import gradio as gr
import os

# PersistDataset -----
import os
import csv
import gradio as gr
from gradio import inputs, outputs
import huggingface_hub
from huggingface_hub import Repository, hf_hub_download, upload_file
from datetime import datetime

# created new dataset as awacke1/MindfulStory.csv
#DATASET_REPO_URL = "https://huggingface.co/datasets/awacke1/MindfulStory.csv"
#DATASET_REPO_ID = "awacke1/MindfulStory.csv"
#DATA_FILENAME = "MindfulStory.csv"
#DATA_FILE = os.path.join("data", DATA_FILENAME)
HF_TOKEN = os.environ.get("HF_TOKEN")

# Download dataset repo using hub download
#try:
#    hf_hub_download(
#        repo_id=DATASET_REPO_ID,
#        filename=DATA_FILENAME,
#        cache_dir=DATA_DIRNAME,
#        force_filename=DATA_FILENAME
#    )
#except:
#    print("file not found")
    
#def AIMemory(title: str, story: str):
#    if title and story:
#        with open(DATA_FILE, "a") as csvfile:
#            writer = csv.DictWriter(csvfile, fieldnames=["title", "story", "time"])
#            writer.writerow({"title": title, "story": story, "time": str(datetime.now())})
        # uncomment line below to begin saving your changes
        #commit_url = repo.push_to_hub()
#    return ""


# Set up cloned dataset from repo for operations
#repo = Repository(
#    local_dir="data", clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN
#)

#generator1 = gr.Interface.load("bigscience/bloom", api_key=HF_TOKEN)


generator1 = gr.Interface.load("huggingface/gpt2-large", api_key=HF_TOKEN)
generator2 = gr.Interface.load("huggingface/EleutherAI/gpt-neo-2.7B", api_key=HF_TOKEN)
generator3 = gr.Interface.load("huggingface/EleutherAI/gpt-j-6B", api_key=HF_TOKEN)


def calculator(intro, operator, outro):
    if operator == "add":
        output = generator2(intro) + generator3(outro)
        title = intro + " " + outro
#        saved = AIMemory(title, output)
        return output
    elif operator == "subtract":
        output = generator2(outro) + generator3(intro)
        title = outro + " " + intro
#        saved = AIMemory(title, output)
        output = output.replace(intro, "").replace(outro, "")
        return output
    elif operator == "multiply":
        output = generator1(intro) + generator2(outro) + generator3(intro)
        title = intro + " " + outro + " " + intro
#        saved = AIMemory(title, output)
        return output
    elif operator == "divide":
        output = generator1(outro) + generator2(intro) + generator3(outro)
        title = outro + " " + intro + " " + outro
#        saved = AIMemory(title, output)
        output = output.replace(intro, "").replace(outro, "")
        return output

#with open('Mindfulness.txt', 'r') as file:
#    context = file.read()
#contextBox = gr.Textbox(lines=3, default=context, label="Story starter")

examples = [
    ["Asynchronous Telemedicine", "multiply", "Provide remote care services live addressing provider shortages"],
    ["Ambient and emotion AI", "multiply", "rtificial intelligence showing empathy and compassion, reducing biases making us feel cared for and assist lifestyle"],
    ["import gradio as gr", "multiply", "import streamlit as st"],
    ["Skin Patch", "multiply", "Allow technology to measure blood pressure, glucose, reducing huge bulky devices"],
    ["Affordable vein scanner", "multiply", "View veins through skin"],
    ["Synthetic medical records", "multiply", "Create synthetic medical records using GANS trained to create synthetic data"],
    ["Blood draw devices used in clinical trials", "multiply", "So you dont have to go to physical location, engagement during trials"],
    ["Smart TVs being used for remote care", "multiply", "Video chat and recordings for remote care consultations"],
    ["Why does a chicken coop have two doors?  Because if had four doors it would be a chicken sedan!", "multiply", "Why did the chicken cross the park?  To get to the other slide."],
    ["What type of shoes do ninjas wear?  Sneakers", "add", "Can a ninja bring a ninja star into the airport?  Shuriken."],
    ["To save the planet with good looks and comedy find your", "multiply", "Everybody laughed at me when I told them I was going to be a comedian. I thought well, thats not bad for a start."]
]

demo = gr.Interface(
    calculator,
    [
        "text",
        gr.Radio(["add", "subtract", "multiply", "divide"]),
        "text"
    ],
    "text",
    examples=examples,
    article="Saved story memory dataset: https://huggingface.co/datasets/awacke1/MindfulStory.csv with available models to use from text gen: https://huggingface.co/models?pipeline_tag=text-generation&sort=downloads",
    live=True,
)
demo.launch()