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Sample: Dozer + LLM + Vector database + Langchain sample #1690
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/bounty $250 |
💎 $250 bounty • Dozer DataSteps to solve:
Additional opportunities:
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/attempt #1690 |
@drrosa you can create a PR on dozer-samples repo |
Okay, I'll do that. Thanks! |
Note: The user @drrosa is already attempting to complete issue #1690 and claim the bounty. If you attempt to complete the same issue, there is a chance that @drrosa will complete the issue first, and be awarded the bounty. We recommend discussing with @drrosa and potentially collaborating on the same solution versus creating an alternate solution. |
/attempt #1690 Options |
Hi @drrosa and @snork-alt is this issue is still open? |
Hi @snork-alt Is the bounty is still live? Can you please assign the issue to me? |
@snork-alt is this issue still active? |
A few days ago we published an article (https://getdozer.io/blog/llm-chatbot) describing how Dozer could improve hyper-personalization when used together with LLMs, Vector databases, and Langchain.
The article describes a hypothetical bank implementing an LLM-based chatbot and leveraging Dozer to create a unified customer profile and later on passing it to an LLM as a context to hyper-personalize the chatbot.
Based on this article, a complete working sample must be produced. Dozer should be configured to source from multiple datasets (like customer profiles, transactions, etc) and Dozer APIs to be integrated with langchain. A similar use case (as described in the article) of credit card products should be built.
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