import asyncio
import json
import os
import time

import numpy as np

from lightrag import LightRAG
from lightrag.llm.openai import openai_complete_if_cache, openai_embed
from lightrag.utils import EmbeddingFunc


## For Upstage API
# please check if embedding_dim=4096 in lightrag.py and llm.py in lightrag direcotry
async def llm_model_func(prompt, system_prompt=None, history_messages=None, **kwargs) -> str:
    if history_messages is None:
        history_messages = []
    return await openai_complete_if_cache(
        'solar-mini',
        prompt,
        system_prompt=system_prompt,
        history_messages=history_messages,
        api_key=os.getenv('UPSTAGE_API_KEY'),
        base_url='https://api.upstage.ai/v1/solar',
        **kwargs,
    )


async def embedding_func(texts: list[str]) -> np.ndarray:
    return await openai_embed(
        texts,
        model='solar-embedding-1-large-query',
        api_key=os.getenv('UPSTAGE_API_KEY'),
        base_url='https://api.upstage.ai/v1/solar',
    )


## /For Upstage API


def insert_text(rag, file_path):
    with open(file_path) as f:
        unique_contexts = json.load(f)

    retries = 0
    max_retries = 3
    while retries < max_retries:
        try:
            rag.insert(unique_contexts)
            break
        except Exception as e:
            retries += 1
            print(f'Insertion failed, retrying ({retries}/{max_retries}), error: {e}')
            time.sleep(10)
    if retries == max_retries:
        print('Insertion failed after exceeding the maximum number of retries')


cls = 'mix'
WORKING_DIR = f'../{cls}'

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


async def initialize_rag():
    rag = LightRAG(
        working_dir=WORKING_DIR,
        llm_model_func=llm_model_func,
        embedding_func=EmbeddingFunc(embedding_dim=4096, func=embedding_func),
    )

    await rag.initialize_storages()  # Auto-initializes pipeline_status
    return rag


def main():
    # Initialize RAG instance
    rag = asyncio.run(initialize_rag())
    insert_text(rag, f'../datasets/unique_contexts/{cls}_unique_contexts.json')


if __name__ == '__main__':
    main()