new(all): General Bots reading comprehension.

EstimateLoanTax/__init__.py

@@ -1,9 +1,36 @@
+import os
 import logging
-
 import azure.functions as func
+from azure.storage.blob import BlobClient
+from tempfile import NamedTemporaryFile
+#from azure.storage.blob import BlockBlobService
+
 #set STORAGE_BLOB_URL='https://pythonazurestorage12345.blob.core.windows.net'
 
+
+# def get_file(filename):
+#     local_file = NamedTemporaryFile()
+#     container_name="datalake"
+#     BlockBlobService.get_blob_to_stream(container_name, filename, stream=local_file, 
+#     max_connections=2)
+
+#     local_file.seek(0)
+#     return local_file
+
+# http://localhost:7071/api/EstimateLoanTax?age=23&income=20000&employeeTime=2
 def main(req: func.HttpRequest) -> func.HttpResponse:
+
+    #key  = '';
+
+    # Create the client object for the resource identified by the connection string,
+    # indicating also the blob container and the name of the specific blob we want.
+    #blob_client = BlobClient.from_connection_string(key,  blob_name="sample.csv")
+
+    # Open a local file and upload its contents to Blob Storage
+    #with open("./sample.csv", "rb") as data:
+    #    blob_client.upload_blob(data)
+
+
     # https://docs.microsoft.com/pt-br/azure/developer/python/azure-sdk-example-storage-use?tabs=cmd
     logging.info('Python HTTP trigger function processed a request.')
 
@@ -15,8 +42,8 @@ def main(req: func.HttpRequest) -> func.HttpResponse:
 
     returnedTax = 1;
 
-    if name:
+    if returnedTax:
-        return func.HttpResponse(returnedTax)
+        return func.HttpResponse('1')
     else:
         return func.HttpResponse(
              "This HTTP triggered function executed successfully. Pass a name in the query string or in the request body for a personalized response.",

GeneralQA/__init__.py

@@ -0,0 +1,34 @@
+import logging
+import azure.functions as func
+import os
+#os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' 
+from allennlp.predictors.predictor import Predictor
+import json
+
+# https://ai.google.com/research/NaturalQuestions
+
+predictor = None
+
+def main(req: func.HttpRequest) -> func.HttpResponse:
+    logging.info('General Bots QA.')
+
+    content = req.form.get('content')
+    question = req.params.get('question')
+                                     
+    global predictor
+    if predictor is None:
+        predictor = Predictor.from_path("https://storage.googleapis.com/allennlp-public-models/transformer-qa-2020-10-03.tar.gz")
+    
+    answer = predictor.predict(
+        passage=content,
+        question=question
+    )['best_span_str']
+       
+
+    if answer:
+        return func.HttpResponse(answer)
+    else:
+        return func.HttpResponse(
+            "This HTTP triggered function executed successfully. Pass a name in the query string or in the request body for a personalized response.",
+            status_code=200
+    )

GeneralQA/function.json

@@ -0,0 +1,20 @@
+{
+  "scriptFile": "__init__.py",
+  "bindings": [
+    {
+      "authLevel": "anonymous",
+      "type": "httpTrigger",
+      "direction": "in",
+      "name": "req",
+      "methods": [
+        "get",
+        "post"
+      ]
+    },
+    {
+      "type": "http",
+      "direction": "out",
+      "name": "$return"
+    }
+  ]
+}

host.json

@@ -10,6 +10,6 @@
   },
   "extensionBundle": {
     "id": "Microsoft.Azure.Functions.ExtensionBundle",
-    "version": "[1.*, 2.0.0)"
+    "version": "[2.*, 3.0.0)"
   }
 }

requirements.txt

@@ -1,11 +1,10 @@
-# DO NOT include azure-functions-worker in this file
-# The Python Worker is managed by Azure Functions platform
-# Manually managing azure-functions-worker may cause unexpected issues
-
 azure-functions
 azure-storage-blob
 azure-identity
 tensorflow
 scikit-learn
 pandas
-numpy
+numpy
+allennlp
+allennlp-models
+nltk