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text-classification

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tangminhanh commited on Jul 29, 2024

Commit

a361653

verified ·

1 Parent(s): cdd2d4a

Update app.py

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app.py +23 -35

app.py CHANGED Viewed

@@ -1,4 +1,5 @@
 from fastapi import FastAPI, Query
 from pydantic import BaseModel
 from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
 import os
@@ -12,51 +13,38 @@ model = AutoModelForSequenceClassification.from_pretrained(
 tokenizer = AutoTokenizer.from_pretrained("kmcs-casulit/department-classification", token=token)
 pipe = pipeline("text-classification", model=model, tokenizer=tokenizer)
-# Define a request model
-class TextRequest(BaseModel):
-    text: str
-@app.get("/")
-def greet_json():
-    return {"message": "Hello, World!"}
-@app.get("/classify", response_class=HTMLResponse)
-def get_form():
     return """
     <html>
         <body>
-            <h2>Text Classification</h2>
-            <form id="classificationForm">
                 <label for="text">Enter text:</label>
-                <input type="text" id="text" name="text" required>
                 <button type="submit">Classify</button>
             </form>
-            <p id="result"></p>
-            <script>
-                document.getElementById('classificationForm').addEventListener('submit', async (event) => {
-                    event.preventDefault();
-                    const text = document.getElementById('text').value;
-                    const response = await fetch('/classify', {
-                        method: 'POST',
-                        headers: {
-                            'Content-Type': 'application/json',
-                        },
-                        body: JSON.stringify({ text }),
-                    });
-                    const result = await response.json();
-                    document.getElementById('result').innerText = 'Classification: ' + result.output;
-                });
-            </script>
         </body>
     </html>
     """
-@app.post("/classify")
-async def classify_post(request: Request):
-    data = await request.json()
-    text = data.get('text')
     if not text:
-        return {"error": "Text field is required."}
     output = pipe(text)
-    return {"output": output[0]['label']}

 from fastapi import FastAPI, Query
+from fastapi.responses import HTMLResponse
 from pydantic import BaseModel
 from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
 import os
 tokenizer = AutoTokenizer.from_pretrained("kmcs-casulit/department-classification", token=token)
 pipe = pipeline("text-classification", model=model, tokenizer=tokenizer)
+@app.get("/", response_class=HTMLResponse)
+def read_root():
     return """
     <html>
         <body>
+            <h1>Welcome to the Text Classification App</h1>
+            <form action="/classify" method="post">
                 <label for="text">Enter text:</label>
+                <input type="text" id="text" name="text">
                 <button type="submit">Classify</button>
             </form>
         </body>
     </html>
     """
+@app.post("/classify", response_class=HTMLResponse)
+async def classify(request: Request):
+    form_data = await request.form()
+    text = form_data.get('text')
     if not text:
+        return HTMLResponse(content="<html><body><p>No text provided.</p></body></html>", status_code=400)
     output = pipe(text)
+    classification = output[0]['label']
+    return HTMLResponse(content=f"""
+    <html>
+        <body>
+            <h1>Classification Result</h1>
+            <p>Text: {text}</p>
+            <p>Classification: {classification}</p>
+            <a href="/">Back</a>
+        </body>
+    </html>
+    """)