from llama_index import VectorStoreIndex, SimpleDirectoryReader, ServiceContext
from llama_index.vector_stores import PineconeVectorStore
from llama_index.storage.storage_context import StorageContext
import pinecone
import logging
import sys
import os
import openai
from pymongo.mongo_client import MongoClient
from datetime import datetime

logging.basicConfig(stream=sys.stdout, level=logging.INFO)
logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout))


pinecone_key = os.environ['PINECONE_KEY']
mongo_key=os.environ["MONGO_KEY"]

def add_file(collection,username, filename):
    document = {
        "brain": username,
        "filename": filename,
        "namespace":None
        "timestamp": datetime.utcnow()
    }
    collection.insert_one(document)


def delete_file(collection,username, filename):
    query = {
        "brain": username,
        "filename": filename
    }
    collection.delete_one(query)

def updateBrain(brainName, files):
    print(len(files))
    print("Updating brain")
    print(brainName)
    
    pinecone.init(api_key=pinecone_key,
                  environment="us-west4-gcp")
   
    documents = []
    corrupt = []
    newfiles = []


    i = 0
    for file in files:
        loader = SimpleDirectoryReader(input_files=[file.name])
        try:
            document1 = loader.load_data()
            for doc in document1:
                doc.doc_id=os.path.basename(file.name)
                doc.extra_info={"filename":os.path.basename(file.name)}
                documents.append(doc)
            newfiles.append(os.path.basename(file.name))
        except Exception as e:
            print(e)
            if (str(e) == "Cannot read an empty file"):
                return "Please Wait! Files are uploading, Try again Later!"
            corrupt.append(os.path.basename(file.name))
        i = i+1
        print(i)

    pindex = pinecone.Index(brainName)

    try:
        print(pindex.describe_index_stats())
    except Exception as e:
        print(e)

    vector_store = PineconeVectorStore(pinecone_index=pindex)
    storage_context = StorageContext.from_defaults(vector_store=vector_store)
    service_context = ServiceContext.from_defaults(chunk_size=512,chunk_overlap=20)
    index = VectorStoreIndex.from_documents([], storage_context=storage_context,service_context=service_context)

    client = MongoClient(mongo_key)
    db = client['nbrain']
    collection = db['files']

    for prevfile in newfiles:
        index.delete_ref_doc(prevfile, delete_from_docstore=True)
        delete_file(collection,brainName,prevfile)

    uploadedFiles=[]
    j = 1
    for doc in documents:
        try:
            index.insert(doc)
            if doc.doc_id not in uploadedFiles:
                print(doc.doc_id)
                add_file(collection,brainName,doc.doc_id)
                uploadedFiles.append(doc.doc_id)
                print(j)
                j = j+1
        except Exception as e:
            if doc.doc_id not in corrupt:
                corrupt.append(doc.doc_id)
            print("ERROR : "+str(e))


    print("Brain Updated")
    try:
        print(pindex.describe_index_stats())
    except Exception as e:
        print(e)

    print(corrupt)

    if (len(corrupt) > 0):
        return """Brain Updated! 
        Below files are corrupt/unformatted, and not added to the brain.
         """ + str(corrupt)

    return brainName+" Brain Updated!"