import os
from utilities.transcripts import VTTTranscriptLoader, DocumentEmbedder
from utilities.setup import get_files


class EmbeddingService:
    def __init__(self, conf):
        self.keys = get_files.get_keys()
        self.conf = conf

    def __enter__(self):
        print("Start Embedding Service")
        return self

    def __exit__(self, exc_type, exc_val, exc_tb):
        print("Exiting Embedding Service")
    
    def get_transcripts(self, files):
        # Get filepaths and load them in document format
        filepaths = [file.name for file in files]
        loader = VTTTranscriptLoader(filepaths)
        results = loader.load()
            
        return results
    
    def run(self, files):
        # gets the files, cleans them, and loads them into pinecone
        results = self.get_transcripts(files)
        
        doc_embedder =  DocumentEmbedder(
            api_keys=self.keys,
            files=results,
            embedding=self.conf["embeddings"]["embedding"],
            index_name=self.conf["embeddings"]["index_name"],
        )
        
        # uploads them into pinecone
        doc_embedder.embed()
        
        return "complete"


class QAService:
    def __init__(self, conf):
        self.keys = get_files.get_keys()
        self.conf = conf

    def __enter__(self):
        print("Start QA Service")
        return self

    def __exit__(self, exc_type, exc_val, exc_tb):
        print("Exiting QA Service")

    # First embed question

    # Next, pass it into pinecone

    # Third, retrieve pinecone search

    # Structure query

    # inference QA model
    
    def run():
        return 0