import asyncio
import inspect
import logging
import os

from lightrag.kg.shared_storage import initialize_pipeline_status
from lightrag.utils import EmbeddingFunc

from Config.Config import LLM_MODEL_NAME, EMBED_DIM, EMBED_MAX_TOKEN_SIZE
from Util.LightRagUtil import configure_logging, initialize_rag, print_stream, llm_model_func, embedding_func
from lightrag import QueryParam, LightRAG

# 在程序开始时添加以下配置
logging.basicConfig(
    level=logging.INFO,  # 设置日志级别为INFO
    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)

# 或者如果你想更详细地控制日志输出
logger = logging.getLogger('lightrag')
logger.setLevel(logging.INFO)
handler = logging.StreamHandler()
handler.setFormatter(logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s'))
logger.addHandler(handler)

ROOT_DIR = '.'
WORKING_DIR = f"{ROOT_DIR}/dickens-pg"

logging.basicConfig(format="%(levelname)s:%(message)s", level=logging.INFO)

if not os.path.exists(WORKING_DIR):
    os.mkdir(WORKING_DIR)

# AGE
os.environ["AGE_GRAPH_NAME"] = "dickens"
os.environ["POSTGRES_HOST"] = "10.10.14.208"
os.environ["POSTGRES_PORT"] = "5432"
os.environ["POSTGRES_USER"] = "postgres"
os.environ["POSTGRES_PASSWORD"] = "postgres"
os.environ["POSTGRES_DATABASE"] = "rag"


async def initialize_rag():
    rag = LightRAG(
        working_dir=WORKING_DIR,
        llm_model_func=llm_model_func,
        llm_model_name=LLM_MODEL_NAME,
        llm_model_max_async=4,
        llm_model_max_token_size=32768,
        enable_llm_cache_for_entity_extract=True,
        embedding_func=EmbeddingFunc(
            embedding_dim=EMBED_DIM,
            max_token_size=EMBED_MAX_TOKEN_SIZE,
            func=embedding_func
        ),
        kv_storage="PGKVStorage",
        doc_status_storage="PGDocStatusStorage",
        graph_storage="PGGraphStorage",
        vector_storage="PGVectorStorage",
        auto_manage_storages_states=False,
    )

    await rag.initialize_storages()
    await initialize_pipeline_status()

    return rag

async def main():
    try:
        rag = await initialize_rag()
        resp = await rag.aquery(
            "What are the top themes in this story",
            param=QueryParam(mode="hybrid", stream=True),
            # hybrid naive
        )
        if inspect.isasyncgen(resp):
            await print_stream(resp)
        else:
            print(resp)
    except Exception as e:
        print(f"An error occurred: {e}")
    finally:
        if rag:
            await rag.finalize_storages()


if __name__ == "__main__":
    configure_logging()
    asyncio.run(main())