Agent Libraries

29 Components & Libraries

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Agent Libraries

WrenAI makes your database RAG-ready. Implement Text-to-SQL more accurately and securely.

WrenAI is reimagining how businesses can interact with and leverage their data through LLM by bringing comprehension capabilities to database data structures. WrenAI enriches LLMs with your specific…

Open source Python SDK for agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks like CrewAI, Langchain, and Autogen

AgentOps helps developers build, evaluate, and monitor AI agents. Tools to build agents from prototype to production. Initialize the AgentOps client and automatically get analytics on every LLM call.…

🔮Pythonic App Framework from Future : Build ⚡Blazing Fast , 🤖Self-Modifying Apps!

Build apps —effortlessly and quickly ⚡. It simplifies Pythonic development for everything from backends to frontends (yes, visually 🦚stunning frontends in Python!), AI integrations, APIs, and beyond—…

🚀🎬 ShortGPT - Experimental AI framework for youtube shorts / tiktok channel automation

Follow the installation steps below for running the web app locally (running the google Colab is highly recommanded). Please read "installation-notes.md" for more details. We hope you find ShortGPT h…

🪢 Open source LLM engineering platform. Observability, metrics, evals, prompt management, testing -- 🍊YC W23 🤖 integrate via Typescript, Python, OpenAI, Langchain, LlamaIndex, Litellm

Managed deployment by the Langfuse team, generous free-tier (hobby plan), no credit card required. You may want to use another integration to get started quickly or implement a use case that we do no…

AGiXT is a dynamic AI Agent Automation Platform that seamlessly orchestrates instruction management and complex task execution across diverse AI providers. Combining adaptive memory, smart features, and a versatile plugin system, AGiXT delivers efficient and comprehensive AI solutions.

AGiXT is a dynamic Artificial Intelligence Automation Platform engineered to orchestrate efficient AI instruction management and task execution across a multitude of providers. Our solution infuses a…

A framework to empower forecasting using Large Language Models (LLMs)

Given the stochastic nature of large language models, individual data points may vary. However, if a sufficient number of agents are employed, the generated models can effectively support comparative…

⚡ Langchain apps in production using Jina & FastAPI

Give us a ⭐ and tell us what more you'd like to see! langchain-serve currently wraps following apps as a service to be deployed on Jina AI Cloud with one command. Integrate autogpt with external ser…

Python client library for improving your LLM app accuracy

⚡ Unified LLM data management to drive accuracy at scale ⚡ A one-line Python integration to manage your LLM data. Use Log10 to log both closed and open-source LLM calls. It helps you: Log10 offers va…

ChatArena (or Chat Arena) is a Multi-Agent Language Game Environments for LLMs. The goal is to develop communication and collaboration capabilities of AIs.

Multi-Agent Language Game Environments for LLMs ChatArena is a library that provides multi-agent language game environments and facilitates research about autonomous LLM agents and their social inter…

ChatArena (or Chat Arena) is a Multi-Agent Language Game Environments for LLMs. The goal is to develop communication and collaboration capabilities of AIs.

🤖️ an AI chat Telegram bot can Web Search Powered by GPT, Claude2.1/3, Gemini and Groq using Python on Zeabur, fly.io and Replit.

The ChatGPT Telegram Bot is a powerful Telegram bot that utilizes the latest GPT models, including GPT3.5, GPT4, GPT4 Turbo, GPT4 Vision, DALLE 3, Groq Mixtral-8x7b/LLaMA2-70b and the official Claude…

A parallel framework for population-based multi-agent reinforcement learning.

MALib is a parallel framework of population-based learning nested with reinforcement learning methods, such as Policy Space Response Oracle, Self-Play, and Neural Fictitious Self-Play. MALib provides…

An open, minimalist Gymnasium environment for autonomous coordination in wireless mobile networks.

mobile-env supports multi-agent and centralized reinforcement learning policies. It provides various choices for rewards and observations. mobile-env is also easily extendable, so that anyone may add…

Dynamic multi-cell selection for cooperative multipoint (CoMP) using (multi-agent) deep reinforcement learning

Multi-Agent Deep Reinforcement Learning for Coordinated Multipoint in Mobile Networks Three variants: DeepCoMP (central agent), DD-CoMP (distributed agents using central policy), D3-CoMP (distributed…

A python interface for training Reinforcement Learning bots to battle on pokemon showdown

You can also clone the latest master version with: Dependencies and development dependencies can then be installed with:

OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.

OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games. OpenSpiel supports n-player (single- and multi- agent) zero-sum, …

OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.

DynamiteNSM is a free Network Security Monitor developed by Dynamite Analytics to enable network visibility and advanced cyber threat detection

Checkout our comprehensive documentation complete with tutorials, guides, and example quickstart deployments.

Python implementation of a bunch of multi-robot path-planning algorithms.

This repository consists of the implementation of some multi-agent path-planning algorithms in Python. The following algorithms are currently implemented: Install the necessary dependencies by runnin…

Implementing Reinforcement Learning, namely Q-learning and Sarsa algorithms, for global path planning of mobile robot in unknown environment with obstacles. Comparison analysis of Q-learning and Sarsa

RL Algorithms implemented in Python for the task of global path planning for mobile robot. Such system is said to have feedback. The agent acts on the environment, and the environment acts on the age…

Deep Reinforcement Learning (DRL) agents applied to medical images

Deep Reinforcement Learning (DRL) agents applied to medical images tensorpack-medical requires: New contributors of any experience level are very welcomed You can clone the latest version of the sour…

Loki.Rat is a fork of the Ares RAT, it integrates new modules, like recording , lockscreen , and locate options. Loki.Rat is a Python Remote Access Tool.

Loki.Rat is made of two main programs: The Web interface can be run on any server running Python. The agent[Payload] can be compiled to native executables using pyinstaller. Install The Loki.Rat Open…

List of major web + mobile browser user agent strings. +1 Bonus script to scrape :)

Pytorch LSTM RNN for reinforcement learning to play Atari games from OpenAI Universe. We also use Google Deep Mind's Asynchronous Advantage Actor-Critic (A3C) Algorithm. This is much superior and efficient than DQN and obsoletes it. Can play on many games

Asynchronous Advantage Actor-Critic (A3C) The A3C algorithm was released by Google’s DeepMind group earlier this year, and it made a splash by essentially obsoleting DQN. It was faster, simpler, more…

Deep & Classical Reinforcement Learning + Machine Learning Examples in Python

We provide here a suite of Python examples that walk you through concepts in: Classical & Deep Reinforcement Learning Basic & Advanced Machine Learning Anson Wong

Python agent for AWS Lambda metrics, tracing, profiling & analytics

This package provides analytics and distributed tracing for event-driven applications running on AWS Lambda. From your project directory: Your folder structure for the function should look similar to…

Mesa is an open-source Python library for agent-based modeling, ideal for simulating complex systems and exploring emergent behaviors.

Mesa allows users to quickly create agent-based models using built-in core components (such as spatial grids and agent schedulers) or customized implementations; visualize them using a browser-based …

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