import os
import gspread
from oauth2client.service_account import ServiceAccountCredentials
from pymongo import MongoClient

# Read the authentication token from the environment variable
hugging_face_token = os.getenv("HUGGING_FACE_TOKEN")
replicate_token = os.getenv("REPLICATE_TOKEN")
groq_token = os.getenv("GROQ_TOKEN")
atlas_token = os.getenv("ATLAS_TOKEN")
open_ruter_token = os.getenv("OPEN_RUTER_TOKEN")

#atlas configuration
class AtlasClient:
    def __init__(self, dbname):
        self.mongodb_client = MongoClient(atlas_token)
        self.database = self.mongodb_client[dbname]

    # A quick way to test if we can connect to Atlas instance
    def ping(self):
        self.mongodb_client.admin.command("ping")


    def add(self, item, collection_name):
        collection = self.database[collection_name]
        collection.insert_one(item)

# Google Sheets configuration
def init_google_sheets_client():
    scope = ["https://spreadsheets.google.com/feeds", "https://www.googleapis.com/auth/drive"]
    creds = ServiceAccountCredentials.from_json_keyfile_name('tokyo-portal-326513-90aee094bab9.json', scope)
    return gspread.authorize(creds)

# Google Sheets name
google_sheets_name = "Chatbot Test"

# Define available models
huggingface_tokenizer = {
    "Meta-Llama-3-8B-Instruct": "meta-llama/Meta-Llama-3-8B-Instruct",
    "Llama-2-7B-Chat": "meta-llama/Llama-2-7b-chat-hf",
    "mistralai/mistral-7b-instruct-v0.2": "mistralai/Mistral-7B-Instruct-v0.2",
    "Meta-Llama-3-70B-Instruct":"meta-llama/Meta-Llama-3-70B-Instruct",
}

#Avaiable models for replicate
replicate_model= {
    "Meta-Llama-3-8B-Instruct": "meta/meta-llama-3-8b-instruct",
    "Llama-2-7B-Chat": "meta/llama-2-7b-chat",
    "mistralai/mistral-7b-instruct-v0.2": "mistralai/mistral-7b-instruct-v0.2",
    "Meta-Llama-3-70B-Instruct":"meta/meta-llama-3-70b-instruct",
}

groq_model = {
    "llama3-8b-8192": "llama3-8b-8192",
    "llama-guard-3-8b": "llama-guard-3-8b",
    "gemma-7b-it": "gemma-7b-it",
    "llama3-70b-8192": "llama3-70b-8192",
}

custom_model = {
    "rodrisouza/Llama-3-8B-Finetuning-Stories":  "rodrisouza/Llama-3-8B-Finetuning-Stories"
}

openai_model = {
    "meta-llama/llama-3.1-70b-instruct:free": "meta-llama/llama-3.1-70b-instruct:free",
    "meta-llama/llama-3.1-8b-instruct:free": "meta-llama/llama-3.1-8b-instruct:free",
    "mistralai/mistral-7b-instruct:free": "mistralai/mistral-7b-instruct:free",
    "google/gemma-2-9b-it:free": "google/gemma-2-9b-it:free",
}


# Default model (first in list)
default_model_name = list(replicate_model.items())[0][0]


# Define available user names
user_names = ["Laura Musto", "Brian Carpenter", "Germán Capdehourat", "Isabel Amigo", "Aiala Rosá", "Luis Chiruzzo", "Ignacio Sastre", "Santiago Góngora", "Ignacio Remersaro", "Rodrigo Souza"]

MAX_INTERACTIONS = 5 
QUESTION_PROMPT = "Please ask a simple question about the story to encourage interaction."