initial upload

.gitignore

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+flagged/

README.md

@@ -1,14 +1,13 @@
 ---
 title: ImBD
-emoji: 🏆
-colorFrom: green
+emoji: 💬
+colorFrom: yellow
 colorTo: purple
 sdk: gradio
-sdk_version: 5.9.1
+sdk_version: 5.0.1
 app_file: app.py
 pinned: false
 license: apache-2.0
-short_description: An online demo for Imitate Before Detect
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+An demo detector using [Gradio](https://gradio.app).

app.py

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+import gradio as gr
+import requests
+import os
+
+class Client:
+    def __init__(self):
+        self.url =  os.getenv("SERVICE_IP")
+        self.headers = {
+            "x-api-key": os.getenv("APIKEY")
+        }
+        
+    def detect(self, document):
+        data = {
+            "document": document,
+            "version": "no-version",
+            "multilingual": False
+        }
+        if len(document) > 3000:
+            return "Document is too long for this demo"
+        response = requests.post(self.url, json=data, headers=self.headers)
+        response = response.json()
+        documents =  response.get("documents")
+        res = ""
+        len_ai=0
+        len_human=0
+        for doc in documents:
+            if "AI" in doc["classification"]:
+                len_ai += len(doc["original_paragraph"])
+                res += f'<span style="color:red;">{doc["original_paragraph"]}</span>'
+            else:
+                len_human += len(doc["original_paragraph"])
+                res += f'<span style="color:green;">{doc["original_paragraph"]}</span>'
+                
+        res += f"<br><br>The above text has a probability of {len_ai/(len_ai+len_human)*100:.2f}% to be AI."
+        return res
+    
+client = Client()
+
+def respond(
+    message,
+):
+    return client.detect(message)
+
+description = '<span style="font-size: 30px;">🤖 Demo for [ImBD](https://github.com/Jiaqi-Chen-00/ImBD) <br></span>'\
+    '<span style="font-size: 18px;">We slice the input text into segments of 300 characters each, ' \
+    'supporting a maximum text length of 3000 characters.<br>'\
+    'The result for each segment is indicated by green for human and red for AI on the right.</span>'
+
+
+demo = gr.Interface(
+    fn=respond,
+    inputs=[
+        gr.Textbox(label="Input Message"),
+    ],
+    outputs="html",
+    description=description
+)
+
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+huggingface_hub==0.25.2
+requests