Merge pull request #721 from cliveseldon/request_logging

update request logger

seldon-request-logger/app/app.py

@@ -2,7 +2,8 @@
 import sys
 import dict_digger
 import json
-from seldon_core.utils import json_to_seldon_message, extract_request_parts
+from seldon_core.utils import json_to_seldon_message, extract_request_parts, array_to_grpc_datadef, seldon_message_to_json
+from seldon_core.proto import prediction_pb2
 import numpy as np
 
 app = Flask(__name__)
@@ -23,7 +24,7 @@ def index():
         if "date" in requestCopy:
             del requestCopy["date"]
         requestMsg = json_to_seldon_message(requestCopy)
-        (req_features, _, req_datadef, _) = extract_request_parts(requestMsg)
+        (req_features, _, req_datadef, req_datatype) = extract_request_parts(requestMsg)
         req_elements = createElelmentsArray(req_features,list(req_datadef.names))
 
     responsePart = dict_digger.dig(content,'response')
@@ -33,22 +34,30 @@ def index():
         if "date" in responseCopy:
             del responseCopy["date"]
         responseMsg = json_to_seldon_message(responseCopy)
-        (res_features, _, res_datadef, _) = extract_request_parts(responseMsg)
+        (res_features, _, res_datadef, res_datatype) = extract_request_parts(responseMsg)
         res_elements = createElelmentsArray(res_features,list(res_datadef.names))
 
     if not req_elements is None and not res_elements is None:
-        for (a,b) in zip(req_elements,res_elements):
+        for i,(a,b) in enumerate(zip(req_elements,res_elements)):
             merged = {**a, **b}
             content["elements"] = merged
+            reqJson = extractRow(i, requestMsg, req_datatype, req_features, req_datadef)
+            resJson = extractRow(i, responseMsg, res_datatype, res_features, res_datadef)
+            content["request"] = reqJson
+            content["response"] = resJson
             #log formatted json to stdout for fluentd collection
             print(str(json.dumps(content)))
     elif not req_elements is None:
-        for e in req_elements:
+        for i,e in enumerate(req_elements):
             content["elements"] = e
+            reqJson = extractRow(i, requestMsg, req_datatype, req_features, req_datadef)
+            content["request"] = reqJson
             print(str(json.dumps(content)))
     elif not res_elements is None:
-        for e in res_elements:
+        for i,e in enumerate(res_elements):
             content["elements"] = e
+            resJson = extractRow(i, responseMsg, res_datatype, res_features, res_datadef)
+            content["response"] = resJson
             print(str(json.dumps(content)))
     else:
         print(str(json.dumps(content)))
@@ -60,15 +69,32 @@ def index():
     #    print(e, file=sys.stderr)
     #    return 'Error processing input'
 
+
+def extractRow(i:int,requestMsg: prediction_pb2.SeldonMessage,req_datatype: str,req_features: np.ndarray,req_datadef: prediction_pb2.SeldonMessage.data):
+    if req_datatype == "data":
+        datatyReq = requestMsg.data.WhichOneof("data_oneof")
+    else:
+        datatyReq = "ndarray"
+    if len(req_features.shape) == 2:
+        dataReq = array_to_grpc_datadef(datatyReq, np.expand_dims(req_features[i], axis=0), req_datadef.names)
+    else:
+        dataReq = array_to_grpc_datadef(datatyReq, req_features, req_datadef.names)
+    requestMsg2 = prediction_pb2.SeldonMessage(data=dataReq, meta=requestMsg.meta)
+    reqJson = seldon_message_to_json(requestMsg2)
+    return reqJson
+
+
 def createElelmentsArray(X: np.ndarray,names: list):
-    results = []
+    results = None
     if isinstance(X,np.ndarray):
         if len(X.shape) == 1:
+            results = []
             d = {}
             for num, name in enumerate(names, start=0):
                 d[name] = X[num]
                 results.append(d)
         elif len(X.shape) == 2:
+            results = []
             for i in range(X.shape[0]):
                 d = {}
                 for num, name in enumerate(names, start=0):

seldon-request-logger/app/test.sh

@@ -0,0 +1,18 @@
+curl 0.0.0.0:8080 -d '{"request":{"data":{"names":["a","b"],"tensor":{"shape":[2,2],"values":[1,2,3,4]}}},"response":{"data":{"names":["c"],"tensor":{"shape":[2,1],"values":[5,6]}}}}' -H "Content-Type: application/json"
+
+
+curl 0.0.0.0:8080 -d '{"request":{"data":{"names":["a","b"],"ndarray":[[1,2],[3,4]]}},"response":{"data":{"names":["c"],"ndarray":[[7],[8]]}}}' -H "Content-Type: application/json"
+
+
+curl 0.0.0.0:8080 -d '{"request":{"data":{"names":["a","b"],"tensor":{"shape":[2,2],"values":[1,2,3,4]}}}}' -H "Content-Type: application/json"
+
+curl 0.0.0.0:8080 -d '{"response":{"data":{"names":["c"],"tensor":{"shape":[2,1],"values":[5,6]}}}}' -H "Content-Type: application/json"
+
+curl 0.0.0.0:8080 -d '{"request":{"data":{"names":["a","b"],"tensor":{"shape":[2,2,1],"values":[1,2,3,4]}}},"response":{"data":{"names":["c"],"tensor":{"shape":[2,1],"values":[5,6]}}}}' -H "Content-Type: application/json"
+
+
+
+
+
+
+