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| # eqa-search | # eqa-search | ||||
| 
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 | ||||
|  | # Enhanced QA Search | ||||
|  | 
 | ||||
|  | ## Description | ||||
|  | 
 | ||||
|  | **Enhanced question-answering** is the process of creating the knowledge base and generating answers with LLMs(large language model), thus preventing illusions. It involves inserting data as knowledge base and querying questions, and **eqa-search** is used to query questions from knowledge base. | ||||
|  | 
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|  | 
 | ||||
|  | <br /> | ||||
|  | 
 | ||||
|  | 
 | ||||
|  | ## Code Example | ||||
|  | 
 | ||||
|  | ### **Create pipeline and set the configuration** | ||||
|  | 
 | ||||
|  | > More parameters refer to the Configuration. | ||||
|  | 
 | ||||
|  | ```python | ||||
|  | from towhee import AutoPipes, AutoConfig | ||||
|  | 
 | ||||
|  | config = AutoConfig.load_config('eqa-search') | ||||
|  | config.collection_name = 'chatbot' | ||||
|  | 
 | ||||
|  | p = AutoPipes.pipeline('eqa-search', config=config) | ||||
|  | res = p('https://raw.githubusercontent.com/towhee-io/towhee/main/README.md') | ||||
|  | ``` | ||||
|  | 
 | ||||
|  | 
 | ||||
|  | <br /> | ||||
|  | 
 | ||||
|  | 
 | ||||
|  | 
 | ||||
|  | ## Enhanced QA Search Config | ||||
|  | 
 | ||||
|  | ### Configuration for Sentence Embedding | ||||
|  | 
 | ||||
|  | ***model (str):*** | ||||
|  | 
 | ||||
|  | The model name in the sentence embedding pipeline, defaults to `'all-MiniLM-L6-v2'`. | ||||
|  | You can refer to the above [Model(s) list ](https://towhee.io/tasks/detail/operator?field_name=Natural-Language-Processing&task_name=Sentence-Embedding)to set the model, some of these models are from [HuggingFace](https://huggingface.co/) (open source), and some are from [OpenAI](https://openai.com/) (not open, required API key). | ||||
|  | 
 | ||||
|  | ***openai_api_key (str):*** | ||||
|  | 
 | ||||
|  | The api key of openai, default to `None`.  | ||||
|  | This key is required if  the model is from OpenAI, you can check the model provider in the above [Model(s) list](https://towhee.io/sentence-embedding/openai). | ||||
|  | 
 | ||||
|  | ***embedding_device (int):*** | ||||
|  | 
 | ||||
|  | The number of devices, defaults to `-1`, which means using the CPU.  | ||||
|  | If the setting is not `-1`, the specified GPU device will be used. | ||||
|  | 
 | ||||
|  | ### Configuration for [Milvus](https://towhee.io/ann-search/milvus-client) | ||||
|  | 
 | ||||
|  | ***host (str):*** | ||||
|  | 
 | ||||
|  | Host of Milvus vector database, default is `'127.0.0.1'`. | ||||
|  | 
 | ||||
|  | ***port (str):*** | ||||
|  | 
 | ||||
|  | Port of Milvus vector database, default is `'19530'`.  | ||||
|  | 
 | ||||
|  | ***top_k (int):*** | ||||
|  | 
 | ||||
|  | The number of nearest search results, defaults to 5. | ||||
|  | 
 | ||||
|  | ***collection_name (str):*** | ||||
|  | 
 | ||||
|  | The collection name for Milvus vector database. | ||||
|  | 
 | ||||
|  | ***user (str):*** | ||||
|  | 
 | ||||
|  | The user name for [Cloud user](https://zilliz.com/cloud), defaults to `None`. | ||||
|  | 
 | ||||
|  | ***password (str):*** | ||||
|  | 
 | ||||
|  | The user password for [Cloud user](https://zilliz.com/cloud), defaults to `None`. | ||||
|  | 
 | ||||
|  | <br /> | ||||
|  | 
 | ||||
|  | 
 | ||||
|  | ## Interface | ||||
|  | 
 | ||||
|  | Query a question from Milvus knowledge base. | ||||
|  | 
 | ||||
|  | **Parameters:** | ||||
|  | 
 | ||||
|  | - ***question (str):*** The question to query. | ||||
|  | 
 | ||||
|  | - ***history (List[str]):*** The chat history to provide background information. | ||||
|  | 
 | ||||
|  | **Returns:** | ||||
|  | 
 | ||||
|  | - ***Answer (str):*** The answer to the question. | ||||
|  | |||||
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