This AI-powered workflow enhances Shopify product descriptions based on product name or URL provided by the user. It leverages LLMs, retrieves product content from Shopify and product URLs, and generates improved descriptions, streamlining product listing optimization for e-commerce stores.
Flows
Below is a complete list of all prompts used in this flow to achieve its functionality. Prompts are the instructions given to the AI model to generate responses or perform actions. They guide the AI in understanding user intent and generating relevant outputs.
Custom AI agent with user-defined backstory and goal, used to generate enhanced product descriptions for Shopify products.
Backstory: marketer with 20 years of experience
Goal: the user will give you a product name in their shopify store or a product URL as input and your task is to enhance its product description
Below is a complete list of all components used in this flow to achieve its functionality. Components are the building blocks of every AI Flow. They allow you to create complex interactions and automate tasks by connecting various functionalities. Each component serves a specific purpose, such as handling user input, processing data, or integrating with external services.
The Chat Input component in FlowHunt initiates user interactions by capturing messages from the Playground. It serves as the starting point for flows, enabling the workflow to process both text and file-based inputs.
The Get Products component connects your FlowHunt workflow to a Shopify store, allowing you to fetch and sort product listings directly from your integrated shop. Easily pull product data by criteria like best-selling, price, or relevance to streamline e-commerce automations and chatbot responses.
Unlock web content in your workflows with the URL Retriever component. Effortlessly extract and process the text and metadata from any list of URLs—including web articles, documents, and more. Supports advanced options like OCR for images, selective metadata extraction, and customizable caching, making it ideal for building knowledge-rich AI flows and automations.
The Chat History component in FlowHunt enables chatbots to remember previous messages, ensuring coherent conversations and improved customer experience while optimizing memory and token usage.
FlowHunt supports dozens of AI models, including Claude models by Anthropic. Learn how to use Claude in your AI tools and chatbots with customizable settings for tailored responses.
The AI Agent component in FlowHunt empowers your workflows with autonomous decision-making and tool-using capabilities. It leverages large language models and connects to various tools to solve tasks, follow goals, and provide intelligent responses. Ideal for building advanced automations and interactive AI solutions.
Discover the Chat Output component in FlowHunt—finalize chatbot responses with flexible, multi-part outputs. Essential for seamless flow completion and creating advanced, interactive AI chatbots.
Flow description
This workflow automates the process of enhancing product descriptions for Shopify stores by leveraging advanced AI and data retrieval tools. It is designed to take either a product name from a user’s Shopify store or a specific product URL, retrieve relevant product information, and generate an improved product description with the help of a specialized AI agent.
User Input Collection:
The workflow starts by collecting input from the user through a chat interface. The user can provide either a product name from their Shopify store or a product URL.
Chat History Management:
The system retrieves the last 5 chat messages or up to 800 tokens from the chat history. This helps the AI agent maintain context, enabling follow-up questions and more coherent conversations.
Product Data and Content Retrieval:
The workflow employs two retrieval mechanisms:
AI Model Integration:
The workflow uses the Anthropic Claude 3.5 Sonnet V2 language model, configured with a high maximum token limit (4000 tokens) and a deterministic temperature (0), to generate high-quality, consistent responses. This model powers both the agent’s general reasoning and its ability to call functions/tools.
AI Agent Orchestration:
At the heart of the workflow is an AI agent, configured with the following properties:
Output Delivery:
The final enhanced product description is presented back to the user via a chat interface, maintaining a seamless conversational experience.
| Step | Input Source | Processing/Tool | Output Type |
|---|---|---|---|
| User Input | Chat Input | – | Product Name/URL (Message) |
| Chat Context | Chat History | – | Last 5 messages |
| Shopify Product Data | Shopify Store (Get Products) | Product Retriever Tool | Product Info (Tool) |
| URL Content Extraction | Provided URL | URL Retriever Tool | Product Page Content (Tool) |
| AI Model | – | Anthropic Claude 3.5 LLM | Language Model (ChatModel) |
| AI Agent | All above | LLM-powered Agent | Enhanced Description (Message) |
| Display Output | AI Agent Output | Chat Output | To User (Chat Message) |
This workflow is particularly valuable for e-commerce businesses looking to scale content creation and maintain high standards for product listings. By automating the process of researching and rewriting product descriptions, businesses can improve SEO, customer experience, and conversion rates without dedicating extensive manual resources. The use of AI ensures that every description is both original and tailored to the product, while the integration of chat history and retrieval tools keeps the workflow adaptable and user-friendly.
In summary:
This workflow empowers users to quickly enhance Shopify product descriptions through an intelligent, automated process that combines AI, data retrieval, and conversational context — all delivered in a scalable, efficient, and user-centric manner.
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