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Templates Overview

Templates are complete, runnable BindAI projects that demonstrate common patterns and best practices. Instead of starting from an empty project, you can use templates to learn the framework, experiment with features, or bootstrap new applications. Every template is designed to be practical, self-contained, and easy to modify.

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What are Templates?

A template is a ready-to-run example that showcases a specific BindAI feature or workflow. Templates include:
  • working source code
  • configuration files
  • comments and documentation
  • recommended project structure
You can run a template immediately and use it as the foundation for your own project.

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Why Use Templates?

Templates help you:
  • learn BindAI faster
  • understand best practices
  • explore framework features
  • avoid repetitive setup
  • bootstrap production projects
Rather than reading documentation and writing everything from scratch, you can begin with working examples.

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Template Categories

BindAI templates cover many common scenarios. Examples include:
  • Agent Basics
  • Prompt Management
  • Tool Calling
  • Memory
  • Knowledge Retrieval (RAG)
  • Workflows
  • Conditional Execution
  • Loops
  • Parallel Execution
  • Human Approval
  • Retry Policies
  • Scheduling
  • Multi-Agent Systems
  • API Integrations
Each template focuses on a single concept while remaining fully functional.

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Template Structure

A typical template looks like this.
Some templates include additional files depending on the demonstrated feature.

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Running a Template

Templates can be executed directly.
If the template requires API credentials, configure your environment variables before running it. Example:

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Learning by Example

The recommended learning path is:
Experimenting with working code is often the fastest way to understand a feature.

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Agent Templates

Agent templates demonstrate how to build AI assistants with different capabilities. Examples include:
  • basic assistant
  • structured output
  • streaming responses
  • multiple tools
  • conversation memory
  • retrieval-augmented generation
These templates focus on individual agent behavior.

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Workflow Templates

Workflow templates demonstrate orchestration between multiple execution steps. Examples include:
  • sequential execution
  • conditional branching
  • loops
  • parallel execution
  • human approval
  • retries
  • scheduled workflows
These examples show how to automate more complex business processes.

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Tool Templates

Tool templates demonstrate how agents interact with external systems. Examples include:
  • calculators
  • weather APIs
  • file readers
  • database queries
  • HTTP requests
  • custom business logic
They illustrate both tool creation and automatic tool calling.

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Knowledge Templates

Knowledge templates demonstrate Retrieval-Augmented Generation (RAG). Typical examples include:
  • document search
  • PDF retrieval
  • Markdown knowledge bases
  • semantic search
  • vector databases
These templates show how agents answer questions using external information.

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Production Templates

Some templates demonstrate production-ready architecture. These may include:
  • logging
  • middleware
  • configuration management
  • project organization
  • dependency injection
  • monitoring
They provide a starting point for larger applications.

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Modifying Templates

Templates are intended to be customized. Typical modifications include:
  • changing the language model
  • updating prompts
  • replacing tools
  • adding workflows
  • connecting different providers
  • integrating business logic
They are starting points rather than fixed solutions.

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Best Practices

When working with templates:
  • Start with the simplest example.
  • Run the template before modifying it.
  • Change one feature at a time.
  • Compare different templates to understand framework patterns.
  • Use templates as references for new projects.
  • Keep your customized versions under version control.

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Summary

Templates provide complete, runnable examples for nearly every BindAI feature. They are the fastest way to learn the framework, explore new capabilities, and bootstrap production-ready AI applications with proven project structures and best practices.