GPTScript
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About
GPTScript is an open-source framework developed by Acorn Labs that enables Large Language Models (LLMs) to operate as functional agents within a computing environment. Unlike traditional LLM interfaces that are confined to text generation, GPTScript bridges the gap between natural language and system execution. It allows users to write scripts in plain English that the LLM interprets to perform complex tasks, such as calling local CLI tools, interacting with OpenAPI-compliant endpoints, or manipulating local file systems. The tool effectively treats system capabilities as modular tools that an AI can discover and use to solve problems. The framework functions as a CLI-based interpreter that processes .gpt files containing a mix of natural language instructions and tool definitions. It features a robust dual-layer caching mechanism designed to optimize performance and minimize API costs. The system caches both Git commit hashes for external tool dependencies and specific LLM responses. Developers can leverage official SDKs for Python, Node.js, and Go, allowing for deep integration into existing application stacks. It also supports persistent chat states and dedicated workspace directories, providing a structured environment for automated workflows and long-running AI interactions. GPTScript is primarily designed for DevOps engineers, software developers, and system administrators who want to automate repetitive tasks using the reasoning capabilities of LLMs. It is particularly useful for creating custom AI assistants that need to interact with internal private tools or complex API ecosystems without writing extensive boilerplate code. Because it is platform-agnostic and supports various model providers, it offers a level of transparency and local-first utility that is well-suited for professional technical environments. By simplifying the way LLMs interact with external systems, it allows teams to build sophisticated automation agents with minimal coding overhead.
Pros & Cons
Enables LLMs to execute local CLI commands and manipulate files directly.
Reduces API costs and latency through a dual-layer caching system for prompts and tools.
Supports seamless integration with any OpenAPI-compliant endpoint using natural language.
Provides official SDKs for major languages including Python, Node.js, and Go.
Allows for persistent AI sessions by saving and loading chat states to JSON files.
Requires a separate OpenAI API key to function, which may incur external costs.
Unauthenticated GitHub requests for tools are subject to low rate limits without a Personal Access Token.
SDKs for Python, Node, and Go are currently under rapid development and may undergo breaking changes.
Caching is less effective in active chat modes because every message hash affects the lookup.
Use Cases
DevOps engineers can create AI assistants to troubleshoot and manage local infrastructure through a simple CLI interface.
Software developers can integrate LLM capabilities into their existing Python or Node.js applications using the provided SDKs.
System administrators can automate complex workflows involving multiple APIs and local file manipulations using plain English scripts.
Data analysts can interact with local datasets and directories to perform file-based operations through a conversational interface.
Platform
Task
Features
• persistent chat state saving
• workspace directory isolation
• git-based tool management
• llm response caching
• python, node, and go sdks
• openapi schema integration
• local cli interaction
• natural language scripting
FAQs
How do I install GPTScript if I do not have Homebrew?
Users on macOS and Linux can install the tool using a standalone shell script via curl. Alternatively, users on any supported system can download the specific architecture archive from the official GitHub releases page.
Does GPTScript have an SDK for programmatic integration?
Yes, there are currently maintained SDKs for Python, Node.js, and Go. These libraries are under rapid development and allow you to integrate GPTScript functionality directly into your own applications.
How does the caching system work in GPTScript?
GPTScript caches both Git commit hashes for external tools and LLM responses to a chat completion request. This speeds up execution and reduces API costs by avoiding redundant network calls and model computations.
Can I save a chat session and resume it at a later time?
Yes, you can use the --save-chat-state-file flag to export the session to a JSON file. To resume, simply run the script again using the --chat-state flag pointing to that saved file.
Why am I encountering rate limits when pulling tools from GitHub?
By default, GPTScript makes unauthenticated requests to GitHub, which have low rate limits. To resolve this, set the GITHUB_AUTH_TOKEN environment variable to your personal access token.
Pricing Plans
Open Source
Free Plan• Full CLI access
• Python, Node, and Go SDKs
• Local and remote tool integration
• OpenAPI support
• LLM response caching
• Workspace management
• Persistent chat states
• GitHub community support
Job Opportunities
There are currently no job postings for this AI tool.
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Ratings & Reviews
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