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from search import SemanticSearch, GoogleSearch, Document
import streamlit as st
from model import RAGModel, load_configs
def run_on_start():
global r
global configs
configs = load_configs(config_file="rag.configs.yml")
r = RAGModel(configs)
def search(query):
g = GoogleSearch(query)
data = g.all_page_data
d = Document(data, min_char_len=configs["document"]["min_char_length"])
st.session_state.doc = d.doc()[0]
st.title("LLM powred Google search")
if "messages" not in st.session_state:
run_on_start()
st.session_state.messages = []
if "doc" not in st.session_state:
st.session_state.doc = None
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.markdown(message["content"])
if prompt := st.chat_input("Search Here insetad of Google"):
st.chat_message("user").markdown(prompt)
st.session_state.messages.append({"role": "user", "content": prompt})
search(prompt)
s, u = SemanticSearch(
prompt,
st.session_state.doc,
configs["model"]["embeding_model"],
configs["model"]["device"],
)
topk = s.semantic_search(query=prompt, k=32)
output = r.answer_query(query=prompt, topk_items=topk)
response = output
with st.chat_message("assistant"):
st.markdown(response)
st.session_state.messages.append({"role": "assistant", "content": response})
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