AI-Powered Comprehensive Web Research Assistant
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This n8n workflow automates comprehensive web research based on a user's query. It intelligently generates multiple, strategic search queries using Google Gemini 2.0 Flash and then executes these queries to gather relevant information, streamlining your research process.
About This Workflow
Unlock advanced information gathering with this powerful n8n workflow, a reproduction of the gemini-fullstack-langgraph-quickstart concept. Designed for deep dives, it begins by taking a user's free-form question and leveraging Google's Gemini 2.0 Flash model to craft a set of diverse, targeted web search queries. The workflow is highly configurable, allowing you to set parameters like the number of initial queries and research loops. It then systematically executes these queries, laying the groundwork for comprehensive data collection. This automation is perfect for professionals needing quick, insightful research without manual query formulation or repetitive searching, enhancing decision-making and knowledge acquisition across various fields.
Key Features
- Intelligent Query Generation: Utilizes Google Gemini 2.0 Flash to dynamically generate sophisticated and diverse search queries based on user input, ensuring highly relevant results.
- Configurable Research Depth: Easily adjust parameters like
number_of_initial_queriesandmax_research_loopsto precisely control the breadth and depth of your automated research efforts. - Structured AI Output: AI-generated queries and their rationales are parsed into a clear, structured JSON format, making subsequent data processing straightforward and actionable.
- Dynamic Contextualization: Automatically incorporates the current date into generated queries for up-to-the-minute information retrieval and maintains conversational context for ongoing research.
- Advanced AI Agent Pattern: Built upon the robust
gemini-fullstack-langgraph-quickstartmethodology, offering a reliable and advanced AI agent framework for complex research tasks.
How To Use
- Configure API Credentials: Ensure your
Google Gemini(PaLM) APIcredentials are properly set up and connected to theGoogle Gemini Chat Modelnode (ID:200465bd-6af2-41dc-9a83-7726b8ea64eb). - Adjust Research Parameters: Navigate to the
Configsnode (ID:81280c83-b194-441b-98cc-0a1e3b32a3a7). Here, you can modifynumber_of_initial_queries(default: 3) to control how many initial search queries Gemini generates, andmax_research_loops(default: 3) to set the maximum iterations for deeper research. - Provide User Query: The workflow is designed to start with a user's chat message or input (implied by expressions like
$('When chat message received').item.json.chatInput). Make sure your initial trigger node provides the user's research question in the expected format. - Review Query Generation Logic: Inspect the
generate_querynode (ID:9f6dca8b-0ecd-4957-860e-bd2fd3757804) to understand how Gemini is prompted to create search queries, including the use of dynamic variables likecurrent_date. - Complete Web Search Integration: The workflow snippet shows the setup for
web_searchusing a code node (ID:89711398-353a-4183-98a3-0cd706331971). You will need to complete this section, typically by integrating anHTTP Requestnode to interact with a Google Search API or similar web search tool to execute the generated queries and retrieve results.
Apps Used
Workflow JSON
{
"id": "e89806b2-8c2f-42ea-ba9c-860bc3c3a745",
"name": "AI-Powered Comprehensive Web Research Assistant",
"nodes": 26,
"category": "Operations",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: e89806b2-8c2f...
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