From the course: Oracle Cloud Infrastructure Generative AI Professional Cert Prep
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Extending a chatbot by adding RAG plus memory - Oracle Cloud Infrastructure Tutorial
From the course: Oracle Cloud Infrastructure Generative AI Professional Cert Prep
Extending a chatbot by adding RAG plus memory
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- [Narrator] In addition to retrieving relevant documents and sending these to the LLM, we also want our chatbot to consider what questions were asked earlier and what responses LLM give as well. For this, we need to pass the chat history to the prompt as well. As we know, we store chat history in memory, so we'll use a type of chain that supports retrieval and memory both. We'll see how do we do this in our next demo.
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Module introduction54s
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Chatbot introduction1m 16s
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Demo: Chatbot7m 25s
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Q&A chatbot architecture and basic components2m 31s
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Models, prompts, and chains4m 15s
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Demo: Set up development environment2m 44s
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Demo: Use prompts, models, and chains10m 22s
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Extending a chatbot by adding memory1m 52s
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Demo: Using memory5m 47s
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Demo: Using memory with Streamlit5m 59s
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Extending a chatbot by adding RAG and a vector database2m 5s
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Demo: RAG: Indexing using a vector database5m 24s
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Demo: RAG: Retrieval and generation using a vector database5m 12s
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Extending a chatbot by adding RAG plus memory45s
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Demo: RAG plus memory plus tracing8m 43s
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Demo: Model evaluation7m 19s
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Chatbot technical architecture1m 41s
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Deploy a chatbot to a VM2m 16s
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Demo: Deploy a chatbot6m 19s
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Deploy a chatbot to OCI Data Science1m 49s
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