Notes

You can find the cosine similarity between two text inputs in Python using the `sklearn` library, which provides a convenient function for this purpose. Here's a step-by-step guide on how to do it:

1. Install the necessary library if you haven't already. You can install it using pip:

```bash
pip install scikit-learn
```

2. Use the following Python code to calculate the cosine similarity between two text inputs:

```python
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.metrics.pairwise import cosine_similarity

# Define your two text inputs
text1 = "This is the first text input."
text2 = "This is the second text input."

# Create a CountVectorizer to convert the text into vectors
vectorizer = CountVectorizer().fit_transform([text1, text2])

# Calculate the cosine similarity
cosine_sim = cosine_similarity(vectorizer)

# The cosine similarity value is in cosine_sim[0][1] (or cosine_sim[1][0]) since there are two text inputs
similarity = cosine_sim[0][1]

# Print the cosine similarity
print("Cosine Similarity:", similarity)
```

In this code, `CountVectorizer` is used to convert the text inputs into vectors, and then `cosine_similarity` calculates the cosine similarity between these vectors. The result is a value between 0 and 1, where 1 indicates perfect similarity and 0 indicates no similarity.

You can replace `text1` and `text2` with your own text inputs to calculate the cosine similarity between them.