run.py

#############################################################################
# Title:  Gradio Interface to AI hosted on Huggingface-Space
# Author: Andreas Fischer
# Date:   October 7th, 2023
# Last update: December 8th, 2023
#############################################################################

import gradio as gr
import requests
import random
import json

def specifications(message, model,prompt_type,verbose=False):
  url="http://0.0.0.0:2600/v1/completions"  
  body=""
  
  if(model=="Local"): 
    url="http://0.0.0.0:2600/v1/completions"  
    if(prompt_type=="Default"): prompt_type="ChatML (German)"
  if(model=="SauerkrautLM-7B"): 
    url="https://SauerkrautLM-GGUF-API.hf.space/v1/completions"  
    if(prompt_type=="Default"): prompt_type="Vicuna (German)"
  if(model=="WizardLM-13B"): 
    url="https://afischer1985-wizardlm-13b-v1-2-q4-0-gguf.hf.space/v1/completions"       
    if(prompt_type=="Default"): prompt_type="Vicuna"
  if(model=="OpenHermes2-7B"): 
    url="https://AFischer1985-OpenHermes-2-GGUF-API.hf.space/v1/completions"
    if(prompt_type=="Default"): prompt_type="ChatML"
  if(model=="CollectiveCognition-7B"): 
    url="https://AFischer1985-CollectiveCognition-GGUF-API.hf.space/v1/completions"  
    if(prompt_type=="Default"): prompt_type="ChatML" 
  
  if(prompt_type=="ChatML"):
    body={"prompt":"<|im_start|>system\nYou are a helpful AI-Assistant.<|im_end|>\n<|im_start|>user\n"+message+"<|im_end|>\n<|im_start|>assistant\n","max_tokens":1000,"stop":"<|im_end|>","echo":"False","stream":True}
  if(prompt_type=="ChatML (German)"):
    body={"prompt":"<|im_start|>system\nu bist ein großes Sprachmodell, das höflich und kompetent antwortet. Schreibe deine Gedanken Schritt für Schritt auf, um Probleme sinnvoll zu lösen.<|im_end|>\n<|im_start|>user\n"+message+"<|im_end|>\n<|im_start|>assistant\n","max_tokens":1000,"stop":"User:","echo":"False","stream":True}
  if(prompt_type=="Alpaca"):
    body={"prompt":"###Instruction:\n"+message+"\n\n###Response:\n","max_tokens":1000,"stop":"###","echo":"False","stream":True}
  if(prompt_type=="Vicuna"):
    body={"prompt":"A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: "+message+" ASSISTANT:","max_tokens":1000,"stop":"USER:","echo":"False","stream":"True"}
  if(prompt_type=="Vicuna (German)"):
    body={"prompt":"Ein Chat zwischen einem Benutzer und einem KI-Assistenten. Der KI-Assistent gibt hilfreiche, detaillierte und höfliche Antworten.\nUser: "+message+"\nAssistant: ","max_tokens":1000,"stop":"User:","echo":"False","stream":True}
  if(verbose==True):
    print("model: "+model+"\n"+"URL: "+url+"\n"+"prompt_type: "+prompt_type+"\n"+"message: "+message+"\n"+"body: "+str(body)+"\n")
  return([url,body,model,prompt_type])

def response(message, history, model, prompt_type):
  print(model)
  [url,body,model,prompt_type]=specifications(message,model,prompt_type,verbose=True)
  response=""
  buffer=""
  print("URL: "+url)
  print("User: "+message+"\nAI: ")
  for text in requests.post(url, json=body, stream=True):  
    text=text.decode('utf-8')
    if(text.startswith(": ping -")==False):buffer=str(buffer)+str(text)
    buffer=buffer.split('"finish_reason": null}]}')
    if(len(buffer)==1):
      buffer="".join(buffer)
      pass
    if(len(buffer)==2):
      part=buffer[0]+'"finish_reason": null}]}'  
      if(part.lstrip('\n\r').startswith("data: ")): part=part.lstrip('\n\r').replace("data: ", "")
      try: 
        part = str(json.loads(part)["choices"][0]["text"])
        print(part, end="", flush=True)
        response=response+part
        buffer="" 
      except:
        pass
    yield response 


gr.ChatInterface(response,additional_inputs=[gr.Dropdown(["Local","CollectiveCognition-7B", "OpenHermes2-7B","WizardLM-13B"],value="WizardLM-13B",label="Model"),gr.Dropdown(["Default", "ChatML","ChatML (German)","Vicuna","Vicuna (German)","Alpaca"],value="Default",label="Prompt Type")]).queue().launch(share=False, server_name="0.0.0.0", server_port=7864) 

#import os
#os.system('python3 -m llama_cpp.server --model "/home/af/gguf/models/SauerkrautLM-7b-HerO-q8_0.gguf" --host 0.0.0.0 --port 2600')