Real Estate Intelligence Tracker with Bright Data & OpenAI

This n8n workflow automates the process of extracting, enriching, and storing real estate listing data. It leverages web scraping (via Bright Data, though the specific node is not present in the provided JSON, it's implied by the directory name), OpenAI for intelligent data extraction, and Google Sheets for structured storage.

The workflow simplifies the task of monitoring real estate markets by automatically pulling listing information, identifying key details, and organizing them in a spreadsheet.

What it does

1. Manual Trigger: Initiates the workflow upon manual execution.
2. Read/Write Files from Disk: (Likely a placeholder or part of a larger external process) Reads data from disk. In the context of "Bright Data," this might involve loading a list of URLs or configurations for scraping.
3. Edit Fields (Set): Prepares the input for the OpenAI model by setting specific fields, likely formatting the raw real estate listing text into a prompt.
4. OpenAI Chat Model: Processes the prepared text using an OpenAI chat model (e.g., GPT-3.5, GPT-4) to extract structured information.
5. Information Extractor: Further refines the output from the OpenAI model, focusing on extracting specific data points relevant to real estate listings (e.g., price, address, number of bedrooms, etc.).
6. Basic LLM Chain: (Potentially used for additional processing or re-prompting the LLM) Applies a basic Langchain LLM chain to the extracted information.
7. Function: Executes custom JavaScript code, likely for data manipulation, transformation, or validation of the extracted real estate data.
8. Merge: Combines data from different branches or previous steps. This could be merging the original listing data with the newly extracted and enriched information.
9. HTTP Request: (Likely a placeholder or part of a larger external process) Makes an HTTP request. In the context of "Bright Data," this could be for triggering a scrape job, fetching results, or interacting with another API.
10. Aggregate: Collects and combines items into a single item or a structured list, preparing the data for final storage.
11. Google Sheets: Appends the processed and enriched real estate listing data as new rows to a specified Google Sheet.
12. Sticky Note: Provides a comment or note within the workflow for documentation purposes.

Prerequisites/Requirements

• n8n Instance: A running n8n instance (cloud or self-hosted).
• OpenAI API Key: An API key for accessing the OpenAI API, configured as an n8n credential.
• Google Account: A Google account with access to Google Sheets, configured as an n8n credential.
• Bright Data Account: (Implied by directory name, but not explicitly in JSON) If using Bright Data for web scraping, an account and associated API keys/credentials would be required.

Setup/Usage

1. Import the Workflow: Download the provided JSON and import it into your n8n instance.
2. Configure Credentials:
   • Set up your OpenAI API Key credential.
   • Set up your Google Sheets credential, granting it access to the target spreadsheet.
   • (If applicable) Configure any Bright Data credentials if you integrate a Bright Data node.
3. Customize Nodes:
   • Read/Write Files from Disk: Adjust the file path if you're loading initial data from disk.
   • Edit Fields (Set): Review and adjust the fields being set to match your input data structure.
   • OpenAI Chat Model: Select the desired OpenAI model and review the prompt for optimal information extraction.
   • Information Extractor: Define the schema or instructions for the specific real estate data points you want to extract.
   • Function: Modify the JavaScript code if custom data transformations are needed.
   • Google Sheets: Specify the Spreadsheet ID and Sheet Name where the data should be appended.
4. Activate the Workflow: Once configured, activate the workflow.
5. Execute: Manually trigger the workflow using the "When clicking ‘Execute workflow’" node to start processing.