Add notebook for integration of BentoML and Milvus to implement RAG #1290
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bootcamp/RAG/zilliz_bento_RAG.ipynb
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Since this is a demo about Zilliz Cloud + BentoCloud. Let's replace all usage of Milvus to Zilliz Cloud (except for function names such as MilvusClient()).
E.g.,
In this demo, we show how to use open-source embedding model and LLM on BentoCloud with vector database on Zilliz Cloud to build a RAG application.
BentoCloud offers serverless infrastructure tailored for model inference, operating in conjunction with BentoML, an open-source model serving framework, to facilitate the easy creation and deployment of high-performance model services. Zilliz Cloud is fully-managed service for open-source vector database - Milvus, with flexible pricing and ease of management. You can sign-up for free on BentoCloud and Zilliz Cloud. Later we will use the API keys from both services to finish the demo.
On BentoCloud, you can setup model services in Deployments, and the corresponding END_POINT and API are located in Playground -> Python. On Zilliz Cloud, we can get endpoint and token in Cluster Details.
After we get API credentials from both platform and the corresponding endpoint, we can start to do RAG!
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bootcamp/RAG/zilliz_bento_RAG.ipynb
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I fix it to "Bento_Zilliz_RAG"
bootcamp/RAG/zilliz_bento_RAG.ipynb
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bootcamp/RAG/zilliz_bento_RAG.ipynb
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bootcamp/RAG/zilliz_bento_RAG.ipynb
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Line #9. for embedding in embedding_split:
- make sure
embedding_splitis a list of embeddings - replace line 9 & 10 with
embeddings += embedding_split
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