import streamlit as st

from open_notebook.database.migrate import MigrationManager
from open_notebook.graphs.chat import ThreadState, graph
from open_notebook.models import model_manager
from open_notebook.utils import (
    compare_versions,
    get_installed_version,
    get_version_from_github,
)


def version_sidebar():
    with st.sidebar:
        try:
            current_version = get_installed_version(
                "open-notebook"
            )  # Note the hyphen instead of underscore
        except Exception:
            # Fallback to reading directly from pyproject.toml
            import tomli

            with open("pyproject.toml", "rb") as f:
                pyproject = tomli.load(f)
                current_version = pyproject["tool"]["poetry"]["version"]

        latest_version = get_version_from_github(
            "https://www.github.com/lfnovo/open-notebook", "main"
        )
        st.write(f"Open Notebook: {current_version}")
        if compare_versions(current_version, latest_version) < 0:
            st.warning(
                f"New version {latest_version} available. [Click here for upgrade instructions](https://github.com/lfnovo/open-notebook/blob/main/docs/SETUP.md#upgrading-open-notebook)"
            )


def setup_stream_state(session_id) -> None:
    """
    Sets the value of the current session_id for langgraph thread state.
    If there is no existing thread state for this session_id, it creates a new one.
    """
    existing_state = graph.get_state({"configurable": {"thread_id": session_id}}).values
    if len(existing_state.keys()) == 0:
        st.session_state[session_id] = ThreadState(
            messages=[], context=None, notebook=None, context_config={}
        )
    else:
        st.session_state[session_id] = existing_state
    st.session_state["active_session"] = session_id


def check_migration():
    mm = MigrationManager()
    if mm.needs_migration:
        st.warning("The Open Notebook database needs a migration to run properly.")
        if st.button("Run Migration"):
            mm.run_migration_up()
            st.success("Migration successful")
            st.rerun()
        st.stop()


def check_models():
    default_models = model_manager.defaults
    if (
        not default_models.default_chat_model
        or not default_models.default_transformation_model
    ):
        st.warning(
            "You don't have default chat and transformation models selected. Please, select them on the settings page."
        )
        st.stop()
    elif not default_models.default_embedding_model:
        st.warning(
            "You don't have a default embedding model selected. Vector search will not be possible and your assistant will be less able to answer your queries. Please, select one on the settings page."
        )
        st.stop()
    elif not default_models.default_speech_to_text_model:
        st.warning(
            "You don't have a default speech to text model selected. Your assistant will not be able to transcribe audio. Please, select one on the settings page."
        )
        st.stop()
    elif not default_models.default_text_to_speech_model:
        st.warning(
            "You don't have a default text to speech model selected. Your assistant will not be able to generate audio and podcasts. Please, select one on the settings page."
        )
        st.stop()
    elif not default_models.large_context_model:
        st.warning(
            "You don't have a large context model selected. Your assistant will not be able to process large documents. Please, select one on the settings page."
        )
        st.stop()


def page_commons():
    version_sidebar()
    check_migration()
    check_models()