import os

from groq import Groq 
import gradio as gr 


client = Groq(
    api_key =os.getenv('api_key_gorq')
)
def response_from_llam3(query):
  messages = [
          {
          "role" : "system",
          "content": "You are an helpul Assistant who has plently of Knowledge on Ayur Veda. If the message is Hi or any greeting say namste how can i assist you "
          },
        { 
          "role": "user",
          "content": "What is the answer to {}".format(query)
          }
      ]
    
  response = client.chat.completions.create(
      messages = messages,
      model = "llama3-70b-8192"

  )
  return response.choices[0].message.content

def response_from_mistral(query):
  messages = [
          {
          "role" : "system",
          "content": "You are an helpul Assistant who has plently of Knowledge on Ayur Veda. If the message is Hi or any greeting say namste how can i assist you "
          },
        { 
          "role": "user",
          "content": "What is the answer to {}".format(query)
          }
      ]
    
  response = client.chat.completions.create(
      messages = messages,
      model = "mixtral-8x7b-32768"

  )
  return response.choices[0].message.content  
# iface = gr.Interface(

#     fn=response_from_llam3,
#     inputs="text",
#     outputs="text",
#        examples=[
#             ['What is importance of fasting according to Ayurveda?'],
#             ['What are the medicinal values of Tusli?'],
#             ['What are the three different doshas?'],
#             ['What is the ideal diet according to ayurveda?']
#             ],
#         cache_examples=False,
#     )
# iface.launch()

def chat_with_models(text):
    llama_response = response_from_llam3(text)
    mistral_response =response_from_mistral(text)
    
    return llama_response, mistral_response


with gr.Blocks() as demo:
    gr.Markdown("<h1>🚀 Mistral 7B vs LLama3 8B 🦙</h1>")
    gr.Markdown("<h3> 🕹️ Compare the performance and responses of two powerful models, Mistral 7B and LLama3 8B instruct. Type your questions or prompts below and see how each model responds to the same input 👾 </h3>")
    with gr.Row():
        input_text = gr.Textbox(label="Enter your prompt here:", placeholder="Type something...", lines=2)
        submit_button = gr.Button("Submit")
    output_llama = gr.Textbox(label="Llama 3 8B 👾", placeholder="", lines=10, interactive=False)
    output_mistral = gr.Textbox(label="Mistral 7B 🌠", placeholder="", lines=10, interactive=False)
    examples=[
            ['What is importance of fasting according to Ayurveda?'],
            ['What are the medicinal values of Tusli?'],
            ['What are the three different doshas?'],
            ['What is the ideal diet according to ayurveda?']
            ],
    
    submit_button.click(fn=chat_with_models, inputs=input_text, outputs=[output_llama, output_mistral])

if __name__ == "__main__":
    demo.launch()