Update app.py

app.py

@@ -1,82 +1,85 @@
+import os
+from dotenv import load_dotenv
 import streamlit as st
-
 from langchain_groq import ChatGroq
 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.callbacks import StreamlitCallbackHandler
 
+# Load .env
+load_dotenv()
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+if not GROQ_API_KEY:
+    st.error("GROQ_API_KEY not found in environment")
+    st.stop()
+
+# Streamlit UI
 st.set_page_config(page_title="General Knowledge Assistant", page_icon="🧭")
 st.title("General Knowledge Assistant")
 
-groq_api_key = st.sidebar.text_input(label="Groq API Key", type="password")
-
-if not groq_api_key:
-    st.info("Please add your Groq API key to continue")
-    st.stop()
-
-llm = ChatGroq(model="meta-llama/llama-4-maverick-17b-128e-instruct", groq_api_key=groq_api_key)
+# Initialize LLM
+llm = ChatGroq(
+    model="meta-llama/llama-4-maverick-17b-128e-instruct",
+    groq_api_key=GROQ_API_KEY
+)
 
+# Wikipedia tool
 wikipedia_wrapper = WikipediaAPIWrapper()
 wikipedia_tool = Tool(
     name="Wikipedia",
     func=wikipedia_wrapper.run,
-    description="Use this tool to fetch updated information from the internet when your base knowledge is outdated or incomplete."
+    description="Fetch summaries from Wikipedia."
 )
 
-prompt = """
-You are a knowledgeable assistant. Your task is to answer the user's questions accurately with your general knowledge.
-If you detect that your stored information is outdated or missing recent details, immediately search Wikipedia for updated info.
-Always ensure your answer is up to date. Whenever I tell you to write essay give a title also to the essay.
-
-Question: {question}
-Answer:
-"""
-
-prompt_template = PromptTemplate(
-    input_variables=["question"],
-    template=prompt
+# DuckDuckGo web search tool
+ddg_wrapper = DuckDuckGoSearchAPIWrapper()
+web_search_tool = Tool(
+    name="WebSearch",
+    func=ddg_wrapper.run,
+    description="Perform a live web search via DuckDuckGo."
 )
 
+# Prompt template
+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+If you’re unsure, think the info may be outdated, or can’t find it, simply say "I don't know" or "Outdated".
+"""
+prompt_template = PromptTemplate(input_variables=["question"], template=prompt)
 chain = LLMChain(llm=llm, prompt=prompt_template)
 
-reasoning_tool = Tool(
-    name="Reasoning tool",
-    func=chain.run,
-    description="A tool for answering general knowledge questions using logical reasoning and factual information. Use Wikipedia if your answer might be outdated."
-)
-
-assistant_agent = initialize_agent(
-    tools=[wikipedia_tool, reasoning_tool],
-    llm=llm,
-    agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
-    verbose=False,
-    handle_parsing_errors=True
-)
-
+# Fallback logic: LLM → DuckDuckGo → Wikipedia
+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
+        return wikipedia_wrapper.run(query)
+    return lm_answer
+
+# 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!"}
     ]
 
-for msg in st.session_state.messages:
-    st.chat_message(msg["role"]).write(msg['content'])
+for msg in st.session_state["messages"]:
+    st.chat_message(msg["role"]).write(msg["content"])
 
-question = st.text_area("Enter your question:", "Please enter your general knowledge question here")
+# User input
+question = st.text_area("Enter your question:", "")
 
-if st.button("find my answer"):
+if st.button("Find my answer"):
     if question:
-        with st.spinner("Generate response.."):
-            st.session_state.messages.append({"role": "user", "content": question})
-            st.chat_message("user").write(question)
-            
-            st_cb = StreamlitCallbackHandler(st.container(), expand_new_thoughts=False)
-            response = assistant_agent.run(st.session_state.messages, callbacks=[st_cb])
-            
-            st.session_state.messages.append({"role": "assistant", "content": response})
-            st.write("### Response:")
-            st.success(response)
+        st.session_state["messages"].append({"role": "user", "content": question})
+        st.chat_message("user").write(question)
+        with st.spinner("Generating response..."):
+            answer = get_answer(question)
+        st.session_state["messages"].append({"role": "assistant", "content": answer})
+        st.chat_message("assistant").write(answer)
     else:
-        st.warning("Please enter the question")
+        st.warning("Please enter a question.")