3f984e8d0c
- Add POST /podcast/pre-estimate endpoint for cost estimation before analysis - Enhance cost_estimator.py with multi-model support (gemini, audio, voice clone, image, video) - Add detailed cost breakdown (llm, audio, media costs + per-phase breakdown) - Remove redundant pricing seeding from init_alpha_subscription_tiers.py - Add SSOT pricing via PricingService.initialize_default_pricing() - Update TopicUrlInput tooltip to show estimate details - Add debug logging for pricing seeding and pre-estimate - Clean up verbose podcast mode debug logs in app.py
281 lines
9.9 KiB
Python
281 lines
9.9 KiB
Python
"""
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Podcast Context Builder Service
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Builds unified context for AI prompts from multiple sources:
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- Podcast Bible (user personalization)
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- Website Extraction (from Exa)
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- Topic Context (category research: News/Finance)
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"""
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from typing import Dict, Any, Optional, List
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from loguru import logger
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class PodcastContextBuilder:
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"""Builds unified context for AI prompt enhancements."""
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def build_enhance_context(
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self,
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idea: str,
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bible_context: str = "",
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website_data: Optional[Dict[str, Any]] = None,
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topic_context: Optional[Dict[str, Any]] = None,
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) -> Dict[str, Any]:
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"""
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Build context for topic enhancement prompt.
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Args:
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idea: Raw podcast idea/keywords
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bible_context: Serialized Podcast Bible string
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website_data: Website extraction data (title, summary, highlights, url, subpages)
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topic_context: Category research data (category, topics, selected_topic)
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Returns:
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Dict with:
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- prompt: The formatted prompt
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- contexts_used: List of context types being used
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- context_description: Human-readable description for logging
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"""
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contexts_used = []
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context_parts = []
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# Track what contexts are available
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if bible_context:
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contexts_used.append("Podcast Bible")
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if website_data:
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contexts_used.append("Website Analysis")
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if topic_context:
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category = topic_context.get("category", "unknown")
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contexts_used.append(f"Category Research ({category})")
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# Build Bible section
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if bible_context:
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context_parts.append(f"USER PERSONALIZATION CONTEXT (Podcast Bible):\n{bible_context}")
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# Build Website section
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if website_data:
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website_section = self._format_website_section(website_data)
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context_parts.append(website_section)
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# Build Topic/Category section
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if topic_context:
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topic_section = self._format_topic_section(topic_context)
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context_parts.append(topic_section)
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# Select appropriate prompt template based on available context
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prompt = self._select_prompt(idea, context_parts, website_data, topic_context)
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return {
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"prompt": prompt,
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"contexts_used": contexts_used,
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"context_description": ", ".join(contexts_used) if contexts_used else "basic idea only",
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}
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def _format_website_section(self, website_data: Dict[str, Any]) -> str:
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"""Format website data for prompt inclusion."""
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parts = []
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if website_data.get("url"):
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parts.append(f"Source URL: {website_data['url']}")
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if website_data.get("title"):
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parts.append(f"Company/Organization: {website_data['title']}")
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if website_data.get("summary"):
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parts.append(f"About: {website_data['summary']}")
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if website_data.get("highlights"):
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highlights = website_data.get("highlights", [])
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if highlights:
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parts.append(f"Key Highlights: {', '.join(highlights[:3])}")
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if website_data.get("subpages"):
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subpages = website_data.get("subpages", [])
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if subpages:
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subpage_titles = [sp.get("title", sp.get("url", "")) for sp in subpages[:3]]
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parts.append(f"Subpages: {', '.join(subpage_titles)}")
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return "WEBSITE CONTENT ANALYSIS:\n" + "\n".join(parts)
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def _format_topic_section(self, topic_context: Dict[str, Any]) -> str:
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"""Format category research data for prompt inclusion."""
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parts = []
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category = topic_context.get("category", "")
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if category:
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parts.append(f"Research Category: {category.upper()}")
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# Include selected topic details
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selected = topic_context.get("selected_topic", {})
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if selected:
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if selected.get("title"):
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parts.append(f"Selected Topic: {selected['title']}")
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if selected.get("snippet"):
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parts.append(f"Context: {selected['snippet']}")
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if selected.get("url"):
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parts.append(f"Source: {selected['url']}")
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# Include some alternative topics for reference
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topics = topic_context.get("topics", [])
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if topics:
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alt_titles = [t.get("title", "") for t in topics[:3] if t.get("title")]
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if alt_titles:
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parts.append(f"Related Topics: {', '.join(alt_titles)}")
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return "CATEGORY RESEARCH CONTEXT:\n" + "\n".join(parts)
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def _select_prompt(
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self,
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idea: str,
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context_parts: List[str],
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website_data: Optional[Dict[str, Any]],
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topic_context: Optional[Dict[str, Any]],
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) -> str:
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"""Select and format the appropriate prompt based on available context."""
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context_str = "\n\n".join(context_parts)
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# Full context prompt (all sources available)
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if website_data and topic_context:
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return f"""You are a creative podcast producer. Generate 3 distinct, compelling podcast episode concepts from the raw idea, enriched with website content analysis AND category research.
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{context_str}
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RAW IDEA/KEYWORDS: "{idea}"
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TASK:
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Generate 3 different enhanced versions that INCORPORATE both the website content AND category research context:
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1. Professional & Expert-led angle (leverage website authority + research insights)
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2. Storytelling & Human interest angle (brand narratives + research findings)
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3. Trendy & Contemporary angle (current trends + research relevance)
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Each version should:
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- Be 2-3 sentences
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- Reference specific elements from both website AND research when relevant
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- Be audience-focused and align with host persona if provided
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- NOT just repeat summaries - create fresh podcast angles
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Return JSON with:
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- enhanced_ideas: array of 3 strings (each a complete episode pitch)
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- rationales: array of 3 strings explaining each approach
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Example format:
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{{
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"enhanced_ideas": ["Pitch 1...", "Pitch 2...", "Pitch 3..."],
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"rationales": ["Reason 1", "Reason 2", "Reason 3"]
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}}
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"""
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# Website-only context
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elif website_data:
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return f"""You are a creative podcast producer. Generate 3 distinct, compelling podcast episode concepts from the raw idea, enriched with website content analysis.
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{context_str}
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RAW IDEA/KEYWORDS: "{idea}"
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TASK:
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Generate 3 different enhanced versions that INCORPORATE the website content:
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1. Professional & Expert-led angle (focus on authority, insights from website)
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2. Storytelling & Human interest angle (brand narratives, personal connections)
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3. Trendy & Contemporary angle (modern perspectives, current relevance)
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Each version should:
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- Be 2-3 sentences
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- Reference specific elements from the website when relevant
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- Be audience-focused and align with host persona if provided
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Return JSON with:
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- enhanced_ideas: array of 3 strings
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- rationales: array of 3 strings
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Example format:
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{{
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"enhanced_ideas": ["Pitch 1...", "Pitch 2...", "Pitch 3..."],
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"rationales": ["Reason 1", "Reason 2", "Reason 3"]
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}}
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"""
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# Category research only context
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elif topic_context:
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category = topic_context.get("category", "research").upper()
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return f"""You are a creative podcast producer. Generate 3 distinct, compelling podcast episode concepts from the raw idea, enriched with {category} category research.
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{context_str}
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RAW IDEA/KEYWORDS: "{idea}"
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TASK:
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Generate 3 different enhanced versions that INCORPORATE the {category} research:
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1. Professional & Expert-led angle (leverage research insights and data)
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2. Storytelling & Human interest angle (real-world applications, human impact)
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3. Trendy & Contemporary angle (cutting-edge trends, future outlook)
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Each version should:
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- Be 2-3 sentences
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- Reference specific elements from the research when relevant
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- Connect the research to the raw idea meaningfully
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Return JSON with:
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- enhanced_ideas: array of 3 strings
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- rationales: array of 3 strings
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Example format:
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{{
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"enhanced_ideas": ["Pitch 1...", "Pitch 2...", "Pitch 3..."],
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"rationales": ["Reason 1", "Reason 2", "Reason 3"]
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}}
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"""
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# Standard context (no additional context)
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else:
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return f"""You are a creative podcast producer. Generate 3 distinct, compelling podcast episode concepts from the raw idea.
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{context_str}
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RAW IDEA/KEYWORDS: "{idea}"
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TASK:
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Generate 3 different enhanced versions with unique angles:
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1. Professional & Expert-led angle (focus on authority, insights)
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2. Storytelling & Human interest angle (focus on narratives, emotions)
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3. Trendy & Contemporary angle (focus on trends, modern relevance)
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Each version should be 2-3 sentences, audience-focused.
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Return JSON with:
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- enhanced_ideas: array of 3 strings
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- rationales: array of 3 strings
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Example format:
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{{
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"enhanced_ideas": ["Pitch 1...", "Pitch 2...", "Pitch 3..."],
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"rationales": ["Reason 1", "Reason 2", "Reason 3"]
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}}
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"""
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def format_context_for_logging(
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self,
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website_data: Optional[Dict] = None,
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topic_context: Optional[Dict] = None,
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) -> str:
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"""Format context description for logging."""
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contexts = []
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if website_data:
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title = website_data.get("title", "Unknown")
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contexts.append(f"Website: {title[:30]}...")
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if topic_context:
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category = topic_context.get("category", "unknown")
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selected = topic_context.get("selected_topic", {})
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topic_title = selected.get("title", "Not selected")
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contexts.append(f"Category: {category} ({topic_title[:20]}...)")
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return " | ".join(contexts) if contexts else "No extended context"
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# Singleton instance for reuse
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context_builder = PodcastContextBuilder() |