Related Articles Paragraph Generator

How the AI Flow works - Related Articles Paragraph Generator

Flows

How the AI Flow works

Prompts used in this flow

Prompt

A simple prompt template for passing through context and input to LLM.

{context} {input} 

Prompt

Prompt to instruct LLM to write a readable, concise paragraph with markdown links to related articles for a web page.

you are skilled copywriter with strong focus on easy readability of text you write.
Don't use sophisticated words - it should be easy to understand.
Focus on detailed information. Don't use phrases like "In todays fast changing world...", "In today's complex...", "is a crucial step", "plays significant role", "fast-paced...", "pivotal role", "In the ever-evolving landscape of" or "In the realm of ...", always cut to the point without useless conclusions or intros.

Write paragraph for web page with url "{input}".
Paragraph should give hint to visitor what he should read as next after reading the current page.

For each related article pick the most relevant keyword to the article and make it a link (markdown format).
Incorporate in the paragraph links to each article in the list.

In Context is list of the most relevant pages to current page, current page can be included as well.
Don't list current page in the paragraph as related article.
--- MOST RELATED ARTICLES ---
 {context} 
--- END OF RELEVANT ARTICLES ---

Write paragraph in the same language as language of related documents.
Paragraph should have 2 sentences for each related document.
If there are no related articles, return just one space character as the answer

Prompt

Prompt to generate a list of useful keywords and context for further LLM steps.

Useful keywords:
 {input}
---

{context} 

Components used in this flow

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.

ChatInput

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.

Document Retriever

FlowHunt's Document Retriever enhances AI accuracy by connecting generative models to your own up-to-date documents and URLs, ensuring reliable and relevant answers using Retrieval-Augmented Generation (RAG).

Prompt Component in FlowHunt

Learn how FlowHunt's Prompt component lets you define your AI bot’s role and behavior, ensuring relevant, personalized responses. Customize prompts and templates for effective, context-aware chatbot flows.

Generator

Explore the Generator component in FlowHunt—powerful AI-driven text generation using your chosen LLM model. Effortlessly create dynamic chatbot responses by combining prompts, optional system instructions, and even images as input, making it a core tool for building intelligent, conversational workflows.

Keyword Frequency Evaluator

Analyze your texts to discover the most frequent and significant keywords using the Keyword Frequency Evaluator component in FlowHunt. Automatically extract top keywords, filter out common stopwords, and fine-tune results based on frequency, word length, and keyword overlap—ideal for text analysis, information extraction, and content summarization workflows.

Chat Output

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.

Message Widget

The Message Widget component displays custom messages within your workflow. Ideal for welcoming users, providing instructions, or showing any important information, it supports Markdown formatting and can be set to appear only once per session.

Chat Opened Trigger

The Chat Opened Trigger component detects when a chat session starts, enabling workflows to respond instantly as soon as a user opens the chat. It initiates flows with the initial chat message, making it essential for building responsive, interactive chatbots.

Flow description

Purpose and benefits

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