mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-11-01 15:10:15 +01:00
103 lines
4.1 KiB
Python
103 lines
4.1 KiB
Python
import time
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import yaml
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import os
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from modules import shared
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from extensions.openai.defaults import get_default_req_params
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from extensions.openai.utils import debug_msg
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from extensions.openai.errors import *
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from modules.text_generation import encode, generate_reply
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def edits(instruction: str, input: str, temperature=1.0, top_p=1.0) -> dict:
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created_time = int(time.time() * 1000)
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# Request parameters
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req_params = get_default_req_params()
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stopping_strings = []
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# Alpaca is verbose so a good default prompt
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default_template = (
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"Below is an instruction that describes a task, paired with an input that provides further context. "
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"Write a response that appropriately completes the request.\n\n"
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"### Instruction:\n{instruction}\n\n### Input:\n{input}\n\n### Response:\n"
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)
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instruction_template = default_template
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# Use the special instruction/input/response template for anything trained like Alpaca
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if shared.settings['instruction_template']:
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if 'Alpaca' in shared.settings['instruction_template']:
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stopping_strings.extend(['\n###'])
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else:
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try:
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instruct = yaml.safe_load(open(f"instruction-templates/{shared.settings['instruction_template']}.yaml", 'r'))
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template = instruct['turn_template']
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template = template\
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.replace('<|user|>', instruct.get('user', ''))\
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.replace('<|bot|>', instruct.get('bot', ''))\
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.replace('<|user-message|>', '{instruction}\n{input}')
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instruction_template = instruct.get('context', '') + template[:template.find('<|bot-message|>')].rstrip(' ')
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if instruct['user']:
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stopping_strings.extend(['\n' + instruct['user'], instruct['user']])
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except Exception as e:
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instruction_template = default_template
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print(f"Exception: When loading instruction-templates/{shared.settings['instruction_template']}.yaml: {repr(e)}")
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print("Warning: Loaded default instruction-following template (Alpaca) for model.")
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else:
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stopping_strings.extend(['\n###'])
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print("Warning: Loaded default instruction-following template (Alpaca) for model.")
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edit_task = instruction_template.format(instruction=instruction, input=input)
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truncation_length = shared.settings['truncation_length']
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token_count = len(encode(edit_task)[0])
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max_tokens = truncation_length - token_count
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if max_tokens < 1:
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err_msg = f"This model maximum context length is {truncation_length} tokens. However, your messages resulted in over {truncation_length - max_tokens} tokens."
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raise InvalidRequestError(err_msg, param='input')
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req_params['max_new_tokens'] = max_tokens
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req_params['truncation_length'] = truncation_length
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req_params['temperature'] = temperature
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req_params['top_p'] = top_p
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req_params['seed'] = shared.settings.get('seed', req_params['seed'])
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req_params['add_bos_token'] = shared.settings.get('add_bos_token', req_params['add_bos_token'])
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req_params['custom_stopping_strings'] = shared.settings['custom_stopping_strings']
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debug_msg({'edit_template': edit_task, 'req_params': req_params, 'token_count': token_count})
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generator = generate_reply(edit_task, req_params, stopping_strings=stopping_strings, is_chat=False)
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longest_stop_len = max([len(x) for x in stopping_strings] + [0])
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answer = ''
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for a in generator:
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answer = a
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# some reply's have an extra leading space to fit the instruction template, just clip it off from the reply.
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if edit_task[-1] != '\n' and answer and answer[0] == ' ':
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answer = answer[1:]
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completion_token_count = len(encode(answer)[0])
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resp = {
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"object": "edit",
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"created": created_time,
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"choices": [{
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"text": answer,
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"index": 0,
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}],
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"usage": {
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"prompt_tokens": token_count,
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"completion_tokens": completion_token_count,
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"total_tokens": token_count + completion_token_count
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}
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}
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return resp
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