output-layer
Working with OpenBench output generators for PDF, PowerPoint, Dashboard, Audio, and Markdown. Use when creating output generators, generating reports, or working with the OutputLayer. Use when this capability is needed.
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- 2026年4月28日 22:53
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SKILL.md
ソースの指示 · 読み取り専用プレビュー- name
- output-layer
- description
- Working with OpenBench output generators for PDF, PowerPoint, Dashboard, Audio, and Markdown. Use when creating output generators, generating reports, or working with the OutputLayer. Use when this capability is needed.
- metadata
- {"author":"ai-kitchen-inc"}
# Output Layer
OpenBench output layer generates artifacts from processed data.
## Key Files
- `src/openbench/output/generators.py` - All generator implementations
- `src/openbench/output/layer.py` - OutputFactory
- `src/openbench/core/abstractions.py` - OutputGenerator base class, GeneratedOutput
## Available Generators
| Generator | Format | Dependency |
|-----------|--------|------------|
| `PDFGenerator` | PDF | `reportlab` |
| `PowerPointGenerator` | PPTX | `python-pptx` |
| `DashboardGenerator` | HTML | `plotly` |
| `AudioGenerator` | Audio | TTS provider |
| `MarkdownGenerator` | MD | None |
## PDFGenerator
```python
from openbench.output.generators import PDFGenerator
generator = PDFGenerator(
template="report", # "default", "report", "corporate"
page_size="letter", # "letter", "a4", "legal"
font_name="Helvetica",
font_size=11,
title_font_size=18,
heading_font_size=14,
)
result = generator.generate(
content="Report content here...",
output_path="report.pdf",
title="Q1 Report",
)
# Returns GeneratedOutput(file_path, format, size_bytes, metadata)
```
Content types supported:
- `str` - Rendered as paragraphs
- `dict` - Keys as section headings, values as content
- `list` - Rendered as bullet points
## MarkdownGenerator
```python
from openbench.output.generators import MarkdownGenerator
generator = MarkdownGenerator()
result = generator.generate(content=data, output_path="output.md")
```
## Using in Workflows
```python
from openbench.core import OutputLayer
from openbench.output.generators import PDFGenerator, MarkdownGenerator
# Single output
workflow = data | intelligence | OutputLayer(generators=PDFGenerator())
# Multiple outputs in parallel
workflow = data | intelligence | OutputLayer(
generators=PDFGenerator() & MarkdownGenerator()
)
```
## OutputGenerator Interface
```python
from openbench.core.abstractions import OutputGenerator, GeneratedOutput
class MyGenerator(OutputGenerator):
@property
def output_format(self) -> str:
return "custom" # Required
def generate(self, content, template=None, **options) -> GeneratedOutput:
file_path = self._create_output(content)
return GeneratedOutput(
file_path=file_path,
format=self.output_format,
size_bytes=os.path.getsize(file_path),
metadata={"template": template}
)
def validate(self, content) -> bool:
return content is not None # Required
```
## Anti-Patterns
**DO NOT:**
- Import heavy dependencies at module level (reportlab, python-pptx) - use lazy imports
- Assume content is always a string - check type and handle dict/list/str
- Forget `validate()` - it's called before `generate()` in the pipeline
- Return raw file paths - always return `GeneratedOutput` dataclass
- Skip `output_format` property - it's required by the abstract class
## Cross-References
- **Composing Workflows**: Generators are `Chainable`, usable with `|` `&` in OutputLayer → see `composing-workflows` skill
- **Creating Abstractions**: `OutputGenerator` base class details → see `creating-abstractions` skill
- **Intelligence Layer**: Agent output feeds into generators → see `intelligence-layer` skill
For examples, see `examples/workflows/reports/sustainability_report.py`
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