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app.py

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+import streamlit as st
+from app_config import SYSTEM_PROMPT
+from langchain_groq import ChatGroq
+from dotenv import load_dotenv
+from pathlib import Path
+import os
+import session_manager
+
+from langchain_community.utilities import GoogleSerperAPIWrapper
+env_path = Path('.') / '.env'
+load_dotenv(dotenv_path=env_path)
+
+
+st.markdown(
+    """
+<style>
+    .st-emotion-cache-janbn0 {
+        flex-direction: row-reverse;
+        text-align: right;
+    }
+    .st-emotion-cache-1ec2a3d{
+        display: none;
+    }
+</style>
+""",
+    unsafe_allow_html=True,
+)
+
+# Intialize chat history
+print("SYSTEM MESSAGE")
+if "messages" not in st.session_state:
+    st.session_state.messages = [{"role": "system", "content": SYSTEM_PROMPT}]
+
+print("SYSTEM MODEL")
+if "llm" not in st.session_state:
+    st.session_state.llm = ChatGroq(
+        model="llama-3.3-70b-versatile",
+        temperature=0,
+        max_tokens=None,
+        timeout=None,
+        max_retries=2,
+        api_key=str(os.getenv('GROQ_API'))
+    )
+
+if "search_tool" not in st.session_state:
+    st.session_state.search_tool = GoogleSerperAPIWrapper(
+        serper_api_key=str(os.getenv('SERPER_API')))
+
+
+def get_answer(query):
+    new_search_query = st.session_state.llm.invoke(
+        f"Convert below query to english for Ahmedabad Municipal Corporation (AMC) You just need to give translated query. Don't add any additional details.\n Query: {query}").content
+    search_result = st.session_state.search_tool.run(
+        f"{new_search_query} site:https://ahmedabadcity.gov.in/")
+
+    system_prompt = """You are a helpful assistance for The Ahmedabad Municipal Corporation (AMC). which asnwer user query from given context only. Output language should be as same as `original_query_from_user`.
+  context: {context}
+  original_query_from_user: {original_query}
+  query: {query}"""
+
+    return st.session_state.llm.invoke(system_prompt.format(context=search_result, query=new_search_query, original_query=query)).content
+
+
+session_manager.set_session_state(st.session_state)
+
+print("container")
+# Display chat messages from history
+st.markdown("<h1 style='text-align: center;'>AMC Bot</h1>", unsafe_allow_html=True)
+container = st.container(height=700)
+for message in st.session_state.messages:
+    if message["role"] != "system":
+        with container.chat_message(message["role"]):
+            if message['type'] == "table":
+                st.dataframe(message['content'].set_index(
+                    message['content'].columns[0]))
+            elif message['type'] == "html":
+                st.markdown(message['content'], unsafe_allow_html=True)
+            else:
+                st.write(message["content"])
+
+# When user gives input
+if prompt := st.chat_input("Enter your query here... "):
+    with container.chat_message("user"):
+        st.write(prompt)
+    st.session_state.messages.append(
+        {"role": "user", "content": prompt, "type": "string"})
+    st.session_state.last_query = prompt
+
+    with container.chat_message("assistant"):
+        current_conversation = """"""
+
+        # if st.session_state.next_agent != "general_agent" and st.session_state.next_agent in st.session_state.agent_history:
+        for message in st.session_state.messages:
+            if message['role'] == 'user':
+                current_conversation += f"""user: {message['content']}\n"""
+            if message['role'] == 'assistant':
+                current_conversation += f"""ai: {message['content']}\n"""
+
+        current_conversation += f"""user: {prompt}\n"""
+
+        print("****************************************** Messages ******************************************")
+        print("messages", current_conversation)
+        print()
+        print()
+        response = get_answer(current_conversation)
+        print("******************************************************** Response ********************************************************")
+        print("MY RESPONSE IS:", response)
+
+        st.write(response)
+        st.session_state.messages.append(
+            {"role": "assistant", "content": response, "type": "string"})

app_config.py

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+SYSTEM_PROMPT = """You are a helpful assistance for The Ahmedabad Municipal Corporation (AMC). which asnwer user query from given context only. Output language should be as same as `original_query_from_user`.
+  context: {context}
+  original_query_from_user: {original_query}
+  query: {query}"""
+
+MODEL = "llama-3.3-70b-versatile"
+MAX_TOKENS = 4000

requirements.txt

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+langchain
+langchain_groq
+langchain_community

session_manager.py

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+session_state = None
+
+def set_session_state(state):
+    global session_state
+    session_state = state
+
+def get_session_state():
+    return session_state