import gradio as gr
import runpod
import os
from dotenv import load_dotenv
load_dotenv()


runpod.api_key = os.getenv("RUNPOD_API_KEY")
endpoint_id = os.getenv("ENDPOINT_ID")

def format_prompt(message, history):
    messages = []
    
    messages.append({"role": "system", "content": "Du bist ein freundlicher, hilfsbereiter Chatbot, der gerne Fragen korrekt und präzise beantwortet."})
    for user_prompt, bot_response in history:
        messages.append({"role": "user", "content": user_prompt})
        messages.append({"role": "assistant", "content": bot_response})
    messages.append({"role": "user", "content": message})
    return messages
    
    
def generate(
        message: str, 
        history: list = [], 
        temperature=0.7,
        max_tokens=1024,
        top_p=0.95,
    ):
    
    formatted_messages = format_prompt(message, history)
        
    temperature = float(temperature)
    temperature = max(temperature, 1e-2) 
    top_p = float(top_p)
    top_k = 50  
    max_tokens = int(max_tokens)

    input_payload = {
        "input": {
            "messages": formatted_messages,
            "sampling_params": {
                "temperature": temperature,
                "top_p": top_p,
                "top_k": top_k,
                "max_tokens": max_tokens
            },
        }
    }

    try:
        endpoint = runpod.Endpoint(os.getenv("ENDPOINT_ID"))  
        run_request = endpoint.run(input_payload)
        stream_output = ''
        for output in run_request.stream():
            for t in output['choices'][0]['tokens']:
                stream_output += t.strip()
                yield stream_output
        #        print (t.strip())
        return stream_output
        
    
    except Exception as e:
        print(f"An error occurred: {e}")

additional_inputs=[
    gr.Slider(
        label="Temperature",
        value=0.7,
        minimum=0.0,
        maximum=1.0,
        step=0.05,
        interactive=True,
        info="Higher values produce more diverse outputs",
    ),
    gr.Slider(
        label="Max new tokens",
        value=1024,
        minimum=0,
        maximum=2048,
        step=64,
        interactive=True,
        info="The maximum numbers of new tokens",
    ),
    gr.Slider(
        label="Top-p (nucleus sampling)",
        value=0.95,
        minimum=0.0,
        maximum=1,
        step=0.05,
        interactive=True,
        info="Higher values sample more low-probability tokens",
    )
]

css = """
  #mkd {
    height: 750px; 
    overflow: auto; 
    border: 1px solid #ccc; 
  }
  
  #component-6 {
      height: 750px !important;
      }
"""

with gr.Blocks(css=css) as demo:
    
    gr.ChatInterface(
        generate,
        additional_inputs=additional_inputs,
        title="Demo Kafka-7B-DARE-TIES-QLoRa-LaserRMT-DPO",
        examples=[["Was ist der Sinn des Lebens?"], ["Was ist der Unterschied zwischen Quantenmechanik und Relativitätstheorie?"]]
    )

demo.queue().launch(max_threads=100, debug=True)