Update app.py

app.py

@@ -1,5 +1,6 @@
 import os
 import gradio as gr
+import logging
 from langchain.document_loaders import PyPDFLoader
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain.embeddings import OpenAIEmbeddings
@@ -8,10 +9,16 @@ from langchain.chat_models import ChatOpenAI
 from langchain.chains import ConversationalRetrievalChain, LLMChain
 from langchain.memory import ConversationBufferMemory
 from langchain.prompts import PromptTemplate
+import concurrent.futures
+import timeout_decorator
+
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
 
 class QueryRefiner:
     def __init__(self):
-        self.refinement_llm = ChatOpenAI(temperature=0.2, model_name='gpt-3.5-turbo')
+        self.refinement_llm = ChatOpenAI(temperature=0.2, model_name='gpt-3.5-turbo', request_timeout=30)
         self.refinement_prompt = PromptTemplate(
             input_variables=['query', 'context'],
             template="""Refine and enhance the following query for maximum clarity and precision:
@@ -32,6 +39,7 @@ Refined Query:"""
             prompt=self.refinement_prompt
         )
 
+    @timeout_decorator.timeout(30)  # 30 seconds timeout
     def refine_query(self, original_query, context_hints=''):
         try:
             refined_query = self.refinement_chain.run({
@@ -40,15 +48,15 @@ Refined Query:"""
             })
             return refined_query.strip()
         except Exception as e:
-            print(f"Query refinement error: {e}")
+            logger.error(f"Query refinement error: {e}")
             return original_query
 
 class AdvancedPdfChatbot:
     def __init__(self, openai_api_key):
         os.environ["OPENAI_API_KEY"] = openai_api_key
-        self.embeddings = OpenAIEmbeddings()
+        self.embeddings = OpenAIEmbeddings(request_timeout=30)
         self.text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)
-        self.llm = ChatOpenAI(temperature=0, model_name='gpt-4')
+        self.llm = ChatOpenAI(temperature=0, model_name='gpt-4', request_timeout=30)
         
         self.memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
         self.query_refiner = QueryRefiner()
@@ -66,6 +74,7 @@ If the answer isn't directly available, explain why.""",
             input_variables=["context", "question"]
         )
 
+    @timeout_decorator.timeout(60)  # 1 minute timeout for PDF processing
     def load_and_process_pdf(self, pdf_path):
         loader = PyPDFLoader(pdf_path)
         documents = loader.load()
@@ -79,6 +88,7 @@ If the answer isn't directly available, explain why.""",
             combine_docs_chain_kwargs={"prompt": self.qa_prompt}
         )
 
+    @timeout_decorator.timeout(30)  # 30 seconds timeout for chat
     def chat(self, query):
         if not self.chain:
             return "Please upload a PDF first."
@@ -113,6 +123,7 @@ def upload_pdf(pdf_file):
         pdf_chatbot.load_and_process_pdf(file_path)
         return f"PDF processed successfully: {file_path}"
     except Exception as e:
+        logger.error(f"PDF processing error: {e}")
         return f"Error processing PDF: {str(e)}"
 
 def respond(message, history):
@@ -123,6 +134,7 @@ def respond(message, history):
         history.append((message, bot_message))
         return "", history
     except Exception as e:
+        logger.error(f"Chat response error: {e}")
         return f"Error: {str(e)}", history
 
 def clear_chatbot():