Update app.py

app.py

@@ -16,7 +16,7 @@ def read_doc(directory):
     documents=file_loader.load()
     return documents
 
-doc=read_doc('documents/')
+doc=read_doc('documents/') #PDF directory
 len(doc)
 
 ## Divide the docs into chunks
@@ -26,7 +26,7 @@ def chunk_data(docs,chunk_size=800,chunk_overlap=50):
     doc=text_splitter.split_documents(docs)
     return docs
 
-documents=chunk_data(docs=doc)
+documents=chunk_data(docs=doc) #Fnct that divides the PDF into chuncks
 len(documents)
 
 embeddings=OpenAIEmbeddings(api_key=os.environ['OPENAI_API_KEY'])
@@ -36,10 +36,10 @@ vectors=embeddings.embed_query("How are you?")
 len(vectors)
 
 pinecone.init(
-    api_key="923d5299-ab4c-4407-bfe6-7f439d9a9cb9",
+    api_key="3cdc872c-aecc-4b11-93d6-b5243930ac3a",
     environment="gcp-starter"
 )
-index_name="langchainvector"
+index_name="knowledgebase"
 
 index=Pinecone.from_documents(doc,embeddings,index_name=index_name)
 
@@ -62,6 +62,6 @@ def retrieve_answers(query):
     return response
 
 
-our_query = "How much the agriculture target will be increased by how many crore?"
+our_query = "What is my name?"
 answer = retrieve_answers(our_query)
 print(answer)