Create app.py

app.py

@@ -0,0 +1,46 @@
+from PyPDF2 import PdfReader
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.text_splitter import CharacterTextSplitter
+from langchain.vectorstores import ElasticVectorSearch, Pinecone, Weaviate, FAISS
+from langchain.chains.question_answering import load_qa_chain
+from langchain.llms import OpenAI
+import gradio as gr
+
+import os
+
+
+
+reader = PdfReader('NEWChanakya Neeti - Radhakrishnan Pillai.pdf')
+
+raw_text = ''
+for i, page in enumerate(reader.pages):
+    text = page.extract_text()
+    if text:
+        raw_text += text
+
+text_splitter = CharacterTextSplitter(        
+    separator = "\n",
+    chunk_size = 1000,
+    chunk_overlap  = 200,
+    length_function = len,
+)
+texts = text_splitter.split_text(raw_text)
+
+embeddings = OpenAIEmbeddings()
+docsearch = FAISS.from_texts(texts, embeddings)
+
+chain = load_qa_chain(OpenAI(), chain_type="stuff")
+
+def learn_from_chanakya_neeti(chat_history,query):
+  docs = docsearch.similarity_search(query)
+  result = chain.run(input_documents=docs, question=query)
+  return chat_history + [(query,result)]
+
+with gr.Blocks() as demo:
+  chatbot = gr.Chatbot()
+  textbox = gr.Textbox(label="Your query")
+
+  textbox.submit(fn=learn_from_chanakya_neeti,inputs=[chatbot,textbox],outputs=[chatbot])
+
+
+demo.launch(debug=True)