py-orc

Getting Started

  • Getting Started
    • What is Orchestrator?
    • Core Concepts
      • Pipelines
      • Tasks
      • AUTO Tags
      • Tools
    • Quick Start Example
    • Key Features in Action
      • Input-Agnostic Design
      • Tool Integration
      • Model Selection
    • Next Steps
  • Installation
    • Requirements
      • System Requirements
      • Optional Requirements
    • Installation Methods
      • Using pip (Recommended)
      • Using conda
      • Using Docker
      • Development Installation
    • Model Setup
      • Ollama Models (Recommended)
      • HuggingFace Models
      • OpenAI/Anthropic Models
    • Tool Dependencies
      • Web Tools
      • System Tools
      • Data Tools
    • Configuration
      • Environment Variables
    • Verifying Installation
    • Troubleshooting
      • Common Issues
      • Getting Help
    • Next Steps
  • Quickstart
    • Your First Pipeline
      • Step 1: Create the Pipeline Definition
      • Step 2: Run the Pipeline
      • Step 3: Check the Results
    • Building More Complex Pipelines
      • Research Report Pipeline
    • Working with Tools
      • Available Tool Actions
    • Using AUTO Tags
    • Pipeline Composition
    • Error Handling
    • Debugging Pipelines
    • Best Practices
    • Next Steps
  • Key Concepts
    • Pipelines
      • Input-Agnostic Design
    • Tasks
      • Task Anatomy
      • Task Dependencies
    • Templates and References
      • Template Syntax
      • Runtime vs Compile-Time Resolution
    • AUTO Tags
      • How AUTO Tags Work
    • Tools and Actions
      • Tool Categories
      • Action Names
      • Automatic Tool Detection
    • Models and Intelligence
      • Model Types
      • Intelligent Model Selection
    • State Management
      • Checkpointing
      • Recovery
    • Control Systems
      • Built-in Control Systems
      • Custom Control Systems
    • Pipeline Composition
      • Pipeline Imports
      • Modular Design
    • Error Handling
      • Error Strategies
      • Error Types
    • Performance Concepts
      • Parallel Execution
      • Caching
      • Resource Management
    • Security Concepts
      • Sandboxing
      • Input Validation
      • Secret Management
    • Best Practices
      • Design Principles
      • Pipeline Organization
      • Testing Strategy
    • Next Steps

User Guide

  • Tutorials
    • Web Research Automation
      • What You’ll Build
      • Prerequisites
      • Tutorial 1: Basic Web Search
        • Step 1: Create the Pipeline
        • Step 2: Run the Pipeline
        • Step 3: Understanding the Results
      • Tutorial 2: Multi-Source Research
        • Step 1: Multi-Source Pipeline
        • Step 2: Run Multi-Source Research
      • Tutorial 3: Fact-Checking Pipeline
        • Step 1: Fact-Checker Pipeline
        • Step 2: Use the Fact-Checker
      • Tutorial 4: Automated Report Generator
        • Step 1: Report Generator Pipeline
        • Step 2: Generate Professional Reports
      • Advanced Exercises
        • Exercise 1: Industry Monitor
        • Exercise 2: Competitive Intelligence
        • Exercise 3: Research Aggregator
      • Solutions
      • Next Steps
      • Tips for Production Use
    • Data Processing Pipelines
      • What You’ll Build
      • Prerequisites
      • Tutorial 1: Basic ETL Pipeline
        • Step 1: Create the ETL Pipeline
        • Step 2: Run the ETL Pipeline
      • Tutorial 2: Multi-Source Data Integration
        • Step 1: Multi-Source Integration Pipeline
        • Step 2: Run Multi-Source Integration
      • Tutorial 3: Data Quality Assessment Pipeline
        • Step 1: Data Quality Pipeline
      • Tutorial 4: Real-Time Data Processing
        • Step 1: Real-Time Processing Pipeline
      • Advanced Examples
        • Example 1: Customer Data Platform
        • Example 2: Financial Data Pipeline
      • Exercises
        • Exercise 1: E-commerce Analytics Pipeline
        • Exercise 2: IoT Data Processing
        • Exercise 3: Social Media Analytics
      • Solutions and Next Steps
      • Best Practices for Production
    • Tutorial Overview
      • Beginner Tutorials
      • Intermediate Tutorials
      • Advanced Tutorials
    • What You’ll Learn
    • Prerequisites
    • Tutorial Format
    • Getting Help
    • Ready to Start?

API Reference

  • API Reference
    • Overview
      • Core Module (core)
      • Compiler Module (compiler)
      • Models Module (models)
      • Tools Module (tools)
      • Orchestrator Module (orchestrator)
    • Quick Reference
      • Core Classes
        • orchestrator.Task
        • orchestrator.Pipeline
        • orchestrator.Orchestrator
        • orchestrator.YAMLCompiler
        • orchestrator.ModelRegistry
      • Main Functions
        • orchestrator.init_models
        • orchestrator.compile
        • orchestrator.compile_async
      • Key Exceptions
    • Usage Examples
      • Basic Usage
      • Advanced Usage
    • Type Annotations
    • Environment Variables
    • Configuration
    • Performance Considerations
      • Model Loading
      • Memory Management
    • Error Handling
    • Debugging
    • Extension Points
      • Custom Control Systems
      • Custom Tools
      • Custom Models
    • Thread Safety
    • Testing
    • Troubleshooting
      • Common Issues
    • Getting Help
py-orc
  • Overview: module code

All modules for which code is available

  • orchestrator
    • orchestrator.compiler.yaml_compiler
    • orchestrator.core.pipeline
    • orchestrator.core.task
    • orchestrator.models.model_registry
    • orchestrator.orchestrator

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