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requirements.txt

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+langchain
+ctransformers
+sentence-transformers
+faiss-cpu
+streamlit== 1.22.0

train.py

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+
+from langchain.document_loaders.csv_loader import CSVLoader
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain.embeddings import HuggingFaceEmbeddings
+from langchain.vectorstores import FAISS
+from langchain.llms import CTransformers
+from langchain.chains import ConversationalRetrievalChain
+import streamlit as st
+import tempfile
+
+def main():
+    st.set_page_config(page_title="👨‍💻 Talk with your CSV")
+    st.title("👨‍💻 Talk with your CSV")
+    st.write("Please insert your link.")
+    uploaded_file = st.sidebar.file_uploader("Upload your Data", type="csv")
+
+    query = st.text_input("Send a Message")
+    if st.button("Submit Query", type="primary"):
+        DB_FAISS_PATH = "vectorstore/db_faiss"
+
+        if uploaded_file :
+            with tempfile.NamedTemporaryFile(delete=False) as tmp_file:
+                tmp_file.write(uploaded_file.getvalue())
+                tmp_file_path = tmp_file.name
+
+            loader = CSVLoader(file_path=tmp_file_path, encoding="utf-8", csv_args={
+                        'delimiter': ','})
+            data = loader.load()
+            st.write(data)
+            text_splitter = RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=20)
+            text_chunks = text_splitter.split_documents(data)
+
+            embeddings = HuggingFaceEmbeddings(model_name = 'sentence-transformers/all-MiniLM-L6-v2')
+
+            docsearch = FAISS.from_documents(text_chunks, embeddings)
+
+            docsearch.save_local(DB_FAISS_PATH)
+
+            llm = CTransformers(model="models/llama-2-7b-chat.ggmlv3.q4_0.bin",
+                                model_type="llama",
+                                max_new_tokens=512,
+                                temperature=0.1)
+
+            qa = ConversationalRetrievalChain.from_llm(llm, retriever=docsearch.as_retriever())
+
+            result = qa(query)
+            st.write(result)
+
+if __name__ == '__main__':
+    main()
+