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# Copyright 2021 Zilliz. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import List
import torch
from transformers import pipeline
from towhee.operator.base import PyOperator
class HuggingfaceDolly(PyOperator):
'''Wrapper of OpenAI Chat API'''
def __init__(self,
model_name: str = 'databricks/dolly-v2-12b',
**kwargs
):
torch_dtype = kwargs.get('torch_dtype', torch.bfloat16)
trust_remote_code = kwargs.get('trust_remote_code', True)
device_map = kwargs.get('device_map', 'auto')
self.pipeline = pipeline(model=model_name, torch_dtype=torch_dtype, trust_remote_code=trust_remote_code, device_map=device_map)
def __call__(self, messages: List[dict]):
prompt = self.parse_inputs(messages)
ans = self.pipeline(prompt)
return ans[0]['generated_text']
def parse_inputs(self, messages: List[dict]):
assert isinstance(messages, list), \
'Inputs must be a list of dictionaries with keys from ["system", "question", "answer"].'
prompt = messages[-1]['question']
history = ''
for m in messages[:-1]:
for k, v in m.items():
if k == 'answer':
history += v + '\n'
return prompt + '\n' + history
@staticmethod
def supported_model_names():
model_list = [
'databricks/dolly-v2-12b',
'databricks/dolly-v2-7b',
'databricks/dolly-v2-3b',
'databricks/dolly-v1-6b'
]
model_list.sort()
return model_list