Delete app.py

app.py

@@ -1,103 +0,0 @@
-import os
-import json
-import gradio as gr
-from typing import Literal
-
-TaskType = Literal["NER", "RE", "EE", "Base"]
-ModeType = Literal["direct", "fast-thinking", "slow-thinking", "customized"]
-
-
-class InterFace:
-    def __init__(self, dm):
-        """
-        receive the Pipeline instance as a parameter
-        """
-        self.dm = dm
-
-    def collect_and_process_inputs(self, task_description, file=None):
-        """
-        collect user inputs, return the processing result directly
-        """
-        # if file is not None:
-        #     file_path = self.save_file(file)
-        #     print(f"Your file has been saved, you can find it at: {file_path}")
-        # else:
-        #     file_path = None
-        file_path = "/disk/disk_20T/luoyujie/Agent/OneKE-Agent-reconstruct/data/input_files/Harry_Potter_Chapter1.pdf"
-        dm_response, dm_code = self.dm.get_extraction_result(file_path, task_description)
-        return json.dumps(dm_response, indent=2), dm_code
-
-    def save_file(self, file):
-        """
-        save file to the server and return the file path
-        """
-        file_path = os.path.join("saved", file.name)
-        os.makedirs(os.path.dirname(file_path), exist_ok=True)
-        with open(file_path, "wb") as f:
-            f.write(file.read())
-        return file_path
-
-    def run_interface(self):
-        """
-        run Gradio interface
-        """
-        task_options = list(TaskType.__args__)
-        mode_options = list(ModeType.__args__)
-
-        # create the interface
-        with gr.Blocks() as demo:
-            gr.HTML("""
-                <div style="text-align:center;">
-                    <p align="center">
-                        <a href="https://github.com/R10836/DeepKE/blob/main/example/llm/assets/oneke_logo.png">
-                            <img src="https://raw.githubusercontent.com/R10836/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://huggingface.co">Paper</a>]
-                    👨‍💻[<a href="https://github.com" target="_blank"><span class="icon"><i class="fab fa-github"></i></span>Code</a>]
-                    📄[<a href="https://zjunlp.gitbook.io">Docs</a>]
-                    🤗[<a href="https:/huggingface.cot" target="_blank">Demo</a>]
-                    </p>
-                </div>
-            """)
-
-            # section: input area
-            with gr.Row():
-                task = gr.Dropdown(choices=task_options, label="Select your Task", value="Base")
-                mode = gr.Dropdown(choices=mode_options, label="Select your Mode", value="direct")
-
-            task_description = gr.Textbox(label="Instruction", placeholder="Enter task description, e.g., extract key information from this article.")
-
-            text = gr.Textbox(label="Text", placeholder="Or enter text here directly")
-
-            use_file = gr.Checkbox(label="Use File", value=False)
-            file = gr.File(label="Upload File", visible=False, container=True, scale=2)
-            use_file.change(
-                lambda use_file: gr.update(visible=use_file),
-                inputs=[use_file],
-                outputs=[file]
-            )
-
-            # section: output area
-            code_output = gr.Code(label="Generated Schema", language="python", lines=10, interactive=False)
-            model_output = gr.Code(label="Final Answer", language="json", lines=10, interactive=False)
-
-            run_button = gr.Button("Submit")
-            run_button.click(
-                self.collect_and_process_inputs,
-                inputs=[task_description, file],
-                outputs=[model_output, code_output],
-            )
-
-        # launch the interface
-        demo.launch(share=False)
-
-
-if __name__ == "__main__":
-    # 你需要替换 dm 为你的 pipeline 实例
-    dm_instance = None  # 填入你的模型实例
-    app = InterFace(dm_instance)
-    app.run_interface()
-