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import gradio as gr
import os
import run_auditor_user_defined
import run_critic_user_defined
import run_rank
import pre_process
from utils import dotdict, clean_folder
os.environ['DISPLAY'] = ':0'
def openAIKey(key):
if key:
os.environ["OPENAI_API_KEY"] = key
return "Let's get you started"
else:
return "Please add your OpenAI API key to continue."
def auditor(key, audit_model, audit_top_k, audit_temperature, audit_number, audit_contract_file, audit_prompt_file):
if audit_contract_file:
args = {
'backend': audit_model.lower(),
'temperature': audit_temperature,
'data_dir': "data/CVE_clean",
'topk': audit_top_k,
'num_auditor': audit_number,
'openai_api_key': key
}
args = dotdict(args)
if os.path.exists("data/CVE"):
clean_folder("data/CVE")
if os.path.exists("data/CVE_clean"):
clean_folder("data/CVE_clean")
if os.path.exists(f"src/logs/auditor_{args.backend}_{args.temperature}_top{args.topk}_{args.num_auditor}"):
clean_folder(f"src/logs/auditor_{args.backend}_{args.temperature}_top{args.topk}_{args.num_auditor}")
for uploaded_file in audit_contract_file:
file_name_int = uploaded_file.rfind("/") + 1
name = uploaded_file[file_name_int:len(uploaded_file)]
fp = open(uploaded_file, 'rb')
bytes_data = fp.read()
with open(f"data/CVE/{name}", "wb") as f:
f.write(bytes_data)
## Pre processing the data
pre_process.mainfnc(args.data_dir)
if audit_prompt_file:
for uploaded_file in audit_prompt_file:
file_name_int = uploaded_file.rfind("/") + 1
name = uploaded_file[file_name_int:len(uploaded_file)]
fp = open(uploaded_file, 'rb')
bytes_data = fp.read()
with open(f"src/prompt.py", "wb") as f:
f.write(bytes_data)
## Running the auditor code
run_auditor_user_defined.mainfnc(args)
message = f"You can find your processed Audit files at ./src/logs/auditor_{args.backend}_{args.temperature}_top{args.topk}_{args.num_auditor}"
else:
message = "Please Upload the Contract Files to proceed"
return message
def critic(key, critic_model, critic_shots, critic_temperature, critic_number, critic_auit_directory):
if critic_auit_directory:
args = {
'backend': critic_model.lower(),
'temperature': critic_temperature,
'dataset': "CVE",
'auditor_dir': critic_auit_directory,
'num_critic': critic_number,
'shot': critic_shots.lower(),
'openai_api_key': key
}
args = dotdict(args)
run_critic_user_defined.mainfnc(args)
message = f"Critic files processed successfully to folder ./src/logs/{args.auditor_dir}/critic_{args.backend}_{args.temperature}_{args.num_critic}_{args.shot}"
else:
message = "Please add the Audit Directory value to proceed"
return message
def ranker(critic_model, critic_shots, critic_temperature, critic_number, critic_auit_directory, ranker_strategy, ranker_audit_location, ranker_critic_location):
if critic_auit_directory and ranker_audit_location:
args_c = {
'auditor_dir': critic_auit_directory,
'backend':critic_model.lower(),
'temperature':critic_temperature,
'num_critic': critic_number,
'shot': critic_shots.lower()
}
args_r = {
'auditor_dir': ranker_audit_location,
'critic_dir': ranker_critic_location,
'strategy': ranker_strategy.lower()
}
args_r = dotdict(args_r)
args_c = dotdict(args_c)
run_rank.mainfnc(args_r)
message = f"Ranking files processed successfully to folder ./src/logs/{args_c.auditor_dir}/critic_{args_c.backend}_{args_c.temperature}_{args_c.num_critic}_{args_c.shot}/ranker_{args_r.strategy}"
else:
message = "Please enter the Audit directory locations to proceed."
return message
with gr.Blocks(theme=gr.themes.Base) as ui:
gr.Image("src/images/header.jpg", min_width=1500, height=80, show_download_button=False, show_label=False)
message = "Hello, Welcome to GPTLens GUI by Aishwarya Solanki..."
audit_output = "Auditor hasn't run yet."
critic_output = "Critic hasn't run yet."
ranker_output = "Ranker hasn't run yet."
with gr.Row(equal_height=500):
with gr.Column(scale=1, min_width=300):
key = gr.Textbox(label="Please input your openAi key", type="password")
gr.Button(value="Don't have an openAi key? Get one here.", link="https://platform.openai.com/account/api-keys")
gr.ClearButton(key, message, variant="primary")
with gr.Column(scale=2, min_width=600):
message = gr.Textbox(label="", value=message, interactive=False, visible=True)
gr.Markdown("### Auditor")
audit_model = gr.Radio(label="GPT Model", value="GPT-4", choices=["GPT-3.5-Turbo", "GPT-4", "GPT-4-Turbo-Preview"])
audit_top_k = gr.Slider(1, 10, value=3, step = 1, label="top-k value", info="Set the 'k' for top-k auditor responses")
audit_temperature = gr.Slider(0.0, 1.0, value=0.7, step = 0.01, label="Temperature", info="Set the Temperature")
audit_number = gr.Slider(1, 10, value=1, step = 1, label="Number of Auditors", info="Set the number of auditors")
with gr.Row():
with gr.Column(min_width=300, scale=2):
gr.Markdown("### Upload smart contract files (.sol)")
audit_contract_file = gr.Files()
audit_btn = gr.Button(value="Start Auditor", variant="primary", elem_id="audit")
with gr.Column(min_width=300, scale=2):
gr.Markdown("### Upload prompt file (optional, .py)")
audit_prompt_file = gr.Files()
audit_output = gr.Textbox(label="Auditor Status", value=audit_output, interactive=False, visible=True, elem_id="auditor_output")
audit_btn.click(fn=auditor, inputs=[key, audit_model, audit_top_k, audit_temperature,
audit_number, audit_contract_file, audit_prompt_file],
outputs=audit_output, api_name="auditor")
gr.Markdown("### Critic")
critic_model = gr.Radio(label="GPT Model", value="GPT-4", choices=["GPT-3.5-Turbo", "GPT-4", "GPT-4-Turbo-Preview"])
critic_shots= gr.Radio(label="Set the num of shots", value="Few", choices=["One", "Few"])
critic_temperature = gr.Slider(0.0, 1.0, value=0.7, step = 0.01, label="Temperature", info="Set the Temperature")
critic_number = gr.Slider(1, 10, value=1, step = 1, label="Number of Critics", info="Set the number of critics")
critic_auit_directory = gr.Textbox(label="Auditor Directory Location",
info="Example = auditor_{audit_model}_{audit_temperature}_top{audit_top_k}_{audit_number}",
value="")
with gr.Row():
with gr.Column(min_width=300, scale=2):
critic_btn = gr.Button(value="Start Critic", variant="primary", elem_id="critic")
with gr.Column(min_width=300, scale=2):
gr.Button(value="Start Ranker", variant="primary", visible=False)
critic_output = gr.Textbox(label="Critic Status", value=critic_output, interactive=False, visible=True, elem_id="criticor_output")
critic_btn.click(fn=critic, inputs=[key, critic_model, critic_shots, critic_temperature, critic_number, critic_auit_directory],
outputs=critic_output, api_name="criticor")
gr.Markdown("### Ranker")
ranker_strategy = gr.Radio(label="Strategy", value="Default", choices=["Custom", "Default"])
ranker_audit_location = gr.Textbox(label="Auditor Directory Location", value="",
info="Example = auditor_{audit_model}_{audit_temperature}_top{audit_top_k}_{audit_number}")
ranker_critic_location = gr.Textbox(label="Critic Directory Location",value="",
info="Example = critic_{critic_model}_{critic_temperature}_{critic_number}_{critic_shots}")
with gr.Row():
with gr.Column(min_width=300, scale=2):
ranker_btn = gr.Button(value="Start Ranker", variant="primary", elem_id="ranker")
with gr.Column(min_width=300, scale=2):
gr.Button(value="Start Ranker", variant="primary", visible=False)
ranker_output = gr.Textbox(label="Ranker Status", value=ranker_output, interactive=False, visible=True, elem_id="ranker_output")
ranker_btn.click(fn=ranker, inputs=[critic_model, critic_shots, critic_temperature, critic_number, critic_auit_directory,
ranker_strategy, ranker_audit_location, ranker_critic_location],
outputs=ranker_output, api_name="ranker")
gr.Button(value="You can checkout the results at path - ./src/logs/", link="https://huggingface.co/spaces/Asolanki97/GPTLens/tree/main/src/logs")
key.change(fn=openAIKey, inputs=key, outputs=message)
ui.launch(share=True)
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