realtimex_toolkit 1.0.0

Lightweight internal utilities for LLM provider configuration and credential management

RealtimeX Internal Utilities

Lightweight internal library providing utilities for LLM provider configuration and credential management across RealtimeX internal services.

Installation

# Using uv (recommended)
uv pip install -e /path/to/realtimex-toolkit

# Using pip
pip install -e /path/to/realtimex-toolkit

Quick Start

LLM Provider Configuration

from realtimex import configure_provider, get_provider_env_vars

# Configure provider (sets environment variables)
env_vars = configure_provider("openai")

# Get provider env vars without setting them
env_vars = get_provider_env_vars("openai")

# With explicit providers
env_vars = configure_provider(
    "openai",
    providers={"openai": {"OPEN_AI_KEY": "sk-..."}}
)

Credential Management

Retrieve encrypted credentials from the RealtimeX app backend and decrypt them for use across RealtimeX ecosystem services.

from realtimex import get_credential

# Simplest usage - just the credential ID
# Connects to local RealtimeX backend (http://localhost:3001) by default
credential = await get_credential("credential-id")
print(credential["payload"])  # {"name": "API_KEY", "value": "secret-value"}

# With API key for authenticated requests
credential = await get_credential("credential-id", api_key="service-api-key")

# With custom backend URL (for non-default configurations)
credential = await get_credential(
    "credential-id",
    api_key="service-api-key",
    base_url="http://custom-host:3001"  # Override default localhost:3001
)

# For long-running services, use CredentialManager directly
from realtimex import CredentialManager

# Connects to http://localhost:3001 by default
manager = CredentialManager(api_key="service-api-key")
try:
    bundle = await manager.get("credential-id")
    # Credentials are cached automatically
    bundle_again = await manager.get("credential-id")  # Returns cached

    # Force refresh from backend
    fresh_bundle = await manager.get("credential-id", force_refresh=True)
finally:
    await manager.close()

Configuration:

• base_url: Base URL of the RealtimeX app backend (default: http://localhost:3001)
• api_key: Authentication token for backend API requests (optional)
• Credentials are encrypted using AES-256-CBC and decrypted using keys from ~/.realtimex.ai/Resources/server/.env.development

Return shape (get_credential):

{
    "credential_id": str,
    "name": str,
    "credential_type": str,
    "payload": dict[str, str],
    "metadata": dict | None,
    "updated_at": str | None,
}

Supported LLM Providers

• Major Providers: OpenAI, Anthropic, Azure OpenAI
• Cloud AI: Google Gemini, AWS Bedrock
• Alternative APIs: Groq, Cohere, Mistral, Perplexity
• Open Source Aggregators: Open Router, Together AI, Fireworks AI
• Emerging: DeepSeek, xAI, Novita
• Local Deployment: Ollama, LocalAI, LM Studio, KoboldCPP
• Custom: Generic OpenAI, LiteLLM, Nvidia NIM, Hugging Face

Development

# Install with dev dependencies
uv pip install -e ".[dev]"

# Run tests
pytest

# Run type checking
mypy src/realtimex

# Format & lint
ruff check src/realtimex tests
ruff format src/realtimex tests

Architecture

• realtimex.llm: LLM provider configuration utilities
• realtimex.credentials: Secure credential retrieval and decryption
• realtimex.api: HTTP client with retry logic and error mapping
• realtimex.utils: Internal utilities (path resolution, logging)

License

Proprietary - Internal use only