Kailash Core SDK - Foundational Skills

Comprehensive guide to Kailash Core SDK fundamentals for workflow automation and integration.

Features

The Core SDK provides the foundational building blocks for creating custom workflows with fine-grained control:

• 110+ Workflow Nodes: Pre-built nodes for AI, API, database, file operations, logic, and more
• WorkflowBuilder API: String-based workflow construction with type safety
• Dual Runtime Support: AsyncLocalRuntime (Docker/FastAPI) and LocalRuntime (CLI/scripts)
• Advanced Patterns: Cyclic workflows, conditional execution, error handling
• MCP Integration: Built-in Model Context Protocol support
• Parameter Passing: Flexible data flow between nodes
• Zero Configuration: Auto-detection of runtime context
• Production Ready: Enterprise features including monitoring, validation, and debugging

Quick Start

from kailash.workflow.builder import WorkflowBuilder
from kailash.runtime.local import LocalRuntime

workflow = WorkflowBuilder()
workflow.add_node("NodeName", "id", {"param": "value"})
runtime = LocalRuntime()
results, run_id = runtime.execute(workflow.build())

Reference Documentation

Getting Started

• workflow-quickstart - Create basic workflows with WorkflowBuilder
• kailash-installation - Installation and setup guide
• kailash-imports - Import patterns and module organization

Core Patterns

• node-patterns-common - Common node usage patterns
• connection-patterns - Linking nodes and data flow
• param-passing-quick - Parameter passing strategies
• runtime-execution - Executing workflows (sync/async)

Advanced Topics

• async-workflow-patterns - Asynchronous workflow execution
• cycle-workflows-basics - Cyclic workflow patterns
• error-handling-patterns - Error management strategies
• switchnode-patterns - Conditional routing with SwitchNode
• pythoncode-best-practices - PythonCode node best practices
• mcp-integration-guide - Model Context Protocol integration

Key Concepts

WorkflowBuilder Pattern

• String-based node API: workflow.add_node("NodeName", "id", {})
• Always call .build() before execution
• Never workflow.execute(runtime) - always runtime.execute(workflow.build())

Runtime Selection

• AsyncLocalRuntime: For Docker/FastAPI (async contexts) - async-first, no threading, 10-100x faster
• LocalRuntime: For CLI/scripts (sync contexts) - synchronous execution with thread support
• get_runtime(): Auto-detection helper that selects appropriate runtime based on context

Both runtimes return identical structure: (results, run_id) tuple.

Runtime Architecture

Both LocalRuntime and AsyncLocalRuntime inherit from BaseRuntime with shared capabilities:

BaseRuntime Foundation:

• 29 configuration parameters (debug, enable_cycles, conditional_execution, connection_validation, etc.)
• Execution metadata management
• Common initialization and validation modes (strict, warn, off)

Shared Mixins:

• CycleExecutionMixin: Cyclic workflow execution with validation
• ValidationMixin: Workflow structure validation (5 methods)
• ConditionalExecutionMixin: Conditional execution and branching with SwitchNode support

AsyncLocalRuntime-Specific:

• WorkflowAnalyzer for optimal execution strategy
• Level-based parallelism for concurrent execution
• Thread pool for sync nodes without blocking
• Semaphore control to prevent resource exhaustion

Critical Rules

• ✅ ALWAYS: runtime.execute(workflow.build())
• ✅ String-based nodes: workflow.add_node("NodeName", "id", {})
• ✅ 4-parameter connections: (source_id, source_param, target_id, target_param)
• ✅ Docker/FastAPI: Use AsyncLocalRuntime (mandatory)
• ✅ CLI/Scripts: Use LocalRuntime
• ❌ NEVER: workflow.execute(runtime)
• ❌ NEVER: Instance-based nodes
• ❌ NEVER: Use LocalRuntime in Docker (causes hangs)

When to Use This Skill

Use this skill when you need to:

• Create custom workflows from scratch
• Understand workflow fundamentals
• Learn node patterns and connections
• Set up runtime execution
• Handle errors in workflows
• Implement cyclic or async patterns
• Integrate with MCP
• Get started with Kailash SDK

Related Skills

• 02-dataflow - Database operations framework built on Core SDK
• 03-nexus - Multi-channel platform framework built on Core SDK
• 04-kaizen - AI agent framework built on Core SDK
• 06-cheatsheets - Quick reference patterns
• 08-nodes-reference - Complete node reference
• 09-workflow-patterns - Industry workflow templates
• 17-gold-standards - Mandatory best practices

Support

For complex workflows or debugging, invoke:

• pattern-expert - Workflow patterns and cyclic debugging
• sdk-navigator - Find specific nodes or patterns
• testing-specialist - Test workflow implementations