Tag: #llms
21 packages • ⭐ 127,766 total stars
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
🚀 The fast, Pythonic way to build MCP servers and clients.
The SDK For Browser Agents
Structured Outputs
The fullstack MCP framework to develop MCP Apps for ChatGPT / Claude & MCP Servers for AI Agents.
MaiSaka, an LLM-based intelligent agent, is a digital lifeform devoted to understanding you and interacting in the style of a real human. She does not pursue perfection, nor does she seek efficiency;
The PHP Agentic Framework to build production-ready AI driven applications. Connect components (LLMs, vector DBs, memory) to agents that can interact with your data. With its modular architecture it's
Published in CNCF Landscape: A MCP server for Kubernetes.
Give your AI agents persistent memory.
Markdown for the AI era
OramaCore is the complete runtime you need for your projects, answer engines, copilots, and search. It includes a fully-fledged full-text search engine, vector database, LLM interface, and many more u
Safely run untrusted Python code using Pyodide and Deno
FlexRAG: A RAG Framework for Information Retrieval and Generation.
A framework for fine-tuning retrieval-augmented generation (RAG) systems.
Autohand Code CLI - Ultra fast self evolving coding agent that runs in your terminal
This repository contains comprehensive pricing and configuration data for LLMs. It powers cost attribution for 200+ enterprises running 400B+ tokens through Portkey AI Gateway every day.
Monocle is a framework for tracing GenAI app code. This repo contains implementation of Monocle for GenAI apps written in Python.
Model eXecution + Context Protocol: Enterprise-Grade Data-to-AI Infrastructure
ToolAgents is a lightweight and flexible framework for creating function-calling agents with various language models and APIs.
This project implements a comprehensive framework for Knowledge Graph Retrieval Augmented Generation (KG-RAG). It focuses on financial data from SEC 10-Q filings and explores how knowledge graphs can
