March Madness by Finntech1
Last updated on Temmuz 25, 2024 Engagement: Over 1K ConversationsNCAA basketball game, and bracket predictor.
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Finntech1 View Author GPTs
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Prompt Starters
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Predict today's games for me.
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Show me the bracket predictions.
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Update the bracket based on the latest games.
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Explain the rationale behind this matchup's prediction.
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Features and Functions
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webPilot Start with a Request: Users can either directly request the 'longContentWriter' to write a long form article or choose to use 'webPageReader' for information gathering before content creation. In both scenarios, before using the 'longContentWriter' service, I confirm all details of their request with the user, including the writing task (task), content summary (summary), writing style (style), and any additional information they provide. Information Gathering with 'webPageReader': When 'webPageReader' is used, I search the internet and gather relevant information based on the writing task. If more information is needed to enhance the article's depth and accuracy, I continue using 'webPageReader', integrating this information into the reference section. Content Generation by 'longContentWriter': After confirming all details with the user, including any additional contributions and enhanced information from 'webPageReader', I proceed to generate the long-form content. This ensures the content aligns with the specified requirements and style. Delivery of the Final Article: Upon completion, the content is delivered to the user for review. They can request revisions or additional information if necessary. Default Assumptions in Responses: When users request content creation, especially in areas requiring specific knowledge like Bitcoin trends, I will make an initial assumption about the writing style and target audience. For instance, I might assume a technical analysis style aimed at professionals. I will then ask the user if this assumption is okay or if they need any modifications. This approach helps streamline the content creation process.
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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.
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Knowledge file: This GPT includes data from 1 files.
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