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Signed-off-by: Jael Gu <mengjia.gu@zilliz.com>

README.md

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-# Dolly
+# OpenAI Chat Completion
+
+*author: Jael*
+
+<br />
+
+## Description
+
+A LLM operator generates answer given prompt in messages using a large language model or service.
+This operator uses a pretrained [Dolly](https://github.com/databrickslabs/dolly) to generate response.
+It will download model from [HuggingFace Models](https://huggingface.co/models).
+
+<br />
+
+## Code Example
+
+Use the default model to continue the conversation from given messages.
+
+*Write a pipeline with explicit inputs/outputs name specifications:*
+
+```python
+from towhee import pipe, ops
+
+p = (
+    pipe.input('messages')
+        .map('messages', 'answer', ops.LLM.Dolly())
+        .output('messages', 'answer')
+)
+
+messages=[
+        {'question': 'Who won the world series in 2020?', 'answer': 'The Los Angeles Dodgers won the World Series in 2020.'},
+        {'question': 'Where was it played?'}
+    ]
+answer = p(messages)
+```
+
+<br />
+
+## Factory Constructor
+
+Create the operator via the following factory method:
+
+***LLM.Dolly(model_name: str)***
+
+**Parameters:**
+
+***model_name***: *str*
+
+The model name in string, defaults to 'databricks/dolly-v2-12b'. Supported model names:
+- databricks/dolly-v2-12b
+- databricks/dolly-v2-7b
+- databricks/dolly-v2-3b
+- databricks/dolly-v1-6b
+
+***\*\*kwargs***
+
+Other Dolly model parameters such as device_map.
+
+<br />
+
+## Interface
+
+The operator takes a piece of text in string as input.
+It returns answer in json.
+
+***\_\_call\_\_(txt)***
+
+**Parameters:**
+
+***messages***: *list*
+
+​	A list of messages to set up chat.
+Must be a list of dictionaries with key value from "system", "question", "answer". For example, [{"question": "a past question?", "answer": "a past answer."}, {"question": "current question?"}]
+
+**Returns**:
+
+*answer: str*
+
+​	The answer generated.
+
+<br />
+
 

__init__.py

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+from .hf_dolly import HuggingfaceDolly
+
+
+def Dolly(*args, **kwargs):
+    return HuggingfaceDolly(*args, **kwargs)

hf_dolly.py

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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
+        
+    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():
+                line = k + ': ' + v + '\n'
+                history += line
+        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
+

requirements.txt

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+transformers[torch]>=4.28.1,<5
+torch>=1.13.1,<2