AI twitter and linkedin writers changes.
This commit is contained in:
ajaysi
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"""
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LinkedIn Company Page Content Generator Module
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This module provides tools for generating and optimizing content for LinkedIn company pages.
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It includes features for company profile optimization, content generation, and engagement tracking.
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"""
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from .linkedin_company_page_generator import LinkedInCompanyPageGenerator
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from .linkedin_company_page_generator_ui import linkedin_company_page_generator_ui
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__all__ = [
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'LinkedInCompanyPageGenerator',
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'linkedin_company_page_generator_ui'
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]
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"""
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LinkedIn Company Page Content Generator
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This module provides the core functionality for generating and optimizing LinkedIn company page content.
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"""
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import json
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from typing import Dict, List, Optional, Union
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from loguru import logger
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from .....gpt_providers.text_generation.main_text_generation import llm_text_gen
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from .....ai_web_researcher.gpt_online_researcher import do_google_serp_search
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from .....ai_web_researcher.metaphor_basic_neural_web_search import metaphor_search_articles
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from .....ai_web_researcher.tavily_ai_search import do_tavily_ai_search
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from .....gpt_providers.text_to_image_generation.main_generate_image_from_prompt import generate_image
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class LinkedInCompanyPageGenerator:
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"""Main class for generating LinkedIn company page content."""
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def __init__(self):
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"""Initialize the LinkedIn Company Page Generator."""
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self.company_info = {}
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self.brand_voice = {}
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self.content_history = []
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async def optimize_company_profile(
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self,
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company_name: str,
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industry: str,
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target_audience: List[str],
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brand_voice: str,
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key_products: List[str],
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company_size: str,
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company_description: str
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) -> Dict[str, str]:
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"""
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Optimize the company profile content for LinkedIn.
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Args:
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company_name: Name of the company
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industry: Industry sector
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target_audience: List of target audience segments
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brand_voice: Desired brand voice/tone
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key_products: List of key products/services
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company_size: Size of the company
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company_description: Current company description
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Returns:
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Dict containing optimized profile sections
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"""
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try:
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# Store company info for future content generation
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self.company_info = {
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"name": company_name,
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"industry": industry,
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"target_audience": target_audience,
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"brand_voice": brand_voice,
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"key_products": key_products,
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"size": company_size,
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"description": company_description
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}
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# Create the prompt for profile optimization
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prompt = f"""
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Optimize the LinkedIn company profile for {company_name}, a {company_size} company in the {industry} industry.
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Current Description:
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{company_description}
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Key Products/Services:
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{', '.join(key_products)}
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Target Audience:
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{', '.join(target_audience)}
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Brand Voice:
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{brand_voice}
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Generate a comprehensive LinkedIn company profile with the following sections:
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1. Company Overview
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2. Mission Statement
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3. Value Proposition
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4. Industry Expertise
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5. Company Culture
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6. Products/Services Overview
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Ensure the content:
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- Maintains the specified brand voice
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- Targets the identified audience segments
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- Highlights key products/services
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- Optimizes for LinkedIn's algorithm
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- Includes relevant industry keywords
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- Maintains professional tone
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"""
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# Define the JSON structure for the response
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json_struct = {
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"company_overview": "string",
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"mission_statement": "string",
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"value_proposition": "string",
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"industry_expertise": "string",
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"company_culture": "string",
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"products_services_overview": "string",
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"recommended_hashtags": ["string"],
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"seo_keywords": ["string"]
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}
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# Generate the optimized profile content
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response = await llm_text_gen(
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prompt=prompt,
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json_struct=json_struct,
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temperature=0.7
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)
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return response
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except Exception as e:
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logger.error(f"Error optimizing company profile: {str(e)}")
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raise
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async def generate_company_update(
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self,
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update_type: str,
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topic: str,
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target_audience: Optional[List[str]] = None,
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include_hashtags: bool = True,
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include_cta: bool = True
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) -> Dict[str, str]:
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"""
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Generate a company update post for LinkedIn.
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Args:
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update_type: Type of update (product_launch, milestone, news, etc.)
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topic: Main topic or focus of the update
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target_audience: Optional list of target audience segments
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include_hashtags: Whether to include hashtags
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include_cta: Whether to include a call-to-action
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Returns:
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Dict containing the generated update content
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"""
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try:
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# Use company info if target audience not specified
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if not target_audience:
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target_audience = self.company_info.get("target_audience", [])
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# Create the prompt for update generation
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prompt = f"""
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Generate a LinkedIn company update post for {self.company_info['name']} about {topic}.
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Update Type: {update_type}
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Target Audience: {', '.join(target_audience)}
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Brand Voice: {self.company_info['brand_voice']}
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The post should:
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- Be engaging and professional
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- Include relevant industry context
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- Highlight the company's expertise
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- Drive meaningful engagement
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- Be optimized for LinkedIn's algorithm
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"""
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if include_hashtags:
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prompt += "\n- Include 3-5 relevant hashtags"
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if include_cta:
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prompt += "\n- Include a clear call-to-action"
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# Define the JSON structure for the response
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json_struct = {
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"post_content": "string",
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"hashtags": ["string"],
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"call_to_action": "string",
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"suggested_image_prompt": "string",
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"engagement_tips": ["string"]
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}
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# Generate the update content
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response = await llm_text_gen(
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prompt=prompt,
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json_struct=json_struct,
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temperature=0.7
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)
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return response
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except Exception as e:
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logger.error(f"Error generating company update: {str(e)}")
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raise
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async def generate_employee_spotlight(
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self,
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employee_name: str,
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role: str,
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achievements: List[str],
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spotlight_type: str = "general"
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) -> Dict[str, str]:
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"""
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Generate an employee spotlight post for LinkedIn.
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Args:
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employee_name: Name of the employee
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role: Employee's role
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achievements: List of key achievements
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spotlight_type: Type of spotlight (general, leadership, innovation, etc.)
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Returns:
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Dict containing the generated spotlight content
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"""
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try:
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# Create the prompt for spotlight generation
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prompt = f"""
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Generate a LinkedIn employee spotlight post for {employee_name}, {role} at {self.company_info['name']}.
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Spotlight Type: {spotlight_type}
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Key Achievements:
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{chr(10).join(f'- {achievement}' for achievement in achievements)}
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Company Context:
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Industry: {self.company_info['industry']}
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Brand Voice: {self.company_info['brand_voice']}
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The post should:
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- Highlight the employee's contributions
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- Showcase company culture
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- Be engaging and professional
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- Include relevant industry context
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- Drive meaningful engagement
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"""
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# Define the JSON structure for the response
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json_struct = {
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"spotlight_content": "string",
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"hashtags": ["string"],
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"call_to_action": "string",
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"suggested_image_prompt": "string",
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"engagement_tips": ["string"]
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}
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# Generate the spotlight content
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response = await llm_text_gen(
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prompt=prompt,
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json_struct=json_struct,
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temperature=0.7
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)
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return response
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except Exception as e:
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logger.error(f"Error generating employee spotlight: {str(e)}")
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raise
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async def generate_industry_content(
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self,
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content_type: str,
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topic: str,
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target_audience: Optional[List[str]] = None
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) -> Dict[str, str]:
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"""
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Generate industry-focused content for LinkedIn.
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Args:
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content_type: Type of content (insight, trend, analysis, etc.)
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topic: Main topic or focus
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target_audience: Optional list of target audience segments
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Returns:
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Dict containing the generated content
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"""
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try:
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# Use company info if target audience not specified
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if not target_audience:
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target_audience = self.company_info.get("target_audience", [])
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# Research industry trends and insights
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research_results = await do_tavily_ai_search(
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query=f"{topic} in {self.company_info['industry']} industry trends insights",
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search_depth="advanced"
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)
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# Create the prompt for content generation
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prompt = f"""
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Generate LinkedIn industry content for {self.company_info['name']} about {topic}.
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Content Type: {content_type}
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Target Audience: {', '.join(target_audience)}
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Industry: {self.company_info['industry']}
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Brand Voice: {self.company_info['brand_voice']}
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Research Context:
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{research_results}
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The content should:
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- Provide valuable industry insights
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- Position the company as a thought leader
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- Be data-driven and professional
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- Drive meaningful engagement
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- Include relevant examples and context
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"""
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# Define the JSON structure for the response
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json_struct = {
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"content": "string",
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"hashtags": ["string"],
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"call_to_action": "string",
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"suggested_image_prompt": "string",
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"engagement_tips": ["string"],
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"key_insights": ["string"]
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}
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# Generate the industry content
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response = await llm_text_gen(
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prompt=prompt,
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json_struct=json_struct,
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temperature=0.7
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)
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return response
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except Exception as e:
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logger.error(f"Error generating industry content: {str(e)}")
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raise
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@@ -0,0 +1,321 @@
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"""
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LinkedIn Company Page Generator UI
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This module provides the Streamlit UI for the LinkedIn Company Page Generator.
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"""
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import streamlit as st
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import json
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from typing import Dict, List, Optional
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from loguru import logger
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from .linkedin_company_page_generator import LinkedInCompanyPageGenerator
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async def linkedin_company_page_generator_ui():
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"""Main UI function for the LinkedIn Company Page Generator."""
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st.title("🏢 LinkedIn Company Page Content Generator")
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st.markdown("""
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Create engaging and professional content for your LinkedIn company page.
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This tool helps you generate optimized company profiles, updates, employee spotlights, and industry content.
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""")
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# Initialize the generator
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generator = LinkedInCompanyPageGenerator()
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# Create tabs for different content types
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tab1, tab2, tab3, tab4 = st.tabs([
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"Company Profile",
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"Company Updates",
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"Employee Spotlights",
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"Industry Content"
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])
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# Company Profile Tab
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with tab1:
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st.header("Optimize Your Company Profile")
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st.markdown("Generate an optimized LinkedIn company profile that highlights your brand and drives engagement.")
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# Company Information Form
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with st.form("company_profile_form"):
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company_name = st.text_input("Company Name", placeholder="Enter your company name")
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industry = st.text_input("Industry", placeholder="e.g., Technology, Healthcare, Finance")
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company_size = st.selectbox(
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"Company Size",
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["1-10", "11-50", "51-200", "201-500", "501-1000", "1000+"]
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)
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target_audience = st.multiselect(
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"Target Audience",
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["Job Seekers", "Customers", "Partners", "Investors", "Industry Professionals", "Media"],
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default=["Job Seekers", "Customers"]
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)
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brand_voice = st.selectbox(
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"Brand Voice",
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["Professional", "Innovative", "Friendly", "Authoritative", "Casual", "Technical"]
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)
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key_products = st.text_area(
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"Key Products/Services",
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placeholder="Enter your key products or services, one per line"
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).split("\n")
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company_description = st.text_area(
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"Current Company Description",
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placeholder="Enter your current company description"
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)
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submit_profile = st.form_submit_button("Generate Optimized Profile")
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if submit_profile:
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if not all([company_name, industry, target_audience, brand_voice, key_products, company_description]):
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st.error("Please fill in all required fields.")
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else:
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with st.spinner("Generating optimized company profile..."):
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try:
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profile_content = await generator.optimize_company_profile(
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company_name=company_name,
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industry=industry,
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target_audience=target_audience,
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brand_voice=brand_voice,
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key_products=key_products,
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company_size=company_size,
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company_description=company_description
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)
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# Display the results
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st.success("Profile generated successfully!")
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# Company Overview
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st.subheader("Company Overview")
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st.write(profile_content["company_overview"])
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# Mission Statement
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st.subheader("Mission Statement")
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st.write(profile_content["mission_statement"])
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# Value Proposition
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st.subheader("Value Proposition")
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st.write(profile_content["value_proposition"])
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# Industry Expertise
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st.subheader("Industry Expertise")
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st.write(profile_content["industry_expertise"])
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# Company Culture
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st.subheader("Company Culture")
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st.write(profile_content["company_culture"])
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# Products/Services Overview
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st.subheader("Products/Services Overview")
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st.write(profile_content["products_services_overview"])
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# SEO Keywords
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st.subheader("Recommended SEO Keywords")
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st.write(", ".join(profile_content["seo_keywords"]))
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# Hashtags
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st.subheader("Recommended Hashtags")
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st.write(" ".join([f"#{tag}" for tag in profile_content["recommended_hashtags"]]))
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except Exception as e:
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st.error(f"Error generating profile: {str(e)}")
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# Company Updates Tab
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with tab2:
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st.header("Generate Company Updates")
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st.markdown("Create engaging company updates for your LinkedIn page.")
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# Update Generation Form
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with st.form("company_update_form"):
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update_type = st.selectbox(
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"Update Type",
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["Product Launch", "Company Milestone", "Industry News", "Company News", "Event Announcement"]
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)
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topic = st.text_input("Topic", placeholder="Enter the main topic of your update")
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target_audience = st.multiselect(
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"Target Audience",
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["Job Seekers", "Customers", "Partners", "Investors", "Industry Professionals", "Media"],
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default=["Customers", "Industry Professionals"]
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)
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include_hashtags = st.checkbox("Include Hashtags", value=True)
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include_cta = st.checkbox("Include Call-to-Action", value=True)
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submit_update = st.form_submit_button("Generate Update")
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if submit_update:
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if not topic:
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st.error("Please enter a topic for your update.")
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else:
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with st.spinner("Generating company update..."):
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try:
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update_content = await generator.generate_company_update(
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update_type=update_type,
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topic=topic,
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target_audience=target_audience,
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include_hashtags=include_hashtags,
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include_cta=include_cta
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)
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# Display the results
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st.success("Update generated successfully!")
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# Post Content
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st.subheader("Generated Post")
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st.write(update_content["post_content"])
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# Hashtags
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if include_hashtags:
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st.subheader("Recommended Hashtags")
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st.write(" ".join([f"#{tag}" for tag in update_content["hashtags"]]))
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# Call-to-Action
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if include_cta:
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st.subheader("Call-to-Action")
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st.write(update_content["call_to_action"])
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# Engagement Tips
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st.subheader("Engagement Tips")
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for tip in update_content["engagement_tips"]:
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st.write(f"• {tip}")
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# Image Prompt
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st.subheader("Suggested Image Prompt")
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st.write(update_content["suggested_image_prompt"])
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||||
|
||||
except Exception as e:
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st.error(f"Error generating update: {str(e)}")
|
||||
|
||||
# Employee Spotlights Tab
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||||
with tab3:
|
||||
st.header("Generate Employee Spotlights")
|
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st.markdown("Create engaging employee spotlight posts to showcase your team.")
|
||||
|
||||
# Spotlight Generation Form
|
||||
with st.form("employee_spotlight_form"):
|
||||
employee_name = st.text_input("Employee Name", placeholder="Enter employee's name")
|
||||
role = st.text_input("Role", placeholder="Enter employee's role")
|
||||
achievements = st.text_area(
|
||||
"Key Achievements",
|
||||
placeholder="Enter key achievements, one per line"
|
||||
).split("\n")
|
||||
spotlight_type = st.selectbox(
|
||||
"Spotlight Type",
|
||||
["General", "Leadership", "Innovation", "Team Player", "Career Growth"]
|
||||
)
|
||||
|
||||
submit_spotlight = st.form_submit_button("Generate Spotlight")
|
||||
|
||||
if submit_spotlight:
|
||||
if not all([employee_name, role, achievements]):
|
||||
st.error("Please fill in all required fields.")
|
||||
else:
|
||||
with st.spinner("Generating employee spotlight..."):
|
||||
try:
|
||||
spotlight_content = await generator.generate_employee_spotlight(
|
||||
employee_name=employee_name,
|
||||
role=role,
|
||||
achievements=achievements,
|
||||
spotlight_type=spotlight_type
|
||||
)
|
||||
|
||||
# Display the results
|
||||
st.success("Spotlight generated successfully!")
|
||||
|
||||
# Spotlight Content
|
||||
st.subheader("Generated Spotlight")
|
||||
st.write(spotlight_content["spotlight_content"])
|
||||
|
||||
# Hashtags
|
||||
st.subheader("Recommended Hashtags")
|
||||
st.write(" ".join([f"#{tag}" for tag in spotlight_content["hashtags"]]))
|
||||
|
||||
# Call-to-Action
|
||||
st.subheader("Call-to-Action")
|
||||
st.write(spotlight_content["call_to_action"])
|
||||
|
||||
# Engagement Tips
|
||||
st.subheader("Engagement Tips")
|
||||
for tip in spotlight_content["engagement_tips"]:
|
||||
st.write(f"• {tip}")
|
||||
|
||||
# Image Prompt
|
||||
st.subheader("Suggested Image Prompt")
|
||||
st.write(spotlight_content["suggested_image_prompt"])
|
||||
|
||||
except Exception as e:
|
||||
st.error(f"Error generating spotlight: {str(e)}")
|
||||
|
||||
# Industry Content Tab
|
||||
with tab4:
|
||||
st.header("Generate Industry Content")
|
||||
st.markdown("Create thought leadership content to position your company as an industry expert.")
|
||||
|
||||
# Industry Content Generation Form
|
||||
with st.form("industry_content_form"):
|
||||
content_type = st.selectbox(
|
||||
"Content Type",
|
||||
["Industry Insight", "Trend Analysis", "Best Practices", "Case Study", "Market Update"]
|
||||
)
|
||||
topic = st.text_input("Topic", placeholder="Enter the main topic of your content")
|
||||
target_audience = st.multiselect(
|
||||
"Target Audience",
|
||||
["Job Seekers", "Customers", "Partners", "Investors", "Industry Professionals", "Media"],
|
||||
default=["Industry Professionals", "Customers"]
|
||||
)
|
||||
|
||||
submit_content = st.form_submit_button("Generate Content")
|
||||
|
||||
if submit_content:
|
||||
if not topic:
|
||||
st.error("Please enter a topic for your content.")
|
||||
else:
|
||||
with st.spinner("Generating industry content..."):
|
||||
try:
|
||||
content = await generator.generate_industry_content(
|
||||
content_type=content_type,
|
||||
topic=topic,
|
||||
target_audience=target_audience
|
||||
)
|
||||
|
||||
# Display the results
|
||||
st.success("Content generated successfully!")
|
||||
|
||||
# Content
|
||||
st.subheader("Generated Content")
|
||||
st.write(content["content"])
|
||||
|
||||
# Key Insights
|
||||
st.subheader("Key Insights")
|
||||
for insight in content["key_insights"]:
|
||||
st.write(f"• {insight}")
|
||||
|
||||
# Hashtags
|
||||
st.subheader("Recommended Hashtags")
|
||||
st.write(" ".join([f"#{tag}" for tag in content["hashtags"]]))
|
||||
|
||||
# Call-to-Action
|
||||
st.subheader("Call-to-Action")
|
||||
st.write(content["call_to_action"])
|
||||
|
||||
# Engagement Tips
|
||||
st.subheader("Engagement Tips")
|
||||
for tip in content["engagement_tips"]:
|
||||
st.write(f"• {tip}")
|
||||
|
||||
# Image Prompt
|
||||
st.subheader("Suggested Image Prompt")
|
||||
st.write(content["suggested_image_prompt"])
|
||||
|
||||
except Exception as e:
|
||||
st.error(f"Error generating content: {str(e)}")
|
||||
|
||||
# Add a footer with tips
|
||||
st.markdown("---")
|
||||
st.markdown("""
|
||||
### Tips for Effective LinkedIn Company Page Content:
|
||||
|
||||
- **Consistency**: Maintain a consistent posting schedule and brand voice
|
||||
- **Engagement**: Encourage comments and discussions on your posts
|
||||
- **Visuals**: Use high-quality images and videos to increase engagement
|
||||
- **Hashtags**: Use relevant industry hashtags to increase visibility
|
||||
- **Analytics**: Monitor your content performance and adjust your strategy
|
||||
- **Employee Advocacy**: Encourage employees to share and engage with company content
|
||||
""")
|
||||
Reference in New Issue
Block a user