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RAG_streamlit_app.py

@@ -3,6 +3,7 @@ from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM, AutoMod
 from sentence_transformers import SentenceTransformer
 import faiss, pickle
 from PIL import Image
+import os
 
 tokenizer = AutoTokenizer.from_pretrained("sentiment_model")
 model = AutoModelForSequenceClassification.from_pretrained("sentiment_model")
@@ -36,7 +37,7 @@ def explain_sentiment(text, predicted_label, k=3):
     return {"retrieved": retrieved, "explanation": explanation}
 
 st.title("Sentiment Analyzer")
-image = Image.open(r"Social-Sentiment-Tracking.png")
+image = Image.open("Social-Sentiment-Tracking.png")
 st.image(image, width='stretch')
 text = st.text_area("Enter text to analyze:")
 if st.button("Predict"):

requirements.txt

@@ -3,4 +3,5 @@ transformers
 sentence-transformers
 faiss-cpu
 torch
-pillow
+pillow
+os