LinkedIn AI Auto Poster

Overview

The LinkedIn AI Auto Poster is an intelligent, AI-driven solution designed to automate the creation and publishing of engaging LinkedIn content. Leveraging cutting-edge Azure OpenAI technology, this application streamlines content generation and ensures consistent, high-quality posting directly to LinkedIn. Ideal for professionals looking to enhance their digital presence effortlessly, this automated system saves significant time while maintaining active audience engagement.

Features

• AI-Enhanced Daily Automation: Automatically executes daily at 9 AM, handling content creation and posting seamlessly.
• Dynamic AI Topic Generation: Utilizes Azure OpenAI to craft unique and relevant topics, intelligently avoiding repetition.
• Automated Content Creation: Produces captivating LinkedIn posts with advanced AI-generated insights.
• DALL-E 3 Image Generation: Creates professional, engaging images for each post to boost engagement and visibility.
• Direct LinkedIn Integration: Publishes AI-crafted content with images directly to your LinkedIn profile or page.
• Efficient Data Storage: Archives generated posts, images, and metadata in Azure Cosmos DB for future reference and analysis.

Architecture

The solution leverages these Azure services:

• Azure Functions: Scheduled timer-triggered functions manage daily automation.
• Azure OpenAI: Provides generative AI capabilities for topic and content creation.
• Azure Cosmos DB: Securely stores generated posts, ensuring data persistence and easy retrieval.
• Azure Blob Storage: Stores generated images before posting.
• Azure Key Vault: Securely manages API keys and connection strings.

Project Structure

linkedin_ai_auto_poster/
├── host.json
├── local.settings.json
├── package.json
├── tsconfig.json
├── src/
│   ├── index.ts
│   ├── constants/
│   ├── flow/
│   │   └── linkedin_post_flow.ts
│   ├── functions/
│   │   ├── auto_post.ts
│   │   ├── test_linkedin_post.ts
│   │   └── test_image_generation.ts
│   ├── prompts/
│   │   ├── generate_linkedin_post_derek_huynen.md
│   │   ├── generate_topic_derek_huynen.md
│   │   └── generate_linkedin_image_prompt.md
│   ├── service/
│   │   ├── CosmosService.ts
│   │   ├── LinkedinService.ts
│   │   ├── MdService.ts
│   │   └── OpenAiService.ts
│   └── types/
│       └── Post.ts
├── scripts/
│   ├── deploy-infra.sh
│   └── publishProfile.publishsettings
├── ReadMe.md

Key Components

• linkedin_post_flow.ts: Coordinates the intelligent AI-driven workflow.
• auto_post.ts: Azure Function scheduled trigger implementation.
• CosmosService.ts: Manages database interactions.
• LinkedinService.ts: Handles LinkedIn API interactions.
• OpenAiService.ts: Facilitates content and topic generation using Azure OpenAI.

Getting Started

Quick Setup

1. Clone & Navigate:

   git clone <repository-url>
   cd linkedin_ai_auto_poster

2. Install Dependencies:

   npm install

3. Configure Variables: Set your environment variables in local.settings.json.

4. Local Execution: Run locally with Azure Functions Core Tools:

   func start

5. Test Image Generation: Test the DALL-E 3 image generation feature:

   .\scripts\test_dalle3.ps1

6. Deploy to Azure:

   func azure functionapp publish <function-app-name>

Documentation

• Main Guide: ReadMe.md - Overview and main documentation
• Environment Variables: ENVIRONMENT_VARIABLES.md - Configuration settings
• Image Generation Guide: IMAGE_GENERATION_GUIDE.md - Using the image generation feature
• DALL-E 3 Testing: DALLE3_TESTING.md - Testing the DALL-E 3 integration
• Customizing Images: CUSTOMIZE_DALLE3_IMAGES.md - Tailoring image generation
• Sample Prompts: SAMPLE_IMAGE_PROMPTS.md - Example prompts for reference

Azure AI Setup

1. Azure AI Foundry & Hub

• Create resources via Azure Portal to host and manage your AI models.

2. Model Deployment

• Deploy your chosen OpenAI model and note endpoint and API details.

LinkedIn API Integration

1. LinkedIn Developer Project:

   • Visit LinkedIn Developers to create and configure your app.

2. Generate OAuth Token:

   • Obtain access tokens via LinkedIn’s OAuth tools.

3. Retrieve LinkedIn URN:

   • Use the LinkedIn API:

     GET https://api.linkedin.com/v2/userinfo

     • Pass the Authorization: Bearer <access_token> header to get your member URN.

4. Secure Credentials:

   • Save tokens securely in your environment variables.

Cosmos DB Configuration

1. Create Cosmos DB Instance:

   • Set up Cosmos DB on Azure Portal and define the data model (src/types/Post.ts).

2. Configure Credentials:

   • Store DB credentials in environment variables.

Best Practices

• Security: Utilize Azure Key Vault for managing sensitive credentials.
• Robust Error Handling: Implement retries with exponential backoff.
• Optimized Performance: Enhance query performance and use caching where feasible.
• Comprehensive Logging: Enable detailed logs for monitoring and troubleshooting.

Future Roadmap

• Multi-platform social media support
• Web dashboard for managing content
• Advanced analytics integration for detailed performance tracking

Additional Resources

• Azure Functions
• Azure OpenAI Service
• Azure Cosmos DB