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LlamaIndex: Augment your LLM Applications with Custom Data Easily

Unite.AI

This approach mitigates the need for extensive model retraining, offering a more efficient and accessible means of integrating private data. But the drawback for this is its reliance on the skill and expertise of the user in prompt engineering.

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Secure a generative AI assistant with OWASP Top 10 mitigation

Flipboard

Sensitive information disclosure is a risk with LLMs because malicious prompt engineering can cause LLMs to accidentally reveal unintended details in their responses. To mitigate the issue, implement data sanitization practices through content filters in Amazon Bedrock Guardrails.

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How Deltek uses Amazon Bedrock for question and answering on government solicitation documents

AWS Machine Learning Blog

Deltek is continuously working on enhancing this solution to better align it with their specific requirements, such as supporting file formats beyond PDF and implementing more cost-effective approaches for their data ingestion pipeline. The first step is data ingestion, as shown in the following diagram. What is RAG?

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Using Agents for Amazon Bedrock to interactively generate infrastructure as code

AWS Machine Learning Blog

Agents for Amazon Bedrock automates the prompt engineering and orchestration of user-requested tasks. After being configured, an agent builds the prompt and augments it with your company-specific information to provide responses back to the user in natural language. Double-check all entered information for accuracy.

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Learn AI Together — Towards AI Community Newsletter #18

Towards AI

It is a roadmap to the future tech stack, offering advanced techniques in Prompt Engineering, Fine-Tuning, and RAG, curated by experts from Towards AI, LlamaIndex, Activeloop, Mila, and more. Building an Enterprise Data Lake with Snowflake Data Cloud & Azure using the SDLS Framework.

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Personalize your generative AI applications with Amazon SageMaker Feature Store

AWS Machine Learning Blog

Another essential component is an orchestration tool suitable for prompt engineering and managing different type of subtasks. Generative AI developers can use frameworks like LangChain , which offers modules for integrating with LLMs and orchestration tools for task management and prompt engineering.

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LlamaIndex vs. LangChain vs. Hugging Face smolagent: A Comprehensive Comparison

Towards AI

However, to unlock their full potential, you often need robust frameworks that handle data ingestion, prompt engineering, memory storage, and tool usage. Introduction Large Language Models (LLMs) have opened up a new world of possibilities, powering everything from advanced chatbots to autonomous AI agents.

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