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title: OralCoachZeroGPU | |
emoji: ⚡ | |
colorFrom: red | |
colorTo: purple | |
sdk: gradio | |
sdk_version: 4.31.4 | |
app_file: app.py | |
pinned: false | |
license: mit | |
Oral Coach 🎤✨ powered by ZeroGPU ⚡ϞϞ(๑⚈ ․̫ ⚈๑)∩ ⚡ and Mixtral 🎭🎓 | |
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. | |
Project Objectives | |
Enhance students' critical thinking when structuring their responses to oral prompts. | |
Provide personalized feedback to students. | |
Improve students' structured response techniques for oral communication. | |
Features | |
Student information input (class and index number) | |
User acceptance policy checkbox | |
Question selection | |
Thinking frame selection | |
Feedback level selection | |
Audio recording and transcription | |
AI-generated personalized feedback | |
Text-to-speech feedback playback | |
Teacher's dashboard (not shown in the provided code) | |
Getting Started | |
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. | |
To get started with the Oral Coach, simply clone the Hugging Space repository as the app is hosted on Hugging Face: | |
Copy codegit clone https://huggingface.co/spaces/your-username/oral-coach | |
Usage | |
Access the application through the provided URL. | |
Enter the student information, agree to the user acceptance policy, and click "Submit Info". | |
Choose a question, thinking frame, and feedback level. | |
Record the oral response using the microphone. | |
Click "Submit Oral Response" to generate personalized feedback. | |
Review the feedback in the chatbot and listen to the audio playback. | |
Code Structure | |
app.py: The main application file containing the Gradio interface and prediction logic. | |
thinkingframes.py: Contains the question prompts, thinking frames, and feedback generation prompts. | |
styles.py: Defines the theme and styling for the Gradio interface. | |
utils.py: Utility functions for displaying images and collecting student information. | |
database_functions.py: Functions for interacting with the database (not shown in the provided code). | |
tab_teachers_dashboard.py: Functions for creating the teacher's dashboard tab (not shown in the provided code). | |
config.py: Configuration variables (not shown in the provided code). | |
ZeroGPU Integration | |
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. | |
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. | |
Contributing | |
Contributions are welcome! If you find any issues or have suggestions for improvements, please create an issue or submit a pull request. | |
License | |
This project is licensed under the MIT License. | |
Acknowledgements | |
Hugging Face for providing the InferenceClient and ZeroGPU initiative. | |
Gradio for the user interface library. | |
edge_tts for text-to-speech conversion. | |
Feel free to customize and expand upon this README template based on your specific Oral Coach application and requirements. | |