Agents
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
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]
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.
💸🤑 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 apps and... See more
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 apps and... See more
GitHub - julep-ai/julep: Open-source alternative to Assistant's API with a managed backend for memory, RAG, tools and tasks. ~Supabase for building AI agents.
📖 Introduction
XAgent is an open-source experimental Large Language Model (LLM) driven autonomous agent that can automatically solve various tasks. It is designed to be a general-purpose agent that can be applied to a wide range of tasks. XAgent is still in its early stages, and we are working hard to improve it.
🏆 Our goal is to create a... See more
XAgent is an open-source experimental Large Language Model (LLM) driven autonomous agent that can automatically solve various tasks. It is designed to be a general-purpose agent that can be applied to a wide range of tasks. XAgent is still in its early stages, and we are working hard to improve it.
🏆 Our goal is to create a... See more
OpenBMB • GitHub - OpenBMB/XAgent: An Autonomous LLM Agent for Complex Task Solving
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
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
GitHub - capjamesg/nanosearch: Build a search engine from a website sitemap.
🤖 Create perpetual chatbots with self-editing memory!
🗃️ Chat with your data - talk to your SQL database or your local files!
📄 You can also talk to docs - for example ask about LlamaIndex!
🗃️ Chat with your data - talk to your SQL database or your local files!
📄 You can also talk to docs - for example ask about LlamaIndex!
cpacker • GitHub - cpacker/MemGPT: Teaching LLMs memory management for unbounded context 📚🦙
The problem I've found with all of them is it is difficult to get consistent solid results that you would want to build around. Even listening to podcasts this seems to be a theme with the people at the forefront of MAS LLMs.
r/AI_Agents - Reddit
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
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