AI-Powered Stock Sentiment Analysis from Chat
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Instantly analyze stock sentiment directly from a chat message. This n8n workflow leverages AI agents to perform real-time financial news research and deliver a comprehensive sentiment analysis, helping you make informed decisions quickly.
About This Workflow
Unlock intelligent insights into market sentiment with this powerful n8n workflow. Triggered by a simple chat message, this automation acts as your personal financial analyst. It orchestrates two sophisticated AI agents: a 'Research Agent' that scours the web for the latest company news using the SearXNG tool and a 'Sentiment Analysis Agent' that meticulously evaluates the compiled information. Powered by Google Gemini, the workflow delivers a clear sentiment categorization (Positive, Negative, or Neutral) along with a detailed justification, enabling rapid, data-driven financial decisions right from your chat interface.
Key Features
- Interactive Chat Trigger: Initiate analysis by sending a company name or stock ticker in a chat message.
- Dual AI Agent Architecture: Separates financial research and sentiment analysis into specialized intelligent agents.
- Real-time Web Search: Automatically finds and summarizes the latest news using configurable search tools (e.g., SearXNG).
- Comprehensive Sentiment Categorization: Provides clear Positive, Negative, or Neutral sentiment with detailed justifications.
- Flexible LLM Integration: Built with Google Gemini, easily swappable with other large language models.
How To Use
- Select Your Language Model (LLM): The workflow is pre-configured with Google Gemini. You can choose a different compatible LLM for both the 'Research Agent' and 'Sentiment Analysis Agent' nodes if desired.
- Configure LLM Credentials: Ensure that valid API credentials for your chosen Large Language Model are correctly set up and connected within your n8n instance.
- Set Up the SearXNG Connection: Configure the 'web_search' node to connect to your self-hosted SearXNG instance or another supported web search tool. This is crucial for the agent's web research capabilities.
- Define the Research Agent's Task: Customize the 'systemMessage' parameter within the 'Research Agent' node to fine-tune its role, research instructions, and how it should conduct its news gathering.
- Define the Sentiment Analysis Agent's Task: Adjust the 'systemMessage' parameter in the 'Sentiment Analysis Agent' node to refine how it analyzes the research output and categorizes sentiment, including the output format.
- Test the Workflow: Once configured, activate the workflow and use the built-in chat interface (accessible from the 'When chat message received' node) in the n8n canvas to send a company name or stock ticker and verify that the agents are functioning correctly.
Apps Used
Workflow JSON
{
"id": "42e37799-7afa-4954-9070-99729e9c36ea",
"name": "AI-Powered Stock Sentiment Analysis from Chat",
"nodes": 22,
"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.
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ID: 42e37799-7afa...
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