Answer to question 1: Some historical Bitcoin data can be downloaded from Kaggle, for example, https://www.kaggle.com/mczielinski/bitcoin-historical-data/data.
Once you've downloaded the dataset, try to extract the most important features and convert the dataset into a time series so that it can be fed into an LSTM model. Then the model can be trained with the time series for each time step.
Answer to question 2: Our sample project only calculates the stock price of those stocks whose actual stock price is given, and not the next day's stock price. It shows actual and predicted, but the next day's stock price should only contain predicted. This is what is happening if we take predicted values as input for the next prediction:
Predicted versus actual prices for ALL categories, where predicted values are input for the next prediction
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