Aden Hive is a Python-based agent framework. Configuration is handled through environment variables and agent-level config files. There is no centralized `config.yaml` or Docker Compose setup.
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# Configuration Guide
Aden Hive is a Python-based agent framework. Configuration is handled through environment variables and agent-level config files. There is no centralized `config.yaml` or Docker Compose setup.
## Configuration Overview
```
~/.hive/configuration.json (global defaults: provider, model, max_tokens)
Environment variables (API keys, runtime flags)
Agent config.py (per-agent settings: model, tools, storage)
pyproject.toml (package metadata and dependencies)
.mcp.json (MCP server connections)
```
## Global Configuration (~/.hive/configuration.json)
The `quickstart.sh` script creates this file during setup. It stores the default LLM provider, model, and max_tokens used by all agents unless overridden in an agent's own `config.py`.
```json
{
"llm": {
"provider": "anthropic",
"model": "claude-sonnet-4-5-20250929",
"max_tokens": 8192,
"api_key_env_var": "ANTHROPIC_API_KEY"
},
"created_at": "2026-01-15T12:00:00+00:00"
}
```
The default `max_tokens` value (8192) is defined as `DEFAULT_MAX_TOKENS` in `framework.graph.edge` and re-exported from `framework.graph`. Each agent's `RuntimeConfig` reads from this file at startup. To change defaults, either re-run `quickstart.sh` or edit the file directly.
## Environment Variables
### LLM Providers (at least one required for real execution)
```bash
# Anthropic (primary provider)
export ANTHROPIC_API_KEY="sk-ant-..."
# OpenAI (optional, for GPT models via LiteLLM)
export OPENAI_API_KEY="sk-..."
# Cerebras (optional, used by output cleaner and some nodes)
export CEREBRAS_API_KEY="..."
# Groq (optional, fast inference)
export GROQ_API_KEY="..."
```
The framework supports 100+ LLM providers through [LiteLLM](https://docs.litellm.ai/docs/providers). Set the corresponding environment variable for your provider.
### Search & Tools (optional)
```bash
# Web search for agents (Brave Search)
export BRAVE_SEARCH_API_KEY="..."
# Exa Search (alternative web search)
export EXA_API_KEY="..."
```
### Runtime Flags
```bash
# Run agents without LLM calls (structure-only validation)
export MOCK_MODE=1
# Fernet encryption key for credential store at ~/.hive/credentials
export HIVE_CREDENTIAL_KEY="your-fernet-key"
# Custom agent storage path (default: /tmp)
export AGENT_STORAGE_PATH="/custom/storage"
```
## Agent Configuration
Each agent package in `exports/` contains its own `config.py`:
```python
# exports/my_agent/config.py
CONFIG = {
"model": "anthropic/claude-sonnet-4-5-20250929", # Default LLM model
"max_tokens": 8192, # default: DEFAULT_MAX_TOKENS from framework.graph
"temperature": 0.7,
"tools": ["web_search", "pdf_read"], # MCP tools to enable
"storage_path": "/tmp/my_agent", # Runtime data location
}
```
If `model` or `max_tokens` are omitted, the agent loads defaults from `~/.hive/configuration.json`.
### Agent Graph Specification
Agent behavior is defined in `agent.json` (or constructed in `agent.py`):
```json
{
"id": "my_agent",
"name": "My Agent",
"goal": {
"success_criteria": [...],
"constraints": [...]
},
"nodes": [...],
"edges": [...]
}
```
See the [Getting Started Guide](getting-started.md) for building agents.
## MCP Server Configuration
MCP (Model Context Protocol) servers are configured in `.mcp.json` at the project root:
```json
{
"mcpServers": {
"agent-builder": {
"command": "uv",
"args": ["run", "-m", "framework.mcp.agent_builder_server"],
"cwd": "core"
},
"tools": {
"command": "uv",
"args": ["run", "mcp_server.py", "--stdio"],
"cwd": "tools"
}
}
}
```
The tools MCP server exposes tools including web search, PDF reading, CSV processing, and file system operations.
## Storage
Aden Hive uses **file-based persistence** (no database required):
```
{storage_path}/
runs/{run_id}.json # Complete execution traces
indexes/
by_goal/{goal_id}.json # Runs indexed by goal
by_status/{status}.json # Runs indexed by status
by_node/{node_id}.json # Runs indexed by node
summaries/{run_id}.json # Quick-load run summaries
```
Storage is managed by `framework.storage.FileStorage`. No external database setup is needed.
## IDE Setup
### VS Code
Add to `.vscode/settings.json`:
```json
{
"python.analysis.extraPaths": [
"${workspaceFolder}/core",
"${workspaceFolder}/exports"
]
}
```
### PyCharm
1. Open Project Settings > Project Structure
2. Mark `core` as Sources Root
3. Mark `exports` as Sources Root
## Security Best Practices
1. **Never commit API keys** - Use environment variables or `.env` files
2. **`.env` is git-ignored** - Copy `.env.example` to `.env` at the project root and fill in your values
3. **Use real provider keys in non-production environments** - validate configuration with low-risk inputs before production rollout
4. **Credential isolation** - Each tool validates its own credentials at runtime
## Troubleshooting
### "ModuleNotFoundError: No module named 'framework'"
Install the core package:
```bash
cd core && uv pip install -e .
```
### API key not found
Ensure the environment variable is set in your current shell session:
```bash
echo $ANTHROPIC_API_KEY # Should print your key
```
On Windows PowerShell:
```powershell
$env:ANTHROPIC_API_KEY = "sk-ant-..."
```
### Agent not found
Run from the project root with PYTHONPATH:
```bash
PYTHONPATH=exports uv run python -m my_agent validate
```
See [Environment Setup](./environment-setup.md) for detailed installation instructions.