Update app.py

app.py

@@ -14,9 +14,18 @@ connection_string = os.getenv("AZURE_CON_STRING")
 openai.api_key = os.getenv("OPENAI_API_KEY")
 computervision_client = ComputerVisionClient(endpoint, CognitiveServicesCredentials(subscription_key))
 
-def ocr_pdf(pdf_url):
-    preprocessing_function(pdf_url)
-    my_blob = pdf_url.split('/')[-1]
+def ocr_pdf(pdf_url1):
+    preprocessing_function(pdf_url1)
+    my_blob = pdf_url1.split('/')[-1]
+    blob = BlobClient.from_connection_string(conn_str=connection_string, container_name= my_container, blob_name=my_blob)
+    with open("answer_paper.pdf", "rb") as data:
+        blob.upload_blob(data,overwrite=True) 
+    text = azure_ocr(blob.url,computervision_client)
+    return text.strip()
+
+def ocr_pdf(pdf_url2):
+    preprocessing_function(pdf_url2)
+    my_blob = pdf_url2.split('/')[-1]
     blob = BlobClient.from_connection_string(conn_str=connection_string, container_name= my_container, blob_name=my_blob)
     with open("answer_paper.pdf", "rb") as data:
         blob.upload_blob(data,overwrite=True) 
@@ -50,23 +59,31 @@ def classify_class(incident_description):
     return classification
 
     
-def avatiation(pdf_url):
-    pdftext = ocr_pdf(pdf_url)
-    defect_class = classify_class(pdftext)
-    main_issue =  classify_cause(pdftext)
-    return main_issue, defect_class
+def avatiation(pdf_url1,pdf_url2):
+    pdftext1 = ocr_pdf(pdf_url1)
+    pdftext2 = ocr_pdf(pdf_url2)
+
+    defect_class1 = classify_class(pdftext1)
+    main_issue1 =  classify_cause(pdftext1)
+
+    defect_class2 = classify_class(pdftext2)
+    main_issue2 =  classify_cause(pdftext2)
+    return main_issue1, defect_class1,main_issue2, defect_class2,
 
 
 
 inputs1 = gr.inputs.Textbox(label="Link for aviation log reports")
-#inputs2 = gr.inputs.Textbox(label="Link for aviation log reports 2")
+inputs2 = gr.inputs.Textbox(label="Link for aviation log reports 2")
 
 
 outputs = [gr.outputs.Textbox(label="Main Issue of the log report"),
-           gr.outputs.Textbox(label="category of the log report")
+           gr.outputs.Textbox(label="category of the log report"),
+
+           gr.outputs.Textbox(label="Main Issue of the log report2"),
+           gr.outputs.Textbox(label="category of the log report2")
            ]
            
 
-demo = gr.Interface(fn=avatiation,inputs=inputs1,outputs=outputs, title="ATA Auto classification using OCR and GPT3 ")
+demo = gr.Interface(fn=avatiation,inputs= [inputs1,inputs2],outputs=outputs, title="ATA Auto classification using OCR and GPT3 ")
 demo.launch()