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app.py

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+import streamlit as st
+import os
+from langchain.embeddings import HuggingFaceEmbeddings
+from langchain_community.vectorstores import FAISS
+from dotenv import load_dotenv
+load_dotenv()
+
+st.set_page_config(page_title="Educate Kids", page_icon=":robot:")
+st.header("Hey, Ask me something & I will give out similar things")
+
+
+embeddings=HuggingFaceEmbeddings()
+
+from langchain.document_loaders.csv_loader import CSVLoader
+loader = CSVLoader(file_path='mydata.csv', csv_args={
+    'delimiter': ',',
+    'quotechar': '"',
+    'fieldnames': ['Words']
+})
+
+data = loader.load()
+
+print(data)
+
+db = FAISS.from_documents(data, embeddings)
+
+
+def get_text():
+    input_text = st.text_input("You: ", key= input)
+    return input_text
+
+
+user_input=get_text()
+submit = st.button('Find similar Things')  
+
+if submit:
+    
+    docs = db.similarity_search(user_input)
+    st.subheader("Top Matches:")
+    if docs:
+        for item in docs[1:]:
+            st.write(item.page_content)
+    else:
+        st.write("No similar things found")
+
+

mydata.csv

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+words
+lion
+elephant
+dog
+cricket
+football
+tennis
+basketball
+apple
+orange
+banana
+cat
+tiger