Harvey Configuration Reference

Overview

Harvey uses a workspace-local configuration system. All configuration files live inside the workspace — the directory where Harvey is launched. A HARVEY.md file in the workspace root provides the system prompt, and environment variables supply cloud provider API keys.

Configuration Sources

┌─────────────────────────────────────────────────────────────┐
│                    CONFIGURATION SOURCES                    │
├─────────────────────────────────────────────────────────────┤
│  1. Workspace Config         <workspace>/agents/harvey.yaml │
│  2. System Prompt            <workspace>/HARVEY.md          │
│  3. Environment Variables    Shell environment              │
└─────────────────────────────────────────────────────────────┘

Precedence: Workspace config > System prompt > Environment variables

Configuration Files

1. Configuration (<workspace>/agents/harvey.yaml)

Purpose: Workspace-level configuration for Harvey’s subsystems: knowledge base, sessions, skills, RAG stores, and model cache.

Locations: Workspace: <workspace>/agents/harvey.yaml

Format: YAML

Example:

# Knowledge base
knowledge_db: "agents/knowledge.db"

# Session recordings
sessions_dir: "agents/sessions"

# Skills/agents directory
agents_dir: "agents"

# Auto-record setting (null = use default)
auto_record: true

# Model capability cache
model_cache_db: "agents/model_cache.db"

# RAG configuration
rag:
  enabled: true
  active: "default"
  stores:
    - name: "default"
      db_path: "agents/rag/default.db"
      embedding_model: "nomic-embed-text"
      model_map:
        "llama3.1:latest": "nomic-embed-text"
        "granite-code:3b": "nomic-embed-text"
        "mistral:latest": "nomic-embed-text"
    - name: "deno_typescript"
      db_path: "agents/rag/deno_typescript.db"
      embedding_model: "nomic-embed-text"
      model_map:
        "llama3.1:latest": "nomic-embed-text"

Top-Level Fields:

RAG Configuration (rag:):

RAG Store Fields:

Important Notes: - Paths are relative to the workspace root - The model_map ensures each generation model uses the correct embedding model - Embedding model binding is enforced: you cannot mix embeddings from different models in the same store

Security Configuration:

The following fields control Harvey’s security features and are also persisted in harvey.yaml by the /safemode, /permissions, and related commands.

Default allowed_commands: ls, cat, grep, head, tail, wc, find, stat, jq, htmlq, bat, batcat

Timeout format (run_timeout, ollama_timeout): Go duration string or plain integer seconds. Examples: "5m", "300", "1m30s", "300s". ollama_timeout should be left unset (no timeout) for local hardware where inference can take several minutes.

permissions map — keys are path prefixes relative to the workspace root; values are lists of allowed actions (read, write, exec, delete). Harvey checks the most specific matching prefix. Default is full access to ..

permissions:
  ".":           [read, write, exec, delete]   # workspace root — full access
  "docs/":       [read]                         # docs tree — read-only
  "scripts/":    [read, exec]                   # scripts — run but not modify

Permission rules: - Prefix "." matches all paths (used as the catch-all default). - A more specific prefix (longer string) takes priority over a shorter one. - If no prefix matches, access is denied (secure by default). - The /permissions REPL command updates these settings and persists them.

Example harvey.yaml with security settings:

safe_mode: true
allowed_commands:
  - ls
  - cat
  - grep
  - git

run_timeout: "5m"
ollama_timeout: ""   # no timeout for local Ollama

permissions:
  ".":      [read, write, exec, delete]
  "docs/":  [read]

2. Route configuration (<workspace>/agents/routes.json)

Purpose: Persists routing endpoints and routing state across Harvey sessions.

Location: <workspace>/agents/routes.json

Format: JSON

Example:

{
  "enabled": true,
  "endpoints": [
    {
      "name": "pi2",
      "url": "ollama://192.168.1.12:11434",
      "model": "llama3.1:8b",
      "kind": "ollama"
    },
    {
      "name": "claude",
      "url": "anthropic://",
      "model": "claude-3-haiku",
      "kind": "anthropic"
    },
    {
      "name": "pi3",
      "url": "ollama://192.168.1.13:11434",
      "model": "mistral:latest",
      "kind": "ollama"
    }
  ]
}

Fields:

Endpoint Fields:

URL Schemes:

Commands: - /route add NAME URL [MODEL] — Register a new endpoint - /route rm NAME — Remove an endpoint - /route list — List all endpoints with status - /route on — Enable routing globally - /route off — Disable routing globally - /route status — Show routing state

3. System Prompt (<workspace>/HARVEY.md)

Purpose: Provides the system prompt for Harvey’s LLM interactions. This is the primary way to give the model context about your project, conventions, and guidelines.

Location: <workspace>/HARVEY.md (loaded from the workspace root at startup)

Format: Markdown with optional dynamic markers

Example:

You are Harvey, a terminal coding agent. You are working in a Go project
located at /home/user/myproject.

## Project Context

Today: <!-- @date -->

Current git status:
<!-- @git-status -->

Workspace files:
<!-- @files -->

## Conventions

- Use Go 1.26+ features
- Prefer stdlib over third-party packages
- All exported symbols need doc comments
- Use `t.TempDir()` in tests

## Available Tools

You have access to the following slash commands: /read, /write, /run, /search,
/git, /apply, /clear, /summarize, /context, /kb, /rag, /ollama, /route, /skill.

## Rules

1. Tag code blocks with file paths for auto-apply
2. Use /run to suggest shell commands
3. Never narrate fake command output

Dynamic Markers: Harvey expands these before injecting the system prompt:

Notes: - The prompt is re-injected after /clear - Pinned context (from /context add) is injected after the system prompt - Skills catalog can be injected into the prompt via configuration

Environment Variables

Harvey reads environment variables for cloud provider API keys. These are optional and only needed when using the corresponding route types.

Note: For local Ollama, Harvey uses the ollama command-line tool’s configuration by default. The OLLAMA_HOST environment variable can override the default http://localhost:11434.

Configuration Workflow

Typical Setup Process

# 1. Start Harvey for the first time (creates defaults)
harvey

# 2. Register remote endpoints
harvey
> /route add pi2 ollama://192.168.1.12:11434 llama3.1:8b
harvey
> /route on

# 3. Configure RAG (optional)
harvey
> /rag new golang
harvey
> /rag switch golang
harvey
> /rag on

# 4. Create workspace-specific config
mkdir -p myproject/agents
echo 'knowledge_db: myproject/agents/knowledge.db' > myproject/agents/harvey.yaml

# 5. Run Harvey in the project
harvey -w myproject

Configuration File Precedence Example

Workspace (myproject/agents/harvey.yaml):
  rag:
    enabled: true
    active: golang
    stores:
      - name: golang
        db_path: myproject/agents/rag/golang.db
        embedding_model: nomic-embed-text

Result: In myproject/, the golang store is active.

Troubleshooting

Common Issues

“No routes configured” - Run /route add NAME URL to register endpoints - Run /route on to enable routing - Check <workspace>/agents/routes.json exists

“Knowledge base not found” - Harvey creates it automatically at first use - Check agents/knowledge.db exists - Verify path in harvey.yaml or create the directory

“Model cache not found” - Harvey creates it automatically - Check agents/model_cache.db exists - Run /ollama probe to populate it

“RAG store not found” - Run /rag new NAME to create a store - Run /rag switch NAME to activate it - Verify the database file exists at the specified path

Verification Commands

# Check workspace routes
harvey --help routing  # or: cat agents/routes.json

# Check workspace config
cat agents/harvey.yaml

# Check knowledge base
sqlite3 agents/knowledge.db ".tables"

# Check model cache
sqlite3 agents/model_cache.db "SELECT count(*) FROM models;"

# Check RAG stores
ls -la agents/rag/*.db

Reference: All Configuration Options

Routes (<workspace>/agents/routes.json)

{
  "enabled": true/false,
  "endpoints": [
    {
      "name": "string (required)",
      "url": "string (required)",
      "model": "string (optional)",
      "kind": "string (optional, auto-detected)"
    }
  ]
}

Workspace Agents (<workspace>/agents/harvey.yaml)

# Paths
knowledge_db: "string (optional, default: agents/knowledge.db)"
sessions_dir: "string (optional, default: agents/sessions)"
agents_dir: "string (optional, default: agents)"
model_cache_db: "string (optional, default: agents/model_cache.db)"

# Behavior
auto_record: true/false/null  # null = use default (true)

# RAG Configuration
rag:
  enabled: true/false
  active: "string (store name)"
  stores:
    - name: "string"
      db_path: "string"
      embedding_model: "string"
      model_map:
        "generation-model": "embedding-model"
      embedder_kind: "ollama"  # or "encoderfile"
      embedder_url: "http://host:port"

For more details on specific subsystems, see: - ROUTING.md — Remote endpoint routing - KNOWLEDGE_BASE.md — Knowledge base schema - RAG_Support_Design.md — RAG implementation details - SESSIONS.md — Session recording format