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Add llm chatbot amp
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amp-catalog-cloudera-default.yaml

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name: Cloudera
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entries:
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- title: LLM Chatbot Augmented with Enterprise Data
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label: llm-chatbot
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short_description: |
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Build a Retrieval Augmented Generation (RAG) Question-Answer Large
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Language Model (LLM) Bot with local documents
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long_description: |
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IMPORTANT: Please read the following before proceeding. By configuring and launching this AMP, you will cause h2oai/h2ogpt-oig-oasst1-512-6.9b, which is a third party large language model (LLM), to be downloaded and installed into your environment from the third party’s website. Please see https://huggingface.co/h2oai/h2ogpt-oig-oasst1-512-6.9b for more information about the LLM, including the applicable license terms. If you do not wish to download and install h2oai/h2ogpt-oig-oasst1-512-6.9b, click “cancel” below. By clicking “Configure Project” below, you acknowledge the foregoing statement and agree that Cloudera is not responsible or liable in any way for h2oai/h2ogpt-oig-oasst1-512-6.9b. Author: Cloudera Inc.
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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This AMP builds a Retrieval Augmented Generation (RAG)
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Question-Answer Large Language Model (LLM) Bot application which
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demonstrates how context from local documents can be used with pre-trained
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LLM models to perform context retrieval and chat response
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generation with factual responses.
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image_path: >-
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https://raw.githubusercontent.com/cloudera/CML_AMP_LLM_Chatbot_Augmented_with_Enterprise_Data/main/images/catalog-screenshot.png
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tags:
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- Chatbot
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- LLM
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- Huggingface
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- Generative AI
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- RAG
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- Vector DB
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- Milvus
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- Transformers
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- NLP
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git_url: 'https://github.com/cloudera/CML_AMP_LLM_Chatbot_Augmented_with_Enterprise_Data'
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is_prototype: true
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- title: Churn Modeling with scikit-learn
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label: churn-prediction
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short_description: Build an scikit-learn model to predict churn using customer telco data.

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