import streamlit as st
import pandas as pd
from huggingface_hub import Repository
import os 
from pathlib import Path
import json
import numpy as np

 
# Declaring the variables for later use to talk to dataset

# the token is saved as secret key-value pair in the environment which can be access as shown below
auth_token = os.environ.get("space_to_dataset") or True

DATASET_REPO_URL = 'ppsingh/annotation_data'   # path to dataset repo
DATA_FILENAME = "paralist.json"
DATA_FILE = os.path.join("data", DATA_FILENAME)

# cloning the dataset repo
repo = Repository( local_dir="data", clone_from=DATASET_REPO_URL, repo_type="dataset", use_auth_token= auth_token)

# Data file name
file_name = 'paralist.json'

# reading the json
with open('data/{}'.format(file_name), 'r', encoding="utf8") as json_file:
  paraList = json.load(json_file)

# getting outer level keys in json  
keys = paraList.keys()              
#data = pd.read_csv("test.csv")

# sidebar with info and drop down to select from the keys
st.sidebar.markdown(
    """
# Data Annotation Demo 
This app is demo how to use the space to provide user interface for the data annotation/tagging. The data resides in repo_type 'dataset'.
"""
)
topic = None
if keys is not None:
  topic = st.sidebar.selectbox(
    label="Choose dataset topic to load", options=keys )
#  st.write(line)
st.write(paraList)
if topic is not None:
  c1, c2, c3 = st.columns([3, 1, 1])
  subtopics = list(paraList[topic].keys())
  #st.write(subtopics)
  val = np.random.randint(0,len(subtopics))
  choice = subtopics[val]
  #st.write(choice)
  #if np.random.randint(0,1) == 0:
  #  choice = "Gender"
  #else:
  #  choice = "Women Empowernment"
  
  idx = np.random.randint(0,3)
  
  with c1:
    st.header('Text')
    st.write(paraList[topic][choice][idx]['textsegment'])
  
  with c2:
    st.header('Tag')
    st.text(choice)
  
  with c3:
    st.header('Feedback')
    feedback = None
    feedback = st.selectbox('0 If Tag is not a good keyword for text, 5 for prefect match',(0,1,2,3,4,5)) 
            
# title = st.text_input('Movie title', 'Life of Brian')
if st.button('Submit'):
    if feedback is not None:
      paraList[topic][choice][idx]['annotation'].append(feedback)
      with open('data/{}'.format(file_name), 'r', encoding="utf8") as json_file:
        json.dump(paraList,json_file, ensure_ascii = True)
        repo.push_to_hub('added new annotation')
        
      
    #new_row  = title
#  data = data.append(new_row, ignore_index=True)
#  st.write(data)
#  st.write(os.getcwd())
#  data.to_csv('test.csv', index= False)


#st.write(df)
#   st.write('data/test.csv')
# iterate over files in
# that directory        
#directory = os.getcwd()
#files = Path(directory).glob('*')
#for file in files:
#    st.write(file)

#with open(DATA_FILE, "a") as csvfile:
#  writer = csv.DictWriter(csvfile, fieldnames=["Sentences"])
#  writer.writerow({'Sentences': new_row})
#  repo.push_to_hub('adding new line')
#  st.write('Succcess')