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README.md
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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Oral Coach 🎤✨ powered by ZeroGPU ⚡ϞϞ(๑⚈ ․̫ ⚈๑)∩ ⚡ and Mixtral 🎭🎓
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The Oral Coach is an AI-powered conversational coach designed to guide students through their oral responses. It is built using Gradio, HuggingFace's InferenceClient, and edge_tts for text-to-speech conversion. The Oral Coach is participating in the Hugging Face ZeroGPU initiative.
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Project Objectives
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Enhance students' critical thinking when structuring their responses to oral prompts.
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Provide personalized feedback to students.
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Improve students' structured response techniques for oral communication.
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Features
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Student information input (class and index number)
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User acceptance policy checkbox
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Question selection
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Thinking frame selection
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Feedback level selection
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Audio recording and transcription
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AI-generated personalized feedback
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Text-to-speech feedback playback
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Teacher's dashboard (not shown in the provided code)
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Getting Started
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The Oral Coach app was piloted in 2024 by over 1000+ students in 5 S4 Cluster Schools. This repository contains the source code for the Oral Coach app. You can run the app locally or deploy it to Render.com.
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To get started with the Oral Coach, simply clone the Hugging Space repository as the app is hosted on Hugging Face:
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Copy codegit clone https://huggingface.co/spaces/your-username/oral-coach
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Usage
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Access the application through the provided URL.
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Enter the student information, agree to the user acceptance policy, and click "Submit Info".
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Choose a question, thinking frame, and feedback level.
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Record the oral response using the microphone.
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Click "Submit Oral Response" to generate personalized feedback.
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Review the feedback in the chatbot and listen to the audio playback.
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Code Structure
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app.py: The main application file containing the Gradio interface and prediction logic.
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thinkingframes.py: Contains the question prompts, thinking frames, and feedback generation prompts.
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styles.py: Defines the theme and styling for the Gradio interface.
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utils.py: Utility functions for displaying images and collecting student information.
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database_functions.py: Functions for interacting with the database (not shown in the provided code).
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tab_teachers_dashboard.py: Functions for creating the teacher's dashboard tab (not shown in the provided code).
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config.py: Configuration variables (not shown in the provided code).
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ZeroGPU Integration
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The Oral Coach leverages Hugging Face's ZeroGPU initiative to enable GPU acceleration for inference. The @spaces.GPU(duration=120) decorator is used to allocate GPU resources for the model function, which performs the inference using the "mistralai/Mixtral-8x7B-Instruct-v0.1" model.
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The Oral Coach utilizes the Mixtral model, a powerful language model specifically designed for educational applications. Mixtral provides the underlying intelligence for generating personalized feedback and guiding students through their oral responses.
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Contributing
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Contributions are welcome! If you find any issues or have suggestions for improvements, please create an issue or submit a pull request.
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License
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This project is licensed under the MIT License.
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Acknowledgements
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Hugging Face for providing the InferenceClient and ZeroGPU initiative.
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Gradio for the user interface library.
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edge_tts for text-to-speech conversion.
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Feel free to customize and expand upon this README template based on your specific Oral Coach application and requirements.
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