text stringlengths 1 93.6k |
|---|
# try:
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# # create a new md5 hash
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# m = md5.new( open( "xvbmc-addons.xml" ).read() ).hexdigest()
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# # save file
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# self._save_file( m, file="xvbmc-addons.xml.md5" )
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# except Exception as e:
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# # oops
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# print("An error occurred creating addons.xml.md5 file!\n%s" % ( e, ))
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def _generate_md5_file(self):
|
try:
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####m = hashlib.md5( open(os.path.join('zips', 'addons.xml'), 'r', encoding='utf-8').read().encode('utf-8') ).hexdigest()
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m = hashlib.md5( open("xvbmc-addons.xml", 'r', encoding='utf-8').read().encode('utf-8') ).hexdigest()
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####self._save_file(m, file=os.path.join('zips', 'addons.xml.md5'))
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self._save_file(m, file="xvbmc-addons.xml.md5")
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except Exception as e:
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print("An error occurred creating addons.xml.md5 file!\n{0}".format(e))
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def _save_file(self, data, file, decode=False):
|
# try:
|
# # write data to the file
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# open( file, "w" ).write( data )
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# except Exception as e:
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# # oops
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# print("An error occurred saving %s file!\n%s" % ( file, e, ))
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try:
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if decode:
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open(file, 'w', encoding='utf-8').write(data.decode('utf-8'))
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else:
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open(file, 'w').write(data)
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except Exception as e:
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print("An error occurred saving {0} file!\n{1}".format(file, e))
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if ( __name__ == "__main__" ):
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# start
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Generator()
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# <FILESEP>
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import torch
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
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import colorful as cf
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cf.use_true_colors()
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cf.use_style('monokai')
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class ReBot:
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def __init__(self):
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print(cf.bold | cf.purple("Preparing for multi-session chat with ReBot..."))
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self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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self.tokenizer = AutoTokenizer.from_pretrained("jihyoung/rebot-generation")
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self.model = AutoModelForSeq2SeqLM.from_pretrained("jihyoung/rebot-generation").to(self.device)
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self.summarizer = pipeline("summarization",
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model=AutoModelForSeq2SeqLM.from_pretrained("jihyoung/rebot-summarization").to(
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self.device),
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tokenizer=AutoTokenizer.from_pretrained("jihyoung/rebot-summarization"), device=0)
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self.single_session = []
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self.sequence = ""
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self.speaker = []
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def observe(self, observation):
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self.single_session.append(observation)
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def set_input(self):
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input_text = " ".join(self.single_session)
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input_text = "{} [now] {}".format(self.sequence, input_text)
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return input_text
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def generate(self, user_response):
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self.observe(user_response)
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input_text = self.set_input()
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inputs = self.tokenizer([input_text], return_tensors="pt").to(self.device)
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outputs = self.model.generate(inputs["input_ids"], max_new_tokens=128, temperature=1.0, top_p=.95,
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do_sample=True)
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rebot_response = self.tokenizer.decode(outputs[0], skip_special_tokens=True, clean_up_tokenization_spaces=False)
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if rebot_response != "[END]":
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self.observe(rebot_response)
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return rebot_response
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def summary(self):
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sequence = " ".join(self.single_session)
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event = self.summarizer(sequence)[0]['summary_text']
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return event
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def reset_history(self):
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self.single_session = []
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def run(self):
|
def get_valid_input(prompt, default):
|
while True:
|
user_input = input(prompt)
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if user_input in ["Y", "N", "y", "n"]:
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return user_input
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if user_input == "":
|
return default
|
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