import gradio as gr

from sklearn.metrics.pairwise import cosine_similarity
#from sklearn.metrics.pairwise import euclidean_distances

def greet(array_of_vectors):
    # [[0 1],[0 5]]
    array_of_vectors = array_of_vectors.replace("[[", "")
    array_of_vectors = array_of_vectors.replace("]]", "")
    array_of_vectors = array_of_vectors.replace("[", "")
    array_of_vectors = array_of_vectors.replace("]", "")
    
    cleaned = []
    vecs = array_of_vectors.split(",")
    for vec in vecs:
        arr = vec.split(" ")
        int_arr = []
        for a in arr:
            int_arr.append(int(a))
        cleaned.append(int_arr)
    
    similarity_matrix2 = cosine_similarity([[0,4]], [[0,0], [0,4], [0,19]])

    similarity_matrix = cosine_similarity([[0,4]], cleaned)
#    similarity_matrix = euclidean_distances(cleaned, cleaned)
    results = ''
    for matrix in similarity_matrix:
        results = results + str(matrix) + "\n"
    
    results = results + "cleaned:" + str(cleaned) + "\n"
    results = results + "sim:" + str(similarity_matrix) + "\n"
    results = results + "sim2:" + str(similarity_matrix2) + "\n"
    return results

iface = gr.Interface(fn=greet, inputs="text", outputs="text")
iface.launch()