Spaces:
Runtime error
Runtime error
Create app.py
Browse files
app.py
ADDED
|
@@ -0,0 +1,142 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import gradio as gr
|
| 2 |
+
from llama_cpp import Llama
|
| 3 |
+
import datetime
|
| 4 |
+
import os
|
| 5 |
+
import datetime
|
| 6 |
+
from huggingface_hub import hf_hub_download
|
| 7 |
+
|
| 8 |
+
#MODEL SETTINGS also for DISPLAY
|
| 9 |
+
convHistory = ''
|
| 10 |
+
modelfile = hf_hub_download(
|
| 11 |
+
repo_id=os.environ.get("REPO_ID", "TheBloke/stablelm-zephyr-3b-GGUF"),
|
| 12 |
+
filename=os.environ.get("MODEL_FILE", "stablelm-zephyr-3b.Q4_K_M.gguf"),
|
| 13 |
+
)
|
| 14 |
+
repetitionpenalty = 1.15
|
| 15 |
+
contextlength=4096
|
| 16 |
+
logfile = 'StableZephyr3b_logs.txt'
|
| 17 |
+
print("loading model...")
|
| 18 |
+
stt = datetime.datetime.now()
|
| 19 |
+
# Set gpu_layers to the number of layers to offload to GPU. Set to 0 if no GPU acceleration is available on your system.
|
| 20 |
+
llm = Llama(
|
| 21 |
+
model_path=modelfile, # Download the model file first
|
| 22 |
+
n_ctx=contextlength, # The max sequence length to use - note that longer sequence lengths require much more resources
|
| 23 |
+
#n_threads=2, # The number of CPU threads to use, tailor to your system and the resulting performance
|
| 24 |
+
)
|
| 25 |
+
dt = datetime.datetime.now() - stt
|
| 26 |
+
print(f"Model loaded in {dt}")
|
| 27 |
+
|
| 28 |
+
def writehistory(text):
|
| 29 |
+
with open(logfile, 'a') as f:
|
| 30 |
+
f.write(text)
|
| 31 |
+
f.write('\n')
|
| 32 |
+
f.close()
|
| 33 |
+
|
| 34 |
+
"""
|
| 35 |
+
gr.themes.Base()
|
| 36 |
+
gr.themes.Default()
|
| 37 |
+
gr.themes.Glass()
|
| 38 |
+
gr.themes.Monochrome()
|
| 39 |
+
gr.themes.Soft()
|
| 40 |
+
"""
|
| 41 |
+
def combine(a, b, c, d,e,f):
|
| 42 |
+
global convHistory
|
| 43 |
+
import datetime
|
| 44 |
+
SYSTEM_PROMPT = f"""{a}
|
| 45 |
+
|
| 46 |
+
|
| 47 |
+
"""
|
| 48 |
+
temperature = c
|
| 49 |
+
max_new_tokens = d
|
| 50 |
+
repeat_penalty = f
|
| 51 |
+
top_p = e
|
| 52 |
+
prompt = f"<|user|>\n{b}<|endoftext|>\n<|assistant|>"
|
| 53 |
+
start = datetime.datetime.now()
|
| 54 |
+
generation = ""
|
| 55 |
+
delta = ""
|
| 56 |
+
prompt_tokens = f"Prompt Tokens: {len(llm.tokenize(bytes(prompt,encoding='utf-8')))}"
|
| 57 |
+
generated_text = ""
|
| 58 |
+
answer_tokens = ''
|
| 59 |
+
total_tokens = ''
|
| 60 |
+
for character in llm(prompt,
|
| 61 |
+
max_tokens=max_new_tokens,
|
| 62 |
+
stop=["</s>"],
|
| 63 |
+
temperature = temperature,
|
| 64 |
+
repeat_penalty = repeat_penalty,
|
| 65 |
+
top_p = top_p, # Example stop token - not necessarily correct for this specific model! Please check before using.
|
| 66 |
+
echo=False,
|
| 67 |
+
stream=True):
|
| 68 |
+
generation += character["choices"][0]["text"]
|
| 69 |
+
|
| 70 |
+
answer_tokens = f"Out Tkns: {len(llm.tokenize(bytes(generation,encoding='utf-8')))}"
|
| 71 |
+
total_tokens = f"Total Tkns: {len(llm.tokenize(bytes(prompt,encoding='utf-8'))) + len(llm.tokenize(bytes(generation,encoding='utf-8')))}"
|
| 72 |
+
delta = datetime.datetime.now() - start
|
| 73 |
+
yield generation, delta, prompt_tokens, answer_tokens, total_tokens
|
| 74 |
+
timestamp = datetime.datetime.now()
|
| 75 |
+
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"""
|
| 76 |
+
writehistory(logger)
|
| 77 |
+
convHistory = convHistory + prompt + "\n" + generation + "\n"
|
| 78 |
+
print(convHistory)
|
| 79 |
+
return generation, delta, prompt_tokens, answer_tokens, total_tokens
|
| 80 |
+
#return generation, delta
|
| 81 |
+
|
| 82 |
+
|
| 83 |
+
# MAIN GRADIO INTERFACE
|
| 84 |
+
with gr.Blocks(theme='Medguy/base2') as demo: #theme=gr.themes.Glass() #theme='remilia/Ghostly'
|
| 85 |
+
#TITLE SECTION
|
| 86 |
+
with gr.Row(variant='compact'):
|
| 87 |
+
with gr.Column(scale=3):
|
| 88 |
+
gr.Image(value='https://github.com/fabiomatricardi/GradioStudies/raw/main/20231205/logo-banner-StableZephyr.jpg',
|
| 89 |
+
show_label = False,
|
| 90 |
+
show_download_button = False, container = False)
|
| 91 |
+
with gr.Column(scale=10):
|
| 92 |
+
gr.HTML("<center>"
|
| 93 |
+
+ "<h3>Prompt Engineering Playground!</h3>"
|
| 94 |
+
+ "<h1>ππ¦ StableLM-Zephyr-3B - 4K context window</h2></center>")
|
| 95 |
+
with gr.Row():
|
| 96 |
+
with gr.Column(min_width=80):
|
| 97 |
+
gentime = gr.Textbox(value="", placeholder="Generation Time:", min_width=50, show_label=False)
|
| 98 |
+
with gr.Column(min_width=80):
|
| 99 |
+
prompttokens = gr.Textbox(value="", placeholder="Prompt Tkn:", min_width=50, show_label=False)
|
| 100 |
+
with gr.Column(min_width=80):
|
| 101 |
+
outputokens = gr.Textbox(value="", placeholder="Output Tkn:", min_width=50, show_label=False)
|
| 102 |
+
with gr.Column(min_width=80):
|
| 103 |
+
totaltokens = gr.Textbox(value="", placeholder="Total Tokens:", min_width=50, show_label=False)
|
| 104 |
+
# INTERACTIVE INFOGRAPHIC SECTION
|
| 105 |
+
|
| 106 |
+
|
| 107 |
+
# PLAYGROUND INTERFACE SECTION
|
| 108 |
+
with gr.Row():
|
| 109 |
+
with gr.Column(scale=1):
|
| 110 |
+
gr.Markdown(
|
| 111 |
+
f"""
|
| 112 |
+
### Tunning Parameters""")
|
| 113 |
+
temp = gr.Slider(label="Temperature",minimum=0.0, maximum=1.0, step=0.01, value=0.42)
|
| 114 |
+
top_p = gr.Slider(label="Top_P",minimum=0.0, maximum=1.0, step=0.01, value=0.8)
|
| 115 |
+
repPen = gr.Slider(label="Repetition Penalty",minimum=0.0, maximum=4.0, step=0.01, value=1.2)
|
| 116 |
+
max_len = gr.Slider(label="Maximum output lenght", minimum=10,maximum=(contextlength-500),step=2, value=900)
|
| 117 |
+
gr.Markdown(
|
| 118 |
+
"""
|
| 119 |
+
Fill the System Prompt and User Prompt
|
| 120 |
+
And then click the Button below
|
| 121 |
+
""")
|
| 122 |
+
btn = gr.Button(value="ππ¦ Generate", variant='primary')
|
| 123 |
+
gr.Markdown(
|
| 124 |
+
f"""
|
| 125 |
+
- **Prompt Template**: StableLM-Zephyr ππ¦
|
| 126 |
+
- **Repetition Penalty**: {repetitionpenalty}
|
| 127 |
+
- **Context Lenght**: {contextlength} tokens
|
| 128 |
+
- **LLM Engine**: llama-cpp
|
| 129 |
+
- **Model**: ππ¦ StableLM-Zephyr-7b
|
| 130 |
+
- **Log File**: {logfile}
|
| 131 |
+
""")
|
| 132 |
+
|
| 133 |
+
|
| 134 |
+
with gr.Column(scale=4):
|
| 135 |
+
txt = gr.Textbox(label="System Prompt", value = "", placeholder = "This models does not have any System prompt...",lines=1, interactive = False)
|
| 136 |
+
txt_2 = gr.Textbox(label="User Prompt", lines=5, show_copy_button=True)
|
| 137 |
+
txt_3 = gr.Textbox(value="", label="Output", lines = 10, show_copy_button=True)
|
| 138 |
+
btn.click(combine, inputs=[txt, txt_2,temp,max_len,top_p,repPen], outputs=[txt_3,gentime,prompttokens,outputokens,totaltokens])
|
| 139 |
+
|
| 140 |
+
|
| 141 |
+
if __name__ == "__main__":
|
| 142 |
+
demo.launch(inbrowser=True)
|