106 lines
4.2 KiB
Python
106 lines
4.2 KiB
Python
"""
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Prompt Builder - Handles building of AI prompts for outline generation.
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Constructs comprehensive prompts with research data, keywords, and strategic requirements.
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"""
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from typing import Dict, Any, List
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from loguru import logger
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class PromptBuilder:
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"""Handles building of comprehensive AI prompts for outline generation."""
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def __init__(self):
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"""Initialize the prompt builder."""
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pass
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def build_outline_prompt(self, primary_keywords: List[str], secondary_keywords: List[str],
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content_angles: List[str], sources: List, search_intent: str,
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request, custom_instructions: str = None) -> str:
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"""Build the comprehensive outline generation prompt using filtered research data."""
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# Use the filtered research data (already cleaned by ResearchDataFilter)
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research = request.research
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return f"""Create a comprehensive blog outline for: {', '.join(primary_keywords)}
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CONTEXT:
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Search Intent: {search_intent}
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Target: {request.word_count or 1500} words
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Industry: {getattr(request.persona, 'industry', 'General') if request.persona else 'General'}
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Audience: {getattr(request.persona, 'target_audience', 'General') if request.persona else 'General'}
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KEYWORDS:
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Primary: {', '.join(primary_keywords)}
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Secondary: {', '.join(secondary_keywords)}
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Long-tail: {', '.join(research.keyword_analysis.get('long_tail', []))}
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Semantic: {', '.join(research.keyword_analysis.get('semantic_keywords', []))}
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Trending: {', '.join(research.keyword_analysis.get('trending_terms', []))}
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Content Gaps: {', '.join(research.keyword_analysis.get('content_gaps', []))}
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CONTENT ANGLES: {', '.join(content_angles)}
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COMPETITIVE INTELLIGENCE:
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Top Competitors: {', '.join(research.competitor_analysis.get('top_competitors', []))}
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Market Opportunities: {', '.join(research.competitor_analysis.get('opportunities', []))}
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Competitive Advantages: {', '.join(research.competitor_analysis.get('competitive_advantages', []))}
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RESEARCH SOURCES: {len(sources)} authoritative sources available
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{f"CUSTOM INSTRUCTIONS: {custom_instructions}" if custom_instructions else ""}
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STRATEGIC REQUIREMENTS:
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- Create SEO-optimized headings with natural keyword integration
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- Build logical narrative flow from problem to solution
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- Include data-driven insights from research sources
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- Address content gaps and market opportunities
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- Optimize for search intent and user questions
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- Ensure engaging, actionable content throughout
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Return JSON format:
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{{
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"outline": [
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{{
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"heading": "Section heading with primary keyword",
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"subheadings": ["Subheading 1", "Subheading 2", "Subheading 3"],
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"key_points": ["Key point 1", "Key point 2", "Key point 3"],
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"target_words": 300,
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"keywords": ["primary keyword", "secondary keyword"]
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}}
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]
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}}"""
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def get_outline_schema(self) -> Dict[str, Any]:
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"""Get the structured JSON schema for outline generation."""
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return {
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"type": "object",
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"properties": {
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"outline": {
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"type": "array",
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"items": {
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"type": "object",
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"properties": {
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"heading": {"type": "string"},
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"subheadings": {
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"type": "array",
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"items": {"type": "string"}
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},
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"key_points": {
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"type": "array",
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"items": {"type": "string"}
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},
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"target_words": {"type": "integer"},
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"keywords": {
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"type": "array",
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"items": {"type": "string"}
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}
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},
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"required": ["heading", "subheadings", "key_points", "target_words", "keywords"]
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}
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}
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},
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"required": ["outline"],
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"propertyOrdering": ["outline"]
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}
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