src/webui.py

import random
import json
import gradio as gr

from pipeline import Pipeline
from models import *


examples = [
    {
        "task": "NER",
        "mode": "quick",
        "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,
        "update_case": False,
    },
    {
        "task": "RE",
        "mode": "quick",
        "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,
        "update_case": False,
    },
    {
        "task": "EE",
        "mode": "quick",
        "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,
        "update_case": False,
    },
    {
        "task": "Base",
        "mode": "quick",
        "use_file": True,
        "file_path": "data/Harry_Potter_Chapter1.pdf",
        "instruction": "Extract main characters and the background setting from this chapter.",
        "constraint": "",
        "text": "",
        "update_case": False,
    },
    {
        "task": "Base",
        "mode": "quick",
        "use_file": True,
        "file_path": "data/Tulsi_Gabbard_News.html",
        "instruction": "Extract key information from the given text.",
        "constraint": "",
        "text": "",
        "update_case": False,
    },
]


def create_interface():
    with gr.Blocks(title="OneKE Demo", theme=gr.themes.Soft(text_size="lg")) 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>
                🌐[<a href="https://oneke.openkg.cn/" target="_blank">Web</a>]
                ⌨️[<a href="https://github.com/zjunlp/OneKE" target="_blank">Code</a>]
                📹[<a href="http://oneke.openkg.cn/demo.mp4" target="_blank">Video</a>]
                </p>
            </div>
        """)

        example_button_gr = gr.Button("🎲 Quick Start with an Example 🎲")


        with gr.Row():
            with gr.Column():
                model_gr = gr.Dropdown(
                    label="🪄 Select your Model",
                    choices=["deepseek-chat", "deepseek-reasoner", "gpt-3.5-turbo", "gpt-4o", "gpt-4o-mini"],
                    value="deepseek-chat",
                )
                api_key_gr = gr.Textbox(
                    label="🔑 Enter your API-Key",
                    value="sk-...",
                )
                base_url_gr = gr.Textbox(
                    label="🔗 Enter your Base-URL",
                    value="DEFAULT",
                )
            with gr.Column():
                task_gr = gr.Dropdown(
                    label="🎯 Select your Task",
                    choices=["Base", "NER", "RE", "EE"],
                    value="Base",
                )
                mode_gr = gr.Dropdown(
                    label="🧭 Select your Mode",
                    choices=["quick", "standard", "customized"],
                    value="quick",
                )
                schema_agent_gr = gr.Dropdown(choices=["NOT REQUIRED", "get_default_schema", "get_retrieved_schema", "get_deduced_schema"], value="NOT REQUIRED", label="🤖 Select your Schema-Agent", visible=False)
                extraction_Agent_gr = gr.Dropdown(choices=["NOT REQUIRED", "extract_information_direct", "extract_information_with_case"], value="NOT REQUIRED", label="🤖 Select your Extraction-Agent", visible=False)
                reflection_agent_gr = gr.Dropdown(choices=["NOT REQUIRED", "reflect_with_case"], value="NOT REQUIRED", label="🤖 Select your Reflection-Agent", visible=False)

        with gr.Row():
            use_file_gr = gr.Checkbox(label="📂 Use File", value=True)
            update_case_gr = gr.Checkbox(label="💰 Update Case", value=False)

        file_path_gr = gr.File(label="📖 Upload a File", visible=True)
        text_gr = gr.Textbox(label="📖 Text", placeholder="Enter your Text", visible=False)
        instruction_gr = gr.Textbox(label="🕹️ Instruction", visible=True)
        constraint_gr = gr.Textbox(label="🕹️ Constraint", visible=False)

        def customized_mode(mode):
            if mode == "customized":
                return gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
            else:
                return gr.update(visible=False, value="NOT REQUIRED"), gr.update(visible=False, value="NOT REQUIRED"), gr.update(visible=False, value="NOT REQUIRED")

        def update_fields(task):
            if task == "Base" or task == "":
                return gr.update(visible=True, label="🕹️ Instruction", placeholder="Enter your Instruction"), gr.update(visible=False)
            elif task == "NER":
                return gr.update(visible=False), gr.update(visible=True, label="🕹️ Constraint", placeholder="Enter your NER Constraint")
            elif task == "RE":
                return gr.update(visible=False), gr.update(visible=True, label="🕹️ Constraint", placeholder="Enter your RE Constraint")
            elif task == "EE":
                return gr.update(visible=False), gr.update(visible=True, label="🕹️ 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["mode"]),
                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"]),
                gr.update(value=example["update_case"]),
                gr.update(value="NOT REQUIRED", visible=False),
                gr.update(value="NOT REQUIRED", visible=False),
                gr.update(value="NOT REQUIRED", visible=False),
            )

        def submit(model, api_key, base_url, task, mode, instruction, constraint, text, use_file, file_path, update_case, schema_agent, extraction_Agent, reflection_agent):
            try:
                if base_url == "DEFAULT" or base_url == "":
                    if model in ["gpt-3.5-turbo", "gpt-4o", "gpt-4o-mini"]:
                        pipeline = Pipeline(ChatGPT(model_name_or_path=model, api_key=api_key))
                    elif model in ["deepseek-chat", "deepseek-reasoner"]:
                        pipeline = Pipeline(DeepSeek(model_name_or_path=model, api_key=api_key))
                else:
                    if model in ["gpt-3.5-turbo", "gpt-4o", "gpt-4o-mini"]:
                        pipeline = Pipeline(ChatGPT(model_name_or_path=model, api_key=api_key, base_url=base_url))
                    elif model in ["deepseek-chat", "deepseek-reasoner"]:
                        pipeline = Pipeline(DeepSeek(model_name_or_path=model, api_key=api_key, base_url=base_url))

                if task == "Base":
                    instruction = instruction
                    constraint = ""
                else:
                    instruction = ""
                    constraint = constraint
                if use_file:
                    text = ""
                    file_path = file_path
                else:
                    text = text
                    file_path = None

                agent3 = {}
                if mode == "customized":
                    if schema_agent not in ["", "NOT REQUIRED"]:
                        agent3["schema_agent"] = schema_agent
                    if extraction_Agent not in ["", "NOT REQUIRED"]:
                        agent3["extraction_agent"] = extraction_Agent
                    if reflection_agent not in ["", "NOT REQUIRED"]:
                        agent3["reflection_agent"] = reflection_agent

                # 调用 Pipeline
                _, _, ger_frontend_schema, ger_frontend_res = pipeline.get_extract_result(
                    task=task,
                    text=text,
                    use_file=use_file,
                    file_path=file_path,
                    instruction=instruction,
                    constraint=constraint,
                    mode=mode,
                    three_agents=agent3,
                    isgui=True,
                    update_case=update_case,
                    output_schema="",
                    truth="",
                    show_trajectory=False,
                )

                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"⚠️ Error:\n {str(e)}"
                return "", "", gr.update(value=error_message, visible=True)

        def clear_all():
            return (
                gr.update(value="NOT REQUIRED", visible=False),  # sechema_agent
                gr.update(value="NOT REQUIRED", visible=False),  # extraction_Agent
                gr.update(value="NOT REQUIRED", visible=False),  # reflection_agent
                gr.update(value="Base"),  # task
                gr.update(value="quick"),  # mode
                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=False),  # update_case
                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="😵‍💫 Ops, an Error Occurred", visible=False)
        with gr.Row():
            with gr.Column(scale=1):
                py_output_gr = gr.Code(label="🤔 Generated Schema", language="python", lines=10, interactive=False)
            with gr.Column(scale=1):
                json_output_gr = gr.Code(label="😉 Final Answer", language="json", lines=10, interactive=False)

        task_gr.change(fn=update_fields, inputs=task_gr, outputs=[instruction_gr, constraint_gr])
        mode_gr.change(fn=customized_mode, inputs=mode_gr, outputs=[schema_agent_gr, extraction_Agent_gr, reflection_agent_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,
                mode_gr,
                use_file_gr,
                file_path_gr,
                text_gr,
                instruction_gr,
                constraint_gr,
                update_case_gr,
                schema_agent_gr,
                extraction_Agent_gr,
                reflection_agent_gr,
            ],
        )
        submit_button_gr.click(
            fn=submit,
            inputs=[
                model_gr,
                api_key_gr,
                base_url_gr,
                task_gr,
                mode_gr,
                instruction_gr,
                constraint_gr,
                text_gr,
                use_file_gr,
                file_path_gr,
                update_case_gr,
                schema_agent_gr,
                extraction_Agent_gr,
                reflection_agent_gr,
            ],
            outputs=[py_output_gr, json_output_gr, error_output_gr],
            show_progress=True,
        )
        clear_button.click(
            fn=clear_all,
            outputs=[
                schema_agent_gr,
                extraction_Agent_gr,
                reflection_agent_gr,
                task_gr,
                mode_gr,
                instruction_gr,
                constraint_gr,
                use_file_gr,
                text_gr,
                file_path_gr,
                update_case_gr,
                py_output_gr,
                json_output_gr,
                error_output_gr,
            ],
        )

    return demo

if __name__ == "__main__":
    interface = create_interface()
    interface.launch()