Warning

We are in the process of a major cleanup. Feel free to test as it is but expect changes/ post cleanup! <:

Enabling teachers to experiment with LLM/ Generative AI

Key Features:

1 Text GenAI:

• a) Chat Assistant (Visibility into backend)
• b) Remarks Co-Pilot (Draft student remarks);
• c) Semantic search on uploaded documents via LanceDB

2 Voice GenAI:

• a) Oral coach (Personalized feedback based on audio input)
• b) Transcription (Speech-to-text)

3 [WIP] Image GenAI

• a) Create comic strips (Creating reasonably consistent images across panels for composition writing)
• b) Historic stylistic art reimagination (Superimposing art styles/ palettes over uploaded images)

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You can fork it at streamlit community cloud for immediate use. Please configure the env variables accordingly:

Important

The following env variables are required for setup. You can add this to the secrets.toml file in your streamlit deployment

openai_key = "YOUR_OPEN_API_KEY"
default_db = "chergpt.db"
default_temp = 0.0
default_frequency_penalty = 0.0
default_presence_penalty = 0.0
default_k_memory = 4
default_model = "gpt-4-1106-preview"
default_password = "default_password"
student_password = "studentp@sswrd"
teacher_password = "teacherp@sswrd"
super_admin_password = "pass1234"
super_admin = "super_admin"
default_title = "GenAI Workshop Framework V2"
sql_ext_path = "None"

*Note, While GPT-4 is the default model, you can also change models by modifying this setting:
default_model = gpt-3.5-turbo

Setting up local dev env

To run this locally, follow the steps below.

1. Clone it to your local computer via Git. See here for a crash course to git.
2. Create a virtual environment while in the project root directory. See here for how to create one.
3. Prior to running locally, you will need to install required dependencies via this command pip install -r requirements.txt
   • If you encounter errors while installing the dependencies that is not related to 'conflicting dependencies', try pip install -r requirements.txt --default-timeout=100
   • Alternatively try again after some time.
4. To run this locally, run streamlit run main.py
   
   

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