app_mcp.py

# Import necessary libraries
import os
import gradio as gr

from mcp_service import make_retrieve_data_mcp, make_retrieve_graphs_mcp
from utils import create_user_id
import logging

from climateqa.engine.embeddings import get_embeddings_function
from climateqa.engine.llm import get_llm
from climateqa.engine.vectorstore import get_azure_search_vectorstore
from climateqa.engine.reranker import get_reranker

logging.basicConfig(level=logging.WARNING)
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"  # Suppresses INFO and WARNING logs
logging.getLogger().setLevel(logging.WARNING)


# Load environment variables in local mode
try:
    from dotenv import load_dotenv

    load_dotenv()
except Exception as e:
    pass


# Set up Gradio Theme
theme = gr.themes.Base(
    primary_hue="blue",
    secondary_hue="red",
    font=[gr.themes.GoogleFont("Poppins"), "ui-sans-serif", "system-ui", "sans-serif"],
)



user_id = create_user_id()


# Create vectorstore and retriever
embeddings_function = get_embeddings_function()

vectorstore = get_azure_search_vectorstore(embeddings=embeddings_function, index_name="climateqa-ipx")
vectorstore_graphs = get_azure_search_vectorstore(embeddings=embeddings_function, index_name="climateqa-owid", text_key="description")
vectorstore_region = get_azure_search_vectorstore(embeddings=embeddings_function, index_name="climateqa-v2")


llm = get_llm(provider="azure", max_tokens=3000, temperature=0.0, streaming=True)
if os.environ["GRADIO_ENV"] == "local":
    reranker = get_reranker("nano")
else:
    reranker = get_reranker("nano")

def mcp_server():
    with gr.Blocks() as mcp_only:
        retrieve_data_mcp = make_retrieve_data_mcp(vectorstore=vectorstore, reranker=reranker)
        gr.api(retrieve_data_mcp)
        retrieve_graphs_mcp = make_retrieve_graphs_mcp(vectorstore=vectorstore_graphs)
        # gr.api(retrieve_graphs_mcp)

    return mcp_only


mcp_demo = mcp_server()
mcp_demo.launch(
    server_name=os.getenv("HOST", "0.0.0.0"),
    server_port=7860,
    mcp_server=True,
)