import gradio as gr
import os
import requests
import openai

def greet(modelpath1="",modelpath2="",modelpath3="",modelpath4="",modelpath5=""):
    names =  [modelpath1,modelpath2,modelpath3,modelpath4,modelpath5]
    names = [name for name in names if name != ""]
    if names == []:
        return "Please enter at least one model name."
    if len(names) < 2:
        return "Please enter at least 2 model names."
    urls = []
    for name in names:
        if name in ["meta-llama/Llama-2-7b-hf","meta-llama/Llama-2-13b-hf","meta-llama/Llama-2-70b-hf","meta-llama/Llama-2-7b-chat-hf","meta-llama/Llama-2-13b-chat-hf","meta-llama/Llama-2-70b-chat-hf","stabilityai/japanese-stablelm-instruct-alpha-7b"]:
            urls.append("https://huggingface.co/spaces/gojiteji/LLM-Comparer/raw/main/" + name + "/config.json")
        else:
            urls.append("https://huggingface.co/" + name + "/raw/main/config.json")
    
    configs = []
    index_to_ignore =[]
    for i in range(len(urls)):
        get_result = requests.get(urls[i])
        if get_result.status_code == 200:
            configs.append(get_result.json())
        else:
            configs.append("")
            index_to_ignore.append(i)
    if configs == []:
        return "Could not find any models. Please check the model name."
    
    gpt_input = ""
    gpt_input += os.environ["prompts"]+os.environ["prompts2"] +"\n\n"
    for i in range(len(names)):
        if i not in index_to_ignore:
            gpt_input += "modelname: " + names[i] + "\n" + " config file:" + str(configs[i]) + "\n\n"

    openai.api_key = os.environ["APIKEY"]

    respose = openai.ChatCompletion.create(
        model="gpt-3.5-turbo",
        messages=[
         {
             "role": "system",
             "content": gpt_input
         },
     ],
    )
    response_text = ""
    for i in index_to_ignore:
      response_text += "- **⚠️Config file inaccessible:** " + names[i] +"\n"

    table_text = respose["choices"][0]["message"]["content"] 
    # get the first | to the last |
    response_text += "\n"+table_text[table_text.find("|")+1:table_text.rfind("|")+1]



    return response_text

text1 = gr.inputs.Textbox(placeholder="ower/modelname1", label="Input modelname like meta-llama/Llama-2-70b-hf",lines=1,optional=False)
text2 = gr.inputs.Textbox(placeholder="ower/modelname2", label="model 2",lines=1,optional=False)
text3 = gr.inputs.Textbox(placeholder="ower/modelname3", label="model 3",lines=1,optional=True)
text4 = gr.inputs.Textbox(placeholder="ower/modelname4", label="model 4",lines=1,optional=True)

if __name__ == '__main__':
  interFace = gr.Interface(fn=greet,
                             inputs=[text1,text2,text3,text4],
                             outputs=[gr.Markdown(value="")],
                             title="LLM Comparer⚖️",
                             description="Plsease copy and paste the owner name / model name from the Hugging Face model hub.\n The same input can produce different results, so please resubmit if the results are not ideal.",
                             theme='finlaymacklon/smooth_slate',
                             allow_flagging=False,
                           )
                             
  interFace.launch(share=False,enable_queue=False)