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import random
import json
import gradio as gr
from pipeline import Pipeline
from models import *
examples = [
{
"task": "NER",
"use_file": False,
"text": "Finally, every other year , ELRA organizes a major conference LREC , the International Language Resources and Evaluation Conference .",
"instruction": "",
"constraint": """["nationality", "country capital", "place of death", "children", "location contains", "place of birth", "place lived", "administrative division of country", "country of administrative divisions", "company", "neighborhood of", "company founders"]""",
"file_path": None,
},
{
"task": "RE",
"use_file": False,
"text": "The aid group Doctors Without Borders said that since Saturday , more than 275 wounded people had been admitted and treated at Donka Hospital in the capital of Guinea , Conakry .",
"instruction": "",
"constraint": """["nationality", "country capital", "place of death", "children", "location contains", "place of birth", "place lived", "administrative division of country", "country of administrative divisions", "company", "neighborhood of", "company founders"]""",
"file_path": None,
},
{
"task": "EE",
"use_file": False,
"text": "The file suggested to the user contains no software related to video streaming and simply carries the malicious payload that later compromises victim \u2019s account and sends out the deceptive messages to all victim \u2019s contacts .",
"instruction": "",
"constraint": """{"phishing": ["damage amount", "attack pattern", "tool", "victim", "place", "attacker", "purpose", "trusted entity", "time"], "data breach": ["damage amount", "attack pattern", "number of data", "number of victim", "tool", "compromised data", "victim", "place", "attacker", "purpose", "time"], "ransom": ["damage amount", "attack pattern", "payment method", "tool", "victim", "place", "attacker", "price", "time"], "discover vulnerability": ["vulnerable system", "vulnerability", "vulnerable system owner", "vulnerable system version", "supported platform", "common vulnerabilities and exposures", "capabilities", "time", "discoverer"], "patch vulnerability": ["vulnerable system", "vulnerability", "issues addressed", "vulnerable system version", "releaser", "supported platform", "common vulnerabilities and exposures", "patch number", "time", "patch"]}""",
"file_path": None,
},
# {
# "task": "Base",
# "use_file": True,
# "file_path": "data/Harry_Potter_Chapter_1.pdf",
# "instruction": "Extract main characters and the background setting from this chapter.",
# "constraint": "",
# "text": "",
# },
# {
# "task": "Base",
# "use_file": True,
# "file_path": "data/Tulsi_Gabbard_News.html",
# "instruction": "Extract key information from the given text.",
# "constraint": "",
# "text": "",
# },
]
def create_interface():
with gr.Blocks(title="OneKE Demo") as demo:
gr.HTML("""
<div style="text-align:center;">
<p align="center">
<a href="https://github.com/zjunlp/DeepKE/blob/main/example/llm/assets/oneke_logo.png">
<img src="https://raw.githubusercontent.com/zjunlp/DeepKE/refs/heads/main/example/llm/assets/oneke_logo.png" width="240"/>
</a>
</p>
<h1>OneKE: A Dockerized Schema-Guided LLM Agent-based Knowledge Extraction System</h1>
<p>
๐[<a href="https://oneke.openkg.cn/" target="_blank">Web</a>]
โจ๏ธ[<a href="https://github.com/zjunlp/OneKE" target="_blank">Code</a>]
๐น[<a href="http://oneke.openkg.cn/demo.mp4" target="_blank">Video</a>]
</p>
</div>
""")
example_button_gr = gr.Button("๐ฒ Quick Start with an Example ๐ฒ")
with gr.Row():
with gr.Column():
model_gr = gr.Dropdown(choices=["gpt-3.5-turbo", "gpt-4o", "gpt-4o-mini"], label="๐ค Select your Model")
api_key_gr = gr.Textbox(label="๐ Enter your API-Key")
with gr.Column():
task_gr = gr.Dropdown(choices=["Base", "NER", "RE", "EE"], label="๐ฏ Select your Task")
use_file_gr = gr.Checkbox(label="๐ Use File", value=True)
file_path_gr = gr.File(label="๐ Upload a File", visible=True)
text_gr = gr.Textbox(label="๐ Text", placeholder="Enter your Text", visible=False)
instruction_gr = gr.Textbox(label="๐น๏ธ Instruction", visible=True)
constraint_gr = gr.Textbox(label="๐น๏ธ Constraint", visible=False)
def update_fields(task):
if task == "Base":
return gr.update(visible=True, label="๐น๏ธ Instruction", placeholder="Enter your Instruction"), gr.update(visible=False)
elif task == "NER":
return gr.update(visible=False), gr.update(visible=True, label="๐น๏ธ Constraint", placeholder="Enter your NER Constraint")
elif task == "RE":
return gr.update(visible=False), gr.update(visible=True, label="๐น๏ธ Constraint", placeholder="Enter your RE Constraint")
elif task == "EE":
return gr.update(visible=False), gr.update(visible=True, label="๐น๏ธ Constraint", placeholder="Enter your EE Constraint")
def update_input_fields(use_file):
if use_file:
return gr.update(visible=False), gr.update(visible=True)
else:
return gr.update(visible=True), gr.update(visible=False)
def start_with_example():
example_index = random.randint(0, len(examples) - 1)
example = examples[example_index]
return (
gr.update(value=example["task"]),
gr.update(value=example["use_file"]),
gr.update(value=example["file_path"], visible=example["use_file"]),
gr.update(value=example["text"], visible=not example["use_file"]),
gr.update(value=example["instruction"], visible=example["task"] == "Base"),
gr.update(value=example["constraint"], visible=example["task"] in ["NER", "RE", "EE"]),
)
def submit(model, api_key, task, instruction, constraint, text, use_file, file_path):
try:
# ๅๅปบ Pipeline ๅฎไพ
pipeline = Pipeline(ChatGPT(model_name_or_path=model, api_key=api_key))
if task == "Base":
instruction = instruction
constraint = ""
else:
instruction = ""
constraint = constraint
if use_file:
text = ""
file_path = file_path
else:
text = text
file_path = None
# ่ฐ็จ Pipeline
_, _, ger_frontend_schema, ger_frontend_res = pipeline.get_extract_result(
task=task,
instruction=instruction,
constraint=constraint,
use_file=use_file,
file_path=file_path,
text=text,
)
ger_frontend_schema = str(ger_frontend_schema)
ger_frontend_res = json.dumps(ger_frontend_res, ensure_ascii=False, indent=4) if isinstance(ger_frontend_res, dict) else str(ger_frontend_res)
return ger_frontend_schema, ger_frontend_res, gr.update(value="", visible=False)
except Exception as e:
error_message = f"โ ๏ธ Error:\n {str(e)}"
return "", "", gr.update(value=error_message, visible=True)
def clear_all():
return (
gr.update(value=""), # model
gr.update(value=""), # API Key
gr.update(value=""), # task
gr.update(value="", visible=False), # instruction
gr.update(value="", visible=False), # constraint
gr.update(value=True), # use_file
gr.update(value="", visible=False), # text
gr.update(value=None, visible=True), # file_path
gr.update(value=""),
gr.update(value=""),
gr.update(value="", visible=False), # error_output
)
with gr.Row():
submit_button_gr = gr.Button("Submit", variant="primary", scale=8)
clear_button = gr.Button("Clear", scale=5)
gr.HTML("""
<div style="width: 100%; text-align: center; font-size: 16px; font-weight: bold; position: relative; margin: 20px 0;">
<span style="position: absolute; left: 0; top: 50%; transform: translateY(-50%); width: 45%; border-top: 1px solid #ccc;"></span>
<span style="position: relative; z-index: 1; background-color: white; padding: 0 10px;">Output:</span>
<span style="position: absolute; right: 0; top: 50%; transform: translateY(-50%); width: 45%; border-top: 1px solid #ccc;"></span>
</div>
""")
error_output_gr = gr.Textbox(label="๐ตโ๐ซ Ops, an Error Occurred", visible=False)
with gr.Row():
with gr.Column(scale=1):
py_output_gr = gr.Code(label="๐ค Generated Schema", language="python", lines=10, interactive=False)
with gr.Column(scale=1):
json_output_gr = gr.Code(label="๐ Final Answer", language="json", lines=10, interactive=False)
task_gr.change(fn=update_fields, inputs=task_gr, outputs=[instruction_gr, constraint_gr])
use_file_gr.change(fn=update_input_fields, inputs=use_file_gr, outputs=[text_gr, file_path_gr])
example_button_gr.click(
fn=start_with_example,
inputs=[],
outputs=[
task_gr,
use_file_gr,
file_path_gr,
text_gr,
instruction_gr,
constraint_gr,
],
)
submit_button_gr.click(
fn=submit,
inputs=[
model_gr,
api_key_gr,
task_gr,
instruction_gr,
constraint_gr,
text_gr,
use_file_gr,
file_path_gr,
],
outputs=[py_output_gr, json_output_gr, error_output_gr],
show_progress=True,
)
clear_button.click(
fn=clear_all,
outputs=[
model_gr,
api_key_gr,
task_gr,
instruction_gr,
constraint_gr,
use_file_gr,
text_gr,
file_path_gr,
py_output_gr,
json_output_gr,
error_output_gr,
],
)
return demo
interface = create_interface()
interface.launch()
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