AI-powered Upwork cover letter generator – Pinecone, Groq, Google Gemin, SerpAPI

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2/3/2026

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🚀 Automated Upwork Cover Letter Generator with n8n + MacOS Shortcut + Pinecone Context Retrieval

This n8n automation is designed to streamline the Upwork proposal process by generating highly personalized, context-aware cover letters using your own skills and project data stored in a Pinecone vector store.

With the help of an AI Agent powered by Groq’s Qwen LLM, and triggered instantly via a MacOS Shortcut, this system takes job descriptions from your clipboard and returns a ready-to-use HTML cover letter—right on your desktop.

⚙️ Workflow Breakdown

🔹 MacOS Shortcut – Trigger the Workflow Instantly

The process begins with a MacOS Shortcut that captures job description text from your clipboard and sends it to a custom webhook in n8n.

🔹 Webhook Node – Receive and Process Input

The webhook node receives the clipboard data, along with the required credentials for authentication. This node serves as the entry point to the full automation.

🔹 Field Mapping & Pre-Processing

A series of basic logic nodes map and clean up the input fields. These are then passed to an LLM Chain to generate specific questions related to the job description.

🔹 Question Answer Chain + Vector Search (Pinecone)

Using your previously stored skills and project data in a Pinecone vector store, the system retrieves relevant information to answer the generated questions and builds a rich context around the job description.

🔹 AI Agent Node – Generate Personalized Cover Letter

With both the job post and contextual data, the AI Agent (powered by Groq’s Qwen LLM) creates a tailored cover letter.
The agent is equipped with:

🔍 Google Search Tool
🧠 Vector Store Retriever Tool
🗃️ Buffer Memory

This ensures the generated proposal is insightful, relevant, and professional.

🔹 Markdown to HTML – Clean Output Conversion

The markdown output from the AI is converted into HTML using a Markdown node, making it easy to paste directly into Upwork or emails.

🔹 Return to Shortcut – Display Final Result

The final HTML response is sent back to the MacOS Shortcut, which displays it in a modal window for easy review and copy-paste.

💼 Use Case

This automation is built specifically for freelancers on Upwork (or any freelance platform) who want to:

✅ Save time on repetitive proposal writing
✅ Create job-specific cover letters with context
✅ Stand out with better personalization
✅ Reduce manual effort with automation

Whether you’re a beginner or a seasoned pro, this tool elevates your workflow while staying simple to use.

📦 Setup Instructions

Import Workflow to your n8n instance
Create and Configure MacOS Shortcut (drag-and-drop ready)
Prepare and Embed Your Skills/Project Data into Pinecone
Add API Credentials:
- Groq (for Qwen LLM)
- Pinecone
- n8n Webhook (Basic Auth if needed)
Run the Workflow & Submit Smarter Proposals

> Note: This workflow is designed for building and returning Upwork cover letters using job descriptions copied to your clipboard. All generation is context-aware and tailored per submission.

AI-Powered Upwork Cover Letter Generator (Pinecone, Groq, Google Gemini, SerpApi)

This n8n workflow automates the generation of personalized Upwork cover letters using a combination of AI models and tools. It leverages Groq for chat, Google Gemini for embeddings, Pinecone for vector store management, and SerpApi for web search, all orchestrated through LangChain nodes.

What it does

This workflow acts as an AI agent that can intelligently generate tailored cover letters.

Receives a Request: The workflow is triggered by an incoming webhook, expecting a payload that likely contains details about an Upwork job posting and the user's profile.
Initial Data Setup: An "Edit Fields" node prepares the incoming data for further processing.
AI Agent Orchestration:
- Groq Chat Model: Serves as the primary language model for conversational AI and generation.
- Google Gemini Embeddings: Used to create vector embeddings for text, enabling semantic search and retrieval.
- Pinecone Vector Store: Stores and retrieves vectorized information, likely for context about the user's skills or past applications.
- SerpApi (Google Search) Tool: Provides the AI agent with real-time web search capabilities to gather information about job requirements, company details, or industry trends.
- Vector Store Question Answer Tool: Allows the AI agent to query the Pinecone vector store to answer specific questions based on stored data.
- Simple Memory: Maintains a conversational history for the AI agent, allowing for more coherent and context-aware responses.
- Question and Answer Chain: A LangChain chain specifically designed for retrieving information from the vector store and answering questions.
- Basic LLM Chain: A general-purpose LangChain LLM chain for various text generation and processing tasks.
Generates Markdown Output: The AI agent's output, which is the generated cover letter, is formatted into Markdown.
Responds to Webhook: The final Markdown-formatted cover letter is sent back as the response to the initial webhook trigger.

Prerequisites/Requirements

To use this workflow, you will need:

n8n Instance: A running instance of n8n.
Groq Account & API Key: For the Groq Chat Model.
Google Cloud Account & Gemini API Key: For the Embeddings Google Gemini.
Pinecone Account & API Key: For the Pinecone Vector Store. You will also need to set up an index in Pinecone.
SerpApi Account & API Key: For the SerpApi (Google Search) Tool.
LangChain Credentials: Ensure your n8n instance has the necessary LangChain credentials configured for Groq, Google Gemini, Pinecone, and SerpApi.

Setup/Usage

Import the Workflow: Download the JSON provided and import it into your n8n instance.
Configure Credentials:
- For each of the AI/tool nodes (Groq Chat Model, Embeddings Google Gemini, Pinecone Vector Store, SerpApi), click on the node and configure your respective API credentials.
- Ensure your Pinecone Vector Store node is configured with the correct index name.
Activate the Workflow: Once all credentials are set, activate the workflow.
Trigger the Webhook: Send an HTTP POST request to the Webhook URL provided by the "Webhook" trigger node. The request body should contain the necessary information for generating a cover letter (e.g., job description, company name, your skills, etc.).
Receive Cover Letter: The workflow will process the request and respond with a Markdown-formatted cover letter.

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