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app.py

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+import streamlit as st
+import pandas as pd
+import numpy as np
+import re
+import pickle
+from tensorflow.keras.preprocessing.sequence import pad_sequences
+from tensorflow.keras.models import load_model
+
+# Modeli yükle
+model = load_model('sherlock_model.h5')
+
+tokenizer = pickle.load(open( "tokenizer.pkl", "rb"))
+word_index_df = pd.read_csv("word_index.csv", header=None, index_col=0)
+word_index = {}
+for word, index in word_index_df.to_dict()[1].items():
+    word_index[word] = int(index)
+tokenizer.word_index = word_index
+
+st.title('Next Word Generator :writing_hand:')
+st.write("This app predicts the next word using a model trained on words from the book 'THE ADVENTURES OF SHERLOCK HOLMES'.") 
+st.write("Write a few words and indicate how many words you want them to guess.")
+
+def next_words(seed_text, n):
+    for _ in range(n):
+        token_list = tokenizer.texts_to_sequences([seed_text])[0]
+        token_list = pad_sequences([token_list], maxlen=17, padding='pre')
+        predicted = np.argmax(model.predict(token_list), axis=-1)
+        output_word = ""
+        for word, index in tokenizer.word_index.items():
+            if index == predicted:
+                output_word = word
+                break
+        seed_text += " " + output_word
+    return seed_text
+
+# Giriş metnini al
+text = st.text_area("Enter text", height=80)
+n=st.number_input("Word number", 1,100)
+
+if st.button("Predict"):
+    sonuc=next_words(text, n)
+    st.info(f'Prediction : {sonuc}')

requirements.txt

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+streamlit

sherlock_model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:db7fbd6be47b84e0b0abab9042ca002581461f9b96786f9cda32aac2c0fce40e
+size 26528400

tokenizer.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:805a9e499dbc4a3997080ac38b0c57036ce65192089cdce5190009be316a8f85
+size 324679