from groq import Groq 
import gradio as gr 
import os


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> 🕹️ Type your questions or prompts related to Ayurveda 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()