Ernie/README.md

# Ernie Bot 文心一言

*author: Jael*

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## Description 描述

A LLM operator generates answer given prompt in messages using a large language model or service.
This operator is implemented with [Ernie Bot SDK from Baidu](https://github.com/PaddlePaddle/ERNIE-Bot-SDK).
Please note you will need [EB_API_TYPE & EB_ACCESS_TOKEN](https://github.com/PaddlePaddle/ERNIE-Bot-SDK/blob/develop/docs/authentication.md) to access the service.

LLM 算子使用大语言模型或服务，为输入的问题或提示生成答案。LLM/Ernie 利用了来自百度的[Ernie Bot SDK](https://github.com/PaddlePaddle/ERNIE-Bot-SDK) 。请注意，您需要文心一言服务的 [EB_API_TYPE & EB_ACCESS_TOKEN](https://github.com/PaddlePaddle/ERNIE-Bot-SDK/blob/develop/docs/authentication.md) 才能访问该服务。

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## Code Example 代码示例

*Write a pipeline with explicit inputs/outputs name specifications:*

```python
from towhee import pipe, ops

p = (
    pipe.input('messages')
        .map('messages', 'answer', ops.LLM.Ernie(eb_api_type=EB_API_TYPE, eb_access_token=EB_ACCESS_TOKEN))
        .output('answer')
)

messages=[
        {'question': 'Zilliz Cloud 是什么？', 'answer': 'Zilliz Cloud 是一种全托管的向量检索服务。'},
        {'question': '它和 Milvus 的关系是什么？'}
    ]
answer = p(messages).get()[0]
```

*Write a [retrieval-augmented generation pipeline](https://towhee.io/tasks/detail/pipeline/retrieval-augmented-generation) with explicit inputs/outputs name specifications:*

```python
from towhee import pipe, ops


temp = '''根据以下材料回答最末尾的问题：

{context}

问题：{question}
'''


docs = ['你可以通过`pip install towhee` 安装 Towhee。']
history = [
    ('什么是 Towhee？', 'Towhee 是一个开源项目，可以将非结构化数据转换为向量。')
]
question = '怎么安装它？'

p = (
    pipe.input('question', 'docs', 'history')
        .map(('question', 'docs', 'history'), 'prompt', ops.prompt.template(temp, ['question', 'context']))
        .map('prompt', 'answer',
             ops.LLM.Ernie(eb_api_type=EB_API_TYPE, eb_access_token=EB_ACCESS_TOKEN)
             )
        .output('answer')
)

answer = p(question, docs, history).get()[0]
```

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## Factory Constructor 接口说明

Create the operator via the following factory method:

***LLM.Ernie(eb_api_type: str, eb_access_token: str)***

**Parameters:**


***eb_api_type***: *str=None*

The API type in string, defaults to None. If None, it will use the environment variable `EB_API_TYPE`. Refer to [authentication](https://github.com/PaddlePaddle/ERNIE-Bot-SDK/blob/develop/docs/authentication.md) for more details.

***eb_access_token***: *str=None*

The access token in string, defaults to None. If None, it will use the environment variable `EB_ACCESS_TOKEN`. Refer to [authentication](https://github.com/PaddlePaddle/ERNIE-Bot-SDK/blob/develop/docs/authentication.md) for more details.

***\*\*kwargs***

Other Ernie parameters such as temperature, etc.

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## Interface 使用说明

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 "question", "answer". For example, [{"question": "a past question?", "answer": "a past answer."}, {"question": "current question?"}].
It also accepts the orignal Ernie message format like [{"role": "user", "content": "a question?"}, {"role": "assistant", "content": "an answer."}]

**Returns**:

*answer: str*

​	The next answer generated by role "assistant".

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