I'm going to give you a python file called app.py. I want you to generate a requirements.txt file for the libraries used in the file. 

from flask import Flask, render\_template, request, jsonify
import random
import numpy as np
from sklearn.metrics.pairwise import cosine\_similarity
import os

app = Flask(\_\_name\_\_)

def load\_glove\_embeddings(file\_path):
 embeddings = {}
 with open(file\_path, 'r', encoding='utf-8') as f:
 for line in f:
 values = line.strip().split()
 word = values[0]
 vector = np.array(values[1:], dtype='float32')
 embeddings[word] = vector
 return embeddings

def load\_common\_nouns(file\_path):
 with open(file\_path, 'r', encoding='utf-8') as f:
 nouns = [line.strip() for line in f]
 return nouns

glove\_embeddings\_path = 'glove.6B.50d.txt' # Update this path to match the location of the downloaded file
glove\_model = load\_glove\_embeddings(glove\_embeddings\_path)
common\_nouns\_path = 'common\_nouns.txt' # Update this path to match the location of the common\_nouns.txt file
common\_nouns = load\_common\_nouns(common\_nouns\_path)

@app.route("/")
def index():
 return render\_template("index.html")

@app.route("/generate\_puzzle")
def generate\_puzzle():
 words = random.sample([word for word in common\_nouns if word in glove\_model], 2)
 operator = random.choice(["+", "-"])

 if operator == "+":
 result\_embedding = glove\_model[words[0]] + glove\_model[words[1]]
 else:
 result\_embedding = glove\_model[words[0]] - glove\_model[words[1]]

 return jsonify({"puzzle": f"{words[0]} {operator} {words[1]}", "result\_embedding": result\_embedding.tolist()})

@app.route("/calculate\_similarity", methods=["POST"])
def calculate\_similarity():
 user\_word = request.form["user\_word"]
 result\_embedding = np.array(request.form.getlist("result\_embedding[]"), dtype=np.float32)

 if user\_word in glove\_model:
 user\_embedding = glove\_model[user\_word]
 similarity = cosine\_similarity([user\_embedding], [result\_embedding])[0][0]
 similarity = float(np.round(similarity, 2))
 return jsonify({"similarity": round(similarity, 2)})
 else:
 return jsonify({"error": "Invalid input. Please enter a word from the vocabulary."})

if \_\_name\_\_ == "\_\_main\_\_":
 app.run(debug=True)
user
based on the provided app.py file, here's the requirements.txt file:

```
flask==2.0.1
numpy==1.21.0
scikit-learn==0.24.2
```

these are the libraries being imported and used in the file. make sure to use compatible versions if your environment requires it.
assistant
Based on the provided app.py file, here's the requirements.txt file:

```
Flask==2.0.1
numpy==1.21.0
scikit-learn==0.24.2
```

These are the libraries being imported and used in the file. Make sure to use compatible versions if your environment requires it.
assistant