3 Ways to Save AI Chat History in Bubble.io (Pros & Cons)
Learn three proven methods for saving AI chat history in your Bubble.io apps: Context Window, Follow-up Prompt, and RAG using Pinecone. This Bubble.io tutorial breaks down the pros and cons of each approach for building no-code AI chatbots with conversation memory.
What You'll Learn
Context Window Reality: Even with million-token limits, AI models lose track of information in the middle and costs skyrocket as conversations grow exponentially with each user message.
Follow-up Prompt Framework: Save 98% on API costs by using expensive models for answers but cheap models to distill chat history into learner profiles that carry forward into every conversation.
Pinecone Vector Search: Implement semantic search using embeddings to retrieve relevant conversation history by meaning, not just keywords but choose integrated embeddings models to unlock hybrid search and skip extra API steps.
