Flipboard

MARCH 31, 2025

The following illustration describes the components of an agentic AI system: Overview of CrewAI CrewAI is an enterprise suite that includes a Python-based open source framework. Amazon Bedrock manages prompt engineering, memory, monitoring, encryption, user permissions, and API invocation.

LLM 177

LLM Automation Generative AI AI Automation 177

Marktechpost

MARCH 26, 2025

Traditional security methods, such as model training and prompt engineering, have shown limited effectiveness, underscoring the urgent need for robust defenses. A custom Python interpreter enforces these fine-grained security policies, monitoring data provenance and ensuring compliance through explicit control-flow constraints.

LLM 88

LLM Metadata Large Language Models Prompt Engineer 88

AWS Machine Learning Blog

JANUARY 28, 2025

By documenting the specific model versions, fine-tuning parameters, and prompt engineering techniques employed, teams can better understand the factors contributing to their AI systems performance. This record-keeping allows developers and researchers to maintain consistency, reproduce results, and iterate on their work effectively.

LLM 101

LLM Large Language Models ML Algorithm 101

AWS Machine Learning Blog

OCTOBER 24, 2024

Try metadata filtering in your OpenSearch index. Try using query rewriting to get the right metadata filtering. The retriever isn’t at fault, the problem is with FM generation (evaluated by a human or LLM): Try prompt engineering to mitigate hallucinations. If none of the above help: Consider training a custom embedding.

Chatbots 87

Chatbots Metadata Generative AI LLM 87

IBM Journey to AI blog

JULY 17, 2023

offers a Prompt Lab, where users can interact with different prompts using prompt engineering on generative AI models for both zero-shot prompting and few-shot prompting. These Slate models are fine-tuned via Jupyter notebooks and APIs. To bridge the tuning gap, watsonx.ai

Machine Learning 186

Machine Learning Metadata Automation AI 186

AWS Machine Learning Blog

MAY 7, 2024

This post walks through examples of building information extraction use cases by combining LLMs with prompt engineering and frameworks such as LangChain. Prompt engineering Prompt engineering enables you to instruct LLMs to generate suggestions, explanations, or completions of text in an interactive way.

Prompt Engineer 120

Prompt Engineer Prompt Engineering Large Language Models LLM 120

AWS Machine Learning Blog

JUNE 25, 2024

Operational efficiency Uses prompt engineering, reducing the need for extensive fine-tuning when new categories are introduced. Prerequisites This post is intended for developers with a basic understanding of LLM and prompt engineering. A prompt is natural language text describing the task that an AI should perform.

Automation 123

Automation Prompt Engineer Prompt Engineering Categorization 123

AWS Machine Learning Blog

MAY 30, 2024

The workflow for NLQ consists of the following steps: A Lambda function writes schema JSON and table metadata CSV to an S3 bucket. The wrapper function reads the table metadata from the S3 bucket. The wrapper function creates a dynamic prompt template and gets relevant tables using Amazon Bedrock and LangChain.

Metadata 128

Metadata Generative AI LLM Prompt Engineer 128

AWS Machine Learning Blog

MAY 30, 2024

Additionally, VitechIQ includes metadata from the vector database (for example, document URLs) in the model’s output, providing users with source attribution and enhancing trust in the generated answers. Prompt engineering Prompt engineering is crucial for the knowledge retrieval system. langsmith==0.0.43

Chatbots 127

Chatbots Prompt Engineer Prompt Engineering Large Language Models 127

Unite.AI

JANUARY 23, 2024

Prompting Rather than inputs and outputs, LLMs are controlled via prompts – contextual instructions that frame a task. Prompt engineering is crucial to steering LLMs effectively. Hybrid retrieval combines dense embeddings and sparse keyword metadata for improved recall.

Large Language Models 100

Large Language Models Prompt Engineering Prompt Engineer LLM 100

Flipboard

NOVEMBER 24, 2023

This use case highlights how large language models (LLMs) are able to become a translator between human languages (English, Spanish, Arabic, and more) and machine interpretable languages (Python, Java, Scala, SQL, and so on) along with sophisticated internal reasoning.

ETL 158

ETL Prompt Engineer Prompt Engineering Generative AI 158

The MLOps Blog

JUNE 27, 2023

For example, if your team is proficient in Python and R, you may want an MLOps tool that supports open data formats like Parquet, JSON, CSV, etc., The platform also offers features for hyperparameter optimization, automating model training workflows, model management, prompt engineering, and no-code ML app development.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

AWS Machine Learning Blog

SEPTEMBER 15, 2023

Tools can take a variety of forms, such as API calls, Python functions, or webhook-based plugins. Often, these LLMs require some metadata about available tools (descriptions, yaml, or JSON schema for their input parameters) in order to output tool invocations. We use prompt engineering only and Flan-UL2 model as-is without fine-tuning.

LLM 126

LLM Prompt Engineer Prompt Engineering Large Language Models 126

AWS Machine Learning Blog

OCTOBER 24, 2023

Refer to our GitHub repository for detailed Python notebooks and a step-by-step walkthrough. For example, we can follow prompt engineering best practices to fine-tune an LLM to format dates into MM/DD/YYYY format, which may be compatible with a database DATE column.

IDP 136

IDP LLM Prompt Engineer Prompt Engineering 136

Bugra Akyildiz

MARCH 16, 2024

You can change the response for the models in the following way: ==baseline You can reverse a list in Python using the built-in `reverse()` method or slicing. You can reverse a list in Python using the built-in reverse() method or slicing. You can use the reverse method to reverse a list in Python. Here's how you can do it [.]

Metadata 59

Metadata Machine Learning LLM Python 59

Heartbeat

JANUARY 19, 2024

As prompt engineering is fundamentally different from training machine learning models, Comet has released a new SDK tailored for this use case comet-llm. In this article you will learn how to log the YOLOPandas prompts with comet-llm, keep track of the number of tokens used in USD($), and log your metadata.

LLM 52

LLM Metadata Prompt Engineering Prompt Engineer 52

AWS Machine Learning Blog

JULY 24, 2024

You can customize the model using prompt engineering, Retrieval Augmented Generation (RAG), or fine-tuning. You can create workflows with SageMaker Pipelines that enable you to prepare data, fine-tune models, and evaluate model performance with simple Python code for each step.

LLM 127

LLM ML Generative AI Machine Learning 127

Unite.AI

AUGUST 4, 2023

In this article, we will delve deeper into these issues, exploring the advanced techniques of prompt engineering with Langchain, offering clear explanations, practical examples, and step-by-step instructions on how to implement them. Prompts play a crucial role in steering the behavior of a model.

Prompt Engineering 245

Prompt Engineering Prompt Engineer Python NLP 245

ODSC - Open Data Science

OCTOBER 6, 2023

Be sure to check out his talk, “ Prompt Optimization with GPT-4 and Langchain ,” there! The difference between the average person using AI and a Prompt Engineer is testing. Most people run a prompt 2–3 times and find something that works well enough.

Prompt Engineering 52

Prompt Engineering Prompt Engineer Python Data Science 52

ODSC - Open Data Science

JULY 26, 2024

You’ll also be introduced to prompt engineering, a crucial skill for optimizing AI interactions. You’ll explore data ingestion from multiple sources, preprocessing unstructured data into a normalized format that facilitates uniform chunking across various file types, and metadata extraction.

Data Scientist 52

Data Scientist Robotics Data Science Metadata 52

Heartbeat

SEPTEMBER 19, 2023

Comet’s LLMOps tool provides an intuitive and responsive view of our prompt history. Prompt Playground: With the LLMOps tool comes the new Prompt Playground, which allows Prompt Engineers to iterate quickly with different Prompt Templates and understand the impact on different contexts.

Large Language Models 52

Large Language Models Metadata LLM Data Scientist 52

Heartbeat

FEBRUARY 8, 2024

LangChain is an open-source framework, available in Python and Javascript libraries, that enables users to build applications using LLMs. Think of LangChain as a toolbox for Python and Javascript that provides ready-to-use building blocks for working with language models. The rest are optional like prompt template, metadata, tags, etc.

Conversational AI 52

Conversational AI Chatbots LLM Prompt Engineering 52

Heartbeat

JANUARY 26, 2024

In this experiment, I’ll use Comet LLM to record prompts, responses, and metadata for each memory type for performance optimization purposes. Make sure you’ve installed the necessary Python packages in requirements.txt and have your OpenAI API and Comet API keys ready. It seems to be a problem with the zipper.

Metadata 52

Metadata LLM OpenAI Chatbots 52

AWS Machine Learning Blog

APRIL 16, 2024

Jupyter notebooks can differentiate between SQL and Python code using the %%sm_sql magic command, which must be placed at the top of any cell that contains SQL code. This command signals to JupyterLab that the following instructions are SQL commands rather than Python code.

Data Scientist 115

Data Scientist Generative AI Machine Learning ML 115

The MLOps Blog

AUGUST 3, 2023

You essentially divide things up into large tasks and chunks, but the software engineering that goes within that task is the thing that you’re generally gonna be updating and adding to over time as your machine learning grows within your company or you have new data sources, you want to create new models, right? To figure it out.

ML 52

ML Data Scientist Software Engineer Machine Learning 52

Bugra Akyildiz

JULY 4, 2024

OneTwo is a Python library designed to simplify interactions with large (language and multimodal) foundation models, primarily aimed at researchers in prompting and prompting strategies. Define prompts as python functions with type hints and docstrings. Metadata, callbacks, and data format conversions.

LLM 52

LLM Python Data Analysis Automation 52

Heartbeat

DECEMBER 15, 2023

This is where BeautifulSoup, a Python library, comes into play. Using the newspaper library, a Python package tailored for news extraction, performs a more refined retrieval. This method returns a list of separators appropriate for programming languages like Python, Java, C++, etc.

AI Chatbots 52

AI Chatbots LLM Chatbots NLP 52

AWS Machine Learning Blog

NOVEMBER 29, 2023

After the selection of the model(s), prompt engineers are responsible for preparing the necessary input data and expected output for evaluation (e.g. input prompts comprising input data and query) and define metrics like similarity and toxicity. The following diagram illustrates this architecture. name: "llama2-7b-finetuned".

LLM 108

LLM Data Scientist Algorithm Generative AI 108

IBM Journey to AI blog

OCTOBER 30, 2024

The enhanced metadata supports the matching categories to internal controls and other relevant policy and governance datasets. The platform incorporates the innovative Prompt Lab tool, specifically engineered to streamline prompt engineering processes. Furthermore, watsonx.ai

Prompt Engineer 238

Prompt Engineer Prompt Engineering ETL Machine Learning 238

AWS Machine Learning Blog

FEBRUARY 3, 2025

By using a combination of transcript preprocessing, prompt engineering, and structured LLM output, we enable the user experience shown in the following screenshot, which demonstrates the conversion of LLM-generated timestamp citations into clickable buttons (shown underlined in red) that navigate to the correct portion of the source video.

UX Design 96

UX Design Auto-complete LLM Prompt Engineer 96