AI Content Generation and Multilingual Metadata for WordPress and Social Media

• AI-powered Content Generation: Utilizes Langchain nodes with various LLMs (OpenAI, Gemini, Azure OpenAI) to generate article titles, body content, and optimize text.
• Multilingual Metadata: Generates structured metadata in both English and Chinese using LLMs and a structured output parser.
• Featured Image Generation: Creates unique featured images using OpenAI DALL-E.
• WordPress Integration: Publishes generated articles as draft posts to WordPress and attaches the featured image.
• Social Media Distribution: Distributes content to multiple social media platforms including X (Twitter), LinkedIn, Discord, Threads, and Bluesky.
• Conditional Logic: Employs 'If' and 'Switch' nodes for conditional execution and routing of content to different platforms.
• Trigger Flexibility: Supports both scheduled (every 3 hours) and manual triggers, as well as a Telegram bot for command-based initiation.
• Content Optimization: Includes an AI Content Optimizer node to refine generated text.
• OpenRouter Integration: Uses OpenRouter for flexible model selection and content generation.
• Structured Output Parsing: Leverages outputParserStructured nodes to ensure consistent data formatting from LLMs.

1. Triggers: The workflow can be initiated via a Scheduled Auto Trigger (Every 3 Hours)1, a Telegram Trigger, or a Start (manual trigger) node.
2. Topic and Title Generation: The Topic Chooser and Title Maker node (using Google Gemini Chat Model and Parse Blog Metadata JSON) generates initial topics and titles. The Article Generator (alt) and Article Generator (alt2) nodes can also be used for alternative content generation.
3. Article Body Generation: The Generate Article Body node, connected to the Topic Chooser and Title Maker, generates the main article content. The Azure OpenAI Chat Model and OpenAI Chat Model are available as potential LLMs for this step.
4. Multilingual Metadata Generation: The Topic Chooser and Title Maker and Parse Blog Metadata JSON nodes are configured to produce structured metadata in English and Chinese. Ensure these nodes are properly configured with prompts to output JSON that includes keys for both 'en' and 'zh' metadata.
5. Featured Image Generation: The Generate Featured Image (OpenAI) node creates an image based on the article content.
6. WordPress Publishing: The Create WP Draft Post node publishes the generated article as a draft. The Upload Image to Wordpress and Attach Feature Image to Post nodes handle adding the featured image.
7. Content Optimization and Distribution Preparation: The AI Content Optimizer node refines the content. The Split Platform Content node prepares the content for different social media platforms.
8. Social Media Routing: The Route to Platform node directs the content to the appropriate social media nodes based on defined conditions.
9. Social Media Posting: Nodes like Post to X, Post to LinkedIn, Post to Discord, Post to Threads, and Post to Bluesky handle the actual posting. The Generate text container, Edit Fields, and Get Access Token nodes are part of the social media posting logic, likely for authentication or specific platform formatting.

Key Configuration Points:

• LLM Nodes (@n8n/n8n-nodes-langchain.*): Ensure API keys and model configurations are set correctly within each LLM node (e.g., Google Gemini Chat Model, Azure OpenAI Chat Model, OpenAI Chat Model, lmChatOpenAi, lmChatGoogleGemini, lmChatOpenRouter).
• WordPress Node: Configure your WordPress credentials.
• Social Media Nodes: Set up API keys and authentication for each social media platform.
• outputParserStructured Nodes: These are crucial for defining the schema of the output from LLMs. The structure defined here will dictate the keys available for multilingual metadata (e.g., en, zh). Ensure the prompt in the preceding LLM node instructs the model to output JSON conforming to this schema.