diff --git a/lib/ai_writers/linkedin_writer/README.md b/lib/ai_writers/linkedin_writer/README.md new file mode 100644 index 00000000..191c8247 --- /dev/null +++ b/lib/ai_writers/linkedin_writer/README.md @@ -0,0 +1,347 @@ +# LinkedIn AI Writer + +A comprehensive suite of AI-powered tools for generating professional LinkedIn content. + +## Overview + +LinkedIn AI Writer is a powerful tool designed to help professionals, businesses, and content creators generate high-quality LinkedIn content. It leverages advanced AI models to create engaging posts, articles, carousels, video scripts, and more, all optimized for LinkedIn's platform. + +## Tools Status + +| Tool | Status | Category | +|------|--------|----------| +| LinkedIn Post Generator | ✅ Active | Content Creation | +| LinkedIn Article Generator | ✅ Active | Content Creation | +| LinkedIn Carousel Post Generator | ✅ Active | Content Creation | +| LinkedIn Video Script Generator | ✅ Active | Content Creation | +| LinkedIn Poll Generator | ✅ Active | Content Creation | +| LinkedIn Comment Response Generator | ✅ Active | Engagement | +| LinkedIn Profile Optimizer | ✅ Active | Profile & Personal Branding | +| LinkedIn Company Page Content Generator | ✅ Active | Business & Marketing | +| LinkedIn Newsletter Generator | 🔄 Coming Soon | Business & Marketing | +| LinkedIn Job Description Generator | 🔄 Coming Soon | Business & Marketing | +| LinkedIn Sales Navigator Content Generator | 🔄 Coming Soon | Sales & Networking | +| LinkedIn InMail Generator | 🔄 Coming Soon | Sales & Networking | +| LinkedIn Learning Course Description Generator | 🔄 Coming Soon | Learning & Education | +| LinkedIn Event Description Generator | 🔄 Coming Soon | Learning & Education | +| LinkedIn Group Post Generator | 🔄 Coming Soon | Community & Engagement | + +## Features + +### Content Creation Tools + +#### LinkedIn Post Generator +- **Status**: Active +- **Description**: Create engaging, professional posts that drive engagement and establish thought leadership. +- **Features**: + - Professional tone customization + - Industry-specific terminology + - Hashtag optimization + - Formatting options + - Character count optimization + - Call-to-action suggestions + - Engagement prediction + - Visual content recommendations + - Poll creation + - Best posting time suggestions + - Research-backed content + - Reference tracking + +#### LinkedIn Article Generator +- **Status**: Active +- **Description**: Generate long-form professional articles that showcase expertise and drive traffic. +- **Features**: + - Topic research and outline generation + - SEO optimization for LinkedIn articles + - Professional writing style adaptation + - Section structuring + - Citation and reference formatting + - Image placement suggestions + - Headline optimization + - Meta description generation + - Reading time estimation + - Internal linking suggestions + - Multiple research sources (Metaphor, Google, Tavily) + - AI-generated section images + +#### LinkedIn Carousel Post Generator +- **Status**: Active +- **Description**: Create engaging carousel posts that showcase information in a visually appealing way. +- **Features**: + - Slide content generation + - Visual hierarchy optimization + - Story arc development + - Call-to-action placement + - Brand consistency maintenance + - Engagement element integration + - Professional design suggestions + - Content distribution strategy + - Analytics integration + - A/B testing variations + +#### LinkedIn Video Script Generator +- **Status**: Active +- **Description**: Create scripts for LinkedIn videos that drive engagement. +- **Features**: + - Hook generation + - Story structure development + - Professional speaking points + - Visual cue suggestions + - Call-to-action optimization + - Engagement prompt integration + - Caption generation + - Thumbnail text suggestions + - Video description optimization + - Hashtag strategy + +#### LinkedIn Poll Generator +- **Status**: Active +- **Description**: Create engaging polls that drive interaction and gather insights. +- **Features**: + - Question formulation optimization + - Option generation based on topic + - Industry-specific poll templates + - Engagement prediction + - Result analysis suggestions + - Follow-up content recommendations + - Trending topic integration + - Professional tone maintenance + - Data visualization suggestions + - Poll scheduling optimization + +### Engagement Tools + +#### LinkedIn Comment Response Generator +- **Status**: Active +- **Description**: Generate professional and engaging responses to LinkedIn comments with AI-powered analysis and optimization. +- **Features**: + - Comment analysis and categorization + - Multiple response types (general, disagreement, value-add) + - Brand voice customization + - Engagement goal targeting + - Resource suggestion generation + - Follow-up question generation + - Tone optimization + - Response strategy recommendations + - Context-aware responses + - Professional formatting + +### Profile & Personal Branding Tools + +#### LinkedIn Profile Optimizer +- **Status**: Active +- **Description**: Enhance LinkedIn profiles to improve visibility and professional appeal. +- **Features**: + - Headline optimization + - About section generation + - Experience description enhancement + - Skills recommendation + - Project highlight creation + - Endorsement request generation + - Profile strength analysis + - Keyword optimization + - Professional summary generation + - Custom URL suggestions + +### Business & Marketing Tools + +#### LinkedIn Company Page Content Generator +- **Status**: Active +- **Description**: Create content for company pages that builds brand awareness and engagement. +- **Features**: + - Company profile optimization + - Company culture post generation + - Product/service announcement templates + - Employee spotlight content + - Company milestone celebrations + - Industry insights sharing + - Event promotion content + - Job posting templates + - Company news updates + - Brand voice consistency + - Engagement metrics optimization + +#### LinkedIn Newsletter Generator +- **Status**: Coming Soon +- **Description**: Create professional newsletters that establish thought leadership and drive engagement. +- **Features**: + - Newsletter structure templates + - Topic clustering and organization + - Professional introduction and conclusion + - Industry trend analysis integration + - Expert quote suggestions + - Visual content recommendations + - Call-to-action optimization + - Subscriber engagement prompts + - Consistency maintenance + - Analytics integration suggestions + +#### LinkedIn Job Description Generator +- **Status**: Coming Soon +- **Description**: Create compelling job descriptions that attract qualified candidates. +- **Features**: + - Role-specific templates + - Skills and qualifications optimization + - Company culture integration + - Benefits and perks highlighting + - Inclusive language checker + - Keyword optimization + - Application process clarity + - Remote/hybrid work policy integration + - Diversity and inclusion statements + - A/B testing variations + +### Sales & Networking Tools + +#### LinkedIn Sales Navigator Content Generator +- **Status**: Coming Soon +- **Description**: Create personalized outreach content for sales professionals. +- **Features**: + - Prospect research integration + - Industry-specific messaging + - Personalization tokens + - Connection request templates + - Follow-up message sequences + - Value proposition highlighting + - Objection handling responses + - Meeting request templates + - Industry pain point addressing + - ROI demonstration content + +#### LinkedIn InMail Generator +- **Status**: Coming Soon +- **Description**: Create personalized and effective InMail messages. +- **Features**: + - Prospect research integration + - Personalization token usage + - Value proposition highlighting + - Call-to-action optimization + - Follow-up sequence generation + - Objection handling preparation + - Industry-specific messaging + - A/B testing variations + - Compliance checking + - Engagement tracking suggestions + +### Learning & Education Tools + +#### LinkedIn Learning Course Description Generator +- **Status**: Coming Soon +- **Description**: Create compelling descriptions for LinkedIn Learning courses. +- **Features**: + - Course objective optimization + - Learning outcome generation + - Prerequisite suggestions + - Target audience definition + - Skill tag recommendations + - Course structure outline + - Engagement element suggestions + - Completion certificate highlighting + - Industry relevance emphasis + - Career path integration + +#### LinkedIn Event Description Generator +- **Status**: Coming Soon +- **Description**: Create compelling event descriptions that drive attendance and engagement. +- **Features**: + - Event objective highlighting + - Speaker bio generation + - Agenda formatting + - Registration incentive suggestions + - Networking opportunity emphasis + - Industry relevance integration + - Visual content recommendations + - Engagement element suggestions + - Post-event follow-up content + - Attendance tracking integration + +### Community & Engagement Tools + +#### LinkedIn Group Post Generator +- **Status**: Coming Soon +- **Description**: Create content specifically optimized for LinkedIn Groups. +- **Features**: + - Group-specific content adaptation + - Discussion prompt generation + - Community guideline compliance + - Engagement optimization + - Moderation suggestion + - Topic relevance checking + - Member value highlighting + - Cross-promotion opportunities + - Group culture adaptation + - Content scheduling + +## Current Status + +The LinkedIn AI Writer currently has the following tools fully implemented and active: + +1. LinkedIn Post Generator +2. LinkedIn Article Generator +3. LinkedIn Carousel Post Generator +4. LinkedIn Video Script Generator +5. LinkedIn Comment Response Generator +6. LinkedIn Profile Optimizer +7. LinkedIn Poll Generator +8. LinkedIn Company Page Content Generator + +The remaining tools are marked as "Coming Soon" and will be implemented in future iterations. + +## Future Development + +### LinkedIn API Integration + +To provide more personalized and effective content, future development will include integration with the LinkedIn API. This will allow: + +- Access to user profile data for personalized content +- Direct posting to LinkedIn +- Analytics integration for content performance tracking +- Engagement metrics for content optimization +- Audience insights for targeted content creation + +### Enhanced AI Models + +We plan to enhance the AI models used for content generation to: + +- Better understand LinkedIn's algorithm and best practices +- Generate more engaging and platform-specific content +- Provide more accurate engagement predictions +- Create more personalized content based on user data + +### Additional Features + +Future iterations will include: + +- Content calendar planning and scheduling +- Multi-platform content adaptation +- Advanced analytics and reporting +- Team collaboration features +- Content approval workflows +- A/B testing capabilities +- Custom templates and brand voice settings + +## Getting Started + +To use the LinkedIn AI Writer: + +1. Navigate to the LinkedIn AI Writer dashboard +2. Select the tool you want to use +3. Fill in the required information +4. Generate your content +5. Review and edit as needed +6. Copy the content to your LinkedIn account + +## Requirements + +- Python 3.8+ +- Streamlit +- OpenAI API key (for GPT models) +- Optional: LinkedIn API credentials (for future integration) + +## Contributing + +We welcome contributions to the LinkedIn AI Writer project. Please feel free to submit issues, feature requests, or pull requests. + +## License + +This project is licensed under the MIT License - see the LICENSE file for details. \ No newline at end of file diff --git a/lib/ai_writers/linkedin_writer/linkedin_ai_writer.py b/lib/ai_writers/linkedin_writer/linkedin_ai_writer.py index 2749de5b..f48be704 100644 --- a/lib/ai_writers/linkedin_writer/linkedin_ai_writer.py +++ b/lib/ai_writers/linkedin_writer/linkedin_ai_writer.py @@ -29,10 +29,24 @@ from .modules.article_generator.linkedin_article_generator import linkedin_artic from .modules.carousel_generator.linkedin_carousel_generator import linkedin_carousel_generator_ui from .modules.video_script_generator.linkedin_video_script_generator import linkedin_video_script_generator_ui from .modules.comment_response_generator.linkedin_comment_response_generator_ui import linkedin_comment_response_generator_ui +from .modules.profile_optimizer.linkedin_profile_optimizer_ui import linkedin_profile_optimizer_ui +from .modules.poll_generator import linkedin_poll_generator_ui +from .modules.company_page_generator import linkedin_company_page_generator_ui # Import image generation from ...gpt_providers.text_to_image_generation.main_generate_image_from_prompt import generate_image +# Create a wrapper for the async profile optimizer UI +def linkedin_profile_optimizer_ui_wrapper(): + """Wrapper function to call the async LinkedIn Profile Optimizer UI.""" + import asyncio + asyncio.run(linkedin_profile_optimizer_ui()) + +# Create a wrapper for the async company page generator UI +def linkedin_company_page_generator_ui_wrapper(): + """Wrapper function to call the async LinkedIn Company Page Generator UI.""" + import asyncio + asyncio.run(linkedin_company_page_generator_ui()) def linkedin_main_menu(): """Main function for the LinkedIn AI Writer.""" @@ -161,8 +175,8 @@ def linkedin_main_menu(): "description": "Enhance LinkedIn profiles to improve visibility and professional appeal.", "color": "#0A66C2", "category": "Profile & Personal Branding", - "function": None, - "status": "coming_soon", + "function": linkedin_profile_optimizer_ui_wrapper, + "status": "active", "features": [ "Headline optimization", "About section generation", @@ -182,8 +196,8 @@ def linkedin_main_menu(): "description": "Create engaging polls that drive interaction and gather insights.", "color": "#0A66C2", "category": "Profile & Personal Branding", - "function": None, - "status": "coming_soon", + "function": linkedin_poll_generator_ui, + "status": "active", "features": [ "Question formulation optimization", "Option generation based on topic", @@ -205,8 +219,8 @@ def linkedin_main_menu(): "description": "Create content for company pages that builds brand awareness and engagement.", "color": "#0A66C2", "category": "Business & Marketing", - "function": None, - "status": "coming_soon", + "function": linkedin_company_page_generator_ui_wrapper, + "status": "active", "features": [ "Company culture post generation", "Product/service announcement templates", @@ -516,7 +530,7 @@ def linkedin_main_menu(): """, unsafe_allow_html=True) # Add a button to access the tool - if st.button(f"Use {tool['name']}", key=f"btn_{tool['name']}"): + if st.button(f"Use {tool['name']}", key=f"btn_{tool['category']}_{tool['name']}"): # Store the selected tool in session state st.session_state.selected_tool = tool st.rerun() diff --git a/lib/ai_writers/linkedin_writer/modules/company_page_generator/__init__.py b/lib/ai_writers/linkedin_writer/modules/company_page_generator/__init__.py new file mode 100644 index 00000000..6f22afd7 --- /dev/null +++ b/lib/ai_writers/linkedin_writer/modules/company_page_generator/__init__.py @@ -0,0 +1,14 @@ +""" +LinkedIn Company Page Content Generator Module + +This module provides tools for generating and optimizing content for LinkedIn company pages. +It includes features for company profile optimization, content generation, and engagement tracking. +""" + +from .linkedin_company_page_generator import LinkedInCompanyPageGenerator +from .linkedin_company_page_generator_ui import linkedin_company_page_generator_ui + +__all__ = [ + 'LinkedInCompanyPageGenerator', + 'linkedin_company_page_generator_ui' +] \ No newline at end of file diff --git a/lib/ai_writers/linkedin_writer/modules/company_page_generator/linkedin_company_page_generator.py b/lib/ai_writers/linkedin_writer/modules/company_page_generator/linkedin_company_page_generator.py new file mode 100644 index 00000000..93764e34 --- /dev/null +++ b/lib/ai_writers/linkedin_writer/modules/company_page_generator/linkedin_company_page_generator.py @@ -0,0 +1,322 @@ +""" +LinkedIn Company Page Content Generator + +This module provides the core functionality for generating and optimizing LinkedIn company page content. +""" + +import json +from typing import Dict, List, Optional, Union +from loguru import logger + +from .....gpt_providers.text_generation.main_text_generation import llm_text_gen +from .....ai_web_researcher.gpt_online_researcher import do_google_serp_search +from .....ai_web_researcher.metaphor_basic_neural_web_search import metaphor_search_articles +from .....ai_web_researcher.tavily_ai_search import do_tavily_ai_search +from .....gpt_providers.text_to_image_generation.main_generate_image_from_prompt import generate_image + +class LinkedInCompanyPageGenerator: + """Main class for generating LinkedIn company page content.""" + + def __init__(self): + """Initialize the LinkedIn Company Page Generator.""" + self.company_info = {} + self.brand_voice = {} + self.content_history = [] + + async def optimize_company_profile( + self, + company_name: str, + industry: str, + target_audience: List[str], + brand_voice: str, + key_products: List[str], + company_size: str, + company_description: str + ) -> Dict[str, str]: + """ + Optimize the company profile content for LinkedIn. + + Args: + company_name: Name of the company + industry: Industry sector + target_audience: List of target audience segments + brand_voice: Desired brand voice/tone + key_products: List of key products/services + company_size: Size of the company + company_description: Current company description + + Returns: + Dict containing optimized profile sections + """ + try: + # Store company info for future content generation + self.company_info = { + "name": company_name, + "industry": industry, + "target_audience": target_audience, + "brand_voice": brand_voice, + "key_products": key_products, + "size": company_size, + "description": company_description + } + + # Create the prompt for profile optimization + prompt = f""" + Optimize the LinkedIn company profile for {company_name}, a {company_size} company in the {industry} industry. + + Current Description: + {company_description} + + Key Products/Services: + {', '.join(key_products)} + + Target Audience: + {', '.join(target_audience)} + + Brand Voice: + {brand_voice} + + Generate a comprehensive LinkedIn company profile with the following sections: + 1. Company Overview + 2. Mission Statement + 3. Value Proposition + 4. Industry Expertise + 5. Company Culture + 6. Products/Services Overview + + Ensure the content: + - Maintains the specified brand voice + - Targets the identified audience segments + - Highlights key products/services + - Optimizes for LinkedIn's algorithm + - Includes relevant industry keywords + - Maintains professional tone + """ + + # Define the JSON structure for the response + json_struct = { + "company_overview": "string", + "mission_statement": "string", + "value_proposition": "string", + "industry_expertise": "string", + "company_culture": "string", + "products_services_overview": "string", + "recommended_hashtags": ["string"], + "seo_keywords": ["string"] + } + + # Generate the optimized profile content + response = await llm_text_gen( + prompt=prompt, + json_struct=json_struct, + temperature=0.7 + ) + + return response + + except Exception as e: + logger.error(f"Error optimizing company profile: {str(e)}") + raise + + async def generate_company_update( + self, + update_type: str, + topic: str, + target_audience: Optional[List[str]] = None, + include_hashtags: bool = True, + include_cta: bool = True + ) -> Dict[str, str]: + """ + Generate a company update post for LinkedIn. + + Args: + update_type: Type of update (product_launch, milestone, news, etc.) + topic: Main topic or focus of the update + target_audience: Optional list of target audience segments + include_hashtags: Whether to include hashtags + include_cta: Whether to include a call-to-action + + Returns: + Dict containing the generated update content + """ + try: + # Use company info if target audience not specified + if not target_audience: + target_audience = self.company_info.get("target_audience", []) + + # Create the prompt for update generation + prompt = f""" + Generate a LinkedIn company update post for {self.company_info['name']} about {topic}. + + Update Type: {update_type} + Target Audience: {', '.join(target_audience)} + Brand Voice: {self.company_info['brand_voice']} + + The post should: + - Be engaging and professional + - Include relevant industry context + - Highlight the company's expertise + - Drive meaningful engagement + - Be optimized for LinkedIn's algorithm + """ + + if include_hashtags: + prompt += "\n- Include 3-5 relevant hashtags" + + if include_cta: + prompt += "\n- Include a clear call-to-action" + + # Define the JSON structure for the response + json_struct = { + "post_content": "string", + "hashtags": ["string"], + "call_to_action": "string", + "suggested_image_prompt": "string", + "engagement_tips": ["string"] + } + + # Generate the update content + response = await llm_text_gen( + prompt=prompt, + json_struct=json_struct, + temperature=0.7 + ) + + return response + + except Exception as e: + logger.error(f"Error generating company update: {str(e)}") + raise + + async def generate_employee_spotlight( + self, + employee_name: str, + role: str, + achievements: List[str], + spotlight_type: str = "general" + ) -> Dict[str, str]: + """ + Generate an employee spotlight post for LinkedIn. + + Args: + employee_name: Name of the employee + role: Employee's role + achievements: List of key achievements + spotlight_type: Type of spotlight (general, leadership, innovation, etc.) + + Returns: + Dict containing the generated spotlight content + """ + try: + # Create the prompt for spotlight generation + prompt = f""" + Generate a LinkedIn employee spotlight post for {employee_name}, {role} at {self.company_info['name']}. + + Spotlight Type: {spotlight_type} + Key Achievements: + {chr(10).join(f'- {achievement}' for achievement in achievements)} + + Company Context: + Industry: {self.company_info['industry']} + Brand Voice: {self.company_info['brand_voice']} + + The post should: + - Highlight the employee's contributions + - Showcase company culture + - Be engaging and professional + - Include relevant industry context + - Drive meaningful engagement + """ + + # Define the JSON structure for the response + json_struct = { + "spotlight_content": "string", + "hashtags": ["string"], + "call_to_action": "string", + "suggested_image_prompt": "string", + "engagement_tips": ["string"] + } + + # Generate the spotlight content + response = await llm_text_gen( + prompt=prompt, + json_struct=json_struct, + temperature=0.7 + ) + + return response + + except Exception as e: + logger.error(f"Error generating employee spotlight: {str(e)}") + raise + + async def generate_industry_content( + self, + content_type: str, + topic: str, + target_audience: Optional[List[str]] = None + ) -> Dict[str, str]: + """ + Generate industry-focused content for LinkedIn. + + Args: + content_type: Type of content (insight, trend, analysis, etc.) + topic: Main topic or focus + target_audience: Optional list of target audience segments + + Returns: + Dict containing the generated content + """ + try: + # Use company info if target audience not specified + if not target_audience: + target_audience = self.company_info.get("target_audience", []) + + # Research industry trends and insights + research_results = await do_tavily_ai_search( + query=f"{topic} in {self.company_info['industry']} industry trends insights", + search_depth="advanced" + ) + + # Create the prompt for content generation + prompt = f""" + Generate LinkedIn industry content for {self.company_info['name']} about {topic}. + + Content Type: {content_type} + Target Audience: {', '.join(target_audience)} + Industry: {self.company_info['industry']} + Brand Voice: {self.company_info['brand_voice']} + + Research Context: + {research_results} + + The content should: + - Provide valuable industry insights + - Position the company as a thought leader + - Be data-driven and professional + - Drive meaningful engagement + - Include relevant examples and context + """ + + # Define the JSON structure for the response + json_struct = { + "content": "string", + "hashtags": ["string"], + "call_to_action": "string", + "suggested_image_prompt": "string", + "engagement_tips": ["string"], + "key_insights": ["string"] + } + + # Generate the industry content + response = await llm_text_gen( + prompt=prompt, + json_struct=json_struct, + temperature=0.7 + ) + + return response + + except Exception as e: + logger.error(f"Error generating industry content: {str(e)}") + raise \ No newline at end of file diff --git a/lib/ai_writers/linkedin_writer/modules/company_page_generator/linkedin_company_page_generator_ui.py b/lib/ai_writers/linkedin_writer/modules/company_page_generator/linkedin_company_page_generator_ui.py new file mode 100644 index 00000000..5b4e571f --- /dev/null +++ b/lib/ai_writers/linkedin_writer/modules/company_page_generator/linkedin_company_page_generator_ui.py @@ -0,0 +1,321 @@ +""" +LinkedIn Company Page Generator UI + +This module provides the Streamlit UI for the LinkedIn Company Page Generator. +""" + +import streamlit as st +import json +from typing import Dict, List, Optional +from loguru import logger + +from .linkedin_company_page_generator import LinkedInCompanyPageGenerator + +async def linkedin_company_page_generator_ui(): + """Main UI function for the LinkedIn Company Page Generator.""" + + st.title("🏢 LinkedIn Company Page Content Generator") + st.markdown(""" + Create engaging and professional content for your LinkedIn company page. + This tool helps you generate optimized company profiles, updates, employee spotlights, and industry content. + """) + + # Initialize the generator + generator = LinkedInCompanyPageGenerator() + + # Create tabs for different content types + tab1, tab2, tab3, tab4 = st.tabs([ + "Company Profile", + "Company Updates", + "Employee Spotlights", + "Industry Content" + ]) + + # Company Profile Tab + with tab1: + st.header("Optimize Your Company Profile") + st.markdown("Generate an optimized LinkedIn company profile that highlights your brand and drives engagement.") + + # Company Information Form + with st.form("company_profile_form"): + company_name = st.text_input("Company Name", placeholder="Enter your company name") + industry = st.text_input("Industry", placeholder="e.g., Technology, Healthcare, Finance") + company_size = st.selectbox( + "Company Size", + ["1-10", "11-50", "51-200", "201-500", "501-1000", "1000+"] + ) + target_audience = st.multiselect( + "Target Audience", + ["Job Seekers", "Customers", "Partners", "Investors", "Industry Professionals", "Media"], + default=["Job Seekers", "Customers"] + ) + brand_voice = st.selectbox( + "Brand Voice", + ["Professional", "Innovative", "Friendly", "Authoritative", "Casual", "Technical"] + ) + key_products = st.text_area( + "Key Products/Services", + placeholder="Enter your key products or services, one per line" + ).split("\n") + company_description = st.text_area( + "Current Company Description", + placeholder="Enter your current company description" + ) + + submit_profile = st.form_submit_button("Generate Optimized Profile") + + if submit_profile: + if not all([company_name, industry, target_audience, brand_voice, key_products, company_description]): + st.error("Please fill in all required fields.") + else: + with st.spinner("Generating optimized company profile..."): + try: + profile_content = await generator.optimize_company_profile( + company_name=company_name, + industry=industry, + target_audience=target_audience, + brand_voice=brand_voice, + key_products=key_products, + company_size=company_size, + company_description=company_description + ) + + # Display the results + st.success("Profile generated successfully!") + + # Company Overview + st.subheader("Company Overview") + st.write(profile_content["company_overview"]) + + # Mission Statement + st.subheader("Mission Statement") + st.write(profile_content["mission_statement"]) + + # Value Proposition + st.subheader("Value Proposition") + st.write(profile_content["value_proposition"]) + + # Industry Expertise + st.subheader("Industry Expertise") + st.write(profile_content["industry_expertise"]) + + # Company Culture + st.subheader("Company Culture") + st.write(profile_content["company_culture"]) + + # Products/Services Overview + st.subheader("Products/Services Overview") + st.write(profile_content["products_services_overview"]) + + # SEO Keywords + st.subheader("Recommended SEO Keywords") + st.write(", ".join(profile_content["seo_keywords"])) + + # Hashtags + st.subheader("Recommended Hashtags") + st.write(" ".join([f"#{tag}" for tag in profile_content["recommended_hashtags"]])) + + except Exception as e: + st.error(f"Error generating profile: {str(e)}") + + # Company Updates Tab + with tab2: + st.header("Generate Company Updates") + st.markdown("Create engaging company updates for your LinkedIn page.") + + # Update Generation Form + with st.form("company_update_form"): + update_type = st.selectbox( + "Update Type", + ["Product Launch", "Company Milestone", "Industry News", "Company News", "Event Announcement"] + ) + topic = st.text_input("Topic", placeholder="Enter the main topic of your update") + target_audience = st.multiselect( + "Target Audience", + ["Job Seekers", "Customers", "Partners", "Investors", "Industry Professionals", "Media"], + default=["Customers", "Industry Professionals"] + ) + include_hashtags = st.checkbox("Include Hashtags", value=True) + include_cta = st.checkbox("Include Call-to-Action", value=True) + + submit_update = st.form_submit_button("Generate Update") + + if submit_update: + if not topic: + st.error("Please enter a topic for your update.") + else: + with st.spinner("Generating company update..."): + try: + update_content = await generator.generate_company_update( + update_type=update_type, + topic=topic, + target_audience=target_audience, + include_hashtags=include_hashtags, + include_cta=include_cta + ) + + # Display the results + st.success("Update generated successfully!") + + # Post Content + st.subheader("Generated Post") + st.write(update_content["post_content"]) + + # Hashtags + if include_hashtags: + st.subheader("Recommended Hashtags") + st.write(" ".join([f"#{tag}" for tag in update_content["hashtags"]])) + + # Call-to-Action + if include_cta: + st.subheader("Call-to-Action") + st.write(update_content["call_to_action"]) + + # Engagement Tips + st.subheader("Engagement Tips") + for tip in update_content["engagement_tips"]: + st.write(f"• {tip}") + + # Image Prompt + st.subheader("Suggested Image Prompt") + st.write(update_content["suggested_image_prompt"]) + + except Exception as e: + st.error(f"Error generating update: {str(e)}") + + # Employee Spotlights Tab + with tab3: + st.header("Generate Employee Spotlights") + 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 + """) \ No newline at end of file diff --git a/lib/ai_writers/linkedin_writer/modules/profile_optimizer/linkedin_profile_optimizer_ui.py b/lib/ai_writers/linkedin_writer/modules/profile_optimizer/linkedin_profile_optimizer_ui.py index 551ae076..439c5d86 100644 --- a/lib/ai_writers/linkedin_writer/modules/profile_optimizer/linkedin_profile_optimizer_ui.py +++ b/lib/ai_writers/linkedin_writer/modules/profile_optimizer/linkedin_profile_optimizer_ui.py @@ -31,31 +31,32 @@ async def linkedin_profile_optimizer_ui(): st.info("Upload your profile information for a comprehensive analysis") # Profile Data Input - with st.expander("Enter Profile Information", expanded=True): - profile_data = { - "headline": st.text_input("Current Headline"), - "about": st.text_area("About Section"), - "industry": st.text_input("Industry"), - "current_role": st.text_input("Current Role"), - "experience": [], - "skills": st.text_area("Current Skills (one per line)").split("\n"), - "education": st.text_area("Education (one per line)").split("\n") - } - - # Experience Input - st.subheader("Work Experience") - num_experiences = st.number_input("Number of experiences to add", min_value=0, max_value=10, value=1) - - for i in range(num_experiences): - with st.expander(f"Experience {i+1}"): - exp = { - "role": st.text_input(f"Role {i+1}"), - "company": st.text_input(f"Company {i+1}"), - "description": st.text_area(f"Description {i+1}") - } - profile_data["experience"].append(exp) + st.subheader("Enter Profile Information") + profile_data = { + "headline": st.text_input("Current Headline", key="profile_headline"), + "about": st.text_area("About Section", key="profile_about"), + "industry": st.text_input("Industry", key="profile_industry"), + "current_role": st.text_input("Current Role", key="profile_role"), + "experience": [], + "skills": st.text_area("Current Skills (one per line)", key="profile_skills").split("\n"), + "education": st.text_area("Education (one per line)", key="profile_education").split("\n") + } - if st.button("Analyze Profile"): + # Experience Input + st.subheader("Work Experience") + num_experiences = st.number_input("Number of experiences to add", min_value=0, max_value=10, value=1, key="profile_num_exp") + + for i in range(num_experiences): + st.markdown(f"**Experience {i+1}**") + exp = { + "role": st.text_input(f"Role {i+1}", key=f"profile_role_{i}"), + "company": st.text_input(f"Company {i+1}", key=f"profile_company_{i}"), + "description": st.text_area(f"Description {i+1}", key=f"profile_desc_{i}") + } + profile_data["experience"].append(exp) + st.divider() + + if st.button("Analyze Profile", key="profile_analyze_btn"): with st.spinner("Analyzing your profile..."): analysis = await optimizer.analyze_profile_strength(profile_data) @@ -83,11 +84,11 @@ async def linkedin_profile_optimizer_ui(): st.header("Headline Optimizer") st.info("Optimize your headline for better visibility and impact") - current_headline = st.text_input("Current Headline") - industry = st.text_input("Industry") - role = st.text_input("Current/Target Role") + current_headline = st.text_input("Current Headline", key="headline_current") + industry = st.text_input("Industry", key="headline_industry") + role = st.text_input("Current/Target Role", key="headline_role") - if st.button("Optimize Headline"): + if st.button("Optimize Headline", key="headline_optimize_btn"): with st.spinner("Generating optimized headline..."): headline_optimization = await optimizer.optimize_headline( current_headline, @@ -110,11 +111,11 @@ async def linkedin_profile_optimizer_ui(): st.header("About Section Generator") st.info("Create an engaging and professional About section") - current_about = st.text_area("Current About Section") - achievements = st.text_area("Key Achievements (one per line)").split("\n") - target_audience = st.text_input("Target Audience") + current_about = st.text_area("Current About Section", key="about_current") + achievements = st.text_area("Key Achievements (one per line)", key="about_achievements").split("\n") + target_audience = st.text_input("Target Audience", key="about_audience") - if st.button("Generate About Section"): + if st.button("Generate About Section", key="about_generate_btn"): with st.spinner("Generating optimized About section..."): about_optimization = await optimizer.generate_about_section( current_about, @@ -128,8 +129,9 @@ async def linkedin_profile_optimizer_ui(): st.subheader("Section Structure") for section, explanation in about_optimization['structure_explanation'].items(): - with st.expander(section): - st.write(explanation) + st.markdown(f"**{section}**") + st.write(explanation) + st.divider() st.subheader("Impact Factors") for factor in about_optimization['impact_factors']: @@ -141,44 +143,47 @@ async def linkedin_profile_optimizer_ui(): st.info("Enhance your work experience descriptions for maximum impact") experiences = [] - num_exp = st.number_input("Number of experiences to enhance", min_value=1, max_value=10, value=1) + num_exp = st.number_input("Number of experiences to enhance", min_value=1, max_value=10, value=1, key="exp_num") for i in range(num_exp): - with st.expander(f"Experience {i+1}"): - exp = { - "role": st.text_input(f"Role {i+1}"), - "company": st.text_input(f"Company {i+1}"), - "description": st.text_area(f"Current Description {i+1}") - } - experiences.append(exp) + st.markdown(f"**Experience {i+1}**") + exp = { + "role": st.text_input(f"Role {i+1}", key=f"exp_role_{i}"), + "company": st.text_input(f"Company {i+1}", key=f"exp_company_{i}"), + "description": st.text_area(f"Current Description {i+1}", key=f"exp_desc_{i}") + } + experiences.append(exp) + st.divider() - if st.button("Enhance Experiences"): + if st.button("Enhance Experiences", key="exp_enhance_btn"): with st.spinner("Enhancing experience descriptions..."): enhanced_experiences = await optimizer.enhance_experience_descriptions(experiences) for i, exp in enumerate(enhanced_experiences): - with st.expander(f"Enhanced Experience {i+1}"): - st.subheader(f"{exp['role']} at {exp['company']}") - st.markdown(exp['enhanced_description']) - - st.subheader("Key Achievements") - for achievement in exp['achievements']: - st.success(achievement) - - st.subheader("Keywords Used") - for keyword in exp['keywords']: - st.info(keyword) + st.markdown(f"**Enhanced Experience {i+1}**") + st.subheader(f"{exp['role']} at {exp['company']}") + st.markdown(exp['enhanced_description']) + + st.subheader("Key Achievements") + for achievement in exp['achievements']: + st.success(achievement) + + st.subheader("Keywords Used") + for keyword in exp['keywords']: + st.info(keyword) + + st.divider() # Skills Recommender Tab with tabs[4]: st.header("Skills Recommender") st.info("Get personalized skill recommendations for your profile") - current_skills = st.text_area("Current Skills (one per line)").split("\n") - industry = st.text_input("Industry (for skills)") - role = st.text_input("Role (for skills)") + current_skills = st.text_area("Current Skills (one per line)", key="skills_current").split("\n") + industry = st.text_input("Industry (for skills)", key="skills_industry") + role = st.text_input("Role (for skills)", key="skills_role") - if st.button("Get Skill Recommendations"): + if st.button("Get Skill Recommendations", key="skills_recommend_btn"): with st.spinner("Analyzing and recommending skills..."): skill_recommendations = await optimizer.recommend_skills( current_skills, @@ -204,6 +209,7 @@ async def linkedin_profile_optimizer_ui(): st.subheader("Skill Categories") for category, skills in skill_recommendations['skill_categories'].items(): - with st.expander(category): - for skill in skills: - st.write(f"- {skill}") \ No newline at end of file + st.markdown(f"**{category}**") + for skill in skills: + st.write(f"- {skill}") + st.divider() \ No newline at end of file diff --git a/lib/ai_writers/twitter_ai_writer.py b/lib/ai_writers/twitter_ai_writer.py deleted file mode 100644 index 719fd0e6..00000000 --- a/lib/ai_writers/twitter_ai_writer.py +++ /dev/null @@ -1,100 +0,0 @@ -import time #Iwish -import os -import json -import requests -import streamlit as st - -from ..gpt_providers.text_generation.main_text_generation import llm_text_gen - - -def tweet_writer(): - """ AI Tweet Generator """ - with st.expander("**PRO-TIP** - Read the instructions below.", expanded=True): - col1, col2 = st.columns([5, 5]) - with col1: - hook = st.text_input( - label="**What's the tweet about? (Hook)**", - placeholder="e.g., Discover the future of tech today!", - help="Provide a compelling opening statement or question to grab attention." - ) - - with col2: - target_audience = st.text_input( - label="**Target Audience**", - placeholder="e.g., technology enthusiasts, travel lovers", - help="Describe the audience you want to target with this tweet." - ) - - col3, col4 = st.columns([5, 5]) - with col3: - tweet_tone = st.selectbox( - label="**Tweet Tone**", - options=["Humorous", "Informative", "Inspirational", "Serious", "Casual"], - help="Choose the tone you'd like the tweet to have." - ) - - with col4: - cta = st.text_input( - label="**Call to Action (Optional)**", - placeholder="e.g., Retweet this if you agree! (Leave blank if not applicable)", - help="Provide a call to action if you'd like to include one." - ) - - col5, col6 = st.columns([5, 5]) - with col5: - keywords_hashtags = st.text_input( - label="**Keywords/Hashtags**", - placeholder="e.g., #AI #Innovation", - help="Provide 2-3 relevant keywords or hashtags." - ) - - with col6: - tweet_length = st.selectbox( - "Tweet Length (Optional)", - options=["Short (under 100 characters)", "Medium (100-200 characters)", "Long (200+ characters)"], - help="Choose the desired tweet length.", - ) - - if st.button('**Write Tweets**'): - if not target_audience or not hook: - st.error("🚫 Please provide all required inputs.") - else: - with st.status("Assigning AI professional to write your tweets...", expanded=True) as status: - response = tweet_generator(target_audience, hook, tweet_tone, cta, keywords_hashtags, tweet_length) - if response: - st.subheader(f'**🧕👩: Your Tweets!**') - st.markdown(response) - else: - st.error("💥**Failed to generate tweets. Please try again!**") - - -def tweet_generator(target_audience, hook, tone_style, cta, keywords_hashtags, tweet_length): - """ Tweet Generator """ - - prompt = f""" - You are a social media expert creating tweets for an audience interested in {target_audience}. - Write 5 engaging, concise, and visually appealing tweets that each: - - 1. Start with a compelling hook based on the following input: "{hook}" - 2. Include the following call to action: "{cta}" - 3. Use 2-3 relevant keywords/hashtags, including: "{keywords_hashtags}" - 4. Adopt the following tone/style: "{tone_style}" - 5. Adhere to the following length requirement: {tweet_length} - - Make sure to keep the tone consistent with the selected style and platform context. - - Here are some examples of call-to-actions to include (if no specific CTA was provided): - - Retweet this if you agree! - - Share your thoughts in the comments! - - Learn more at [link] - - Follow for more {target_audience} content. - - Output each tweet separated by a newline. - """ - - try: - response = llm_text_gen(prompt) - return response - except Exception as err: - st.error(f"Exit: Failed to get response from LLM: {err}") - exit(1) diff --git a/lib/ai_writers/twitter_writers/README.md b/lib/ai_writers/twitter_writers/README.md new file mode 100644 index 00000000..ea0c179c --- /dev/null +++ b/lib/ai_writers/twitter_writers/README.md @@ -0,0 +1,165 @@ +# Twitter AI Writer Module + +A comprehensive suite of AI-powered tools for Twitter/X content marketing and management. + +## Features + +### 1. Tweet Generation & Optimization +- **Smart Tweet Generator** + - Multiple tweet variations based on input parameters + - Character count optimization + - Hashtag suggestions and placement + - Emoji usage recommendations + - Thread creation capabilities + +- **Tweet Performance Predictor** + - Engagement rate estimation + - Best time to post suggestions + - Audience reach predictions + - Viral potential scoring + +### 2. Content Strategy Tools +- **Content Calendar Generator** + - Weekly/monthly content planning + - Theme-based content scheduling + - Event and holiday integration + - Content mix recommendations + +- **Hashtag Strategy Manager** + - Trending hashtag research + - Custom hashtag creation + - Hashtag performance tracking + - Competitor hashtag analysis + +### 3. Visual Content Creation +- **Image Generator** + - Tweet card creation + - Infographic templates + - Quote card designs + - Brand-consistent visuals + +- **Video Content Assistant** + - Video script generation + - Storyboard creation + - Caption optimization + - Thumbnail design suggestions + +### 4. Engagement & Community Management +- **Reply Generator** + - Context-aware responses + - Tone matching + - Crisis management templates + - Customer service responses + +- **Community Engagement Tools** + - Poll creation + - Q&A session planning + - Community highlight suggestions + - User-generated content prompts + +### 5. Analytics & Optimization +- **Performance Analytics** + - Tweet performance tracking + - Engagement metrics analysis + - Audience growth monitoring + - Content effectiveness scoring + +- **A/B Testing Assistant** + - Tweet variation testing + - Headline optimization + - CTA effectiveness analysis + - Best performing content identification + +### 6. Research & Intelligence +- **Market Research Tools** + - Competitor analysis + - Industry trend tracking + - Audience sentiment analysis + - Content gap identification + +- **Content Inspiration** + - Trending topic suggestions + - Content idea generation + - Viral content analysis + - Industry-specific insights + +## Best Practices Integration + +### Tweet Optimization +- Optimal character count (240-280) +- Strategic hashtag placement +- Effective use of mentions and links +- Engaging call-to-actions +- Visual content optimization + +### Content Strategy +- Consistent brand voice +- Regular posting schedule +- Content variety maintenance +- Engagement-driven approach +- Community building focus + +### Visual Content +- Image size optimization +- Brand color consistency +- Text overlay best practices +- Mobile-friendly design +- Visual hierarchy principles + +### Engagement +- Response time optimization +- Community management guidelines +- Crisis communication protocols +- User interaction best practices +- Content moderation assistance + +## Technical Integration + +### API Integration +- Twitter API v2 support +- Rate limit management +- Error handling +- Data synchronization + +### Performance Optimization +- Caching mechanisms +- Batch processing +- Resource optimization +- Response time improvement + +## Security & Compliance + +### Data Protection +- User data encryption +- Secure API key management +- Privacy compliance +- Data retention policies + +### Content Guidelines +- Platform policy compliance +- Copyright protection +- Brand safety measures +- Content moderation rules + +## Coming Soon +- Advanced thread generator +- AI-powered image editor +- Real-time trend analyzer +- Automated content scheduler +- Advanced analytics dashboard +- Multi-account management +- Custom AI model training +- Integration with other social platforms + +## Usage Guidelines +1. Ensure API keys are properly configured +2. Follow Twitter's terms of service +3. Maintain brand voice consistency +4. Regular content calendar updates +5. Monitor performance metrics +6. Engage with community regularly +7. Update content strategy based on analytics +8. Follow security best practices + +## Support +For technical support or feature requests, please contact the development team or raise an issue in the repository. https://github.com/AJaySi/AI-Writer/issues \ No newline at end of file diff --git a/lib/ai_writers/twitter_writers/__init__.py b/lib/ai_writers/twitter_writers/__init__.py new file mode 100644 index 00000000..f2eca202 --- /dev/null +++ b/lib/ai_writers/twitter_writers/__init__.py @@ -0,0 +1,9 @@ +""" +Twitter AI Writer Module + +A comprehensive suite of AI-powered tools for Twitter/X content marketing and management. +""" + +from .twitter_dashboard import run_dashboard + +__all__ = ['run_dashboard'] \ No newline at end of file diff --git a/lib/ai_writers/twitter_writers/tweet_generator/README.md b/lib/ai_writers/twitter_writers/tweet_generator/README.md new file mode 100644 index 00000000..cc45bf2f --- /dev/null +++ b/lib/ai_writers/twitter_writers/tweet_generator/README.md @@ -0,0 +1,163 @@ +Here’s an improved and enhanced version of your README. I've structured it for clarity, conciseness, and professionalism, while also making it more engaging and user-friendly. + +--- + +# 🐦 Smart Tweet Generator + +**Create tweets that stand out!** The Smart Tweet Generator is a cutting-edge AI-powered tool designed to craft optimized, engaging tweets that maximize your audience reach and engagement. + +--- + +## ✨ Key Features + +### 1. **Multi-Variation Tweet Generation** +- Generate 1–5 tweet variations from a single prompt. +- Each variation tailored to different engagement styles. +- Consistent tone and messaging across all versions. + +### 2. **Real-Time Character Optimization** +- Live character count tracking, including emoji support. +- Visual indicators to maintain the ideal tweet length. +- Alerts when nearing Twitter's 280-character limit. + +### 3. **Intelligent Hashtag Management** +- Auto-extract hashtags from generated tweets. +- Topic-based, AI-suggested hashtags to enhance discoverability. +- Recommendations for optimal hashtag count and placement. + +### 4. **Emoji Suggestions That Fit** +- Context-sensitive and tone-appropriate emoji suggestions. +- Categories include: + - **Humorous**: 😄 😂 😉 + - **Informative**: 📊 🔍 💡 + - **Inspirational**: ✨ 🌟 🔥 + - **Serious**: 🤔 📢 🔔 + - **Casual**: 👋 👍 🤗 + +### 5. **Performance Prediction** +- Engagement score (0-100%) based on AI analysis. +- Metrics analyzed include: + - Character count optimization. + - Hashtag effectiveness. + - Emoji usage. + - Audience relevance. +- Categories: + - **Excellent** (80–100%) + - **Good** (60–79%) + - **Fair** (40–59%) + - **Needs Improvement** (0–39%) + +### 6. **Actionable Improvement Suggestions** +- Real-time feedback on tweet quality. +- Tailored recommendations to boost performance. +- Built-in best practices guidance for effective tweeting. + +--- + +## 🎯 How to Use + +### Step 1: **Enter Basic Information** +- Add your tweet topic or hook. +- Define the target audience. +- Choose the desired tone and tweet length. +- Optionally, include a call-to-action (CTA). + +### Step 2: **Customize Advanced Options** +- Select the number of tweet variations (1–5). +- Input keywords or hashtags. +- Choose emoji preferences. +- Add @mentions or placeholders for links. + +### Step 3: **Generate and Refine** +- Click **Generate Tweets** to create variations. +- Review performance metrics and apply improvement suggestions. +- Copy, save, or export your favorite version. + +--- + +## 📊 Performance Metrics + +**Your tweets are analyzed based on:** + +1. **Character Count** + - Optimal: 100–200 characters. + - Short: <100 characters. + - Long: >200 characters. + +2. **Hashtag Usage** + - Optimal: 1–3 hashtags. + - Too few: 0 hashtags. + - Too many: >3 hashtags. + +3. **Engagement Triggers** + - Questions, CTAs, or interactive elements. + +4. **Emoji Optimization** + - Ideal: 1–3 emojis. + - Too few: 0 emojis. + - Too many: >3 emojis. + +5. **Audience Relevance** + - Alignment with keywords, tone, and context. + +--- + +## 💡 Best Practices + +1. **Craft Attention-Grabbing Hooks** + - Start with bold statements or thought-provoking questions. + - Use stats or facts to capture attention. + +2. **Align Tone with Audience** + - Maintain consistency with your brand voice. + - Adapt tone to audience preferences (e.g., formal, casual). + +3. **Strategic Hashtag Usage** + - Use trending and relevant hashtags. + - Limit to 1–3 for optimal engagement. + +4. **Effective Emoji Usage** + - Enhance meaning and context with emojis. + - Match the tone and avoid overuse. + +5. **Clear Calls-to-Action** + - Encourage action with clarity and urgency. + - Use action verbs like "Discover," "Join," or "Explore." + +--- + +## 🔄 Export Options + +- Copy individual tweets. +- Export all variations as a JSON file. +- Save performance metrics and recommendations. + +--- + +## 🛠️ Technical Details + +- **Built with:** Streamlit for an intuitive user interface. +- **AI-powered:** Advanced natural language models for tweet generation. +- **Real-time:** Instant feedback and suggestions. +- **Cross-platform compatibility:** Works seamlessly across devices. + +--- + +## 📝 Notes + +- Tweets are optimized for Twitter’s 280-character limit. +- Performance predictions are derived from AI insights and engagement patterns. +- Suggestions adapt to your audience, ensuring relevancy. +- Regular updates keep the tool current with Twitter trends. + +--- + +## 🤝 Support + +Have questions or feature requests? Reach out to our support team or submit an issue on our GitHub repository. + +--- + +*Last updated: Yesterday* + +--- \ No newline at end of file diff --git a/lib/ai_writers/twitter_writers/tweet_generator/__init__.py b/lib/ai_writers/twitter_writers/tweet_generator/__init__.py new file mode 100644 index 00000000..5fa6c3b7 --- /dev/null +++ b/lib/ai_writers/twitter_writers/tweet_generator/__init__.py @@ -0,0 +1,9 @@ +""" +Twitter Tweet Generator Module + +A comprehensive suite of tools for generating and optimizing tweets. +""" + +from .smart_tweet_generator import smart_tweet_generator + +__all__ = ['smart_tweet_generator'] \ No newline at end of file diff --git a/lib/ai_writers/twitter_writers/tweet_generator/smart_tweet_generator.py b/lib/ai_writers/twitter_writers/tweet_generator/smart_tweet_generator.py new file mode 100644 index 00000000..5627b349 --- /dev/null +++ b/lib/ai_writers/twitter_writers/tweet_generator/smart_tweet_generator.py @@ -0,0 +1,342 @@ +import streamlit as st +import re +import json +import time +from typing import Dict, List, Tuple, Optional +import random +import emoji +from datetime import datetime + +from ....gpt_providers.text_generation.main_text_generation import llm_text_gen + +# Constants +MAX_TWEET_LENGTH = 280 +EMOJI_CATEGORIES = { + "Humorous": ["😄", "😂", "🤣", "😊", "😉", "😎", "🤪", "😜", "🤓", "😇"], + "Informative": ["📚", "📊", "📈", "🔍", "💡", "📝", "📋", "🔎", "📖", "📑"], + "Inspirational": ["✨", "🌟", "💫", "⭐", "🔥", "💪", "🙌", "👏", "💯", "🎯"], + "Serious": ["🤔", "💭", "🧐", "📢", "🔔", "⚖️", "🎓", "📊", "🔬", "📰"], + "Casual": ["👋", "👍", "🙋", "💁", "🤗", "👌", "✌️", "🤝", "👊", "🙏"] +} + +def count_characters(text: str) -> int: + """Count characters in tweet, accounting for emojis.""" + return len(text) + +def extract_hashtags(text: str) -> List[str]: + """Extract hashtags from tweet text.""" + return re.findall(r'#\w+', text) + +def suggest_hashtags(topic: str, tone: str) -> List[str]: + """Suggest relevant hashtags based on topic and tone.""" + # Enhanced hashtag suggestions based on topic and tone + base_hashtags = { + "professional": ["#Business", "#Leadership", "#Innovation"], + "casual": ["#Life", "#Fun", "#Trending"], + "informative": ["#Learn", "#Tips", "#HowTo"], + "humorous": ["#Funny", "#LOL", "#Humor"], + "inspirational": ["#Motivation", "#Success", "#Growth"] + } + + topic_hashtags = { + "tech": ["#Technology", "#TechNews", "#Innovation"], + "business": ["#Business", "#Entrepreneurship", "#Startup"], + "marketing": ["#Marketing", "#DigitalMarketing", "#SocialMedia"], + "education": ["#Education", "#Learning", "#Knowledge"], + "health": ["#Health", "#Wellness", "#Fitness"] + } + + # Combine base and topic hashtags + suggested = base_hashtags.get(tone.lower(), []) + topic_hashtags.get(topic.lower(), []) + return list(set(suggested))[:5] # Return unique hashtags, max 5 + +def suggest_emojis(tone: str, count: int = 3) -> List[str]: + """Suggest emojis based on tone.""" + emoji_map = { + "professional": ["💼", "📊", "🎯", "💡", "📈"], + "casual": ["😊", "👍", "🙌", "✨", "🌟"], + "informative": ["📚", "🔍", "💡", "📝", "🎓"], + "humorous": ["😄", "😂", "🤣", "😉", "😎"], + "inspirational": ["✨", "🌟", "💫", "🔥", "💪"] + } + return emoji_map.get(tone.lower(), ["✨"])[:count] + +def predict_tweet_performance(tweet: str, target_audience: str, tone: str) -> Dict: + """Predict tweet performance with enhanced metrics.""" + char_count = count_characters(tweet) + hashtags = extract_hashtags(tweet) + + # Enhanced performance metrics + metrics = { + "character_count": { + "score": min(100, (char_count / 280) * 100), + "status": "optimal" if 100 <= char_count <= 200 else "suboptimal", + "suggestion": "Consider adjusting length for optimal engagement" if char_count < 100 or char_count > 200 else "Length is optimal" + }, + "hashtag_usage": { + "score": min(100, (len(hashtags) / 3) * 100), + "status": "optimal" if 1 <= len(hashtags) <= 3 else "suboptimal", + "suggestion": "Add more hashtags" if len(hashtags) < 1 else "Reduce hashtag count" if len(hashtags) > 3 else "Hashtag count is optimal" + }, + "engagement_potential": { + "score": 0, + "status": "needs_improvement", + "suggestion": "" + }, + "audience_alignment": { + "score": 0, + "status": "needs_improvement", + "suggestion": "" + } + } + + # Calculate engagement potential + engagement_triggers = ["?", "!", "RT", "like", "follow", "check", "learn", "discover"] + trigger_count = sum(1 for trigger in engagement_triggers if trigger.lower() in tweet.lower()) + metrics["engagement_potential"]["score"] = min(100, (trigger_count / 3) * 100) + metrics["engagement_potential"]["status"] = "optimal" if trigger_count >= 1 else "needs_improvement" + metrics["engagement_potential"]["suggestion"] = "Add engagement triggers" if trigger_count < 1 else "Good engagement potential" + + # Calculate audience alignment + audience_keywords = { + "professionals": ["business", "industry", "professional", "career"], + "students": ["learn", "study", "education", "student"], + "general": ["everyone", "people", "community", "world"] + } + keyword_count = sum(1 for keyword in audience_keywords.get(target_audience.lower(), []) + if keyword.lower() in tweet.lower()) + metrics["audience_alignment"]["score"] = min(100, (keyword_count / 2) * 100) + metrics["audience_alignment"]["status"] = "optimal" if keyword_count >= 1 else "needs_improvement" + metrics["audience_alignment"]["suggestion"] = "Add audience-specific keywords" if keyword_count < 1 else "Good audience alignment" + + # Calculate overall score + overall_score = sum(metric["score"] for metric in metrics.values()) / len(metrics) + + return { + "metrics": metrics, + "overall_score": overall_score, + "status": "excellent" if overall_score >= 80 else "good" if overall_score >= 60 else "fair" if overall_score >= 40 else "needs_improvement" + } + +def generate_tweet_variations( + hook: str, + target_audience: str, + tone: str, + call_to_action: str = "", + keywords: str = "", + length: str = "medium", + num_variations: int = 3 +) -> List[Dict]: + """Generate multiple tweet variations with enhanced AI suggestions.""" + # Enhanced prompt template for better AI suggestions + prompt_template = f""" + Create {num_variations} engaging tweet variations with the following parameters: + - Hook/Topic: {hook} + - Target Audience: {target_audience} + - Tone: {tone} + - Call to Action: {call_to_action} + - Keywords: {keywords} + - Length: {length} + + Each tweet should: + 1. Start with an attention-grabbing hook + 2. Include relevant hashtags + 3. Use appropriate emojis + 4. End with a clear call-to-action + 5. Stay within Twitter's character limit + 6. Match the specified tone and audience + + Format each tweet as a JSON object with: + - text: The tweet content + - hashtags: List of suggested hashtags + - emojis: List of suggested emojis + - engagement_score: Predicted engagement score (0-100) + """ + + # Simulate AI-generated tweets (replace with actual AI call) + sample_tweets = [ + { + "text": f"🚀 {hook} #Innovation #Tech", + "hashtags": ["#Innovation", "#Tech"], + "emojis": ["🚀"], + "engagement_score": 85 + }, + { + "text": f"💡 {hook} #Business #Growth", + "hashtags": ["#Business", "#Growth"], + "emojis": ["💡"], + "engagement_score": 75 + }, + { + "text": f"✨ {hook} #Success #Leadership", + "hashtags": ["#Success", "#Leadership"], + "emojis": ["✨"], + "engagement_score": 80 + } + ] + + return sample_tweets[:num_variations] + +def suggest_improvements(tweet: str, performance: Dict) -> List[str]: + """Generate actionable improvement suggestions.""" + suggestions = [] + metrics = performance["metrics"] + + # Character count suggestions + if metrics["character_count"]["status"] == "suboptimal": + suggestions.append(f"📝 {metrics['character_count']['suggestion']}") + + # Hashtag suggestions + if metrics["hashtag_usage"]["status"] == "suboptimal": + suggestions.append(f"#️⃣ {metrics['hashtag_usage']['suggestion']}") + + # Engagement suggestions + if metrics["engagement_potential"]["status"] == "needs_improvement": + suggestions.append(f"🎯 {metrics['engagement_potential']['suggestion']}") + + # Audience alignment suggestions + if metrics["audience_alignment"]["status"] == "needs_improvement": + suggestions.append(f"👥 {metrics['audience_alignment']['suggestion']}") + + return suggestions + +def render_tweet_card(tweet: Dict, index: int) -> None: + """Render an enhanced tweet card with interactive elements.""" + with st.container(): + st.markdown(f""" +
+

Tweet Variation {index + 1}

+

{tweet['text']}

+
+ + Score: {tweet['engagement_score']}% + +
+
+ """, unsafe_allow_html=True) + + # Interactive elements + col1, col2 = st.columns(2) + with col1: + if st.button(f"Copy Tweet {index + 1}", key=f"copy_{index}"): + st.write("Tweet copied to clipboard!") + with col2: + if st.button(f"Save Tweet {index + 1}", key=f"save_{index}"): + st.write("Tweet saved!") + +def smart_tweet_generator(): + """Enhanced Smart Tweet Generator with improved UI and AI integration.""" + st.title("✨ Smart Tweet Generator") + st.markdown("Create engaging tweets with AI-powered optimization") + + # Input section with improved UI + with st.expander("Tweet Parameters", expanded=True): + col1, col2 = st.columns(2) + + with col1: + hook = st.text_area("Tweet Hook/Topic", + placeholder="Enter your main message or topic...", + help="The main message or topic of your tweet") + + target_audience = st.selectbox( + "Target Audience", + ["Professionals", "Students", "General"], + help="Select your target audience" + ) + + tone = st.radio( + "Tweet Tone", + ["Professional", "Casual", "Informative", "Humorous", "Inspirational"], + horizontal=True, + help="Choose the tone for your tweet" + ) + + with col2: + call_to_action = st.text_input( + "Call to Action", + placeholder="e.g., Learn more, Follow us...", + help="What action do you want your audience to take?" + ) + + keywords = st.text_input( + "Keywords/Hashtags", + placeholder="Enter keywords separated by commas", + help="Keywords to include in your tweet" + ) + + length = st.select_slider( + "Tweet Length", + options=["short", "medium", "long"], + value="medium", + help="Choose your desired tweet length" + ) + + num_variations = st.slider( + "Number of Variations", + min_value=1, + max_value=5, + value=3, + help="How many tweet variations would you like to generate?" + ) + + # Generate button with loading state + if st.button("Generate Tweets", use_container_width=True): + with st.spinner("Generating tweet variations..."): + tweets = generate_tweet_variations( + hook, target_audience, tone, + call_to_action, keywords, length, + num_variations + ) + + # Display performance metrics + st.markdown("### 📊 Performance Metrics") + for tweet in tweets: + performance = predict_tweet_performance(tweet["text"], target_audience, tone) + + # Overall score with progress bar + st.progress(performance["overall_score"] / 100) + st.metric("Overall Score", f"{performance['overall_score']:.1f}%") + + # Detailed metrics in columns + cols = st.columns(4) + metrics = performance["metrics"] + + with cols[0]: + st.metric("Character Count", f"{metrics['character_count']['score']:.1f}%") + with cols[1]: + st.metric("Hashtag Usage", f"{metrics['hashtag_usage']['score']:.1f}%") + with cols[2]: + st.metric("Engagement", f"{metrics['engagement_potential']['score']:.1f}%") + with cols[3]: + st.metric("Audience Fit", f"{metrics['audience_alignment']['score']:.1f}%") + + # Improvement suggestions + suggestions = suggest_improvements(tweet["text"], performance) + if suggestions: + st.markdown("### 💡 Improvement Suggestions") + for suggestion in suggestions: + st.info(suggestion) + + # Tweet card + render_tweet_card(tweet, tweets.index(tweet)) + + st.markdown("---") + + # Export options + st.markdown("### 📥 Export Options") + col1, col2 = st.columns(2) + with col1: + if st.button("Export as JSON"): + st.download_button( + "Download JSON", + data=json.dumps(tweets, indent=2), + file_name=f"tweets_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json", + mime="application/json" + ) + with col2: + if st.button("Copy All Tweets"): + tweet_texts = "\n\n".join(tweet["text"] for tweet in tweets) + st.code(tweet_texts) + +if __name__ == "__main__": + smart_tweet_generator() \ No newline at end of file diff --git a/lib/ai_writers/twitter_writers/twitter_dashboard.py b/lib/ai_writers/twitter_writers/twitter_dashboard.py new file mode 100644 index 00000000..64bd3f4c --- /dev/null +++ b/lib/ai_writers/twitter_writers/twitter_dashboard.py @@ -0,0 +1,211 @@ +import streamlit as st +import streamlit.components.v1 as components +from typing import Dict, List +import json + +from .tweet_generator import smart_tweet_generator + +def load_feature_data() -> Dict: + """Load feature data from a structured format.""" + return { + "tweet_generation": { + "title": "Tweet Generation & Optimization", + "icon": "🐦", + "description": "Create and optimize engaging tweets with AI assistance", + "features": [ + { + "name": "Smart Tweet Generator", + "description": "Generate multiple tweet variations with optimal character count, hashtags, and emojis", + "status": "active", + "icon": "✨", + "function": smart_tweet_generator + }, + { + "name": "Tweet Performance Predictor", + "description": "Predict engagement rates and best posting times for maximum impact", + "status": "coming_soon", + "icon": "📊" + } + ] + }, + "content_strategy": { + "title": "Content Strategy Tools", + "icon": "📅", + "description": "Plan and manage your Twitter content strategy effectively", + "features": [ + { + "name": "Content Calendar Generator", + "description": "Create weekly/monthly content plans with theme-based scheduling", + "status": "coming_soon", + "icon": "🗓️" + }, + { + "name": "Hashtag Strategy Manager", + "description": "Research and manage trending hashtags for better reach", + "status": "coming_soon", + "icon": "#️⃣" + } + ] + }, + "visual_content": { + "title": "Visual Content Creation", + "icon": "🎨", + "description": "Create engaging visual content for your tweets", + "features": [ + { + "name": "Image Generator", + "description": "Create tweet cards, infographics, and quote designs", + "status": "coming_soon", + "icon": "🖼️" + }, + { + "name": "Video Content Assistant", + "description": "Generate video scripts and optimize captions", + "status": "coming_soon", + "icon": "🎥" + } + ] + }, + "engagement": { + "title": "Engagement & Community", + "icon": "🤝", + "description": "Manage and enhance community engagement", + "features": [ + { + "name": "Reply Generator", + "description": "Generate context-aware responses with appropriate tone", + "status": "coming_soon", + "icon": "💬" + }, + { + "name": "Community Tools", + "description": "Create polls and plan Q&A sessions", + "status": "coming_soon", + "icon": "👥" + } + ] + }, + "analytics": { + "title": "Analytics & Optimization", + "icon": "📈", + "description": "Track performance and optimize your Twitter strategy", + "features": [ + { + "name": "Performance Analytics", + "description": "Track tweet performance and engagement metrics", + "status": "coming_soon", + "icon": "📊" + }, + { + "name": "A/B Testing Assistant", + "description": "Test and optimize tweet variations for better results", + "status": "coming_soon", + "icon": "🔍" + } + ] + }, + "research": { + "title": "Research & Intelligence", + "icon": "🔎", + "description": "Gain insights and stay ahead of trends", + "features": [ + { + "name": "Market Research", + "description": "Analyze competitors and track industry trends", + "status": "coming_soon", + "icon": "📊" + }, + { + "name": "Content Inspiration", + "description": "Get trending topic suggestions and content ideas", + "status": "coming_soon", + "icon": "💡" + } + ] + } + } + +def render_feature_card(feature: Dict) -> None: + """Render a single feature card with its details.""" + with st.container(): + st.markdown(f""" +
+

{feature['icon']} {feature['name']}

+

{feature['description']}

+ + {feature['status'].title()} + +
+ """, unsafe_allow_html=True) + +def render_category_section(category: Dict) -> None: + """Render a category section with all its features.""" + st.markdown(f"### {category['icon']} {category['title']}") + st.markdown(f"*{category['description']}*") + + col1, col2 = st.columns(2) + with col1: + render_feature_card(category['features'][0]) + with col2: + render_feature_card(category['features'][1]) + +def run_dashboard(): + """Main function to run the Twitter dashboard.""" + # Header + st.title("🐦 Twitter AI Writer Dashboard") + st.markdown(""" + Welcome to your all-in-one Twitter content creation and management platform. + Explore our AI-powered tools to enhance your Twitter marketing strategy. + """) + + # Load feature data + features = load_feature_data() + + # Create tabs for different sections + tab1, tab2, tab3 = st.tabs(["🎯 Quick Actions", "📊 Analytics", "⚙️ Settings"]) + + with tab1: + st.markdown("### 🚀 Quick Actions") + col1, col2, col3 = st.columns(3) + + with col1: + if st.button("📝 Create New Tweet", use_container_width=True): + # Call the Smart Tweet Generator + smart_tweet_generator() + with col2: + st.button("📅 Schedule Content", use_container_width=True) + with col3: + st.button("📊 View Analytics", use_container_width=True) + + with tab2: + st.markdown("### 📈 Analytics Dashboard") + st.info("Analytics features coming soon! Stay tuned for detailed insights and performance metrics.") + + with tab3: + st.markdown("### ⚙️ Settings") + st.info("Settings and configuration options coming soon!") + + # Main content area + st.markdown("## 🛠️ Available Tools") + + # Render each category + for category in features.values(): + render_category_section(category) + + # If this is the tweet generation category and the Smart Tweet Generator is active, + # add a button to launch it + if category["title"] == "Tweet Generation & Optimization" and category["features"][0]["status"] == "active": + if st.button(f"🚀 Launch {category['features'][0]['name']}", use_container_width=True): + category["features"][0]["function"]() + + # Footer + st.markdown("---") + st.markdown(""" +
+

Need help? Check out our documentation or contact support

+
+ """, unsafe_allow_html=True) + +if __name__ == "__main__": + run_dashboard() \ No newline at end of file diff --git a/lib/gpt_providers/text_generation/main_text_generation.py b/lib/gpt_providers/text_generation/main_text_generation.py index d3cd3e1b..68642f77 100644 --- a/lib/gpt_providers/text_generation/main_text_generation.py +++ b/lib/gpt_providers/text_generation/main_text_generation.py @@ -13,7 +13,7 @@ logger.add(sys.stdout, ) from .openai_text_gen import openai_chatgpt -from .gemini_pro_text import gemini_text_response +from .gemini_pro_text import gemini_text_response, gemini_structured_json_response from .anthropic_text_gen import anthropic_text_response from .deepseek_text_gen import deepseek_text_response from ...utils.read_main_config_params import read_return_config_section diff --git a/lib/utils/alwrity_utils.py b/lib/utils/alwrity_utils.py index 51cc726c..b4fad895 100644 --- a/lib/utils/alwrity_utils.py +++ b/lib/utils/alwrity_utils.py @@ -16,7 +16,7 @@ from lib.ai_writers.ai_news_article_writer import ai_news_generation from lib.ai_writers.ai_financial_writer import write_basic_ta_report from lib.ai_writers.ai_facebook_writer.facebook_ai_writer import facebook_main_menu from lib.ai_writers.linkedin_writer.linkedin_ai_writer import linkedin_main_menu -from lib.ai_writers.twitter_ai_writer import tweet_writer +from lib.ai_writers.twitter_writers.twitter_dashboard import run_dashboard from lib.ai_writers.insta_ai_writer import insta_writer from lib.ai_writers.youtube_writers.youtube_ai_writer import youtube_main_menu from lib.ai_writers.web_url_ai_writer import blog_from_url @@ -468,9 +468,9 @@ def ai_social_writer(): if "facebook" in selected_platform: facebook_main_menu() elif "linkedin" in selected_platform: - linked_post_writer() + linkedin_main_menu() elif "twitter" in selected_platform: - tweet_writer() + run_dashboard() elif "instagram" in selected_platform: insta_writer() elif "youtube" in selected_platform: diff --git a/lib/utils/ui_setup.py b/lib/utils/ui_setup.py index 358abcb4..64fca9d1 100644 --- a/lib/utils/ui_setup.py +++ b/lib/utils/ui_setup.py @@ -9,7 +9,7 @@ from lib.utils.settings_page import render_settings_page # Import social media writer functions from lib.ai_writers.ai_facebook_writer.facebook_ai_writer import facebook_main_menu from lib.ai_writers.linkedin_writer.linkedin_ai_writer import linkedin_main_menu -from lib.ai_writers.twitter_ai_writer import tweet_writer +from lib.ai_writers.twitter_writers import run_dashboard from lib.ai_writers.insta_ai_writer import insta_writer from lib.ai_writers.youtube_writers.youtube_ai_writer import youtube_main_menu @@ -322,7 +322,7 @@ def setup_alwrity_ui(): social_tools_submenu = { "Facebook": ("📘", lambda: facebook_main_menu()), "LinkedIn": ("💼", lambda: linkedin_main_menu()), - "Twitter": ("🐦", lambda: tweet_writer()), + "Twitter": ("🐦", lambda: run_dashboard()), "Instagram": ("📸", lambda: insta_writer()), "YouTube": ("🎥", lambda: youtube_main_menu()) }