output-layer

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

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

from openbench.output.generators import MarkdownGenerator

generator = MarkdownGenerator()
result = generator.generate(content=data, output_path="output.md")

Using in Workflows

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

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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