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######################################################################################### | |
# Title: Gradio Interface to LLM-chatbot with on premises | |
# Author: Andreas Fischer | |
# Date: October 15th, 2023 | |
# Last update: January 21st, 2024 | |
########################################################################################## | |
#https://github.com/abetlen/llama-cpp-python/issues/306 | |
#sudo apt install libclblast-dev | |
#CMAKE_ARGS="-DLLAMA_CLBLAST=on" FORCE_CMAKE=1 pip install llama-cpp-python --force-reinstall --upgrade --no-cache-dir -v | |
# Get model | |
#----------- | |
import os | |
import requests | |
##modelPath="/home/af/gguf/models/phi-2.Q4_0.gguf" | |
#modelPath="/home/af/gguf/models/openchat-3.5-0106.Q4_0.gguf" | |
modelPath="/home/af/gguf/models/SauerkrautLM-7b-HerO-q8_0.gguf" | |
#modelPath="/home/af/gguf/models/sauerkrautlm-una-solar-instruct.Q4_0.gguf" | |
#modelPath="/home/af/gguf/models/decilm-7b-uniform-gqa-q8_0.gguf" | |
#modelPath="/home/af/gguf/models/mixtral-8x7b-instruct-v0.1.Q4_0.gguf" | |
if(os.path.exists(modelPath)==False): | |
#url="https://huggingface.co/TheBloke/WizardLM-13B-V1.2-GGUF/resolve/main/wizardlm-13b-v1.2.Q4_0.gguf" | |
#url="https://huggingface.co/TheBloke/Mixtral-8x7B-Instruct-v0.1-GGUF/resolve/main/mixtral-8x7b-instruct-v0.1.Q4_0.gguf?download=true" | |
url="https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.2-GGUF/resolve/main/mistral-7b-instruct-v0.2.Q4_0.gguf?download=true" | |
response = requests.get(url) | |
with open("./model.gguf", mode="wb") as file: | |
file.write(response.content) | |
print("Model downloaded") | |
modelPath="./model.gguf" | |
print(modelPath) | |
# Llama-cpp-Server | |
#------------------ | |
import subprocess | |
command = ["python3", "-m", "llama_cpp.server", "--model", modelPath, "--host", "0.0.0.0", "--port", "2600", "--n_threads", "4", "--n_gpu_layers","20"] | |
subprocess.Popen(command) | |
print("Server ready!") | |
# Gradio-GUI | |
#------------ | |
import gradio as gr | |
import requests | |
import json | |
def response(message, history): | |
prompt=message | |
system="Du bist ein KI-basiertes Assistenzsystem." | |
if("mixtral-8x7b-instruct" in modelPath): | |
prompt=f"[INST] {prompt} [/INST]" | |
if("Mistral-7B-Instruct" in modelPath): | |
prompt=f"[INST] {prompt} [/INST]" | |
if("openchat-3.5" in modelPath): | |
prompt=f"GPT4 Correct User: {system} {prompt}<|end_of_turn|>GPT4 Correct Assistant:" | |
if("SauerkrautLM-7b-HerO" in modelPath): | |
prompt=f"<|im_start|>system\n{system}<|im_end|>\n<|im_start|>user\n{prompt}<|im_end|>\n<|im_start|>assistant\n" | |
if("WizardLM-13B-V1.2" in modelPath): | |
prompt=f"{system} USER: {prompt} ASSISTANT: " | |
if("phi-2" in modelPath): | |
prompt=f"Instruct: {prompt}\nOutput:" | |
print(prompt) | |
#url="https://afischer1985-wizardlm-13b-v1-2-q4-0-gguf.hf.space/v1/completions" | |
url="http://0.0.0.0:2600/v1/completions" | |
body={"prompt":prompt,"max_tokens":1000, "echo":"False","stream":"True"} #e.g. Mixtral-Instruct | |
response="" | |
buffer="" | |
print("URL: "+url) | |
print("User: "+message+"\nAI: ") | |
for text in requests.post(url, json=body, stream=True): #-H 'accept: application/json' -H 'Content-Type: application/json' | |
if buffer is None: buffer="" | |
buffer=str("".join(buffer)) | |
#print("*** Raw String: "+str(text)+"\n***\n") | |
text=text.decode('utf-8') | |
if((text.startswith(": ping -")==False) & (len(text.strip("\n\r"))>0)): buffer=buffer+str(text) | |
#print("\n*** Buffer: "+str(buffer)+"\n***\n") | |
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="" # reset buffer | |
except Exception as e: | |
print("Exception:"+str(e)) | |
pass | |
yield response | |
gr.ChatInterface(response, chatbot=gr.Chatbot(render_markdown=True),title="AI-Interface").queue().launch(share=True) #False, server_name="0.0.0.0", server_port=7864) | |
print("Interface up and running!") | |