add files

app.py

@@ -1,4 +1,3 @@
-from langchain import HuggingFacePipeline
 from langchain.chains import RetrievalQA
 from langchain.embeddings import HuggingFaceEmbeddings
 from langchain.vectorstores import Chroma
@@ -7,10 +6,9 @@ from data import prepare_data
 path = './llm'
 persist_directory = "vector_db"
 
-prepare_data(db_path = persist_directory, llm_path = path)
+llm = prepare_data(db_path = persist_directory, llm_path = path)
 
 embeddings = HuggingFaceEmbeddings()
-llm = HuggingFacePipeline.from_pretrained(path)
 vectordb = Chroma(persist_directory = persist_directory, embedding_function = embeddings)
 doc_retriever = vectordb.as_retriever()
 shakespeare_qa = RetrievalQA.from_chain_type(llm = llm, chain_type = "stuff", retriever = doc_retriever)

data.py

@@ -24,3 +24,5 @@ def prepare_data(db_path, llm_path):
 
     vectordb = Chroma.from_documents(documents=documents, embedding=embeddings, persist_directory=db_path)
     vectordb.persist()
+
+    return llm