AI Content Idea Generator

Generate unique content ideas and summaries using AI by researching top Google results for any keyword. Ideal for content marketers and creators to quickly discover trending topics and avoid repetitive suggestions.

Flows

How the AI Flow works

User provides a keyword.: The user enters a keyword or topic they want content ideas for.
Google search for top links.: The workflow searches Google for relevant URLs based on the user’s keyword.
Retrieve content from URLs.: The workflow extracts key content and context from the top search results.
Generate unique content ideas.: An AI model analyzes the gathered content and creates original topic ideas and summaries, avoiding repetition from previous outputs.
Present ideas to user.: The generated content ideas and summaries are displayed to the user for inspiration or direct use.

Prompts used in this flow

Prompt

Prompt template used to instruct the LLM to generate unique and detailed content ideas based on input, chat history, and optional context, while enforcing a spe...

You are an AI language model assistant tasked with generating content ideas based on web searches of the product or URLs, while avoiding repeating ideas from previous articles.

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.

Your task is to provide unique content suggestions based on INPUT, considering any previous discussion in CHAT HISTORY. 

If CONTEXT is provided, use it to enhance the relevance of your suggestions. 

Answer in English and format the answer with markdown. 

Additionally, assist the user by suggesting related topics or trends as requested.  

*** CONTEXT START ***
{context}
***

*** CHAT HISTORY ***
{chat_history}
***

INPUT:
{input}

ANSWER:

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.

See ChatInput

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.

See Chat Opened Trigger

Button Widget

The Button Widget component in FlowHunt transforms text or input into interactive, clickable buttons within your workflow. Perfect for creating dynamic user interfaces, collecting user choices, and improving engagement in AI-driven chatbots or automated processes.

See Button Widget

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.

See Chat Output

Chat History Component

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.

See Chat History Component

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.

See Prompt Component in FlowHunt

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.

See Generator

GoogleSearch Component

FlowHunt's GoogleSearch component enhances chatbot accuracy using Retrieval-Augmented Generation (RAG) to access up-to-date knowledge from Google. Control results with options like language, country, and query prefixes for precise and relevant outputs.

See GoogleSearch Component

URL Retriever

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.

See URL Retriever

Flow description

Purpose and benefits

Overview

The “Content Idea Generator” workflow is designed to automate the process of generating unique content topics and concise summaries based on a user’s keyword or subject of interest. It leverages real-time web search, content extraction from URLs, and an AI language model to provide high-quality, non-repetitive content ideas. This workflow is especially useful for content creators, marketers, bloggers, or researchers aiming to scale topic ideation and ensure their content remains fresh and relevant.

Step-by-Step Workflow

1. User Input & Welcome Interface

Chat Opened Trigger: When the user opens the chat, a welcome message and instructions are displayed via a Button Widget. Example buttons like “I want to write about chatbots” or “I want to write about Transformer models” are shown to guide the user.
Manual Input Option: The user can also type a custom keyword or topic through a chat input field.

2. Web Search & Content Gathering

Google Search Node: Once the user submits a keyword, the workflow performs a Google search for relevant URLs and content on the topic.
URL Retriever: The workflow fetches the actual content from the list of URLs returned by the search. This ensures the AI has up-to-date, context-rich information to work with.

3. Contextual Awareness

Chat History Node: Maintains a history of previous interactions, so the AI avoids repeating ideas and can reference past discussions.
Context Compilation: The content extracted from URLs is assembled and prepared as “context” for prompt generation.

4. Dynamic Prompt Generation

Prompt Template Node:
- A specially crafted prompt template is used, taking into account the user input, content from recent web searches, chat history, and any additional context.
- The prompt is strict about avoiding generic or cliché phrases, ensuring the generated suggestions are direct, detailed, and valuable.
- The AI is instructed to answer in English and format results using Markdown for easy readability.
- If requested, the AI can also suggest related topics and trends.

5. AI Content Generation

Generator Node: The AI model receives the formatted prompt and generates a list of unique content ideas along with brief summaries, all informed by the latest web-sourced context and previous chat history.

6. Output & User Interaction

Chat Output Nodes: The generated content ideas and summaries are displayed to the user in the chat interface, ready to be reviewed or used for further content development.

Workflow Structure (Simplified Table)

Step	Component	Purpose/Action
1. Chat Trigger	ChatOpenedTrigger	Welcomes user, displays example topic buttons
2. User Input	ChatInput, Buttons	User enters or selects topic
3. Search	GoogleSearch	Finds relevant URLs for user topic
4. Content Fetch	URLRetriever	Extracts content from top URLs
5. Context Memory	ChatHistory	Feeds previous chat to avoid repeats
6. Prompting	PromptTemplate	Merges input, context, and history into a tailored prompt
7. Generation	Generator	AI generates topic ideas and summaries
8. Display Output	ChatOutput	Shows results to user in chat

Why This Workflow is Useful for Scaling & Automation

Automates Research: Instantly searches the web and retrieves current information, saving hours of manual work.
Ensures Uniqueness: Remembers previous ideas and avoids repeating them, helping maintain content originality across large-scale campaigns.
Consistent Quality: Uses a rigorously defined prompt to ensure concise, on-topic, and actionable suggestions, minimizing fluff or generic statements.
Flexible Input: Supports both button-based quick starts and custom keyword input, adapting to different user needs or workflows.
Ready for Integration: The modular structure allows for easy integration into larger content pipelines or automation systems.

Ideal Use Cases

Content Teams: Quickly generate new article or video topics at scale, informed by the latest online trends and discussions.
SEO & Marketing: Discover fresh angles and keyword-rich topics based on live search data.
Research & Academia: Identify potential research topics or literature review angles with up-to-date context.
Product or Service Launches: Brainstorm unique content ideas for new product announcements, using real-world context and competitor analysis.

Conclusion

This workflow streamlines and supercharges the content ideation process by combining live data gathering, intelligent prompt engineering, and AI-powered generation. It is particularly valuable for anyone aiming to automate, scale, and improve the quality of content topic generation while ensuring each suggestion is relevant and up-to-date.

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How the AI Flow works