Core Concepts
Reasoning
Memory & Retrieval
Agent Types
Design Patterns
Training & Alignment
Frameworks
Tools
Safety & Security
Evaluation
Meta
Core Concepts
Reasoning
Memory & Retrieval
Agent Types
Design Patterns
Training & Alignment
Frameworks
Tools
Safety & Security
Evaluation
Meta
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gptme is a free, open-source AI agent that runs in your terminal, acting as a personal coding copilot with local tools for executing shell commands, Python code, file editing, web browsing, and vision processing. It supports multiple LLM providers and features self-correcting behavior with an extensible plugin architecture.1)2)
ai_agent cli coding terminal local_tools open_source
| Repository | https://github.com/gptme/gptme |
| Website | https://gptme.org |
| Language | Python |
| License | MIT |
| Creator | Erik Bjare (ErikBjare) |
gptme brings AI agent capabilities directly into your terminal with zero cloud dependency for execution. The agent can write code, run shell commands, edit files, browse the web, and analyze images – all locally on your machine. It feeds output back to the AI for iterative self-correction, enabling autonomous task completion from a single prompt. A web UI and server mode extend its capabilities beyond the terminal.
gptme is built with a modular architecture consisting of several interconnected components:
gptme integrates with multiple LLM providers, selectable at startup:
# Clone and install git clone https://github.com/gptme/gptme(([[https://github.com/gptme/gptme|gptme on GitHub]]))(([[https://github.com/ErikBjare/gptme-webui|gptme Web UI]])) cd gptme pip install . # Or install directly pip install gptme # Run the CLI gptme # Start the server for web UI gptme-server # Web UI (separate repo) git clone https://github.com/ErikBjare/gptme-webui cd gptme-webui npm install npm run dev
# Start interactive session (prompts for provider and API key on first use) gptme # Send a prompt directly gptme "Build a modern React to-do app" # The agent will: # 1. Generate code # 2. Execute shell commands (npx create-react-app, npm install) # 3. Edit component files # 4. Run the dev server # 5. Self-correct based on output
The agent uses a generate-execute-feedback loop: each step's output feeds back into the AI for the next iteration, enabling autonomous multi-step task completion.