Update app.py

app.py

@@ -130,13 +130,7 @@ class ChatDocumentQA:
         file_path = file_paths[0].name
         file_extension = os.path.splitext(file_path)[1]
 
-        if file_extension == '.pdf':
-            pdf_docs = [file_path.name for file_path in file_paths]
-            raw_text = self._extract_text_from_pdfs(pdf_docs)
-            text_chunks = self._split_text_into_chunks(raw_text)
-            vectorstore = self._create_vector_store_from_text_chunks(text_chunks)
-            return "file uploaded", {"knowledge_base": vectorstore}
-        elif file_extension == '.csv':  
+        if file_extension == '.csv':  
             # agent = self.create_agent(file_path)
             # tools = self.get_agent_tools(agent)
             # memory,tools,prompt = self.create_memory_for_csv_qa(tools)
@@ -150,7 +144,12 @@ class ChatDocumentQA:
             return "file uploaded", {"knowledge_base": agent_chain}
             
         else:
-            return "file uploaded", ""
+            pdf_docs = [file_path.name for file_path in file_paths]
+            raw_text = self._extract_text_from_pdfs(pdf_docs)
+            text_chunks = self._split_text_into_chunks(raw_text)
+            vectorstore = self._create_vector_store_from_text_chunks(text_chunks)
+            return "file uploaded", {"knowledge_base": vectorstore}        
+
 
     def _get_urls_knowledge_base(self, urls: str) -> Tuple[str, Dict[str, FAISS]]:
         """Build knowledge base from URLs.
@@ -232,24 +231,15 @@ class ChatDocumentQA:
             file_path = file_paths[0].name
             file_extension = os.path.splitext(file_path)[1]
 
-            if file_extension == ".pdf":
-                vectorstore = state["knowledge_base"]
-                chat = self._create_conversation_chain(vectorstore)
-                # user_ques = {"question": message}
-                print("chat_history",chat_history)
-                response = chat({"question": message,"chat_history": chat_history})
-                chat_history.append((message, response["answer"]))
-                return "", chat_history
-
-            elif file_extension == '.csv':
+            if file_extension == '.csv':
                 agent_chain = state["knowledge_base"]
                 response = agent_chain.run(input = message)
                 chat_history.append((message, response))
                 return "", chat_history
+            
             else:
                 vectorstore = state["knowledge_base"]
                 chat = self._create_conversation_chain(vectorstore)
-                # user_ques = {"question": message}
                 print("chat_history",chat_history)
                 response = chat({"question": message,"chat_history": chat_history})
                 chat_history.append((message, response["answer"]))