Agents
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
memary: Open-Source Longterm Memory for Autonomous Agents
memary demo
Why use memary?
Agents use LLMs that are currently constrained to finite context windows. memary overcomes this limitation by allowing your agents to store a large corpus of information in knowledge graphs, infer user knowledge through our memory modules, and only retrieve... See more
memary demo
Why use memary?
Agents use LLMs that are currently constrained to finite context windows. memary overcomes this limitation by allowing your agents to store a large corpus of information in knowledge graphs, infer user knowledge through our memory modules, and only retrieve... See more
GitHub - kingjulio8238/memary: Longterm Memory for Autonomous Agents.
Data
The Semantic Layer
for every data app
Connect data silos, drive consistent metrics, and power your AI and analytics with context.
for every data app
Connect data silos, drive consistent metrics, and power your AI and analytics with context.
Cube — Semantic Layer for Building Data Applications
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.
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
Large Language Model State Machine (llmstatemachine)
Introduction
llmstatemachine is a library for creating agents with GPT-based language models and state machine logic.
Introduction
llmstatemachine is a library for creating agents with GPT-based language models and state machine logic.
- Chat History as Memory : Leverages large context window models, making chat history the primary source of agent memory.
- Custom Python Functions with JSON Generation : Allows the
GitHub - robocorp/llmstatemachine: A Python library for building GPT-powered agents with state machine logic and chat history memory.
AgentTuning: Enabling Generalized Agent Abilities For LLMs
🤗 Model (AgentLM-70B) • 🤗 Dataset (AgentInstruct) • 📃 Paper • 🌐 Project Page
中文版(Chinese)
AgentTuning represents the very first attempt to instruction-tune LLMs using interaction trajectories across multiple agent tasks. Evaluation results indicate that AgentTuning enables the agent... See more
🤗 Model (AgentLM-70B) • 🤗 Dataset (AgentInstruct) • 📃 Paper • 🌐 Project Page
中文版(Chinese)
AgentTuning represents the very first attempt to instruction-tune LLMs using interaction trajectories across multiple agent tasks. Evaluation results indicate that AgentTuning enables the agent... See more
THUDM • GitHub - THUDM/AgentTuning: AgentTuning: Enabling Generalized Agent Abilities for LLMs
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
GitHub - vinhnx/VT.ai: VT.ai - Multi-modal AI Chatbot Assistant
React.js LLM Agent for next generation codingReactAgent 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.