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import streamlit as st
import requests
import json
print("UI Starting up...")
st.set_page_config(page_title="Enterprise RAG Search", layout="wide")
import os
API_URL = os.getenv("API_URL", "http://localhost:8000/api/v1/chat")
st.title("Enterprise RAG Search")
with st.sidebar:
st.header("Configuration")
top_k_retrieval = st.slider("Retrieval Top-K", 5, 50, 20)
top_k_rerank = st.slider("Rerank Top-K", 1, 10, 5)
# use_hyde = st.checkbox("Use HyDE", value=False)
query = st.chat_input("Enter your query...")
if query:
st.session_state.messages = st.session_state.get("messages", [])
st.session_state.messages.append({"role": "user", "content": query})
# s = requests.Session()
for msg in st.session_state.get("messages", []):
with st.chat_message(msg["role"]):
st.write(msg["content"])
if query:
with st.chat_message("assistant"):
with st.spinner("Searching..."):
try:
payload = {
"query": query,
"top_k_retrieval": top_k_retrieval,
"top_k_rerank": top_k_rerank,
# "use_hyde": use_hyde
}
response = requests.post(API_URL, json=payload)
response.raise_for_status()
data = response.json()
answer = data["answer"]
st.write(answer)
with st.expander("View Context"):
for i, (doc, score) in enumerate(data["context"]):
st.markdown(f"**Relevance Score:** {score:.4f}")
st.text(doc)
st.divider()
st.session_state.messages.append({"role": "assistant", "content": answer})
except Exception as e:
st.error(f"Error: {e}")
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