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from typing import List |
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from queue import Queue |
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def build_chat_input(tokenizer, messages: List[dict]): |
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prompt = "<s>" |
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for msg in messages: |
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role = msg["role"] |
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message = msg["content"] |
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if message is None : |
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continue |
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if role == "user": |
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prompt += "Human: " + message + "\n\nAssistant: </s>" |
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if role == "assistant": |
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prompt += message + "</s>" |
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input_tokens = tokenizer.encode(prompt) |
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return input_tokens |
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class TextIterStreamer: |
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def __init__(self, tokenizer, skip_prompt=False, skip_special_tokens=False): |
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self.tokenizer = tokenizer |
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self.skip_prompt = skip_prompt |
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self.skip_special_tokens = skip_special_tokens |
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self.tokens = [] |
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self.text_queue = Queue() |
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self.next_tokens_are_prompt = True |
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def put(self, value): |
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if self.skip_prompt and self.next_tokens_are_prompt: |
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self.next_tokens_are_prompt = False |
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else: |
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if len(value.shape) > 1: |
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value = value[0] |
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self.tokens.extend(value.tolist()) |
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self.text_queue.put( |
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self.tokenizer.decode(self.tokens, skip_special_tokens=self.skip_special_tokens)) |
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def end(self): |
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self.text_queue.put(None) |
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def __iter__(self): |
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return self |
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def __next__(self): |
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value = self.text_queue.get() |
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if value is None: |
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raise StopIteration() |
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else: |
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return value |
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