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import gradio as gr | |
from llama_cpp import Llama | |
import datetime | |
import os | |
from huggingface_hub import hf_hub_download | |
#MODEL SETTINGS also for DISPLAY | |
convHistory = '' | |
modelfile = hf_hub_download( | |
repo_id=os.environ.get("REPO_ID", "TheBloke/stablelm-zephyr-3b-GGUF"), | |
filename=os.environ.get("MODEL_FILE", "stablelm-zephyr-3b.Q4_K_M.gguf"), | |
) | |
repetitionpenalty = 1.15 | |
contextlength=4096 | |
logfile = 'StableZephyr3b_logs.txt' | |
print("loading model...") | |
stt = datetime.datetime.now() | |
# Set gpu_layers to the number of layers to offload to GPU. Set to 0 if no GPU acceleration is available on your system. | |
llm = Llama( | |
model_path=modelfile, # Download the model file first | |
n_ctx=contextlength, # The max sequence length to use - note that longer sequence lengths require much more resources | |
#n_threads=2, # The number of CPU threads to use, tailor to your system and the resulting performance | |
) | |
dt = datetime.datetime.now() - stt | |
print(f"Model loaded in {dt}") | |
def writehistory(text): | |
with open(logfile, 'a') as f: | |
f.write(text) | |
f.write('\n') | |
f.close() | |
""" | |
gr.themes.Base() | |
gr.themes.Default() | |
gr.themes.Glass() | |
gr.themes.Monochrome() | |
gr.themes.Soft() | |
""" | |
def combine(a, b, c, d,e,f): | |
global convHistory | |
import datetime | |
SYSTEM_PROMPT = f"""{a} | |
""" | |
temperature = c | |
max_new_tokens = d | |
repeat_penalty = f | |
top_p = e | |
prompt = f"<|user|>\n{b}<|endoftext|>\n<|assistant|>" | |
start = datetime.datetime.now() | |
generation = "" | |
delta = "" | |
prompt_tokens = f"Prompt Tokens: {len(llm.tokenize(bytes(prompt,encoding='utf-8')))}" | |
generated_text = "" | |
answer_tokens = '' | |
total_tokens = '' | |
for character in llm(prompt, | |
max_tokens=max_new_tokens, | |
stop=["</s>"], | |
temperature = temperature, | |
repeat_penalty = repeat_penalty, | |
top_p = top_p, # Example stop token - not necessarily correct for this specific model! Please check before using. | |
echo=False, | |
stream=True): | |
generation += character["choices"][0]["text"] | |
answer_tokens = f"Out Tkns: {len(llm.tokenize(bytes(generation,encoding='utf-8')))}" | |
total_tokens = f"Total Tkns: {len(llm.tokenize(bytes(prompt,encoding='utf-8'))) + len(llm.tokenize(bytes(generation,encoding='utf-8')))}" | |
delta = datetime.datetime.now() - start | |
yield generation, delta, prompt_tokens, answer_tokens, total_tokens | |
timestamp = datetime.datetime.now() | |
logger = f"""time: {timestamp}\n Temp: {temperature} - MaxNewTokens: {max_new_tokens} - RepPenalty: 1.5 \nPROMPT: \n{prompt}\nStableZephyr3B: {generation}\nGenerated in {delta}\nPromptTokens: {prompt_tokens} Output Tokens: {answer_tokens} Total Tokens: {total_tokens}\n\n---\n\n""" | |
writehistory(logger) | |
convHistory = convHistory + prompt + "\n" + generation + "\n" | |
print(convHistory) | |
return generation, delta, prompt_tokens, answer_tokens, total_tokens | |
#return generation, delta | |
# MAIN GRADIO INTERFACE | |
with gr.Blocks(theme='Medguy/base2') as demo: #theme=gr.themes.Glass() #theme='remilia/Ghostly' | |
#TITLE SECTION | |
with gr.Row(variant='compact'): | |
with gr.Column(scale=3): | |
gr.Image(value='https://github.com/fabiomatricardi/StableLM-Zephyr3B_Playground/raw/main/logo-banner-StableZephyr.jpg', | |
show_label = False, | |
show_download_button = False, container = False) | |
with gr.Column(scale=10): | |
gr.HTML("<center>" | |
+ "<h3>Prompt Engineering Playground!</h3>" | |
+ "<h1>ππ¦ StableLM-Zephyr-3B - 4K context window</h2></center>") | |
with gr.Row(): | |
with gr.Column(min_width=80): | |
gentime = gr.Textbox(value="", placeholder="Generation Time:", min_width=50, show_label=False) | |
with gr.Column(min_width=80): | |
prompttokens = gr.Textbox(value="", placeholder="Prompt Tkn:", min_width=50, show_label=False) | |
with gr.Column(min_width=80): | |
outputokens = gr.Textbox(value="", placeholder="Output Tkn:", min_width=50, show_label=False) | |
with gr.Column(min_width=80): | |
totaltokens = gr.Textbox(value="", placeholder="Total Tokens:", min_width=50, show_label=False) | |
# INTERACTIVE INFOGRAPHIC SECTION | |
# PLAYGROUND INTERFACE SECTION | |
with gr.Row(): | |
with gr.Column(scale=1): | |
gr.Markdown( | |
f""" | |
### Tunning Parameters""") | |
temp = gr.Slider(label="Temperature",minimum=0.0, maximum=1.0, step=0.01, value=0.42) | |
top_p = gr.Slider(label="Top_P",minimum=0.0, maximum=1.0, step=0.01, value=0.8) | |
repPen = gr.Slider(label="Repetition Penalty",minimum=0.0, maximum=4.0, step=0.01, value=1.2) | |
max_len = gr.Slider(label="Maximum output lenght", minimum=10,maximum=(contextlength-500),step=2, value=900) | |
gr.Markdown( | |
""" | |
Fill the System Prompt and User Prompt | |
And then click the Button below | |
""") | |
btn = gr.Button(value="ππ¦ Generate", variant='primary') | |
gr.Markdown( | |
f""" | |
- **Prompt Template**: StableLM-Zephyr ππ¦ | |
- **Repetition Penalty**: {repetitionpenalty} | |
- **Context Lenght**: {contextlength} tokens | |
- **LLM Engine**: llama-cpp | |
- **Model**: ππ¦ StableLM-Zephyr-7b | |
- **Log File**: {logfile} | |
""") | |
with gr.Column(scale=4): | |
txt = gr.Textbox(label="System Prompt", value = "", placeholder = "This models does not have any System prompt...",lines=1, interactive = False) | |
txt_2 = gr.Textbox(label="User Prompt", lines=6, show_copy_button=True) | |
txt_3 = gr.Textbox(value="", label="Output", lines = 12, show_copy_button=True) | |
btn.click(combine, inputs=[txt, txt_2,temp,max_len,top_p,repPen], outputs=[txt_3,gentime,prompttokens,outputokens,totaltokens]) | |
if __name__ == "__main__": | |
demo.launch(inbrowser=True) |