Agents

nanosearch

Nanosearch is an in-memory search engine designed for small (< 10,000 URL) websites.

With Nanosearch, you can build a search engine in a few lines of code.

Nanosearch supports the BM25 and TF/IDF algorithms.

Nanosearch also computes a link graph and uses the number of inlinks to a page as a ranking factor. This is useful for ranking ... See more

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

💸🤑 Announcing our Bounty Program: Help the Julep community fix bugs and ship features and get paid. More details here.

Start your project with conversation history, support for any LLM, agentic workflows, integrations & more.

Explore the docs »

Report Bug · Request Feature · Join Our Discord · X · LinkedIn

Why Julep?

We've built a lot of AI ap... See more

Large Language Model State Machine (llmstatemachine)

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 c

... See more

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 As... See more

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 weig

... See more

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 relevan... See more

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 tas... See more

Self-Operating Computer Framework

A framework to enable multimodal models to operate a computer.

Using the same inputs and outputs of a human operator, the model views the screen and decides on a series of mouse and keyboard actions to reach an objective.

Key Features

• Compatibility : Designed for various multimodal models.


• Integration : Currently

... See more

So right now, LLMs (Large Language Models) are all the rage. But in the future, it’s possible that the way we get things done is composing things with a combination of LLMs, SMMs (Small, Mighty Models), agents and tools.

It’s what I call Cognitive Composition (because it sounds cool and I have a longtime love affair with alliteration).

This is how we... See more