Agents
Here are example ways to increase the success rate of these custom agents:
Provide a more focused, use-case specific system prompt to kick things off. Since you know what kinds of goals the agent supports, you can improve the odds of coming up with the right set of tasks initially. In fact, there’s nothing wrong with actually defining the set of... See more
Provide a more focused, use-case specific system prompt to kick things off. Since you know what kinds of goals the agent supports, you can improve the odds of coming up with the right set of tasks initially. In fact, there’s nothing wrong with actually defining the set of... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
In an Agentic UX, an AI agent pulls weight across 3 categories: cognitive, creative, and logistical.
- Cognitive weight — the built-in agent pulls analysis and decision-making weight
- Creative weight — the built-in agent takes on visualization and media creation weight
- Logistical weight — the built-in agent takes tasks on operational and workflow
The agentic era of UX
The two most important problems (at least how I am thinking about them currently), are:
Finding a rigorous scientific framework for how different agent skills, personalities, and instructions combine to be most capable for different problems (think of this as social management science for AI agents) .
Figuring out how you formally validate and verify... See more
Finding a rigorous scientific framework for how different agent skills, personalities, and instructions combine to be most capable for different problems (think of this as social management science for AI agents) .
Figuring out how you formally validate and verify... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
The LLM doesn’t call the tool directly (yet), but it does pass back to the application what functions should be called — and with which parameters. And, now, OpenAI lets multiple function calls be “invoked” at once.
But, this idea is not just about GPT. The open source world is moving towards this model as well.
This Is The Future…It’s Just Not Here... See more
But, this idea is not just about GPT. The open source world is moving towards this model as well.
This Is The Future…It’s Just Not Here... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
In the open-source community, there are huge numbers of people leveraging AutoGen in creative ways, and solving surprising problems. One pattern that we see as fundamental is the "generator+critic" pattern, where one agent generates content (writing, code, etc.) and another agent critiques it (finds bugs, etc.) They can iterate until the solution... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
Adala is an Autonomous DA ta (Labeling) Agent framework.
Adala offers a robust framework for implementing agents specialized in data processing, with an emphasis on diverse data labeling tasks. These agents are autonomous, meaning they can independently acquire one or more skills through iterative learning. This learning process is influenced by... See more
Adala offers a robust framework for implementing agents specialized in data processing, with an emphasis on diverse data labeling tasks. These agents are autonomous, meaning they can independently acquire one or more skills through iterative learning. This learning process is influenced by... See more
HumanSignal • GitHub - HumanSignal/Adala: Adala: Autonomous DAta (Labeling) Agent framework
ht - headless terminal
ht (short for headless terminal ) is a command line program that wraps an arbitrary other binary (e.g. bash , vim , etc.) with a VT100 style terminal interface--i.e. a pseudoterminal client (PTY) plus terminal server--and allows easy programmatic access to the input and output of that terminal (via JSON over stdin/stdout). ht... See more
ht (short for headless terminal ) is a command line program that wraps an arbitrary other binary (e.g. bash , vim , etc.) with a VT100 style terminal interface--i.e. a pseudoterminal client (PTY) plus terminal server--and allows easy programmatic access to the input and output of that terminal (via JSON over stdin/stdout). ht... See more
GitHub - andyk/ht: headless terminal - wrap any binary with a terminal interface for easy programmatic access.
📖 Introduction
ReactAgent is an experimental autonomous agent that uses GPT-4 language model to generate and compose React components from user stories. It is built with React, TailwindCSS, Typescript, Radix UI, Shandcn UI, and OpenAI API.
🚀 Features
ReactAgent is an experimental autonomous agent that uses GPT-4 language model to generate and compose React components from user stories. It is built with React, TailwindCSS, Typescript, Radix UI, Shandcn UI, and OpenAI API.
🚀 Features
- Generate React Components from user stories
- Compose React Components from existing components
- Use a
eylonmiz • GitHub - eylonmiz/react-agent: The open-source React.js Autonomous LLM Agent
Introduction
VT.ai is a multi-modal AI Chatbot Assistant, offering a chat interface to interact with Large Language Models (LLMs) from various providers. Both via remote API or running locally with Ollama.
The application supports multi-modal conversations, seamlessly integrating text, images, and vision processing with LLMs.
[Beta] Multi-modal AI... See more
VT.ai is a multi-modal AI Chatbot Assistant, offering a chat interface to interact with Large Language Models (LLMs) from various providers. Both via remote API or running locally with Ollama.
The application supports multi-modal conversations, seamlessly integrating text, images, and vision processing with LLMs.
[Beta] Multi-modal AI... See more