sin puerto en el app.py

app.py

@@ -1,153 +1,153 @@
-import gradio as gr
-import json
-from flask import jsonify
-from sentence_transformers import SentenceTransformer, InputExample, util
-from codeScripts.utils import save_json, load_json, create_file_path
-from plentas import Plentas
-import pandas as pd
-import zipfile
-import os
-
-def Main(configuration, uploadedFile):
-  
-    error = ""
-    modelResult  = ""
-
-    configuration_dict = json.loads(configuration)
-
-    try:        
-        uploadedFilePath = uploadedFile.name
-                     
-        config_json = load_json("configV2.json")
-
-        #configuring plentas methodology
-        response = Plentas(config_json[0], [answersTodict(uploadedFilePath), createTeacherJson(configuration_dict)])
-        # #overwriting the custom settings for the settings from the api      
-        response.setApiSettings(configuration)
-    
-        modelResult = jsonify(response.processApiData())
-    except Exception as e:
-        error = "Oops: " + str(e)
-    
-    return [error, modelResult]
-
-def createTeacherJson(configuration):
-    """
-    This function extracts the information about the subquestions and subanswers and puts them in the correct format.
-    Inputs:
-        config: The configured info from the api.
-    Outputs:
-        teachersJson: The generated dictionary with the subquestions.
-    """
-    teachersJson = {"enunciado": "", "minipreguntas":[], "keywords":""}
-
-    #5 is the maximum number of permitted subquestions in the configuration2 page
-    
-    for i in range(5):
-       
-        try:
-            teachersJson["minipreguntas"].append({
-				"minipregunta": configuration["minip" + str(i+1)],
-				"minirespuesta": configuration["minir" + str(i+1)]
-			})
-
-        except:
-            break
-
-    return teachersJson
-
-def extractZipData(ruta_zip):
-    """
-    This function extracts the students's answers from the zip file (the one the teacher has in the task section).
-    Inputs:
-        ruta_zip: The path inherited from answersTodict
-    """
-    #defining the path where the extracted info is to be stored
-    ruta_extraccion = create_file_path("StudentAnswers/", doctype= 1)
-    #extracting the info
-    archivo_zip = zipfile.ZipFile(ruta_zip, "r")
-    try:
-        archivo_zip.extractall(pwd=None, path=ruta_extraccion)
-    except:
-        pass
-    archivo_zip.close()
-    
-def removeHtmlFromString(string):
-    """
-    This function removes the html tags from the student's response.
-    Inputs:
-        -string: The student's response
-    Outputs:
-        -new_string: The filtered response
-    """
-    string = string.encode('utf-8', 'replace')
-    string = string.decode('utf-8', 'replace')
-    new_string = ""
-    skipChar = 0
-    for char in string:
-        if char == "<":
-            skipChar = 1
-        elif char == ">":
-            skipChar = 0
-        else:
-            if not skipChar:        
-                new_string = new_string+char
-
-    new_string = new_string.encode('utf-8', 'replace')
-    new_string = new_string.decode('utf-8', 'replace')
-    return new_string
-
-def answersTodict(zip_path):
-    """
-    This function extracts the students's answers and stacks them in one specific format so that it can be processed next.
-    Inputs:
-        ruta_zip: The path where the zip file is stored
-    Outputs:
-        studentAnswersDict: The dictionary with all the responses
-    """
-    #extracting the data
-    extractZipData(zip_path)
-    
-    studentAnswersDict = []
-
-    #stacking the information of each extracted folder
-    for work_folder in os.listdir(create_file_path("StudentAnswers/", doctype= 1)):
-        for student, indx in zip(os.listdir(create_file_path("StudentAnswers/" + work_folder, doctype= 1)), range(len(os.listdir(create_file_path("StudentAnswers/" + work_folder, doctype= 1))))):
-            student_name = student.split("(")
-            student_name = student_name[0]
-            try:
-                #opening the file
-
-                #fichero = open(create_file_path("StudentAnswers/" + work_folder + "/" + student + "/" + 'comments.txt', doctype= 1))
-                #where the actual response is
-                fichero = open(create_file_path("StudentAnswers/" + work_folder + "/" + student + "/" + 'Adjuntos del envio/Respuesta enviada', doctype= 1), encoding='utf-8')                
-                #reading it
-                lineas = fichero.readlines()
-
-                #removing html                
-                lineas[0] = removeHtmlFromString(lineas[0])           
-                                
-                #saving it                                
-                studentAnswersDict.append({"respuesta":lineas[0], "hashed_id":student_name, "TableIndex":indx})
-
-            except:
-                studentAnswersDict.append({"respuesta":"", "hashed_id":student_name, "TableIndex":indx})
-
-    #saving the final dictionary
-    save_json(create_file_path('ApiStudentsDict.json', doctype= 1),studentAnswersDict)
-    return studentAnswersDict
-
-configuration = gr.inputs.Textbox(lines=10, placeholder="JSON de Configuración")
-zipFileInput = gr.inputs.File(label="ZIP file")
-#dataFrameOutput = gr.outputs.Dataframe(headers=["Resultados"], max_rows=20, max_cols=None, overflow_row_behaviour="paginate", type="pandas", label="Resultado")
-
-labelOutput = gr.outputs.Label(num_top_classes=None, type="auto", label="")
-labelError = gr.outputs.Label(num_top_classes=None, type="auto", label="")
-
-iface = gr.Interface(fn=Main
-    , inputs=[configuration, zipFileInput]
-    , outputs=[labelError, labelOutput]
-    , title = "PLENTAS"
-)
-
-iface.launch(share = False,enable_queue=True, show_error =True, server_port=7870)
+import gradio as gr
+import json
+from flask import jsonify
+from sentence_transformers import SentenceTransformer, InputExample, util
+from codeScripts.utils import save_json, load_json, create_file_path
+from plentas import Plentas
+import pandas as pd
+import zipfile
+import os
+
+def Main(configuration, uploadedFile):
+  
+    error = ""
+    modelResult  = ""
+
+    configuration_dict = json.loads(configuration)
+
+    try:        
+        uploadedFilePath = uploadedFile.name
+                     
+        config_json = load_json("configV2.json")
+
+        #configuring plentas methodology
+        response = Plentas(config_json[0], [answersTodict(uploadedFilePath), createTeacherJson(configuration_dict)])
+        # #overwriting the custom settings for the settings from the api      
+        response.setApiSettings(configuration)
+    
+        modelResult = jsonify(response.processApiData())
+    except Exception as e:
+        error = "Oops: " + str(e)
+    
+    return [error, modelResult]
+
+def createTeacherJson(configuration):
+    """
+    This function extracts the information about the subquestions and subanswers and puts them in the correct format.
+    Inputs:
+        config: The configured info from the api.
+    Outputs:
+        teachersJson: The generated dictionary with the subquestions.
+    """
+    teachersJson = {"enunciado": "", "minipreguntas":[], "keywords":""}
+
+    #5 is the maximum number of permitted subquestions in the configuration2 page
+    
+    for i in range(5):
+       
+        try:
+            teachersJson["minipreguntas"].append({
+				"minipregunta": configuration["minip" + str(i+1)],
+				"minirespuesta": configuration["minir" + str(i+1)]
+			})
+
+        except:
+            break
+
+    return teachersJson
+
+def extractZipData(ruta_zip):
+    """
+    This function extracts the students's answers from the zip file (the one the teacher has in the task section).
+    Inputs:
+        ruta_zip: The path inherited from answersTodict
+    """
+    #defining the path where the extracted info is to be stored
+    ruta_extraccion = create_file_path("StudentAnswers/", doctype= 1)
+    #extracting the info
+    archivo_zip = zipfile.ZipFile(ruta_zip, "r")
+    try:
+        archivo_zip.extractall(pwd=None, path=ruta_extraccion)
+    except:
+        pass
+    archivo_zip.close()
+    
+def removeHtmlFromString(string):
+    """
+    This function removes the html tags from the student's response.
+    Inputs:
+        -string: The student's response
+    Outputs:
+        -new_string: The filtered response
+    """
+    string = string.encode('utf-8', 'replace')
+    string = string.decode('utf-8', 'replace')
+    new_string = ""
+    skipChar = 0
+    for char in string:
+        if char == "<":
+            skipChar = 1
+        elif char == ">":
+            skipChar = 0
+        else:
+            if not skipChar:        
+                new_string = new_string+char
+
+    new_string = new_string.encode('utf-8', 'replace')
+    new_string = new_string.decode('utf-8', 'replace')
+    return new_string
+
+def answersTodict(zip_path):
+    """
+    This function extracts the students's answers and stacks them in one specific format so that it can be processed next.
+    Inputs:
+        ruta_zip: The path where the zip file is stored
+    Outputs:
+        studentAnswersDict: The dictionary with all the responses
+    """
+    #extracting the data
+    extractZipData(zip_path)
+    
+    studentAnswersDict = []
+
+    #stacking the information of each extracted folder
+    for work_folder in os.listdir(create_file_path("StudentAnswers/", doctype= 1)):
+        for student, indx in zip(os.listdir(create_file_path("StudentAnswers/" + work_folder, doctype= 1)), range(len(os.listdir(create_file_path("StudentAnswers/" + work_folder, doctype= 1))))):
+            student_name = student.split("(")
+            student_name = student_name[0]
+            try:
+                #opening the file
+
+                #fichero = open(create_file_path("StudentAnswers/" + work_folder + "/" + student + "/" + 'comments.txt', doctype= 1))
+                #where the actual response is
+                fichero = open(create_file_path("StudentAnswers/" + work_folder + "/" + student + "/" + 'Adjuntos del envio/Respuesta enviada', doctype= 1), encoding='utf-8')                
+                #reading it
+                lineas = fichero.readlines()
+
+                #removing html                
+                lineas[0] = removeHtmlFromString(lineas[0])           
+                                
+                #saving it                                
+                studentAnswersDict.append({"respuesta":lineas[0], "hashed_id":student_name, "TableIndex":indx})
+
+            except:
+                studentAnswersDict.append({"respuesta":"", "hashed_id":student_name, "TableIndex":indx})
+
+    #saving the final dictionary
+    save_json(create_file_path('ApiStudentsDict.json', doctype= 1),studentAnswersDict)
+    return studentAnswersDict
+
+configuration = gr.inputs.Textbox(lines=10, placeholder="JSON de Configuración")
+zipFileInput = gr.inputs.File(label="ZIP file")
+#dataFrameOutput = gr.outputs.Dataframe(headers=["Resultados"], max_rows=20, max_cols=None, overflow_row_behaviour="paginate", type="pandas", label="Resultado")
+
+labelOutput = gr.outputs.Label(num_top_classes=None, type="auto", label="")
+labelError = gr.outputs.Label(num_top_classes=None, type="auto", label="")
+
+iface = gr.Interface(fn=Main
+    , inputs=[configuration, zipFileInput]
+    , outputs=[labelError, labelOutput]
+    , title = "PLENTAS"
+)
+
+iface.launch(share = False,enable_queue=True, show_error =True)