- At least 8GB of RAM
- At least 12.3GB of free storage (just for the models)
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Install Python 3.12.0 (https://www.python.org/downloads/)
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Install ollama (https://ollama.com/download)
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Clone this repository
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Cd into the StudyCopilot directory
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(optional) Get an ngrok account and set up ngrok (https://dashboard.ngrok.com/get-started/setup/)
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(optional) Get a free static domain
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Install required Python libraries and backages
pip install -r requirements.txt- (optional) Enter your ngrok auth token using this command (replace
[AUTH TOKEN]with your actual auth token)
ngrok config add-authtoken [AUTH TOKEN]- Pull the mistral, phi3, llava and nomic-embed-text models
ollama pull mistral
ollama pull phi3
ollama pull llava-llama3
ollama pull nomic-embed-text-
Create a Hugging Face account (https://huggingface.co/)
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Get gated model access for Mistral (model: mistralai/Mistral-7B-Instruct-v0.2)
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Get a Hugging Face User Access Token (https://huggingface.co/settings/tokens)
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Get a Google API key and a and a Programmable Search Engine ID (https://developers.google.com/custom-search/v1/overview)
- Configure StudyCopilot if you have not already done so
python3 edit_config.py- (optional) Start a tunnel
ngrok http 11434 --host-header="localhost:11434" --domain=xxxxxxxx.ngrok-free.app- Wait for the client to show something like
HTTP tunnel: https://xxxxxxxx.ngrok-free.app- Open another terminal, then run the client
python3 client/client.py- Wait for the client to show something like
Running on local URL: http://127.0.0.1:7860
To create a public link, set `share=True` in `launch()`.- Open the local URL on your browser
- Flashcard Generator
- Study Chatbot
- You can only make 20000 HTTP/S requests per month and transfer 1 GB out of the server per month with a free account
- However, unless you are a heavy user of Study Copilot (in that case I applaud you), you are very unlikely to exhaust your free consumption limits
- Please double-check everything generated by AI; it may generate inaccurate information or information not found in the original input data!
- https://mattmazur.com/2023/12/14/running-mistral-7b-instruct-on-a-macbook/ for the suggestion of using Ollama
- https://www.reddit.com/r/Anki/comments/11cgw1j/casting_a_spell_on_chatgpt_let_it_write_anki/ for system prompt of flashcards_helper
- https://youtu.be/jENqvjpkwmw?si=n_nOXS_CLallmsfb and https://mer.vin/2024/02/ollama-embedding/ for the UI library suggestion and RAG idea
- https://www.youtube.com/watch?v=N8p6u1OtARs and https://github.com/daveshap/latent_space_activation for the LSA prompting system
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