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74 lines
1.6 KiB
Markdown
74 lines
1.6 KiB
Markdown
# Declarative Workflows
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Declarative workflows allow you to define multi-agent orchestration patterns in YAML, including:
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- Variable manipulation and state management
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- Control flow (loops, conditionals, branching)
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- Agent invocations
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- Human-in-the-loop patterns
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See the [main workflows README](../README.md#declarative) for the list of available samples.
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## Prerequisites
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```bash
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pip install agent-framework-declarative
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```
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## Running Samples
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Each sample directory contains:
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- `workflow.yaml` - The declarative workflow definition
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- `main.py` - Python code to load and execute the workflow
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- `README.md` - Sample-specific documentation
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To run a sample:
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```bash
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cd <sample_directory>
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python main.py
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```
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## Workflow Structure
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A basic workflow YAML file looks like:
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```yaml
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name: my-workflow
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description: A simple workflow example
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actions:
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- kind: SetValue
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path: turn.greeting
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value: Hello, World!
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- kind: SendActivity
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activity:
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text: =turn.greeting
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```
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## Action Types
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### Variable Actions
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- `SetValue` - Set a variable in state
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- `SetVariable` - Set a variable (.NET style naming)
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- `ResetVariable` - Clear a variable
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### Control Flow
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- `If` - Conditional branching
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- `ConditionGroup` - Multi-way branching
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- `Foreach` - Iterate over collections
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- `GotoAction` - Jump to labeled action
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### Output
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- `SendActivity` - Send text/attachments to user
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### Agent Invocation
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- `InvokeAzureAgent` - Call an Azure AI agent
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### Tool Invocation
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- `InvokeFunctionTool` - Call a registered Python function
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### Human-in-Loop
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- `Question` - Request user input
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- `RequestExternalInput` - Request external data/approval
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