Generate LinkedIn Posts from Books Using OpenAI, LangChain & Pinecone Vector Search

Automates the process of generating, storing, and publishing engaging LinkedIn posts derived from books (PDFs) using AI and vector search. --- ## Overview This workflow: 1. **Watches a Google Drive folder** for new or updated book PDFs. 2. **Extracts and embeds** the content using OpenAI. 3. **Stores the data** in a Pinecone vector database. 4. **Uses a LangChain agent** to generate post ideas. 5. **Creates concise LinkedIn posts** with hook, insight, CTA. 6. **Updates a Google Sheet** and posts to LinkedIn. --- ## Workflow Breakdown ### 1. Google Drive Trigger - **Trigger:** Watches a folder for new or updated PDF files. - **Action:** Downloads the updated PDF. ### 2. Extract and Embed Content - **Extract from File:** Parses PDF to extract text. - **Text Splitter:** Breaks text into chunks. - **Embeddings (OpenAI):** Converts chunks into vector embeddings. - **Pinecone Vector Store:** Saves the embeddings with the book name as namespace. ### 3. Post Idea Generation (LangChain Agent) - Uses a prompt to: - Search Pinecone DB - Extract insights - Format into 5 LinkedIn post ideas with: - **Hook** - **Insight** - **CTA** - **Memory buffer** and structured output parser are used for clean AI interaction. ### 4. Post Creation - Each idea is: - **Split** - Rewritten with a GPT model prompt to match LinkedIn tone - Styled for under 600 characters - Includes emojis, hashtags, and tone guidelines ### 5. Google Sheet Integration - Saves all generated posts to a **Google Sheet**. - Marks status: `published` or `no`. ### 6. Scheduled Publishing - Every day: - Pulls an unpublished post - Publishes it to LinkedIn - Updates the post's status and timestamp in the Google Sheet --- ## Setup Guide ### Google Drive - Create a folder for book PDFs - Connect your Google Drive account to n8n - Provide access token with file read permission ### Google Sheets - Create a Google Sheet with columns: - `bookname`, `hook`, `insight`, `cta`, `postContent`, `published`, `date` - Add credentials in n8n with read/write permission ### Pinecone - Set up a Pinecone project and index (`linkedinpost`) - Namespace will be auto-named using the book filename ### API Credentials Required - **OpenAI API** (for embeddings and post generation) - **Pinecone API** (for vector storage and retrieval) - **LinkedIn OAuth2** (to publish posts) - **Google Drive & Sheets** credentials --- ## Flow Summary ```mermaid graph D A[Google Drive Trigger] --> B[Download PDF] B --> C[Extract Text] C --> D[Text Splitter] D --> E[Create Embeddings] E --> F[Pinecone Vector Store] F --> G[LangChain Agent] G --> H[Structured Output (5 Post Ideas)] H --> I[Split Ideas] I --> J[Format as LinkedIn Post (GPT)] J --> K[Store in Google Sheet] L[Schedule Trigger] --> M[Get Unpublished Post] M --> N[Post to LinkedIn] N --> O[Mark as Published] ``` --- ## Prompt Example (Used in LangChain Agent) ```text You are a content strategist. Search the Pinecone vector DB containing a book. Generate 5 unique LinkedIn post ideas with: - A Hook (curiosity driven) - Insight (summary < 100 words) - CTA (Agree or disagree?, etc.) Respond in structured JSON: [ { "Hook": ..., "Insight": ..., "CTA": ... }, ... ] ``` --- ## Output Sample ```json { "Hook": "Why your lab's results might be invalid ±", "Insight": "ISO/IEC 17025 stresses that labs must plan and address risks to impartiality and validity.", "CTA": "Does your lab audit for these risks?" } ``` --- ## Schedule Control - Uses **Schedule Trigger** to post daily at a set time. - Ensures automation with LinkedIn and accurate Google Sheet syncing. --- ## Notes - Posts remain **professional and concise** for a LinkedIn audience. - Works with **any PDF book**. - Supports multi-book pipelines. - You can filter and tag books by filename or folder for segmenting post styles.

Platform

n8n

Category

Social Media

Price

Free

Creator

Mohamed Abdelwahab

• if
• limit
• linkedIn
• splitOut
• aggregate
• stickyNote
• googleDrive
• googleSheets
• agent
• extractFromFile