Update main.py

main.py

@@ -24,6 +24,7 @@ nlp_qa = pipeline("document-question-answering", model="jinhybr/OCR-DocVQA-Donut
 nlp_qa_v2 = pipeline("document-question-answering", model="faisalraza/layoutlm-invoices")
 nlp_qa_v3 = pipeline("question-answering", model="deepset/roberta-base-squad2")
 nlp_classification = pipeline("text-classification", model="distilbert/distilbert-base-uncased-finetuned-sst-2-english")
+nlp_classification_v2 = pipeline("text-classification", model="cardiffnlp/twitter-roberta-base-sentiment-latest")
 
 description = """
 ## Image-based Document QA
@@ -128,6 +129,14 @@ async def classify_text(text: str = Form(...)):
     except Exception as e:
         return JSONResponse(content=f"Error classifying text: {str(e)}", status_code=500)
 
+@app.post("/test_classify/", description="Classify the provided text with positive, neutral, or negative sentiment.")
+async def test_classify_text(text: str = Form(...)):
+    try:
+        # Perform text classification using the updated model that returns positive, neutral, or negative
+        result = nlp_classification_v2(text)
+        return result
+    except Exception as e:
+        return JSONResponse(content=f"Error classifying text: {str(e)}", status_code=500)
 
 # Set up CORS middleware
 origins = ["*"]  # or specify your list of allowed origins