from pathlib import Path

import hellocomputer
import polars as pl
import pytest
from hellocomputer.config import Settings, StorageEngines
from hellocomputer.db.sessions import SessionDB
from hellocomputer.models import AvailableModels
from hellocomputer.prompts import Prompts
from hellocomputer.extraction import initial_intent_parser
from langchain_core.prompts import ChatPromptTemplate
from langchain_community.agent_toolkits import SQLDatabaseToolkit
from langchain_openai import ChatOpenAI

settings = Settings(
    storage_engine=StorageEngines.local,
    path=Path(hellocomputer.__file__).parents[2] / "test" / "output",
)

TEST_XLS_PATH = (
    Path(hellocomputer.__file__).parents[2]
    / "test"
    / "data"
    / "TestExcelHelloComputer.xlsx"
)

SID = "test"


@pytest.mark.asyncio
@pytest.mark.skipif(settings.llm_api_key == "Awesome API", reason="API Key not set")
async def test_chat_simple():
    llm = ChatOpenAI(
        base_url=settings.llm_base_url,
        api_key=settings.llm_api_key,
        model=AvailableModels.mixtral_8x7b,
        temperature=0.5,
    )
    prompt = ChatPromptTemplate.from_template(
        """Say literally {word}, a single word. Don't be verbose, 
        I'll be disappointed if you say more than a single word"""
    )
    chain = prompt | llm
    response = await chain.ainvoke({"word": "Hello"})

    assert "hello" in response.content.lower()


@pytest.mark.asyncio
@pytest.mark.skipif(settings.llm_api_key == "Awesome API", reason="API Key not set")
async def test_query_context():
    db = SessionDB(settings, sid=SID).load_xls(TEST_XLS_PATH).llmsql

    llm = ChatOpenAI(
        base_url=settings.llm_base_url,
        api_key=settings.llm_api_key,
        model=AvailableModels.mixtral_8x7b,
        temperature=0.5,
    )

    toolkit = SQLDatabaseToolkit(db=db, llm=llm)
    context = toolkit.get_context()
    assert "table_info" in context
    assert "table_names" in context


@pytest.mark.asyncio
@pytest.mark.skipif(settings.llm_api_key == "Awesome API", reason="API Key not set")
async def test_initial_intent():
    llm = ChatOpenAI(
        base_url=settings.llm_base_url,
        api_key=settings.llm_api_key,
        model=AvailableModels.llama_small,
        temperature=0,
    )
    prompt = await Prompts.intent()
    chain = prompt | llm | initial_intent_parser

    response = await chain.ainvoke({"query", "Make me a sandwich"})
    assert response == "general"

    response = await chain.ainvoke(
        {"query", "Which is the average score of all the students"}
    )
    assert response == "query"


#
#     chat = await chat.sql_eval(db.query_prompt(query))
#     query = extract_code_block(chat.last_response_content())
#     assert query.startswith("SELECT")
#
#
# @pytest.mark.asyncio
# @pytest.mark.skipif(settings.llm_api_key == "Awesome API", reason="API Key not set")
# async def test_data_query():
#     q = "Find the average score of all the sudents"
#
#     llm = Chat(
#         api_key=settings.llm_api_key,
#         temperature=0.5,
#     )
#     db = SessionDB(
#         storage_engine=TEST_STORAGE, path=TEST_OUTPUT_FOLDER, sid="test"
#     ).load_folder()
#
#     chat = await llm.sql_eval(db.query_prompt(q))
#     query = extract_code_block(chat.last_response_content())
#     result: pl.DataFrame = db.query(query).pl()
#
#     assert result.shape[0] == 1
#     assert result.select([pl.col("avg(Score)")]).to_series()[0] == 0.5
#