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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
from orchestrator.gemini import gemini_generate, gemini_generate_code
def main():
st.set_page_config(
page_title="🚀 MCP Research Companion",
layout="wide",
initial_sidebar_state="expanded"
)
# Sidebar (updated return values)
(query, num_results, theme, search_clicked, gemini_prompt,
mcp_codegen_prompt, codegen_clicked) = render_sidebar()
if theme == "Dark":
st.markdown(
"""
<style>
body {background-color: #0E1117; color: #E6E1DC;}
.stButton>button {background-color: #2563EB; color: white;}
</style>
""",
unsafe_allow_html=True,
)
# -- Gemini Q&A --
if gemini_prompt:
st.header("💡 Gemini Research Q&A")
with st.spinner("Gemini is thinking..."):
answer = gemini_generate(gemini_prompt)
st.success(answer)
# -- MCP Code Generation --
if mcp_codegen_prompt and codegen_clicked:
st.header("🛠️ Gemini MCP Server Code Generation")
with st.spinner("Gemini is coding your MCP server..."):
system_instruction = (
"You are an expert in Model Context Protocol (MCP) server development. "
"Generate clean, production-ready Python code for an MCP server as described below. "
"Use best practices and include all necessary imports and comments."
)
code_result = gemini_generate_code(system_instruction, mcp_codegen_prompt)
st.code(code_result, language="python")
st.download_button("Download code as mcp_server.py", code_result, file_name="mcp_server.py", mime="text/x-python")
# -- Search and Display Papers --
if search_clicked and query:
dispatcher = Dispatcher()
with st.spinner("Searching MCP servers..."):
papers = dispatcher.search_papers(query, limit=num_results)
render_paper_list(papers)
if papers:
first_paper = papers[0]
st.subheader("Gemini-Powered Abstract Summarizer")
if st.button("Summarize Abstract with Gemini"):
with st.spinner("Gemini is generating summary..."):
summary = gemini_generate(first_paper["abstract"])
st.success(summary)
notebook_cells = dispatcher.get_notebook_cells(first_paper["id"])
render_notebook(notebook_cells)
graph_data = dispatcher.get_graph(first_paper["id"])
render_graph(graph_data)
if __name__ == "__main__":
main()
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