Creating an Assistant
Learn how to design, configure, and bring your first assistant to life by combining nodes into a functional whole.
The Creation Process
Creating an AI assistant in BlueCoral is like building a coral reef—you start with individual nodes and gradually connect them to form something beautiful and functional. The process involves planning, building, testing, and refining.
Planning Phase
Define what your assistant should do, what nodes it needs, and how they should interact with each other.
Building Phase
Assemble your nodes, configure their settings, and establish the connections between them.
Step-by-Step Creation
Define Your Assistant's Purpose
Start by clearly defining what you want your assistant to accomplish. What problem should it solve? What tasks should it perform?
Example: "I want an assistant that can help me research topics, summarize articles, and generate content outlines for my blog posts."
Choose Your Nodes
Select the appropriate nodes that will give your assistant the capabilities it needs. Consider data processing, AI models, and integration nodes.
Data Nodes: Input processing, storage, retrieval
AI Nodes: Language models, analysis, generation
Integration Nodes: APIs, external tools, workflows
Configure Node Settings
Each node needs to be configured with the right parameters, API keys, and behavior settings to work properly.
Set API keys and authentication
Configure input/output formats
Adjust model parameters
Set rate limits and timeouts
Connect Your Nodes
Establish the flow of data between nodes. This defines how information moves through your assistant and how decisions are made.
Connection Types: Sequential (step-by-step), Parallel (simultaneous), Conditional (if-then), and Loop (repetitive) connections.
Test and Refine
Test your assistant with real inputs, identify issues, and refine the configuration until it works as expected.
Test with various input types
Check error handling
Optimize performance
Gather user feedback
Best Practices for Creation
Architecture Design
Start simple and add complexity gradually
Use modular design for easy maintenance
Plan for scalability from the beginning
Document your node connections
Configuration
Use environment variables for sensitive data
Set appropriate timeouts and retry limits
Implement proper error handling
Test with realistic data volumes
Common Assistant Patterns
Chat Assistant
Input → Processing → Response generation → Output formatting
Perfect for: Customer support, Q&A systems, personal assistants
Data Processing
Data input → Analysis → Transformation → Visualization/Output
Perfect for: Analytics, reporting, data cleaning, insights
Workflow Automation
Trigger → Action → Decision → Next action → Completion
Perfect for: Task automation, process management, scheduling