Update app.py

app.py

@@ -211,6 +211,16 @@ def ask_question(question, temperature, top_p, repetition_penalty, web_search):
         if web_search:
             search_results = google_search(question)
             context_str = "\n".join([result["text"] for result in search_results if result["text"]])
+            prompt_template = """
+            Answer the question based on the following web search results:
+
+            Web Search Results:
+            {context}
+
+            Current Question: {question}
+
+            Provide a concise and direct answer to the question:
+            """
         else:
             database = FAISS.load_local("faiss_database", embed, allow_dangerous_deserialization=True)
             if is_related_to_history(question, conversation_history):
@@ -219,9 +229,10 @@ def ask_question(question, temperature, top_p, repetition_penalty, web_search):
                 retriever = database.as_retriever()
                 relevant_docs = retriever.get_relevant_documents(question)
                 context_str = "\n".join([doc.page_content for doc in relevant_docs])
+            prompt_template = prompt  # Use the original prompt for document-based answers
         
-        prompt_val = ChatPromptTemplate.from_template(prompt)
-        formatted_prompt = prompt_val.format(history=history_str, context=context_str if not web_search else "", question=question)
+        prompt_val = ChatPromptTemplate.from_template(prompt_template)
+        formatted_prompt = prompt_val.format(history=history_str, context=context_str, question=question)
         
         answer = generate_chunked_response(model, formatted_prompt)
         answer = re.split(r'Question:|Current Question:', answer)[-1].strip()