Update app.py

app.py

@@ -4,8 +4,8 @@ print(data)
 
 from langchain.docstore.document import Document as LangchainDocument
 from langchain.text_splitter import RecursiveCharacterTextSplitter
-splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=15,separators=["\n\n", "\n", " ", ""])
-docs = splitter.create_documents(str(dataset))
+#splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=15,separators=["\n\n", "\n", " ", ""])
+#docs = splitter.create_documents(str(dataset))
 
 from sentence_transformers import SentenceTransformer
 #from langchain_community.embeddings import HuggingFaceEmbeddings
@@ -16,17 +16,17 @@ data = data.add_faiss_index("embeddings") # column name that has the embeddings
 from langchain_community.vectorstores import Chroma
 persist_directory = 'docs/chroma/'
 
-vectordb = Chroma.from_documents(
-    documents=docs,
-    embedding=embedding_model,
-    persist_directory=persist_directory
-)
+#vectordb = Chroma.from_documents(
+ #   documents=docs,
+  #  embedding=embedding_model,
+   # persist_directory=persist_directory
+#)
 
 
 
-retriever = vectordb.as_retriever(
-    search_type="similarity", search_kwargs={"k": 2}
-)
+#retriever = vectordb.as_retriever(
+#    search_type="similarity", search_kwargs={"k": 2}
+#)
 
 
 from langchain.prompts import PromptTemplate