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import weave | |
import streamlit as st | |
from rag.rag import SimpleRAGPipeline | |
WANDB_PROJECT = "paper_reader" | |
weave.init(f"{WANDB_PROJECT}") | |
st.set_page_config(page_title="Chat with the Llama 3 paper!", page_icon="π¦", layout="centered", initial_sidebar_state="auto", menu_items=None) | |
st.title("Chat with the Llama 3 paper π¬π¦") | |
def load_rag_pipeline(): | |
rag_pipeline = SimpleRAGPipeline() | |
rag_pipeline.build_query_engine() | |
return rag_pipeline | |
if "rag_pipeline" not in st.session_state.keys(): | |
st.session_state.rag_pipeline = load_rag_pipeline() | |
rag_pipeline = st.session_state["rag_pipeline"] | |
# openai_api_key = st.sidebar.text_input('OpenAI API Key', type='password') | |
def generate_response(query): | |
response = rag_pipeline.predict(query) | |
st.write_stream(response.response_gen) | |
with st.form('my_form'): | |
query = st.text_area('Ask your question about the Llama 3 paper here:') | |
submitted = st.form_submit_button('Submit') | |
if submitted: | |
generate_response(query) | |