Update app.py

app.py

@@ -181,9 +181,9 @@ conversation_history = []
 def predict(user_input, timeout_seconds=1800): # 30 minutes = 1800 seconds
     
     filter = "/content/drive/My Drive/Colab Notebooks/medical/Conoscenze-unito.pdf"
-    relevant_document_chunks = vectorstore.similarity_search(user_input, k=10,filter={"source": filter})
+    relevant_document_chunks = vectorstore.similarity_search(user_input, k=10)
     context_list = [d.page_content + "\ ###Page: " + str(d.metadata['page']) + "\n\n " for d in relevant_document_chunks]
-    context_for_query = ".".join(context_list) + "this is all thhe context I have"
+    context_for_query = ".".join(context_list) + "this is all the context I have"
     
     global conversation_history
 
@@ -232,10 +232,11 @@ def predict(user_input, timeout_seconds=1800): # 30 minutes = 1800 seconds
        # if user_input.lower() in ["quit", "exit"]:
         #    break
                     
+    save_feedback(user_input, context_for_query, prediction)
     
-    prediction = bot_response.choices[0].message.content.strip()
+    prediction = response.choices[0].message.content.strip()
 
-    save_feedback(user_input, context_for_query, prediction)
+    
     
     #except Exception as e:
      #   prediction = str(e)
@@ -244,7 +245,7 @@ def predict(user_input, timeout_seconds=1800): # 30 minutes = 1800 seconds
     # while writing to the log file, ensure that the commit scheduler is locked to avoid parallel
     # access
 
-    return prediction
+    return prediction, context_for_query
 
 # Set-up the Gradio UI
 # Add text box.