main.py

import logging
import os
import time
import openai
from plexapi.server import PlexServer
from utils.classes import UserInputs

userInputs = UserInputs(
    plex_url=os.getenv("PLEX_URL"),
    plex_token=os.getenv("PLEX_TOKEN"),
    openai_key=os.getenv("OPEN_AI_KEY"),
    openai_version=os.getenv("OPEN_AI_VERSION"),
    library_name=os.getenv("LIBRARY_NAME"),
    collection_title=os.getenv("COLLECTION_TITLE"),
    history_amount=int(os.getenv("HISTORY_AMOUNT")),
    recommended_amount=int(os.getenv("RECOMMENDED_AMOUNT")),
    minimum_amount=int(os.getenv("MINIMUM_AMOUNT")),
    wait_seconds=int(os.getenv("SECONDS_TO_WAIT", 432000)),
)

logger = logging.getLogger()
logging.basicConfig(level=logging.INFO)

openai.api_key = userInputs.openai_key

def create_collection(plex, movie_items, description, library):
    logging.info("Finding matching movies in your library...")
    movie_list = []
    for item in movie_items:
        movie_search = plex.search(item, mediatype="movie", limit=3)
        if len(movie_search) > 0:
            movie_list.append(movie_search[0])
            logging.info(item + " - found")
        else:
            logging.info(item + " - not found")

    if len(movie_list) > userInputs.minimum_amount:
        try:
            collection = library.collection(userInputs.collection_title)
            collection.removeItems(collection.items())
            collection.addItems(movie_list)
            collection.editSummary(description)
            logging.info("Updated pre-existing collection")
        except:
            collection = plex.createCollection(
                title=userInputs.collection_title,
                section=userInputs.library_name,
                items=movie_list
            )
            collection.editSummary(description)
            logging.info("Added new collection")
    else:
        logging.info("Not enough movies were found")

def run():
    # Connect
    while True:
        logger.info("Starting collection run")
        try:
            plex = PlexServer(userInputs.plex_url, userInputs.plex_token)
            logging.info("Connected to Plex server")
        except Exception as e:
            logging.error("Plex Authorization error")
            return

        try:
            # Find history items for the library
            library = plex.library.section(userInputs.library_name)
            account_id = plex.systemAccounts()[1].accountID

            # a = library.hubs()

            items_string = ""
            history_items_titles = []
            watch_history_items = plex.history(librarySectionID=library.key, maxresults=userInputs.history_amount, accountID=account_id)
            logging.info("Fetching items from your watch history")

            for history_item in watch_history_items:
                history_items_titles.append(history_item.title)

            items_string = ", ".join(history_items_titles)
            logging.info("Found " + items_string + " to base recommendations off")

        except Exception as e:
            logging.error("Failed to get watched items")
            return

        try:
            query = "Can you give me movie recommendations based on what I've watched? "
            query += "I've watched " + items_string + ". "
            query += "Can you base your recommendations solely on what I've watched already. "
            query += "I need around " + str(userInputs.recommended_amount) + ". "
            query += "Please give me the comma separated result, and then a short explanation separated from the movie values, separated by 3 pluses like '+++'."
            query += "Not a numbered list. "

            # create a chat completion
            logging.info("Querying openai for recommendations...")
            chat_completion = openai.ChatCompletion.create(model=openai_version, messages=[{"role": "user", "content": query}])
            ai_result = chat_completion.choices[0].message.content
            ai_result_split = ai_result.split("+++")
            ai_movie_recommendations = ai_result_split[0]
            ai_movie_description = ai_result_split[1]

            movie_items = list(filter(None,  ai_movie_recommendations.split(",")))
            logging.info("Query success!")
        except:
            logging.error('Was unable to query openai')
            return

        if len(movie_items) > 0:
            create_collection(plex, movie_items, ai_movie_description, library)

        logging.info("Waiting on next call...")
        time.sleep(userInputs.wait_seconds)

if __name__ == '__main__':
    run()