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Streamlit vs Gradio – A Guide to Building Dashboards in Python

Analytics Vidhya

Introduction Machine Learning is a fast-growing field, and its applications have become ubiquitous in our day-to-day lives. As the demand for ML models increases, so makes the demand for user-friendly interfaces to interact with these models.

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Vitech uses Amazon Bedrock to revolutionize information access with AI-powered chatbot

AWS Machine Learning Blog

To serve their customers, Vitech maintains a repository of information that includes product documentation (user guides, standard operating procedures, runbooks), which is currently scattered across multiple internal platforms (for example, Confluence sites and SharePoint folders). streamlit==1.28.0 streamlit-extras==0.3.4

AI 91
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Build Streamlit apps in Amazon SageMaker Studio

AWS Machine Learning Blog

Developing web interfaces to interact with a machine learning (ML) model is a tedious task. With Streamlit , developing demo applications for your ML solution is easy. Streamlit is an open-source Python library that makes it easy to create and share web apps for ML and data science.

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Build a contextual chatbot application using Knowledge Bases for Amazon Bedrock

AWS Machine Learning Blog

This architecture includes the following steps: A user interacts with the Streamlit chatbot interface and submits a query in natural language This triggers a Lambda function, which invokes the Knowledge Bases RetrieveAndGenerate API. You need to clone the GitHub repository to your local machine.

AWS 93
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Build a powerful question answering bot with Amazon SageMaker, Amazon OpenSearch Service, Streamlit, and LangChain

AWS Machine Learning Blog

In this post we provide a step-by-step guide with all the building blocks for creating an enterprise ready RAG application such as a question answering bot. Figure 1: Architecture Step-by-step explanation: The User provides a question via the Streamlit web application. The API Gateway provides the response to the Streamlit application.

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Automate chatbot for document and data retrieval using Agents and Knowledge Bases for Amazon Bedrock

AWS Machine Learning Blog

Our unstructured data comes from the Amazon EC2 User Guide for Linux Instances and Amazon EC2 Instance Types documentation, and the structured data is derived from the EC2 Instance On-Demand Pricing for the US East (N. Virginia) AWS Region. The following diagram illustrates the solution architecture. xlarge instance to $24.78

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Learn AI Together — Towards AI Community Newsletter #7

Towards AI

The AI Tutor can help with your questions as you learn about topics such as building LLM apps (including training and fine-tuning LLMs), working with Langchain, LlamaIndex, agents, and the Deep Lake vector database, and lots of insights on advanced RAG techniques! Learn AI Together Community section! Share it in the thread on Discord.

AI 101