Update app.py

app.py

@@ -4,16 +4,14 @@ from langchain.docstore.document import Document
 from langchain.embeddings import HuggingFaceEmbeddings
 from langchain.text_splitter import CharacterTextSplitter
 embeddings = HuggingFaceEmbeddings()
-#with open('Gita.txt') as f:
-    #gita = f.read()
-gita="story of Arjun and Krishna refered to as song celestial"
+g=open('gita.txt')
+gita=g.read()
 text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
 texts = text_splitter.split_text(gita)
 docsearch = Chroma.from_texts(texts, embeddings)
 def answer(query):
   docs = docsearch.similarity_search(query)
   out=docs[0].page_content
-  #out=gita
   return out
 demo = gr.Interface(fn=answer, inputs='text',outputs='text',examples=[['song celestial']])
 demo.launch()