Spaces:
Sleeping
Sleeping
File size: 2,961 Bytes
e881355 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 | import streamlit as st
import os
from pipeline import run_research_pipeline
from dotenv import load_dotenv
# Load local environment variables if present
load_dotenv()
# Map Gemini_API_KEY to GOOGLE_API_KEY for LangChain if necessary
if "Gemini_API_KEY" in os.environ and "GOOGLE_API_KEY" not in os.environ:
os.environ["GOOGLE_API_KEY"] = os.environ["Gemini_API_KEY"]
st.set_page_config(
page_title="Multi-Agent Research Assistant",
page_icon="🤖",
layout="wide"
)
# Custom Styling
st.markdown("""
<style>
.main-title {
font-size: 3rem;
font-weight: 700;
color: #1E3A8A;
margin-bottom: 0.5rem;
}
.subtitle {
font-size: 1.2rem;
color: #4B5563;
margin-bottom: 2rem;
}
</style>
""", unsafe_allow_html=True)
st.markdown('<div class="main-title">🤖 Multi-Agent RAG Research Assistant</div>', unsafe_allow_html=True)
st.markdown('<div class="subtitle">Enter a topic. The system will search the web, scrape articles, compile a report, and critique it.</div>', unsafe_allow_html=True)
topic = st.text_input("What would you like to research?", placeholder="e.g., Advancements in Quantum Computing")
if st.button("Start Agent Collaboration", type="primary"):
if not topic.strip():
st.error("Please enter a research topic first.")
else:
# Visual collaboration status
with st.status("Agents are collaborating...", expanded=True) as status_box:
st.write("🔍 Search Agent: Searching the web via Tavily...")
# Run the research pipeline
try:
result = run_research_pipeline(topic)
status_box.update(label="Research Complete!", state="complete", expanded=False)
st.success("Research completed successfully!")
# Show results in nice clean tabs
tab1, tab2, tab3 = st.tabs(["📄 Final Report", "⭐ Critic Review", "🔧 Technical Data"])
with tab1:
st.markdown("### Drafted Report")
st.markdown(result.get("report", "No report generated."))
with tab2:
st.markdown("### Critic Score and Feedback")
st.markdown(result.get("feedback", "No feedback generated."))
with tab3:
col1, col2 = st.columns(2)
with col1:
st.subheader("Web Search Output")
st.code(result.get("search_results", "None"))
with col2:
st.subheader("Scraped Content Summary")
st.code(result.get("scraped_content", "None"))
except Exception as e:
status_box.update(label="Pipeline Failed", state="error")
st.error(f"Error executing pipeline: {str(e)}")
|