Chapter 6

Long-Form Generation

Building systems that can research, plan, and write coherent, factual, and well-cited long-form articles.

Introduction

Generating high-quality long-form content (like 5,000-word articles) is fundamentally different from short-form chat. It requires planning, maintaining context across sections, and rigorous fact-checking.

System Architecture

A robust long-form generation pipeline typically involves:

  • Outline Generator: Breaks the topic into logical sections.
  • Section Generator: Writes one section at a time.
  • Context Manager: Ensures the current section knows what was written before.
  • Citation Manager: Inserts and tracks references.

1. Context Management

The ContextManager is crucial for coherence. It feeds a summary of previous sections into the generator for the current section.

class ContextManager(dspy.Module):
    def __init__(self):
        self.summarize_context = dspy.ChainOfThought("previous_sections, current_section -> context_summary")

2. Section Generation with Citations

This module writes the content, explicitly integrating retrieved research data as citations.

class SectionGenerator(dspy.Module):
    def __init__(self):
        self.generate = dspy.ChainOfThought("topic, section_title, research_data -> content, citations")

Quality Assurance

Automated QA is essential for long outputs. We can build modules to check for:

  • Factuality: Verifying claims against source documents.
  • Completeness: Ensuring the outline was fully covered.
  • Neutrality: checking for biased language.
Next: Outline Generation