import cohere
import gradio as gr
import os
api_key=os.environ.get("api-key")
shade=os.environ.get("shade")
co = cohere.Client(api_key)
config=shade
zero = config
Counter = 0
Counters = ""
origin = ""
slash = ""
newprompt = ""



import random
from datetime import date

# specify the directory to save the file in

#Gradient Directory
directory = '/home/user/app/'

#Google Colab Directory
#directory = os.getcwd()

## generate a random number
rand_num = random.randint(1, 1000000)
# get the current date
today = date.today()
# format the date as a string
date_str = today.strftime("%Y-%m-%d")
# create the file name
file_name = f'conversation_{rand_num}_{date_str}.txt'
# create the full file path
file_path = os.path.join(directory, file_name)
# write some sample content to the file
#with open(file_path, 'w') as f:
#    f.write('Sample notes for the day')



count = 0
mood = "nice"
def AI(userdata):
    global directory
    global rand_num
    global today
    global date_str
    global file_name
    global file_path
    global count
    global co
    global config
    global zero
    global Counter
    global Counters
    global origin
    global slash
    global newprompt
    
    with open(file_path, 'a') as f:
      f.write('\nUser: '+userdata)
    
    zero = zero+"\nUser:"+userdata+"\nAnuska:"


    #response = co.generate(model='xlarge', prompt=zero, max_tokens=512, temperature = 0.7, p=0.6 , k = 20, frequency_penalty=0.58, stop_sequences=["\n"])
    # Try to generate a response
    #response = co.generate(model='xlarge', prompt=zero, max_tokens=512, temperature = 0.7, p=0.6 , k = 20, frequency_penalty=0.58, stop_sequences=["\n"])
    response = co.generate(model='xlarge', prompt=zero, max_tokens=512, temperature = 0.5, p=0.4 , k = 10, frequency_penalty=0.58, stop_sequences=["\n"])
    # check if response is empty
    if response=="":
        # rerun the query
        #response = co.generate(model='xlarge', prompt=zero, max_tokens=512, temperature = 0.7, p=0.6 , k = 20, frequency_penalty=0.58, stop_sequences=["\n"])
        response = co.generate(model='xlarge', prompt=zero, max_tokens=512, temperature = 0.5, p=0.4 , k = 10, frequency_penalty=0.58, stop_sequences=["\n"])
        
    
    one = format(response.generations[0].text)
    two = one.rsplit("\n")[0]
    if two=="":
      two = "Huh?"

    Counter = len(zero)
    Counters = str(Counter)
    if Counter > 2100:
      origin=config
      slash = zero[1500:]
      newprompt=origin+slash
      zero=newprompt

    zero=zero+two
    count = count + 1
    with open(file_path, 'a') as f:
      f.write('\nAnuska: '+two)
    return two

block = gr.Blocks()

with block:
    gr.Markdown("""
<h1><center>Aitrium AI Tech Demo: Anuska</center></h1>
<div style="display: flex;">
    <div style="flex: 1; text-align: center; background-color: #cccccc; padding: 10px; border-right: 5px solid white;">
      <strong>💬 Examples:</strong>
      <hr style="border-top: 5px solid white; margin: 0px;">
      <br><strong>You can talk to Anuska naturally:</strong>
      <br>"Hey Anuska!"
      <br>"Hello Anuska, how are you?"
      <br>"Anuska, what have you done today?"
      <br>"What have you been up to today?"
      <br>"What's new with you?"
    </div>
    <div style="flex: 1; text-align: center; background-color: #cccccc; padding: 10px; border-right: 5px solid white;">
      <strong>🤖 Capabilities:</strong>
      <hr style="border-top: 5px solid white; margin: 0px;">
      <br><strong>Anuska isn't like most chatbots:</strong>
      <br>Anuska remembers the conversation she is having.
      <br>She has her own personality, character and memory.
      <br>She is designed to be a companion.
      <br>She understands what she is saying.
      <br>She is capable of becoming disinterested.
    </div>
    <div style="flex: 1; text-align: center; background-color: #cccccc; padding: 10px;">
      <strong>⚠️ Limitations:</strong>
      <hr style="border-top: 5px solid white; margin: 0px;">
      <br><strong>Anuska, like other large language models may:</strong>
      <br>Sometimes give inaccurate information
      <br>Sometimes generate harmful or biased content
      <br>Generate inappropriate content
      <br>Sometimes hallucinate or generate information about herself
      <br>Her world knowledge may be limited or out of date.
    </div>
  </div>
""")





    #demo = gr.Interface(fn=AI, inputs="text", outputs="text")

    demo = gr.Interface(fn=AI, inputs="text", outputs="text",)
    gr.Markdown("""
<style>
  .disclaimer {
    background-color: yellow;
    color: black;
    padding: 10px;
    font-family: 'Roboto', sans-serif;
    text-align: center;
    font-size: 1em;
  }
</style>

<div class="disclaimer">
    <strong>Disclaimer:</strong><br>By using this web app, you understand and agree that all conversations within the app will be logged, monitored, and analyzed for the purposes of improving the service and ensuring compliance with legal and ethical guidelines. Any personal information collected will be kept confidential and used in accordance with our privacy policy.  Aitrium is not responsible for the content generated by this app. The app is powered by a language model and its outputs are based on the patterns and associations it has learned from the data it was trained on. Aitrium cannot guarantee the accuracy, completeness, or suitability of any information generated by Anuska.
</div>
""")

block.launch()