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# Workflow Loop Config Sample
## Overview
This sample demonstrates how to define a workflow with a feedback loop using a YAML configuration file. It mirrors the `workflow_samples/loop` sample, but uses YAML to define the workflow structure instead of Python.
## Sample Inputs
- `Python programming`
- `Baking cookies`
## Graph
```mermaid
graph TD
START --> process_input[process_input]
process_input --> generate_headline[generate_headline.yaml]
generate_headline --> evaluate_headline[evaluate_headline.yaml]
evaluate_headline --> route_headline[route_headline]
route_headline -->|unrelated| generate_headline
```
## How To
This sample uses some special syntax in `root_agent.yaml` to support dynamic resolution and graph construction:
### 1. `_code` Suffix
Fields ending with `_code` (like `output_schema_code` in `evaluate_headline.yaml`) tell the ADK YAML mapper to resolve the value as a Python code reference rather than treating it as a plain string.
- If it starts with `.`, it resolves relative to the current agent directory's Python package path.
- Example: `output_schema_code: .agent.Feedback` resolves to the `Feedback` Pydantic model in `agent.py` in the same directory.
### 2. Function References in Edges
If a string in the edge list does not end with `.yaml` and is not `'START'`, it is treated as a function reference.
- If it starts with `.`, it resolves relative to the current agent directory's Python package path.
- Example: `.agent.process_input` resolves to the `process_input` function in `agent.py`.
- It automatically creates a `FunctionNode` with the function's name as the node name.
### 3. External Agent Files
Agents can be defined in their own YAML files and referenced by filename in the edges list.
- Example: `generate_headline.yaml` references the agent defined in that file.
- The mapper caches resolved nodes by their string value, so using the same filename in multiple edges correctly reuses the same agent instance, preserving the graph structure (e.g. for loops).