It is a terminal-based integrated AI environment designed to build, test, and instruct AI agents. Instrukt allows users to create, manage, and interact with AI agents directly from the terminal. These agents are implemented as simple drop-in Python packages that can be extended, shared, and augmented with tools or document indexes. Users can instruct agents using natural language, and for safety, agents run inside secure Docker containers, ensuring tasks are performed in a sandboxed environment.
Instrukt is built with technologies like Langchain, Textual, and Chroma, and supports features such as coding assistance, conversational agents, and document indexing for Retrieval Augmented Generation (RAG). It also includes an in-built IPython console for debugging and introspection. The platform is designed to work with private local LLM models, reducing reliance on external APIs, and supports headless servers or Docker containers with CUDA for GPU acceleration.
To use Instrukt, users need to install it via pip, set their OpenAI API key, and run the application. A configuration file is automatically created at `~/.config/instrukt/instrukt.yml`. The project is open-source under the AGPL license, meaning it can be used freely, but any public instances must provide access to the modified source code. Contributions, feedback, and pull requests are encouraged, and users can support the project through Patreon for early access to features like the Docker agent.
Instrukt aims to make AI accessible and empower users by providing tools that prioritize freedom and minimal reliance on external services. It is a work in progress, with ongoing development and planned features. Users can join the Discord server for updates and support.
Instrukt AI Agent Alternatives
It is a platform designed to build and deploy AI agents that address trust barriers in adopting agentic AI by embedding data protection, policy enforcement, and validation into every agent, ensuring business success.
It is an autonomous AI testing agent designed to simplify and accelerate software testing processes.
It is a framework designed to build modular and scalable Large Language Model (LLM) applications in Rust.
It is an open-source platform designed to enhance AI development by providing tools for tracing, evaluating, and optimizing large language model (LLM) applications in real time.
It is a unified observability and evaluation platform for AI designed to accelerate the development of AI applications and agents while optimizing their performance in production.
It is a comprehensive platform and suite of tools designed to provide high-quality data and solutions for training, fine-tuning, and evaluating AI models, particularly for generative AI, government, and enterprise applications.
It is an AI-driven observability platform designed to monitor, analyze, and optimize GitHub Actions workflows by detecting anomalies, identifying root causes, and providing actionable fixes to improve CI pipeline performance and developer productivity.
It is an open-source AI agent platform designed for financial analysis using large language models (LLMs).
It is a framework for programming language models (LMs) rather than relying on traditional prompting methods.
It is an all-in-one platform designed to monitor, debug, and improve production-ready large language model (LLM) applications.
It is an all-in-one developer platform designed to support every phase of the lifecycle of LLM-powered applications, whether built with LangChain or not.
It is a terminal-based platform designed for experimenting with AI-driven software engineering, specifically focusing on code generation and improvement.
It is a comprehensive cloud-based testing platform designed to facilitate manual and automated testing across various browsers, devices, and operating systems.
It is a 124-billion-parameter open-weights multimodal model called Pixtral Large, built on Mistral Large 2, designed to excel in both image and text understanding.
It is a platform designed to build and deploy Generative AI (GenAI) in mission-critical applications, enabling enterprises to create AI Assistants and Agents that deliver accurate, secure, and scalable solutions.
Other AI Agents
It is an AI-powered voice agent platform designed to automate and optimize call operations for businesses.
It is a framework designed to facilitate the deployment of multiple large language model (LLM)-based agents in various applications, primarily offering two frameworks: task-solving and simulation.
It is a framework designed to orchestrate applications powered by autonomous AI agents and Large Language Models (LLMs).
It is a directory or file path typically found in Unix-like operating systems, such as Linux, that is associated with system or application-level processes, often related to agents or daemons.
It is a library designed to embed a developer agent, referred to as a "smol developer," into your own application, enabling human-centric and coherent whole program synthesis.
It is a multi-agent system for AI-driven software development that combines Large Language Models (LLMs) with DevOps tools to convert natural language requirements into working software.
It is a system designed to power the Agent Engine, enabling the transformation of intent into actionable outcomes.
It is an AI-powered platform designed to assist Marketing, Product, and Sales teams in delivering value to clients more efficiently and effectively.
It is a framework designed to unify and optimize human-designed prompt engineering techniques for improving problem-solving capabilities of Large Language Models (LLMs) by representing LLM-based agents as computational graphs.