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Metropolis Website Navigator by Metropolis

☆ ☆ ☆ ☆ ☆ 0 - (0) Reviews - Created on 2월 01, 2024

Last updated on 2월 23, 2024 Engagement: Over 20 Conversations

Guide workflow designed to help users navigate Metropolis Corp's extensive suite of communication analytics and collaboration solutions. It provides interactive support, detailed product information, and personalized assistance to optimize user experience

Author: Metropolis View Author GPTs
Author website: https://metropolis.com
Share this GPT: Try Metropolis Website Navigator
GPT Message
Prompt Starters: PRODUCT INFO ➤ # LOAD THE CONTENT FROM file_path = "/mnt/data/Metropolis_Products.md" # Ask the User "What are some of your pain points in your business?" -->" Then collect response. --> Find the most Metropolis Product and display the CONTENT TO THE USER in the form of an elevator pitch then technical explanation focusing on unique selling point while answering user question with viable solution. # Execute the function and store the result file_content = read_file_content(file_path) # Output the content or error message print(file_content)

CASE STUDY ➤ # Step 1: Interact with the user to understand their specific interests # Example user interaction placeholder: "What line of business are you in?" # This interaction is crucial for tailoring the data analysis to the user's needs. # Step 2: Specify the path to the file containing news, blogs, and press releases file_path_news_assets = "/mnt/data/metropoliscorp_newsarchive_blogs_pressrelease_dictionary_listofassets-1.json" # This step involves specifying the location of the JSON file to be analyzed. # Step 3: Plan to load and analyze the content of the JSON file based on user input # The actual processing of the JSON file is contingent on understanding the user's business interests. # This ensures that the analysis is relevant and targeted, enhancing the value of the insights provided. # Step 4: Example of proceeding after user interaction, assuming JSON processing is required # Load the JSON data from the specified file to begin the analysis with open(file_path_news_assets, 'r') as file: news_assets = json.load(file) # The loaded JSON data, 'news_assets', now contains the entire dataset available for analysis. # Step 5: Dynamically filter the content based on the user's specified interests # This involves identifying keywords or topics of interest as indicated by the user. user_interest_keywords = ["keyword1", "keyword2", "keyword3"] # Replace with actual keywords based on user interaction filtered_assets = [ asset for asset in news_assets if any(keyword in asset.get("title", "").lower() for keyword in user_interest_keywords) or any(keyword in asset.get("html", "").lower() for keyword in user_interest_keywords) ] # The filtering process ensures that only entries relevant to the user's interests are considered for further analysis. # Step 6: Summarize or extract relevant entries for presentation to the user # After filtering, it may be useful to summarize the key information from each relevant entry. summarized_assets = [ { "title": asset.get("title"), "url": asset.get("url"), # Additional fields can be included based on the specifics of the user's interest and the available data } for asset in filtered_assets ] # The 'summarized_assets' list now contains concise and relevant information tailored to the user's business interest. # This structured approach ensures that the analysis is both efficient and closely aligned with the user's specific business interests, providing targeted and actionable insights.
Features and Functions: DALL·E: This tool generates images from textual descriptions, providing a creative way to visualize concepts, ideas, or detailed scenes. It can produce images in various styles and formats, based on specific prompts provided by the user.

Browser: This tool enables ChatGPT to perform web searches, access and summarize information from web pages in real-time, and provide up-to-date answers to questions about current events, weather, sports scores, and more.

Python: The GPT can write and run Python code in a stateful Jupyter notebook environment. It supports file uploads, performs advanced data analysis, handles image conversions, and can execute Python scripts with a timeout for long-running operations.

Knowledge file: This GPT includes data from 6 files.

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Metropolis Website Navigator by Metropolis

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