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dc93404e38
Keep project config and checked-in workflows under .fabro so they stay out of normal repo listings. Update config discovery, CLI project commands, fixtures, docs, and checked-in workflow paths to use .fabro/project.toml and .fabro/workflows/*.
103 lines
3.1 KiB
Text
103 lines
3.1 KiB
Text
---
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title: "Variables"
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description: "Using templates in workflows"
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---
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Fabro uses `{{ ... }}` templates for workflow strings and prompts.
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## Template context
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Workflow and prompt templates can reference:
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| Expression | Resolves to |
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|---|---|
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| `{{ goal }}` | The workflow goal |
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| `{{ inputs.name }}` | A value from `[run.inputs]` |
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Environment variables are **not** available in workflow or prompt templates. Use `{{ env.NAME }}` only in config strings and HTTP hook headers.
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## Run config inputs
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Define typed inputs in `[run.inputs]`:
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```toml title="run.toml"
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_version = 1
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[workflow]
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graph = "check.fabro"
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[run]
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goal = "Run repository checks"
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[run.inputs]
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repo_name = "fabro"
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repo_url = "https://github.com/fabro-sh/fabro"
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language = "rust"
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```
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These values are available throughout the workflow as `{{ inputs.* }}`:
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```dot title="check.fabro"
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digraph Check {
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graph [goal="Run tests for {{ inputs.repo_name }}"]
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start [shape=Mdiamond, label="Start"]
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exit [shape=Msquare, label="Exit"]
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clone [label="Clone", shape=parallelogram, script="git clone {{ inputs.repo_url }} repo"]
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test [label="Test", prompt="Run the {{ inputs.language }} test suite in the repo/ directory."]
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start -> clone -> test -> exit
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}
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```
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## `goal`
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Agent and prompt nodes also receive the workflow goal at runtime:
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```dot title="example.fabro"
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digraph Example {
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graph [goal="Implement the login feature"]
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plan [label="Plan", prompt="Create a plan for: {{ goal }}"]
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}
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```
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That prompt becomes `Create a plan for: Implement the login feature`.
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## Expansion timing
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Fabro expands templates in multiple passes:
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1. Before DOT parsing, `{{ inputs.* }}` can parameterize structural parts of the graph, including imported `.fabro` files.
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2. After parsing, all string graph, node, and edge attributes are rendered again with the real `{ goal, inputs }` context.
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3. Agent and prompt handlers do a final runtime render pass as a safety net.
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`{{ goal }}` is preserved through the pre-parse step so it can be resolved later. That means goal-dependent MiniJinja control flow such as `{% if goal %}` is not useful in structural pre-parse templates.
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## Undefined variables
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Fabro uses strict undefined-variable handling. If a workflow template references an unknown value such as `{{ inputs.langauge }}`, validation fails instead of passing the literal text through to the model.
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## Escaping
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To emit literal template syntax, use MiniJinja escaping:
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```dot
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test [prompt="{% raw %}{{ goal }}{% endraw %}"]
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```
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You can also emit literal braces with expressions such as `{{ '{{' }}` when needed.
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## Input merging
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`[run.inputs]` intentionally replaces the inherited map wholesale rather than merging by key. Whichever layer has the highest precedence and sets `[run.inputs]` wins its entire map.
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| Source | Priority |
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|---|---|
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| CLI flags (`-V key=value`, repeated) | Highest |
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| `workflow.toml` `[run.inputs]` | |
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| `.fabro/project.toml` `[run.inputs]` | |
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| `~/.fabro/settings.toml` `[run.inputs]` | Lowest |
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If you need per-key overrides on top of inherited defaults, set each input explicitly in the winning layer.
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