Configuration Guide
HelseCLI is highly configurable to suit your workflow. Configuration is handled through environment variables, JSON files, and YAML files.
Configuration Reference
HelseCLI utilizes a multi-layered configuration system to manage system behavior, API integration, and project-specific parameters.
Environment Configuration (.env)
The .env file, located in the application root, manages secure credentials and global environmental flags.
API Integration Keys
| Variable | Description |
|---|---|
OPENAI_API_KEY | Primary credential for OpenAI services. |
ANTHROPIC_API_KEY | Primary credential for Anthropic (Claude) services. |
GOOGLE_API_KEY | Primary credential for Google Vertex AI / Gemini services. |
OLLAMA_BASE_URL | Endpoint for local inference via Ollama (Default: http://localhost:11434). |
Feature-Specific Credentials
| Variable | Description |
|---|---|
TAVILY_API_KEY | Credential for Tavily hyper-search integration. |
BRAVE_API_KEY | Credential for Brave Search API. |
SERPER_API_KEY | Credential for Serper.dev Google Search abstraction. |
E2B_API_KEY | Credential for E2B Cloud sandboxed execution. |
STABILITY_API_KEY | Credential for Stability AI image synthesis. |
System Runtime Settings
| Variable | Description | Default |
|---|---|---|
HELSE_HOME_ENABLED | Enables the interactive home interface. | 1 |
HELSE_DEBUG | Activates verbose diagnostic logging. | 0 |
HELSE_DEFAULT_MODEL | Sets the system-wide default inference model. | gpt-4o |
Configuration Schemas
1. Global System Configuration (~/.helsecli_config.json)
Maintains persistent user preferences across different directory contexts.
- Default inference parameters
- Interface theme specifications
- Interaction history retention policies
2. Local Project Configuration (.helsecli.yaml)
Enables repository-specific overrides and logic tuning.
project_name: "ResearchProjectAlpha"
description: "Statistical analysis and document synthesis workflow"
custom_instructions:
- "Enforce PEP8 compliance for all Python generation"
- "Utilize type-hinting for all function definitions"
verification:
enabled: true
linter: "pylint"
Contextual Instructions
HelseCLI integrates instructions from three primary levels:
- Global Layer: Defined within the system-wide configuration file.
- Project Layer: Resides in
.helsecli.yamlor anAGENTS.mdmanifest. - Session Layer: Volatile instructions injected during runtime via the
/initcommand.
Knowledge Injection via AGENTS.md
Users can deploy an AGENTS.md file in the project root to provide comprehensive architectural context and standard operating procedures for the AI agent.
Model Selection Protocol
The inference model can be modified during an active session using the !m command. This opens the model selection interface, allowing for dynamic switching between configured providers.
Execution Sandboxing
HelseCLI supports three distinct execution environments for code validation:
- Local Host: Direct execution (use with caution).
- Docker: Local containerized isolation.
- E2B: Managed cloud-based sandboxing for maximum security.
These environments are toggled via project configuration or environment-specific variables.