vicode

TUI coding agent for local LLMs. Like Claude Code but runs on your own hardware.

Install

pip install vicode

Quick Start

# Start llama-server with your model
llama-server -m model.gguf -p 8080 --jinja

# Launch vicode in any project directory
cd my-project
vicode

On first run, vicode auto-detects your local LLM server. If none is found, an interactive setup wizard configures your provider (OpenAI, Anthropic, OpenRouter, Groq, or custom endpoint).

Features

• 13 tools: bash, file read/write/edit, grep, glob, ls, web search/fetch, memory, undo, explore, plan
• Supervisor system: Safety guardian validates actions against plans, memory guardian auto-stores learnings, task tracker shows progress
• Persistent memory: Remembers preferences, error fixes, and patterns across sessions (powered by engram)
• Persistent session traces: Stores structured traces for every TUI, CLI, and one-shot prompt session so you can inspect and improve agent behavior later
• Memory consolidation: Learns only from successful sessions, prunes noisy/redundant memories, and can be run as a daily maintenance task
• Sub-agents: Explore and Plan run with isolated context to avoid polluting the main conversation
• Slash commands: /help, /clear, /compact, /init, /undo, /model, /provider, /status, /memory, /sessions, /resume, /trace, /learn, /consolidate
• Custom commands: Drop .md files in .vicode/commands/ for project-specific shortcuts
• Provider support: Local (llama-server, Ollama, LM Studio), OpenAI, Anthropic, OpenRouter, Groq

Configuration

• VICODE.md / CLAUDE.md / AGENT.md in project root are loaded into the system prompt
• ~/.vicode/config.json stores provider settings
• vicode --setup to reconfigure provider
• vicode --consolidate-memory --cwd <project> runs daily-style memory cleanup + learning consolidation for one project namespace

Requirements

• Python 3.11+
• A running LLM server (llama-server, Ollama) or API key for a cloud provider