fix: credit tracking, voice clone TTL, avatar upload ui, asset serving fallback, OAuth encryption, free plan video renders, backlink outreach sprint
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ajaysi
307
backend/services/backlink_outreach_template_generator.py
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307
backend/services/backlink_outreach_template_generator.py
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"""AI-powered outreach email template generation."""
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from __future__ import annotations
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import json
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import re
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from typing import List, Optional
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from loguru import logger
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from services.llm_providers.main_text_generation import llm_text_gen
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SYSTEM_PROMPT = """You are an expert outreach copywriter specializing in guest post and backlink pitch emails.
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Write concise, personalized outreach emails that get high response rates.
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Follow these rules:
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- Be specific about why you're reaching out (mention their content)
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- Keep it under 200 words
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- Include a clear call to action
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- Sound human, not templated
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- Never use spammy phrases
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- Output ONLY valid JSON with "subject" and "body" keys"""
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SUBJECT_LINES_PROMPT = """You are an expert email subject line writer.
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Given an outreach email body, generate subject lines that are:
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- Intriguing but not clickbait
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- Personalized when possible
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- Under 60 characters
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- Varied in style (question, curiosity, value-prop)
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Output ONLY valid JSON with a "subjects" key containing an array of strings."""
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FOLLOW_UP_PROMPT = """You are an expert outreach copywriter.
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Write a polite follow-up email for a guest post pitch that hasn't received a response.
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Rules:
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- Reference the original email without repeating it verbatim
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- Keep it shorter than the original (under 100 words)
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- Add a new angle or piece of value
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- Include a clear call to action
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- Sound human and respectful, never pushy
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- Output ONLY valid JSON with "subject" and "body" keys"""
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PERSONALIZATION_PROMPT = """You are an expert outreach personalization specialist.
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Given a lead's information and a draft outreach email, personalize it for that specific lead.
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Rules:
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- Mention their specific content or website
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- Reference something relevant from their site
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- Keep the core pitch but make it feel custom-written
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- Under 200 words
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- Output ONLY valid JSON with "subject" and "body" keys"""
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def generate_outreach_email(
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topic: str,
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target_site: Optional[str] = None,
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tone: str = "professional",
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user_id: str = "default",
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existing_body: Optional[str] = None,
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) -> dict:
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"""Generate an outreach email using the LLM.
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Args:
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topic: The topic/keyword to pitch.
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target_site: Optional target website name/URL.
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tone: professional, friendly, casual, or formal.
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user_id: Clerk user ID for subscription check.
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existing_body: If provided, rewrite/improve this existing template.
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Returns:
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dict with "subject" and "body" keys.
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"""
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if existing_body:
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prompt = (
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f"Rewrite and improve the following outreach email for a {tone} tone. "
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f"Topic: {topic}. "
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f"{f'Target website: {target_site}. ' if target_site else ''}"
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f"Keep the core message but make it more effective. "
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f"Original email:\n\n{existing_body}\n\n"
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f"Return ONLY valid JSON with 'subject' and 'body' keys."
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)
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else:
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prompt = (
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f"Write a {tone} outreach email for a guest post opportunity about: {topic}. "
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f"{f'We are pitching this to: {target_site}. ' if target_site else ''}"
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f"Mention specific value the guest post would bring to their audience. "
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f"Return ONLY valid JSON with 'subject' and 'body' keys."
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)
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try:
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raw = llm_text_gen(
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prompt=prompt,
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system_prompt=SYSTEM_PROMPT,
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user_id=user_id,
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temperature=0.7,
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)
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result = _parse_json_response(raw)
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if result:
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return result
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return _fallback_extract(raw, topic)
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except Exception as e:
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logger.error(f"Failed to generate outreach email: {e}")
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return {
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"subject": f"Guest post opportunity: {topic}",
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"body": f"Hi there,\n\nI came across your site and I'd love to contribute a guest post about {topic}. "
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f"Please let me know if you're open to submissions.\n\nBest regards",
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}
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def generate_personalized_email(
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lead_name: str,
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lead_site: str,
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lead_content_topic: str,
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pitch_topic: str,
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existing_body: str = "",
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user_id: str = "default",
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) -> dict:
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"""Personalize an outreach email for a specific lead.
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Args:
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lead_name: Contact name or site owner name.
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lead_site: The lead's website URL.
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lead_content_topic: Topic of relevant content on their site.
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pitch_topic: The topic we want to pitch.
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existing_body: Optional draft to personalize further.
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user_id: Clerk user ID for subscription check.
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Returns:
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dict with "subject" and "body" keys.
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"""
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if existing_body:
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prompt = (
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f"Personalize this outreach email for {lead_name} from {lead_site}. "
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f"They have content about '{lead_content_topic}'. "
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f"We want to pitch: {pitch_topic}. "
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f"Mention something specific about their content on {lead_content_topic} "
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f"to show we've done our research. "
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f"Draft email to personalize:\n\n{existing_body}\n\n"
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f"Return ONLY valid JSON with 'subject' and 'body' keys."
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)
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else:
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prompt = (
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f"Write a personalized outreach email to {lead_name} at {lead_site}. "
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f"They have published content about '{lead_content_topic}'. "
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f"We want to pitch a guest post about: {pitch_topic}. "
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f"Reference their article on {lead_content_topic} and explain how our pitch "
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f"would provide value to their audience. "
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f"Return ONLY valid JSON with 'subject' and 'body' keys."
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)
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try:
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raw = llm_text_gen(
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prompt=prompt,
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system_prompt=PERSONALIZATION_PROMPT,
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user_id=user_id,
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temperature=0.7,
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)
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result = _parse_json_response(raw)
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if result:
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return result
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return _fallback_extract(raw, pitch_topic)
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except Exception as e:
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logger.error(f"Failed to personalize email: {e}")
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return {"subject": f"Question about your content on {lead_content_topic}", "body": existing_body or f"Hi {lead_name},\n\nI enjoyed your article about {lead_content_topic}..."}
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def generate_subject_lines(
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body: str,
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count: int = 5,
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user_id: str = "default",
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) -> List[str]:
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"""Generate subject line suggestions for an email body.
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Args:
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body: The email body to generate subject lines for.
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count: Number of subject lines to generate.
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user_id: Clerk user ID for subscription check.
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Returns:
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List of subject line strings.
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"""
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prompt = (
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f"Generate {count} subject lines for the following outreach email. "
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f"Make them varied in style and optimized for open rates.\n\n"
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f"Email body:\n{body}\n\n"
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f"Return ONLY valid JSON with a 'subjects' key containing an array of strings."
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)
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try:
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raw = llm_text_gen(
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prompt=prompt,
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system_prompt=SUBJECT_LINES_PROMPT,
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user_id=user_id,
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temperature=0.8,
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)
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if raw:
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text = raw.strip()
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if text.startswith("```"):
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text = re.sub(r"^```(?:json)?\s*", "", text)
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text = re.sub(r"\s*```$", "", text)
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try:
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data = json.loads(text)
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if isinstance(data, dict) and "subjects" in data and isinstance(data["subjects"], list):
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return [s.strip() for s in data["subjects"][:count]]
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except json.JSONDecodeError:
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pass
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lines = [l.strip("- ").strip() for l in raw.strip().split("\n") if l.strip() and not l.strip().startswith("```")]
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return [l for l in lines if len(l) > 10][:count]
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except Exception as e:
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logger.error(f"Failed to generate subject lines: {e}")
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return [f"Guest post opportunity", f"Question about your content", f"Collaboration idea"]
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def generate_follow_up(
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original_subject: str,
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original_body: str,
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days_elapsed: int = 7,
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reply_context: str = "",
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user_id: str = "default",
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) -> dict:
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"""Generate a follow-up email for an outreach that hasn't received a response.
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Args:
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original_subject: Subject line of the original email.
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original_body: Body of the original email.
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days_elapsed: Number of days since the original was sent.
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reply_context: If the recipient replied, context of their reply.
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user_id: Clerk user ID for subscription check.
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Returns:
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dict with "subject" and "body" keys.
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"""
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if reply_context:
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prompt = (
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f"The recipient replied with: '{reply_context}'. "
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f"Write a follow-up email that addresses their response and keeps the conversation moving. "
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f"Original subject: {original_subject}.\n\n"
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f"Original email:\n{original_body}\n\n"
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f"Return ONLY valid JSON with 'subject' and 'body' keys."
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)
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else:
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prompt = (
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f"Write a polite follow-up email. {days_elapsed} days have passed since the original email. "
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f"Do not apologize for following up. Add a new piece of value or angle. "
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f"Original subject: {original_subject}.\n\n"
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f"Original email:\n{original_body}\n\n"
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f"Return ONLY valid JSON with 'subject' and 'body' keys."
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)
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try:
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raw = llm_text_gen(
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prompt=prompt,
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system_prompt=FOLLOW_UP_PROMPT,
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user_id=user_id,
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temperature=0.7,
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)
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result = _parse_json_response(raw)
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if result:
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return result
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return _fallback_extract(raw, original_subject)
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except Exception as e:
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logger.error(f"Failed to generate follow-up: {e}")
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return {
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"subject": f"Re: {original_subject}",
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"body": f"Hi there,\n\nI wanted to follow up on my previous email. "
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f"I'd love to hear your thoughts when you have a moment.\n\nBest regards",
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}
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def _parse_json_response(raw: str) -> Optional[dict]:
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"""Try to parse JSON from LLM response, handling markdown fences."""
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if not raw:
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return None
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text = raw.strip()
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if text.startswith("```"):
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text = re.sub(r"^```(?:json)?\s*", "", text)
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text = re.sub(r"\s*```$", "", text)
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try:
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data = json.loads(text)
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if isinstance(data, dict) and "subject" in data and "body" in data:
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return {"subject": data["subject"].strip(), "body": data["body"].strip()}
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except json.JSONDecodeError:
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pass
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return None
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def _fallback_extract(raw: str, topic: str) -> dict:
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"""Fallback: try to extract subject line and body from unstructured text."""
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lines = [l.strip() for l in raw.strip().split("\n") if l.strip()]
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subject = topic
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body_lines = []
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for i, line in enumerate(lines):
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lower = line.lower()
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if lower.startswith("subject") or lower.startswith("subject:"):
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subject = line.split(":", 1)[-1].strip()
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elif lower.startswith("body") or lower.startswith("body:"):
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body_lines.append(line.split(":", 1)[-1].strip())
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else:
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body_lines.append(line)
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body = "\n".join(body_lines) if body_lines else raw
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return {"subject": subject, "body": body}
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