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Update src/streamlit_app.py
Browse files- src/streamlit_app.py +58 -39
src/streamlit_app.py
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import altair as alt
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import numpy as np
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import pandas as pd
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import streamlit as st
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import streamlit as st
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import requests
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import uuid
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# Constants
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WEBHOOK_URL = "https://shahrukh1472.app.n8n.cloud/webhook/2f9e9f00-7ce8-485e-bd34-0df1014c4303"
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BEARER_TOKEN = "TestCreds99"
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def generate_session_id():
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return str(uuid.uuid4())
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def send_message_to_llm(session_id, message):
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headers = {
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"Authorization": f"Bearer {BEARER_TOKEN}",
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"Content-Type": "application/json"
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}
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payload = {
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"sessionId": session_id,
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"chatInput": message
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}
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response = requests.post(WEBHOOK_URL, json=payload, headers=headers)
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if response.status_code == 200:
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return response.json()["output"]
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else:
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return f"Error: {response.status_code} - {response.text}"
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def main():
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st.title("Hey, I'm your Real-estate AI Agent. Let's Chat!")
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# Initialize session state
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if "messages" not in st.session_state:
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st.session_state.messages = []
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if "session_id" not in st.session_state:
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st.session_state.session_id = generate_session_id()
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# Display chat messages
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for message in st.session_state.messages:
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with st.chat_message(message["role"]):
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st.write(message["content"])
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# User input
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user_input = st.chat_input("Type your message here...")
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if user_input:
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# Add user message to chat history
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st.session_state.messages.append({"role": "user", "content": user_input})
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with st.chat_message("user"):
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st.write(user_input)
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# Get LLM response
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llm_response = send_message_to_llm(st.session_state.session_id, user_input)
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# Add LLM response to chat history
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st.session_state.messages.append({"role": "assistant", "content": llm_response})
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with st.chat_message("assistant"):
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st.write(llm_response)
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if __name__ == "__main__":
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main()
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