Release 3.13

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What’s New

• Seamless Deployment Integration: Invoke any Orq Deployment directly from your n8n workflows
• Knowledge Base Search: Search through Knowledge Bases and retrieve relevant content.
• 1,000+ App Connections: Connect your LLM applications with popular tools including databases, APIs, CRMs, messaging platforms, and more.

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Use Cases

• Automate content generation workflows across multiple platforms.
• Build intelligent data processing pipelines with RAG-enabled Deployments.
• Orchestrate complex multi-step AI workflows with conditional logic.
• Integrate LLM outputs with CRMs, databases, and notification systems.

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Getting Started

1. Install the Orq Deployment node in your n8n instance (requires owner permissions).
2. Configure authentication with your Orq.ai API Key.
3. Add a Orq Deployment node or Knowledge Base node to your n8n workflow.
4. Connect with other n8n nodes to build complete automations

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What’s new

• HTTP Tools – External API integrations with templating & authentication.
• URL templates with {{parameter}} substitution
• Support for HTTP methods (GET, POST, PUT, DELETE, etc.)
• Custom headers (including authentication)
• Parameter definitions with types, descriptions, default values
• Control over which parameters are visible to the LLM (send_to_model)
• Function Tools – Define tool schemas via API (same as in the UI).
• OpenAPI-style schemas for custom business logic
• Function name, description, parameters
• Strict parameter validation
• Optional manual approval before execution
• Code Tools (Python) – Run custom Python code in a secure sandbox.
• Define parameters in JSON Schema
• Access params variable for LLM-provided inputs
• Supports return value processing & error handling
• Fully isolated execution environment

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Key Features

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Persistent & Isolated Memory

• Entity-based Isolation: Use entity_id to scope memory per user, session, or organization.
• Multi-Tenant Support: Secure separation of data across entities.

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Structured Memory Storage

• Memory Stores: Named containers for storing different types of contextual data.
• Built-in Tools: Automatic read, write, and query operations for seamless integration.

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Agent Memory Workflow

• Discover First: Agents must use retrieve_memory_stores to discover available memory before interacting with them.
• Query Smartly: Once discovered, use query_memory_store to fetch relevant information before responding.
• System Prompt Guidance: Example:

“Use retrieve_memory_stores to see what memory stores are available, then use query_memory_store to search for relevant information before responding.”

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Streaming & Entity Tracking

• Streaming Support: Use entity_id for real-time memory tracking during ongoing conversations.

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Key Features

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Built on Modern Standards

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Intelligent Memory & Context

• Memory Stores: Persistent context across conversations with entity-based isolation.
• Knowledge Base: Ground responses in your data with dynamic discovery and querying

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Multi-Modal Processing

• File Processing - Handle images and PDFs with support varying per given model
• Search & Web Scraping - Bring in real-time insights with built-in search and scraping tools

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Flexible Tool Ecosystem

• HTTP Tools - Seamless external API integrations with parameter templating and authentication
• Function Tools - Custom business logic and access to internal systems with OpenAI function calling schema validation
• Code Tools - Custom Python logic and transformations in secure sandbox environments

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Architecture

• Multi-Agent Systems - Build sophisticated hierarchies with specialized sub-agents and intelligent delegation.
• Synchronous and streaming endpoints for different use cases.

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Example

curl --location 'https://my.orq.ai/v2/agents/stream-run' \
--header 'Content-Type: application/json' \
--header 'Authorization: $ORQ_API_KEY' \
--data '{
"key": "simple-agent-1",
"role": "Assistant",
"description": "A helpful assistant for general tasks",
"instructions": "Be helpful and concise",
"settings": {
"max_iterations": 3,
"max_execution_time": 300,
"tools": [
{
"type": "current_date"
}
]
},
"message": {
"role": "user",
"parts": [
{
"kind": "text",
"text": "What'\''s today'\''s date and day of the week?"
}
]
},
"model": "openai/gpt-4o",
"path": "Default/agents",
"memory_stores": [],
"team_of_agents": []
}'