Update app.py

app.py

@@ -6,8 +6,7 @@ from langchain.chains import LLMChain
 from langchain.prompts import PromptTemplate
 from langchain_community.utilities import WikipediaAPIWrapper
 from langchain_community.utilities.duckduckgo_search import DuckDuckGoSearchAPIWrapper
-from langchain.agents.agent_types import AgentType
-from langchain.agents import Tool, initialize_agent
+from langchain.agents import Tool
 from langchain.callbacks import StreamlitCallbackHandler
 
 # Load .env
@@ -43,30 +42,37 @@ web_search_tool = Tool(
     description="Perform a live web search via DuckDuckGo."
 )
 
-# Prompt template
+# Prompt template for the LLM
 prompt = """
 You are a knowledgeable assistant. Answer {question} using your internal knowledge.
-If you’re unsure, think the info may be outdated, or can’t find it, simply say "I don't know" or "Outdated".
+If you’re unsure, say "I don't know" or "Outdated".
 """
 prompt_template = PromptTemplate(input_variables=["question"], template=prompt)
 chain = LLMChain(llm=llm, prompt=prompt_template)
 
-# Fallback logic: LLM → DuckDuckGo → Wikipedia
+# Enhanced fallback logic:
 def get_answer(query: str) -> str:
-    lm_answer = chain.run({"question": query}).strip()
-    if any(flag in lm_answer.lower() for flag in ["i don't know", "outdated", "not sure"]):
-        web_ans = ddg_wrapper.run(query)
-        if web_ans and len(web_ans) > 20:
-            return web_ans
+    ql = query.lower()
+    # 1) If it's asking for recent info, always web‑search first:
+    if any(k in ql for k in ["recent", "latest", "today", "current", "2025"]):
+        ddg_ans = ddg_wrapper.run(query)
+        if ddg_ans and len(ddg_ans) > 20:
+            return ddg_ans
         return wikipedia_wrapper.run(query)
-    return lm_answer
+    # 2) Otherwise, use your LLM
+    lm_ans = chain.run({"question": query}).strip()
+    # 3) If the LLM defers, fall back to Wikipedia
+    if any(flag in lm_ans.lower() for flag in ["i don't know", "outdated", "not sure"]):
+        return wikipedia_wrapper.run(query)
+    return lm_ans
 
 # Conversation history
 if "messages" not in st.session_state:
     st.session_state["messages"] = [
-        {"role": "assistant", "content": "Hi, I'm your general knowledge assistant. Feel free to ask me any question!"}
+        {"role": "assistant", "content": "Hi! Ask me anything—I'll fetch the latest data for recent questions."}
     ]
 
+# Display history
 for msg in st.session_state["messages"]:
     st.chat_message(msg["role"]).write(msg["content"])
 
@@ -82,4 +88,4 @@ if st.button("Find my answer"):
         st.session_state["messages"].append({"role": "assistant", "content": answer})
         st.chat_message("assistant").write(answer)
     else:
-        st.warning("Please enter a question.")
+        st.warning("Please enter a question.")