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app.py

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+
+import streamlit as st
+import pickle
+import string
+from nltk.corpus import stopwords
+from nltk.stem import WordNetLemmatizer
+from nltk.tokenize import word_tokenize
+import nltk
+
+# Download NLTK data
+nltk.download('punkt')
+nltk.download('stopwords')
+nltk.download('wordnet')
+
+# Load models and TF-IDF
+with open('rf_goboult_model.pkl', 'rb') as f:
+    goboult_model = pickle.load(f)
+with open('tfidf_goboult.pkl', 'rb') as f:
+    goboult_tfidf = pickle.load(f)
+
+with open('rf_flipflop_model.pkl', 'rb') as f:
+    flipflop_model = pickle.load(f)
+with open('tfidf_flipflop.pkl', 'rb') as f:
+    flipflop_tfidf = pickle.load(f)
+
+stop_words = set(stopwords.words('english'))
+lemmatizer = WordNetLemmatizer()
+
+def preprocess_text(text):
+    text = text.lower()
+    text = text.translate(str.maketrans('', '', string.punctuation))
+    tokens = word_tokenize(text)
+    tokens = [lemmatizer.lemmatize(word) for word in tokens if word not in stop_words]
+    return " ".join(tokens)
+
+# Streamlit UI
+st.title("Sentiment Analysis for Goboult & Flipflop")
+dataset = st.selectbox("Select Dataset", ["Goboult", "Flipflop"])
+review = st.text_area("Enter your review here:")
+
+if st.button("Predict Sentiment"):
+    if review.strip() == "":
+        st.warning("Please enter a review!")
+    else:
+        cleaned = preprocess_text(review)
+        if dataset.lower() == "goboult":
+            vectorized = goboult_tfidf.transform([cleaned])
+            pred = goboult_model.predict(vectorized)[0]
+        else:
+            vectorized = flipflop_tfidf.transform([cleaned])
+            pred = flipflop_model.predict(vectorized)[0]
+        st.success(f"Predicted Sentiment: {pred}")

requirements.txt

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+streamlit
+nltk
+scikit-learn
+pandas
+matplotlib
+seaborn
+wordcloud

rf_flipflop_model.pkl

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+oid sha256:f9d555d29a6320c18bb3847a8088e6d10b4dfe782cc82634cab9f9275842a431
+size 1412648

rf_goboult_model.pkl

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+oid sha256:203c87252888ff9f886557a0c290c2d1f20a79deb814c7eecbd5c28329379403
+size 2058929

tfidf_flipflop.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:57315661dda21c7b025b2d76c2ad8c24462657fdd0178f47e193aff842f4a917
+size 23913

tfidf_goboult.pkl

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+oid sha256:6939290d53f67d137083b776b07d458962a96acf938627ce5ae10feb3d32e758
+size 78455