用flask框架基于sbert写一个问答系统，写一个基础的案例

好的，这是一个使用 Flask 框架基于 Sentence-BERT 的问答系统的基础案例。

首先，您需要安装 Flask 和 Sentence-BERT：

pip install flask
pip install sentence-transformers

然后，创建一个名为 `app.py` 的文件，并编写以下代码：

from flask import Flask, request
from sentence_transformers import SentenceTransformer

app = Flask(__name__)

# Load Sentence-BERT model
model = SentenceTransformer('bert-base-nli-mean-tokens')

# Define a question-answer pair
qa_pair = [("What is Sentence-BERT?", "Sentence-BERT is a variant of BERT that has been fine-tuned for the natural language inference task.")]

@app.route("/", methods=["GET", "POST"])
def index():
    if request.method == "POST":
        # Get the user's question
        question = request.form["question"]

        # Get the most similar question from the qa_pair based on Sentence-BERT's cosine similarity
        similarities = model.encode(question)
        most_similar_index = 0
        max_similarity = float('-inf')
        for index, similarity in enumerate(similarities):
            cos_sim = model.get_cosine_similarity(similarity, model.encode(qa_pair[index][0]))
            if cos_sim > max_similarity:
                most_similar_index = index
                max_similarity = cos_sim

        # Return the answer to the most similar question
        answer = qa_pair[most_similar_index][1]
        return answer
    return """
        <form action="/" method="post">
            <input type="text" name="question">
            <input type="submit" value="Submit">
        </form>
    """

if __name__ == "__main__":
    app.run(debug=True)

最后，运行这个程序：

python app.py

打开您的浏览器，访问 `http://localhost:5000/`，您就可以输入问题，并得到相应的回答了。

希望这个案例能帮助您入门 Flask 和 Sentence-BERT。