formate response

app.py

@@ -18,63 +18,29 @@ from transformers import pipeline
 # pytesseract.pytesseract.tesseract_cmd = r’./Tesseract-OCR/tesseract.exe’
 choices = os.popen('tesseract --list-langs').read().split('\n')[1:-1]
 description = """
-## DocQA with 🤗 transformers, FastAPI, and Docker
-This app shows how to do Document Question Answering using
-FastAPI in a Docker Space 🚀
-Check out the docs for the `/predict` endpoint below to try it out!
+Upload Receipt and get
 """
-
-# NOTE - we configure docs_url to serve the interactive Docs at the root path
-# of the app. This way, we can use the docs as a landing page for the app on Spaces.
 app = FastAPI(
-    title="ChimichangApp",
+    title="ReceiptOCR",
     docs_url="/", description=description)
 
 pipe = pipeline("document-question-answering", model="impira/layoutlm-document-qa")
 
 
-#st.write(output)
-
-# @app.post("/predict")
-# def predict(image_file: bytes = File(...), question: str = Form(...)):
-#     """
-#     Using the document-question-answering pipeline from `transformers`, take
-#     a given input document (image) and a question about it, and return the
-#     predicted answer. The model used is available on the hub at:
-#     [`impira/layoutlm-document-qa`](https://huggingface.co/impira/layoutlm-document-qa).
-#     """
-#     image = Image.open(BytesIO(image_file))
-#     output = pipe(image, question)
-#     return output
 
 @app.get("/hello_2")
 def read_root():
     image = 'https://templates.invoicehome.com/invoice-template-us-neat-750px.png'
 
-    question = "What is the invoice number?"
-    output = pipe(image, question)
-    return output
-
-@app.get("/hello_3")
-def read_root():
-    image = 'https://templates.invoicehome.com/invoice-template-us-neat-750px.png'
-
-    question = "What is the invoice number?"
-    output = pipe(image, question)
-    return output
-
-@app.get("/hello_4")
-def read_root():
-    image = 'https://templates.invoicehome.com/invoice-template-us-neat-750px.png'
-
-    question = "What is the invoice number?"
-    output = pipe(image, question)
-    return output
-
-@app.get("/hello")
-def read_root():
-    image = 'https://templates.invoicehome.com/invoice-template-us-neat-750px.png'
-
-    question = "What is the invoice number?"
-    output = pipe(image, question)
-    return output
+    question_1 = "What is the Total amount?"
+    question_2 = "What is Total VAT amount?"
+    question_3 = "What is the Date?"
+    output_1 = pipe(image, question_1)
+    output_2 = pipe(image, question_2)
+    output_3 = pipe(image, question_3)
+    
+    response = {}
+    response['total amount'] = output_1.first['answer']
+    response['toal vat'] = output_2.first['answer']
+    response['date'] = output_3.first['answer']
+    return response