Spaces:
Running
Running
File size: 1,480 Bytes
7bd5533 ee233a4 7bd5533 c8c75ba 7bd5533 c8c75ba 7bd5533 c8c75ba 7bd5533 c8c75ba 7bd5533 |
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 |
# File: app.py
import streamlit as st
from orchestrator.dispatcher import Dispatcher
from components.sidebar import render_sidebar
from components.paper_list import render_paper_list
from components.notebook_view import render_notebook
from components.graph_view import render_graph
def main():
# Page configuration with theming
st.set_page_config(page_title="AI Research Companion", layout="wide", initial_sidebar_state="expanded")
# Render sidebar for inputs: query, num results, theme
query, num_results, theme, search_clicked = render_sidebar()
# Dynamically inject simple dark CSS if chosen
if theme == "Dark":
st.markdown(
"<style>body {background-color: #0E1117; color: #E6E1DC;} .stButton>button {background-color: #2563EB; color: white;}</style>",
unsafe_allow_html=True
)
if search_clicked and query:
dispatcher = Dispatcher()
# 1. Search for papers via MCP servers
papers = dispatcher.search_papers(query, limit=num_results)
render_paper_list(papers)
# 2. Show notebook for the first paper
if papers:
first_id = papers[0]["id"]
notebook_cells = dispatcher.get_notebook_cells(first_id)
render_notebook(notebook_cells)
# 3. Visualize a knowledge graph for the paper
graph_data = dispatcher.get_graph(first_id)
render_graph(graph_data)
if __name__ == "__main__":
main()
|