Configuring Agent Brain

Installation and configuration for Agent Brain document search with pluggable providers.

Quick Setup
Prerequisites
Installation
Provider Configuration
Project Initialization
Verification
When Not to Use
Reference Documentation

Quick Setup

Option A: Local with Ollama (FREE, No API Keys)

# 1. Install packages
pip install agent-brain-rag agent-brain-cli

# 2. Install and start Ollama
brew install ollama  # macOS
ollama serve &
ollama pull nomic-embed-text
ollama pull llama3.2

# 3. Configure for Ollama
export EMBEDDING_PROVIDER=ollama
export EMBEDDING_MODEL=nomic-embed-text
export SUMMARIZATION_PROVIDER=ollama
export SUMMARIZATION_MODEL=llama3.2

# 4. Initialize and start
agent-brain init
agent-brain start
agent-brain status

Option B: Cloud Providers (Best Quality)

# 1. Install packages
pip install agent-brain-rag agent-brain-cli

# 2. Configure API keys
export OPENAI_API_KEY="sk-proj-..."       # For embeddings
export ANTHROPIC_API_KEY="sk-ant-..."     # For summarization (optional)

# 3. Initialize and start
agent-brain init
agent-brain start
agent-brain status

Validation: After each step, verify success before proceeding to the next.

Prerequisites

Required

Python 3.10+: Verify with python --version
pip: Python package manager

Provider-Dependent

OpenAI API Key: Required for OpenAI embeddings
Ollama: Required for local/private deployments (no API key needed)

System Requirements

~500MB RAM for typical document collections
~1GB RAM with GraphRAG enabled
Disk space for ChromaDB vector store

Installation

Standard Installation

pip install agent-brain-rag agent-brain-cli

Verify installation succeeded:

agent-brain --version

Expected: Version number displayed (e.g., 3.0.0 or current version)

With GraphRAG Support

pip install "agent-brain-rag[graphrag]" agent-brain-cli
# Kuzu backend (optional):
pip install "agent-brain-rag[graphrag-kuzu]" agent-brain-cli

Enable GraphRAG (server)

export ENABLE_GRAPH_INDEX=true            # Master switch (default: false)
export GRAPH_STORE_TYPE=simple            # or kuzu
export GRAPH_INDEX_PATH=./graph_index
export GRAPH_USE_CODE_METADATA=true       # Extract from AST metadata
export GRAPH_USE_LLM_EXTRACTION=true      # Use LLM extractor when available
export GRAPH_MAX_TRIPLETS_PER_CHUNK=10    # Triplet cap per chunk
export GRAPH_TRAVERSAL_DEPTH=2            # Default traversal depth
export GRAPH_EXTRACTION_MODEL=claude-haiku-4-5

Add the same values to your .env if you prefer file-based config.

Virtual Environment (Recommended)

python -m venv .venv
source .venv/bin/activate  # macOS/Linux
pip install agent-brain-rag agent-brain-cli

Installation Troubleshooting

Problem	Solution
`pip not found`	Run `python -m ensurepip`
Permission denied	Use `pip install --user` or virtual env
Module not found after install	Restart terminal or activate venv
Wrong Python version	Use `python3.10 -m pip install`

Counter-example - Wrong approach:

# DO NOT use sudo with pip
sudo pip install agent-brain-rag  # Wrong - creates permission issues

Correct approach:

pip install --user agent-brain-rag  # Correct - user installation
# OR use virtual environment

Provider Configuration

Agent Brain supports pluggable providers with two configuration methods.

Method 1: Configuration File (Recommended)

Create a config.yaml file in one of these locations:

Project-level: .claude/agent-brain/config.yaml
User-level: ~/.agent-brain/config.yaml
XDG config: ~/.config/agent-brain/config.yaml
Current directory: ./config.yaml or ./agent-brain.yaml

# ~/.agent-brain/config.yaml
server:
  url: "http://127.0.0.1:8000"
  port: 8000

project:
  state_dir: null  # null = use default (.claude/agent-brain)

embedding:
  provider: "openai"
  model: "text-embedding-3-large"
  api_key: "sk-proj-..."  # Direct key, OR use api_key_env
  # api_key_env: "OPENAI_API_KEY"  # Read from env var

summarization:
  provider: "anthropic"
  model: "claude-haiku-4-5-20251001"
  api_key: "sk-ant-..."  # Direct key, OR use api_key_env
  # api_key_env: "ANTHROPIC_API_KEY"

Config file search order: AGENT_BRAIN_CONFIG env → current dir → project dir → user home

Security: If storing API keys in config file:

Set file permissions: chmod 600 ~/.agent-brain/config.yaml
Add to .gitignore: config.yaml
Never commit API keys to version control

Method 2: Environment Variables

Set variables in shell or .env file:

export EMBEDDING_PROVIDER=openai
export EMBEDDING_MODEL=text-embedding-3-large
export SUMMARIZATION_PROVIDER=anthropic
export SUMMARIZATION_MODEL=claude-haiku-4-5-20251001
export OPENAI_API_KEY="sk-proj-..."
export ANTHROPIC_API_KEY="sk-ant-..."

Precedence order: CLI options → environment variables → config file → defaults

Provider Profiles

Fully Local with Ollama (No API Keys)

Best for privacy, air-gapped environments:

Config file (~/.agent-brain/config.yaml):

embedding:
  provider: "ollama"
  model: "nomic-embed-text"
  base_url: "http://localhost:11434/v1"

summarization:
  provider: "ollama"
  model: "llama3.2"
  base_url: "http://localhost:11434/v1"

Or environment variables:

export EMBEDDING_PROVIDER=ollama
export EMBEDDING_MODEL=nomic-embed-text
export SUMMARIZATION_PROVIDER=ollama
export SUMMARIZATION_MODEL=llama3.2

Prerequisite: Ollama must be installed and running with models pulled.

Cloud (Best Quality)

Config file:

embedding:
  provider: "openai"
  model: "text-embedding-3-large"
  api_key: "sk-proj-..."

summarization:
  provider: "anthropic"
  model: "claude-haiku-4-5-20251001"
  api_key: "sk-ant-..."

Or environment variables:

export OPENAI_API_KEY="sk-proj-..."
export ANTHROPIC_API_KEY="sk-ant-..."

Mixed (Balance Quality and Privacy)

embedding:
  provider: "openai"
  model: "text-embedding-3-large"
  api_key: "sk-proj-..."

summarization:
  provider: "ollama"
  model: "llama3.2"

Verify Configuration

agent-brain verify

Counter-example - Common mistake:

# DO NOT put keys in shell command history
OPENAI_API_KEY="sk-proj-abc123" agent-brain start  # Wrong - key in history

Correct approaches:

# Use config file (keys are in file, not command line)
agent-brain start

# Or use environment from shell profile
export OPENAI_API_KEY="sk-proj-..."  # In ~/.bashrc
agent-brain start

Project Initialization

Initialize Project

Navigate to the project root and run:

agent-brain init

Verify initialization succeeded:

ls .claude/agent-brain/config.json

Expected: File exists

Start Server

agent-brain start

Verify server started:

agent-brain status

Expected output:

Server Status: healthy
Port: 49321
Documents: 0
Mode: project

Index Documents

agent-brain index ./docs

Verify indexing succeeded:

agent-brain status

Expected: Documents count > 0

Test Search

agent-brain query "test query" --mode hybrid

Expected: Search results or "No results" (not an error)

Verification

Full Verification Checklist

Run each command and verify expected output:

agent-brain --version shows version number (7.0.0+)
echo ${OPENAI_API_KEY:+SET} shows "SET" (if using OpenAI)
ls .claude/agent-brain/config.json file exists
agent-brain status shows "healthy"
agent-brain status shows document count > 0
agent-brain query "test" returns results or "no matches"
agent-brain folders list shows indexed folders
agent-brain types list shows file type presets
agent-brain jobs shows job queue (empty or with history)

GraphRAG Verification (if enabled)

echo ${ENABLE_GRAPH_INDEX} shows "true"
agent-brain status --json | jq '.graph_index' shows graph index info
agent-brain query "class relationships" --mode graph returns results or graceful error
agent-brain query "how it works" --mode multi returns fused results

Automated Verification

agent-brain verify

This runs all checks and reports any issues.

Post-Indexing Verification

After indexing documents, verify the pipeline is working:

# Monitor indexing job
agent-brain jobs --watch

# Check job completed successfully
agent-brain jobs <job_id>

# Verify incremental indexing works
agent-brain index ./docs  # Should show eviction summary with unchanged files

# Validate injection scripts before use
agent-brain inject ./docs --script enrich.py --dry-run

When Not to Use

This skill focuses on installation and configuration. Do NOT use for:

Searching documents - Use using-agent-brain skill instead
Query optimization - Use using-agent-brain skill instead
Understanding search modes - Use using-agent-brain skill instead
GraphRAG queries - Use using-agent-brain skill instead

Scope boundary: Once Agent Brain is installed, configured, initialized, and verified healthy, switch to the using-agent-brain skill for search operations.

Common Setup Issues

Issue: Module Not Found

pip install --force-reinstall agent-brain-rag agent-brain-cli

Issue: API Key Not Working

# Test OpenAI key
curl -s https://api.openai.com/v1/models \
  -H "Authorization: Bearer $OPENAI_API_KEY" | head -c 100

Expected: JSON response (not error)

Issue: Server Won't Start

# Check for stale state
rm -f .claude/agent-brain/runtime.json
rm -f .claude/agent-brain/lock.json
agent-brain start

Issue: Ollama Connection Failed

# Verify Ollama is running
curl http://localhost:11434/api/tags

Expected: JSON with model list

Issue: No Search Results

agent-brain status  # Check document count

If count is 0, index documents:

agent-brain index ./docs

Environment Variables Reference

Variable	Required	Default	Description
`AGENT_BRAIN_CONFIG`	No	-	Path to config.yaml file
`AGENT_BRAIN_URL`	No	`http://127.0.0.1:8000`	Server URL for CLI
`AGENT_BRAIN_STATE_DIR`	No	`.claude/agent-brain`	State directory path
`EMBEDDING_PROVIDER`	No	`openai`	Provider: openai, cohere, ollama
`EMBEDDING_MODEL`	No	`text-embedding-3-large`	Model name
`SUMMARIZATION_PROVIDER`	No	`anthropic`	Provider: anthropic, openai, gemini, grok, ollama
`SUMMARIZATION_MODEL`	No	`claude-haiku-4-5-20251001`	Model name
`OPENAI_API_KEY`	Conditional	-	Required if using OpenAI
`ANTHROPIC_API_KEY`	Conditional	-	Required if using Anthropic
`GOOGLE_API_KEY`	Conditional	-	Required if using Gemini
`XAI_API_KEY`	Conditional	-	Required if using Grok
`COHERE_API_KEY`	Conditional	-	Required if using Cohere
`EMBEDDING_CACHE_MAX_MEM_ENTRIES`	No	1000	Max in-memory LRU entries (~12 MB at 3072 dims per 1000 entries)
`EMBEDDING_CACHE_MAX_DISK_MB`	No	500	Max disk size for the SQLite embedding cache

Note: Environment variables override config file values. Config file values override defaults.

Embedding Cache Tuning

The embedding cache is automatic — no setup required. Embeddings are cached on first compute and reused on subsequent reindexes of unchanged content, significantly reducing OpenAI API costs when using file watching or frequent reindexing.

The two cache env vars allow tuning for specific environments:

Large indexes — increase EMBEDDING_CACHE_MAX_MEM_ENTRIES (e.g., 5000) to keep more embeddings in the fast in-memory tier and reduce SQLite lookups
Memory-constrained environments — decrease EMBEDDING_CACHE_MAX_MEM_ENTRIES (e.g., 200) to limit RAM usage; the disk cache still provides cost savings even with a small memory tier
Disk space constrained — decrease EMBEDDING_CACHE_MAX_DISK_MB (e.g., 100) to cap the SQLite cache database size; oldest entries are evicted when the limit is reached

The disk cache uses SQLite with WAL mode for safe concurrent access during indexing operations.

Reference Documentation

Guide	Description
Configuration Guide	Config file format and locations
Installation Guide	Detailed installation options
Provider Configuration	All provider settings
Troubleshooting Guide	Extended issue resolution

Support

Issues: https://github.com/SpillwaveSolutions/agent-brain-plugin/issues
Documentation: Reference guides in this skill

configuring-agent-brain