[FEATURE] Load Agentic Configurations from a Dictionary #142
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vawsgit
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Comprehensive ConfigLoader tutorial implementation covering the entire ecosystem: Tutorial Structure: - 01-tool-loading.ipynb - Tool configuration and loading fundamentals - 02-agent-loading.ipynb - Agent configuration with models, tools, structured output - 03-agents-as-tools.ipynb - Agent-as-Tool patterns for nested agent workflows - 04-swarm-loading.ipynb - Multi-agent swarm coordination and configuration - 05-graph-loading.ipynb - Graph-based agent workflows with nodes, edges, conditions - 06-structured-output-config.ipynb - Advanced structured output configuration - 07-swarms-as-tools.ipynb - Swarm-as-Tool patterns for complex workflows - 08-graphs-as-tools.ipynb - Graph-as-Tool patterns for reusable graph components Configuration Files: - tools.strands.yml - Tool configuration examples with proper top-level keys - weather-agent.strands.yml - Complete agent configuration with structured output - agents-as-tools.strands.yml - Agent-as-Tool configuration patterns - swarm.strands.yml - Multi-agent swarm configuration - graph-simple.strands.yml - Basic graph configuration with sequential flow - graph-parallel.strands.yml - Parallel graph execution patterns - graph-conditional.strands.yml - Conditional graph routing with complex conditions - swarms-as-tools.strands.yml - Swarm-as-Tool configuration - graphs-as-tools.strands.yml - Graph-as-Tool configuration Supporting Code: - weather_tool.py - Custom tool implementation for examples - workflow/conditions.py - Custom condition implementations for graph tutorials - workflow/__init__.py - Package initialization - README.md - Comprehensive tutorial overview and navigation Key Features Demonstrated: - Cache-free ConfigLoader architecture (simplified API without caching) - Top-level key requirements enforced (agent:, graph:, swarm:, tools:) - Schema validation integration with real-time IDE support - Advanced patterns: nested configurations, parameter substitution - Complex workflows: conditional routing, parallel execution, multi-agent coordination - Structured output configuration with Pydantic models - Error handling and troubleshooting patterns - Production-ready configuration examples Tutorial Progression: 1. Fundamentals: Tool and agent loading basics 2. Intermediate: Agent-as-Tool and swarm coordination 3. Advanced: Graph workflows and conditional routing 4. Expert: Structured output and complex nested patterns 5. Composition: Multi-agent tools (Swarms-as-Tools, Graphs-as-Tools) Production Quality: - 100% working examples tested with current ConfigLoader implementation - Comprehensive error handling and troubleshooting guidance - Real-world use cases and practical patterns - Progressive complexity from beginner to expert level - Complete ecosystem coverage for all ConfigLoader capabilities This tutorial system provides hands-on learning for the complete ConfigLoader ecosystem with cache-free architecture, enabling developers to master configuration-driven agent development.
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[FEATURE] Load Agentic Configurations from a Dictionary #606
Description of changes:
This PR implements comprehensive configuration loader tutorial examples and documentation to support the experimental config_loader feature for dictionary-based agent configuration loading.
Major Additions:
configs/directoryTutorial Notebooks Added:
01-tool-loading.ipynb- ToolConfigLoader demonstrations02-agent-loading.ipynb- AgentConfigLoader with tools and prompts03-agents-as-tools.ipynb- Agent-as-Tool configuration patterns04-swarm-loading.ipynb- SwarmConfigLoader multi-agent examples05-graph-loading.ipynb- GraphConfigLoader workflow examples06-structured-output-config.ipynb- Structured output schema configuration07-swarms-as-tools.ipynb- Swarm-as-Tool advanced patterns08-graphs-as-tools.ipynb- Graph-as-Tool workflow integrationConfiguration Infrastructure:
weather_tool.py)Documentation Updates:
Recent Cleanup (addressing documentation inconsistencies):
09-yaml-schema-simple.ipynband10-yaml-schema.ipynbKey Features Demonstrated:
This comprehensive tutorial suite enables developers to understand and implement the experimental config_loader system for programmatic agent configuration management, addressing the core requirements of issue #606.
By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.