gptme — AI Agent Framework: Live Stats & TrendScore

Live GitHub stats, community sentiment, and trend data for gptme. TrendingBots tracks star velocity, fork activity, and what developers are saying — updated from real data sources.

GitHub data synced: May 6, 2026 • Sentiment updated: Apr 24, 2026

GitHub Statistics

Community Sentiment

Community Buzz: I've used chatgpt-shell, but I have since turned my LLM usage to gptel inside org-mode buffers, said a HackerNews user, while another Reddit user noted 'Eu prefiro a imagem nb2'

Pros & Cons

What People Love

Private and persistent chats, Reddit users praise the flexibility of gptme

Common Complaints

Error sending images, Quillbot detector issues

Biggest Positive: Private chats

Biggest Negative: Error sending images

Why gptme Stands Out

gptme stands out from other AI agent frameworks due to its focus on local, free, and open-source development, providing an alternative to proprietary solutions like Claude Code and Codex. Its plugin system, context compression, and subagent planner mode enable flexible and efficient agent creation. By leveraging gptme's features, such as background jobs, form tools, and content-addressable storage, users can build custom agents tailored to their specific needs. The project's active development and community-driven approach ensure that gptme remains a cutting-edge solution for AI agent development.

Built With

Build a personal AI assistant that automates daily tasks — gptme's CLI interface and plugin system enable easy integration with various tools and services, Build a research agent that reads and summarizes academic papers — gptme's natural language processing capabilities and context generation features facilitate efficient information extraction, Build a web scraping agent that extracts data from websites — gptme's web browsing tool and morph editing capabilities allow for fast and accurate data collection, Build a coding agent that writes and edits code — gptme's code generation and editing features, combined with its terminal access, enable rapid development and testing, Build an autonomous agent that performs tasks independently — gptme's autonomous agent features, such as run loops and context generation, allow for creating self-sustaining agents

Getting Started

  1. Install gptme using pip: `pip install gptme`
  2. Configure gptme by running `gptme config` and following the prompts
  3. Initialize a new agent using `gptme init`
  4. Start the gptme server with `gptme start`
  5. Try interacting with your agent using the `gptme interact` command to verify it works

About

Your agent in your terminal, equipped with local tools: writes code, uses the terminal, browses the web. Make your own persistent autonomous agent on top!

Official site: https://gptme.org/docs/

Category & Tags

Category: social

Tags: agent, agents, ai-agents, ai-assistant, anthropic, chatbot, chatgpt, cli, code-generation, llamacpp, llm, llm-agent, llm-apps, openai, openrouter, rag

Market Context

Competing with chatgpt-shell and other LLM tools