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A newer version of the Gradio SDK is available: 5.6.0

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metadata
title: SenseMakingTool
emoji: 📊
colorFrom: pink
colorTo: gray
sdk: gradio
sdk_version: 5.4.0
app_file: app.py
pinned: false
short_description: Enter a user story to extract the unarticulated needs
author: victor daniel

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

Unarticulated Needs & Wants Extractor

This project is a Q&A chatbot built using Google Gemini API and Gradio, hosted on Hugging Face Spaces. It extracts unarticulated needs and wants from a user-provided story, based on natural language understanding.

How It Works

The application leverages Google Gemini API to process the user story and identify the unspoken needs or desires (needs) and wishes (wants) that are not explicitly mentioned by the user.

  • Input: A user story describing a person's situation, actions, or decisions.
  • Output: Extracted unarticulated needs and wants based on the story.

Features

  • Easy-to-use interface: Enter a user story in plain text, and the model will automatically extract and display the hidden needs and wants.
  • Example usage: Examples are provided to guide the user in submitting relevant stories.
  • Powered by Google Gemini: The application uses Google's powerful language model to generate insightful results.

Usage

  1. Enter a user story in the input text box.
  2. Click on the Submit button.
  3. The app will process the input and return a list of unarticulated needs and wants.

Example Input:

The user often speaks about wanting to improve their health but is hesitant to join a gym.

Example Output:

Needs: The user needs encouragement and a plan to overcome their fear of commitment. Wants: The user wants to get healthier without feeling pressure to join a gym.

How to Access

You can try out the live demo of this application by visiting the following link:

Live Demo on Hugging Face Spaces

Requirements

To replicate this project, you will need the following:

  • Gradio: For building the interactive web interface.
  • Google Gemini API: For generating responses.
  • Python-dotenv: For handling environment variables.

Install the dependencies using the following command:

pip install -r requirements.txt

Running Locally

To run the app locally, follow these steps:

1. Clone this repository.


2. Set up your environment variables with the Google Gemini API key (GOOGLE_API_KEY).


3. Install the required dependencies:

pip install -r requirements.txt


4. Run the app:

python app.py


5. The app will be available at http://127.0.0.1:7860/ in your browser.



License

This project is licensed under the MIT License.