOps, and systems engineering. He is based in Rawalpindi, Pakistan and is the founder of GROVE SYSTEMS.