82 lines
3.0 KiB
Python
82 lines
3.0 KiB
Python
"""
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Content Angle Generator - AI-powered content angle discovery.
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Generates strategic content angles from research content for blog posts.
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"""
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from typing import List
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from loguru import logger
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class ContentAngleGenerator:
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"""Generates strategic content angles from research content."""
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def generate(self, content: str, topic: str, industry: str) -> List[str]:
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"""Parse strategic content angles from the research content using AI."""
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angles_prompt = f"""
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Analyze the following research content and create strategic content angles for: {topic} in {industry}
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Research Content:
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{content[:3000]}
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Create 7 compelling content angles that:
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1. Leverage current trends and data from the research
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2. Address content gaps and opportunities
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3. Appeal to different audience segments
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4. Include unique perspectives not covered by competitors
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5. Incorporate specific statistics, case studies, or expert insights
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6. Create emotional connection and urgency
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7. Provide actionable value to readers
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Each angle should be:
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- Specific and data-driven
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- Unique and differentiated
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- Compelling and click-worthy
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- Actionable for readers
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Respond with JSON:
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{{
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"content_angles": [
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"Specific angle 1 with data/trends",
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"Specific angle 2 with unique perspective",
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"Specific angle 3 with actionable insights",
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"Specific angle 4 with case study focus",
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"Specific angle 5 with future outlook",
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"Specific angle 6 with problem-solving focus",
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"Specific angle 7 with industry insights"
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]
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}}
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"""
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from services.llm_providers.gemini_provider import gemini_structured_json_response
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angles_schema = {
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"type": "object",
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"properties": {
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"content_angles": {
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"type": "array",
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"items": {"type": "string"},
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"minItems": 5,
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"maxItems": 7
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}
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},
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"required": ["content_angles"]
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}
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angles_result = gemini_structured_json_response(
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prompt=angles_prompt,
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schema=angles_schema,
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temperature=0.7,
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max_tokens=4000
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)
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if isinstance(angles_result, dict) and 'content_angles' in angles_result:
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logger.info("✅ AI content angles generation completed successfully")
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return angles_result['content_angles'][:7]
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else:
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# Fail gracefully - no fallback data
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error_msg = angles_result.get('error', 'Unknown error') if isinstance(angles_result, dict) else str(angles_result)
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logger.error(f"AI content angles generation failed: {error_msg}")
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raise ValueError(f"Content angles generation failed: {error_msg}")
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