import gradio as gr

import difflib
from io import BytesIO



import matplotlib.pyplot as plt
import numpy as np
import gradio as gr
import difflib

 
def word_lcs(text1, text2):
    words1 = text1.split()
    words2 = text2.split()

    m, n = len(words1), len(words2)

    # Initialize a 2D array to store the length of word-level LCS
    dp = [[0] * (n + 1) for _ in range(m + 1)]

    # Fill the dp array using bottom-up dynamic programming
    for i in range(1, m + 1):
        for j in range(1, n + 1):
            if words1[i - 1] == words2[j - 1]:
                dp[i][j] = dp[i - 1][j - 1] + 1
            else:
                dp[i][j] = max(dp[i - 1][j], dp[i][j - 1])

    # Reconstruct the word-level LCS from the dp array
    i, j = m, n
    word_lcs = []
    while i > 0 and j > 0:
        if words1[i - 1] == words2[j - 1]:
            word_lcs.append(words1[i - 1])
            i -= 1
            j -= 1
        elif dp[i - 1][j] > dp[i][j - 1]:
            i -= 1
        else:
            j -= 1

    # Reverse the word-level LCS to get the correct order
    word_lcs = word_lcs[::-1]
    result=[]
    for word in text2.split():
        if word in word_lcs:
            result.append((word+" ","-"))
            word_lcs.remove(word)
        else:
            result.append((word,"+"))
        
    #result=[(word+" ",None) for word in word_lcs]
    
    return result
#定义处理函数

# 定义处理函数 f
def process(text1, text2,function):
    # 这里替换成你的处理逻辑，生成图片的代码
    # 示例：使用Matplotlib生成一个简单的图像
   if function=="naive":
        d = difflib.Differ()
        return [
            (token[2:], token[0] if token[0] != " " else None)
            for token in d.compare(text1, text2)
        ]
   else:
       return(word_lcs(text1,text2))
   
      

# 创建 Gradio 界面
iface = gr.Interface(
    fn=process,  # 此处的 fn 将在运行时动态设置
    inputs=[
        gr.Textbox(label="Origin Text",value="The quick brown fox jumped over the lazy dogs.",lines=3),
        gr.Textbox(label="Edited Text",value="The fast brown fox jumps over lazy dogs.",lines=3),
        gr.Radio(["naive", "Largest Common Subsequence"], label="Select Function")
    ],
    outputs=gr.HighlightedText(
        label="Diff",
        combine_adjacent=True,
        show_legend=True,
        color_map={"+": "red", "-": "green"}),
    theme=gr.themes.Base()
    
)

# 设置动态函数选择

# 启动 Gradio 应用
iface.launch(share=True)