Harvey

Harvey is an agent REPL written in Go and designed to use Llamafile models or Ollama server to access language models locally. It is a terminal based application.

The Harvey name was inspired by the play of that name by Mary Chase. I saw parallels between the story Harvey and my personal language model agent. Many people think of agents only in the context of very big companies. I think small models running on small or tiny computers are an opportunity. Harvey, is a small agent for small and tiny computers and is a play on a mythic creature. Harvey is a Púca, a software Púca. Harvey can be fun for those who take time for it. It runs on a little computers. Have an adventure and some fun with Harvey.

Security Note

Harvey is experimental — a working proof of concept, not production-ready software. Letting a probabilistic model direct command execution is an inherently risky attack surface; Harvey mitigates this with safe mode, workspace sandboxing, permission checks, audit logging, and security reviews with each release, but the risk is never zero. Don’t use Harvey where the risks might endanger your data, people, or planet. See SECURITY.md for details.

Features

Language Model Support

• Llamafile (primary): register and run local model binaries — no server required
• Ollama: connect to a local Ollama server for broader model selection
• Cloud routes: Anthropic, DeepSeek, Gemini, Mistral, and OpenAI via configured routes
• Multi-model dispatch via @mention and model aliasing; routing feedback shown in spinner

Core Capabilities

• Interactive terminal REPL sandboxed to a workspace directory
• Auto-execute: tagged code blocks in model replies are written to workspace files automatically
• HARVEY.md provides a customizable system prompt per workspace
• Context utilization hint [ctx: N%] in spinner when approaching the model’s context window

Knowledge, Memory & Sessions

• Three-silo memory: RAG vector stores, session-experience memory with rolling summaries, and a SQLite knowledge base
• Sessions recorded as human-readable Fountain screenplay (.spmd) files — replay, continue, or mine them for memories
• Model provenance recorded in session headers for audit and replay accuracy
• Pinned context and conversation summarization to manage the context window

File & Code Support

• Code-aware RAG chunking, documentation extraction, and ANSI syntax highlighting (13 languages)
• Automatic code formatting on write_file: gofmt, clang-format, black, rustfmt, prettier, and built-in Pascal/Oberon/Basic formatters
• PDF text extraction via poppler; image reading via vision-capable model routes
• Remote RAG ingest: s3://, sftp://, scp://, http://, https:// URIs
• File-reference injection: for models that ignore the tools schema, Harvey pre-injects workspace files mentioned in the prompt so they can still work with file content

Extensibility

• SKILL.md skills, bundled skill sets, and multi-step prompt pipelines
• Git integration and per-workspace profile templates

Quick Start

1. Download a llamafile from the Mozilla AI pre-built models page and make it executable

2. Install Harvey: run the installer for your platform

   • Linux/macOS: ./installer.sh
   • Windows: run installer.ps1 in PowerShell

3. Run: harvey

4. Try it:

   harvey > /llamafile add /path/to/model.llamafile
   harvey > /read LICENSE
   harvey > /help

See Getting Started and Installation for detailed instructions.

Platform Support

Harvey runs on: - Linux: x86_64, aarch64, armv7l (including Raspberry Pi OS) - macOS: Intel and Apple Silicon (M1 and above) - Windows: x86_64

Documentation

• User Manual — Main documentation index
• Overview — What Harvey is, why you might use it, and the design philosophy
• Getting Started — First session, keyboard shortcuts, slash commands
• Configuration Reference — harvey.yaml fields and environment variables
• Installation — Get Harvey installed on your system
• Developer Guide — Architecture, conventions, and contributing
• Vision — Philosophy, motivation, and future direction
• About — Project metadata and version information
• GitHub Repository — Source code and issues

Release Notes

• version: 0.0.15

• status: active

• released: 2026-06-26

• /model mode [MODEL] {structured|prose|inject|none}: set or display the tool-execution strategy for a model; persisted in the model cache and survives re-probes

• File-reference injection: when a model does not reliably call tools, Harvey pre-injects the content of workspace files mentioned in the prompt as ### File: blocks

• Cannot-read retry: if a model responds indicating it cannot access a file, Harvey retries once with file content pre-loaded; retry uses RunToolLoop when in structured mode so tool calls are correctly dispatched

• ModelCapability.ToolMode field and ToolMode* constants added to the model cache; tool_mode column migrated automatically on first open

• Bug fix: re-probing a model no longer overwrites a user-set tool mode

• Bug fix: option-2 retry session recording, noToolCalls flag, and RunToolLoop dispatch corrected

• Bug fix: "please provide the file" refusal phrase tightened to avoid spurious retries on benign model responses

Authors

• Doiel, R. S.

Software Requirements

• Llamafile v0.10 models or Ollama plus Ollama models

Software Suggestions

• Go >= 1.26.4
• CMTools >= 0.0.45
• Pandoc >= 3.9
• GNU Make >= 3.8

Getting Help & License

• GitHub Issues — Bug reports and feature requests
• AGPL-3.0 License