def view_hello(request):
"""gRPC: Call from UI as a hearbeat"""
user_info = get_authenticated_user(request)
if not user_info.success:
return JsonResponse(get_json_error(user_info.err_msg))
# --------------------------------
# Behavioral logging
# --------------------------------
log_data = dict(session_key=get_session_key(request),
feature_id=ta2_static.HELLO,
activity_l1=bl_static.L1_SYSTEM_ACTIVITY,
activity_l2=bl_static.L2_APP_LAUNCH)
LogEntryMaker.create_ta2ta3_entry(user_info.result_obj, log_data)
# note: this is just a heartbeat, so no params are sent
#
# Begin to log D3M call
#
call_entry = None
if ServiceCallEntry.record_d3m_call():
call_entry = ServiceCallEntry.get_dm3_entry(\
request_obj=request,
call_type='Hello',
request_msg=('no params for this call'))
# Let's call the TA2!
#
resp_info = ta2_hello()
if not resp_info.success:
return JsonResponse(get_json_error(resp_info.err_msg))
json_str = resp_info.result_obj
# Convert JSON str to python dict - err catch here
# - let it blow up for now--should always return JSON
json_format_info = json_loads(json_str)
if not json_format_info.success:
return JsonResponse(get_json_error(json_format_info.err_msg))
# Save D3M log
#
if call_entry:
call_entry.save_d3m_response(json_format_info.result_obj)
json_info = get_json_success('success!',
data=json_format_info.result_obj)
return JsonResponse(json_info, safe=False)
def view_list_primitives(request):
"""gRPC: Call from UI with a ListPrimitivesRequest"""
user_info = get_authenticated_user(request)
if not user_info.success:
return JsonResponse(get_json_error(user_info.err_msg))
# --------------------------------
# (2) Begin to log D3M call
# --------------------------------
call_entry = None
if ServiceCallEntry.record_d3m_call():
call_entry = ServiceCallEntry.get_dm3_entry(\
request_obj=request,
call_type='ListPrimitives',
request_msg='no params for this call')
# --------------------------------
# (2a) Behavioral logging
# --------------------------------
log_data = dict(session_key=get_session_key(request),
feature_id=ta2_static.LIST_PRIMITIVES,
activity_l1=bl_static.L1_SYSTEM_ACTIVITY,
activity_l2=bl_static.L2_ACTIVITY_BLANK)
LogEntryMaker.create_ta2ta3_entry(user_info.result_obj, log_data)
# Let's call the TA2!
#
search_info = list_primitives()
#print('search_info', search_info)
if not search_info.success:
return JsonResponse(get_json_error(search_info.err_msg))
# Convert JSON str to python dict - err catch here
#
json_format_info = json_loads(search_info.result_obj)
if not json_format_info.success:
return JsonResponse(get_json_error(json_format_info.err_msg))
# Save D3M log
#
if call_entry:
call_entry.save_d3m_response(json_format_info.result_obj)
json_info = get_json_success('success!', data=json_format_info.result_obj)
return JsonResponse(json_info, safe=False)
def view_end_search_solutions(request):
"""gRPC: Call from UI with a EndSearchSolutionsRequest"""
print('view_end_search_solutions 1')
user_info = get_authenticated_user(request)
if not user_info.success:
return JsonResponse(get_json_error(user_info.err_msg))
user = user_info.result_obj
print('view_end_search_solutions 2')
req_body_info = get_request_body(request)
if not req_body_info.success:
return JsonResponse(get_json_error(req_body_info.err_msg))
print('view_end_search_solutions 3')
# --------------------------------
# Behavioral logging
# --------------------------------
log_data = dict(session_key=get_session_key(request),
feature_id=ta2_static.END_SEARCH_SOLUTIONS,
activity_l1=bl_static.L1_SYSTEM_ACTIVITY,
activity_l2=bl_static.L2_ACTIVITY_BLANK)
LogEntryMaker.create_ta2ta3_entry(user, log_data)
print('view_end_search_solutions 4')
# Let's call the TA2 and end the session!
#
params = dict(user=user)
search_info = end_search_solutions(req_body_info.result_obj,
**params)
if not search_info.success:
return JsonResponse(get_json_error(search_info.err_msg))
# The session is over, write the log entries files
#
#LogEntryMaker.write_user_log_from_request(request)
# User is done at this point!
# Write out the log and delete it....
user_workspace = None
ws_info = get_latest_user_workspace(request)
if ws_info.success:
user_workspace = ws_info.result_obj
ResetUtil.write_and_clear_behavioral_logs(user, user_workspace)
json_info = get_json_success('success!', data=search_info.result_obj)
return JsonResponse(json_info, safe=False)
def view_stop_search_solutions(request):
"""gRPC: Call from UI with a StopSearchSolutions"""
user_info = get_authenticated_user(request)
if not user_info.success:
return JsonResponse(get_json_error(user_info.err_msg))
req_body_info = get_request_body(request)
if not req_body_info.success:
return JsonResponse(get_json_error(req_body_info.err_msg))
# Begin to log D3M call
#
call_entry = None
if ServiceCallEntry.record_d3m_call():
call_entry = ServiceCallEntry.get_dm3_entry(\
request_obj=request,
call_type=ta2_static.STOP_SEARCH_SOLUTIONS,
request_msg=req_body_info.result_obj)
# --------------------------------
# Behavioral logging
# --------------------------------
log_data = dict(session_key=get_session_key(request),
feature_id=ta2_static.STOP_SEARCH_SOLUTIONS,
activity_l1=bl_static.L1_SYSTEM_ACTIVITY,
activity_l2=bl_static.L2_ACTIVITY_BLANK)
LogEntryMaker.create_ta2ta3_entry(user_info.result_obj, log_data)
# Let's call the TA2!
#
search_info = stop_search_solutions(req_body_info.result_obj)
#print('search_info', search_info)
if not search_info.success:
return JsonResponse(get_json_error(search_info.err_msg))
# Convert JSON str to python dict - err catch here
# - let it blow up for now--should always return JSON
json_dict = json.loads(search_info.result_obj, object_pairs_hook=OrderedDict)
# Save D3M log
#
if call_entry:
call_entry.save_d3m_response(json_dict)
json_info = get_json_success('success!', data=json_dict)
return JsonResponse(json_info, safe=False)
def run_describe_solution(self, pipeline_id, solution_id, msg_cnt=-1):
"""sync: Run a DescribeSolution call for each solution_id"""
print(f'run_describe_solution 1. pipeline_id: {pipeline_id}')
# ----------------------------------
# Create the input
# ----------------------------------
req_params = {ta2_static.KEY_SOLUTION_ID: solution_id}
json_str_info = json_dumps(req_params)
if not json_str_info.success:
self.add_err_msg(json_str_info.err_msg)
return
json_str_input = json_str_info.result_obj
# --------------------------------
# (2) Save request
# --------------------------------
stored_request = StoredRequest(\
user=self.user_object,
search_id=self.search_id,
pipeline_id=pipeline_id,
workspace='(not specified)',
request_type=ta2_static.DESCRIBE_SOLUTION,
is_finished=False,
request=req_params)
stored_request.save()
# --------------------------------
# (2a) Behavioral logging
# --------------------------------
log_data = dict(session_key=self.session_key,
feature_id=ta2_static.DESCRIBE_SOLUTION,
activity_l1=bl_static.L1_MODEL_SELECTION,
activity_l2=bl_static.L2_MODEL_SUMMARIZATION,
other=req_params)
LogEntryMaker.create_ta2ta3_entry(self.user_object, log_data)
print(
f'run_describe_solution 2. stored_request.pipeline_id: {stored_request.pipeline_id}'
)
# ----------------------------------
# Run Describe Solution
# ----------------------------------
describe_info = describe_solution(json_str_input)
if not describe_info.success:
self.add_err_msg(describe_info.err_msg)
StoredResponse.add_err_response(\
stored_request,
describe_info.err_msg)
return
# ----------------------------------
# Parse the DescribeSolutionResponse
# ----------------------------------
describe_data_info = json_loads(describe_info.result_obj)
if not describe_data_info.success:
self.add_err_msg(describe_data_info.err_msg)
StoredResponse.add_err_response(\
stored_request,
describe_data_info.err_msg)
return
# -----------------------------------------------
# Add the pipline id to the result
# -----------------------------------------------
describe_data = describe_data_info.result_obj
describe_data[ta2_static.KEY_PIPELINE_ID] = pipeline_id
describe_data[ta2_static.KEY_SEARCH_ID] = self.search_id
describe_data[ta2_static.KEY_SOLUTION_ID] = solution_id
describe_data.move_to_end(ta2_static.KEY_PIPELINE_ID, last=False)
# params = dict()
# if not stored_request.pipeline_id:
# params['pipeline_id'] = describe_data[KEY_PIPELINE_ID]
stored_info = StoredResponse.add_success_response(\
stored_request,
describe_data,
pipeline_id=pipeline_id)
if not stored_info.success:
print('stored info fail!', stored_info.err_msg)
print(
f'run_describe_solution 3. stored_info.result_obj.pipeline_id: {stored_info.result_obj.pipeline_id}'
)
print(
f'run_describe_solution 4. stored_request.pipeline_id: {stored_request.pipeline_id}'
)
# -----------------------------------------
# Tracking this in the behavioral log,
# e.g. checking time lapse between creation
# of solution and if user investigates this model,
# later, if at all
# -----------------------------------------
log_data = dict(session_key=self.session_key,
feature_id=ta2_static.DESCRIBE_SOLUTION_RESPONSE,
activity_l1=bl_static.L1_MODEL_SELECTION,
activity_l2=bl_static.L2_MODEL_SEARCH,
other=describe_data)
LogEntryMaker.create_ta2ta3_entry(self.user_object, log_data)
# -----------------------------------------------
# send responses back to WebSocket
# ---------------------------------------------
ws_msg = WebsocketMessage.get_success_message(\
'DescribeSolution',
'it worked',
msg_cnt=msg_cnt,
data=describe_data)
print('ws_msg: %s' % ws_msg)
#print('ws_msg', ws_msg.as_dict())
ws_msg.send_message(self.websocket_id)
def run_get_search_solution_results(self):
"""Run SearchSolutions against a TA2"""
# -----------------------------------
# (1) make GRPC request object
# -----------------------------------
params_dict = dict(searchId=self.search_id)
params_info = json_dumps(params_dict)
if not params_info.success:
self.send_websocket_err_msg(\
ta2_static.GET_SEARCH_SOLUTIONS_RESULTS,
params_info.err_msg)
return
try:
grpc_req = Parse(params_info.result_obj,
core_pb2.GetSearchSolutionsResultsRequest())
except ParseError as err_obj:
err_msg = ('GetSearchSolutionsResultsRequest: Failed to'
' convert JSON to gRPC: %s') % (err_obj)
self.send_websocket_err_msg(\
ta2_static.GET_SEARCH_SOLUTIONS_RESULTS,
params_info.err_msg)
return
# --------------------------------
# (2) Save the request to the db
# --------------------------------
stored_request = StoredRequest(\
user=self.user_object,
search_id=self.search_id,
workspace='(not specified)',
request_type=ta2_static.GET_SEARCH_SOLUTIONS_RESULTS,
is_finished=False,
request=params_dict)
stored_request.save()
# --------------------------------
# (2a) Behavioral logging
# --------------------------------
log_data = dict(session_key=self.session_key,
feature_id=ta2_static.GET_SEARCH_SOLUTIONS_RESULTS,
activity_l1=bl_static.L1_MODEL_SELECTION,
activity_l2=bl_static.L2_MODEL_SEARCH,
other=params_dict)
LogEntryMaker.create_ta2ta3_entry(self.user_object, log_data)
# --------------------------------
# (3) Make the gRPC request
# --------------------------------
core_stub, err_msg = TA2Connection.get_grpc_stub()
if err_msg:
return err_resp(err_msg)
msg_cnt = 0
try:
# -----------------------------------------
# Iterate through the streaming responses
# Note: The StoredResponse.id becomes the pipeline id
# -----------------------------------------
for reply in core_stub.GetSearchSolutionsResults(\
grpc_req, timeout=settings.TA2_GRPC_LONG_TIMEOUT):
msg_cnt += 1
# -----------------------------------------------
# Parse the response into JSON + store response
# -----------------------------------------------
msg_json_str = message_to_json(reply)
msg_json_info = json_loads(msg_json_str)
if not msg_json_info.success:
user_msg = 'Failed to convert response to JSON: %s' % \
msg_json_info.err_msg
self.send_websocket_err_msg(\
ta2_static.GET_SEARCH_SOLUTIONS_RESULTS,
user_msg)
StoredResponse.add_stream_err_response(\
stored_response, user_msg)
# Wait for next response....
continue
result_json = msg_json_info.result_obj
# TA2s (specifically NYU) responds once when trying a new pipeline, with a message missing a solutionId
# the same process responds again once the solution contains a solutionId
print('results json from TA2')
print(result_json)
if not result_json.get('solutionId'):
continue
if ta2_static.KEY_SOLUTION_ID not in result_json:
user_msg = '"%s" not found in response to JSON: %s' % \
(ta2_static.KEY_SOLUTION_ID, result_json)
StoredResponse.add_stream_err_response(\
stored_response, user_msg)
self.send_websocket_err_msg(\
ta2_static.GET_SEARCH_SOLUTIONS_RESULTS,
user_msg)
# Wait for next response....
continue
# Solution id used for DescribeSolution...
#
solution_id = result_json[ta2_static.KEY_SOLUTION_ID]
# -----------------------------------------
# Looks good, save the response
# -----------------------------------------
stored_resp_info = StoredResponse.add_stream_success_response(\
stored_request, result_json)
# -----------------------------------------
# Tracking this in the behavioral log,
# e.g. checking time lapse between creation
# of solution and if user investigates this model,
# later, if at all
# -----------------------------------------
log_data = dict(session_key=self.session_key,
feature_id=ta2_static.
GET_SEARCH_SOLUTIONS_RESULTS_RESPONSE,
activity_l1=bl_static.L1_MODEL_SELECTION,
activity_l2=bl_static.L2_MODEL_SEARCH,
other=result_json)
LogEntryMaker.create_ta2ta3_entry(self.user_object, log_data)
# -----------------------------------------
# Make sure the response was saved (probably won't happen)
# -----------------------------------------
if not stored_resp_info.success:
# Not good but probably won't happen
# send a message to the user...
#
user_msg = 'Failed to store response from %s: %s' % \
(ta2_static.GET_SEARCH_SOLUTIONS_RESULTS,
msg_json_info.err_msg)
StoredResponse.add_stream_err_response(\
stored_response, user_msg)
self.send_websocket_err_msg(\
ta2_static.GET_SEARCH_SOLUTIONS_RESULTS,
user_msg)
# Wait for the next response...
continue
# ---------------------------------------------
# Looks good! Get the StoredResponse
# - This id will be used as the pipeline id
# ---------------------------------------------
stored_response = stored_resp_info.result_obj
stored_response.use_id_as_pipeline_id()
StoredResponse.add_stream_success_response(\
stored_response, stored_response)
# -----------------------------------------------
# send responses back to WebSocket
# ---------------------------------------------
ws_msg = WebsocketMessage.get_success_message(\
ta2_static.GET_SEARCH_SOLUTIONS_RESULTS,
'it worked',
msg_cnt=msg_cnt,
data=stored_response.as_dict())
print('ws_msg: %s' % ws_msg)
#print('ws_msg', ws_msg.as_dict())
ws_msg.send_message(self.websocket_id)
stored_response.mark_as_sent_to_user()
print('msg received #%d' % msg_cnt)
# -----------------------------------------------
# continue the process describe/score/etc
# -----------------------------------------------
# DescribeSolution - run sync
#
self.run_describe_solution(stored_response.pipeline_id,
solution_id, msg_cnt)
# FitSolution - run async
#
print('PRE run_fit_solution')
self.run_fit_solution(stored_response.pipeline_id, solution_id)
print('POST run_fit_solution')
print('PRE run_score_solution')
self.run_score_solution(stored_response.pipeline_id,
solution_id)
print('POST run_score_solution')
# -----------------------------------------------
# All results arrived, send message to UI
# -----------------------------------------------
ws_msg = WebsocketMessage.get_success_message( \
ta2_static.ENDGetSearchSolutionsResults,
{'searchId': self.search_id, 'message': 'it worked'})
print('ws_msg: %s' % ws_msg)
ws_msg.send_message(self.websocket_id)
except grpc.RpcError as err_obj:
stored_request.set_error_status(str(err_obj))
return
except Exception as err_obj:
stored_request.set_error_status(str(err_obj))
return
StoredRequestUtil.set_finished_ok_status(stored_request.id)
def make_search_solutions_call(all_params, websocket_id, user_id,
**kwargs):
"""Return the result of a SearchSolutions call.
If successful, an async process is kicked off"""
if not websocket_id:
return err_resp('websocket_id must be set')
print('make_search_solutions_call 1')
param_check = SearchSolutionsHelper.check_params(all_params)
if not param_check.success:
return param_check
print('make_search_solutions_call 2')
try:
user_obj = User.objects.get(pk=user_id)
except User.DoesNotExist:
user_msg = 'No user found for id: %s' % user_id
return err_resp(user_msg)
search_solution_params = all_params[
ta2_static.KEY_SEARCH_SOLUTION_PARAMS]
# --------------------------------
# (2) Logging
# --------------------------------
stored_request = StoredRequest(\
user=user_obj,
# search_id=self.search_id,
workspace='(not specified)',
request_type=ta2_static.SEARCH_SOLUTIONS,
is_finished=False,
request=search_solution_params)
stored_request.save()
# --------------------------------
# (2a) Behavioral logging
# --------------------------------
session_key = kwargs.get(SESSION_KEY, None)
log_data = dict(session_key=session_key,
feature_id=ta2_static.SEARCH_SOLUTIONS,
activity_l1=bl_static.L1_MODEL_SELECTION,
activity_l2=bl_static.L2_MODEL_SEARCH,
other=search_solution_params)
LogEntryMaker.create_ta2ta3_entry(user_obj, log_data)
# 11/6/2019 - late night hack, these variables shouldn't be here
# - introduced somewhere in the .js when setting a problem
#
search_solution_params.pop('id', None)
search_solution_params.pop('session_key', None)
# Run SearchSolutions against the TA2
#
search_info = search_solutions(search_solution_params)
if not search_info.success:
StoredResponse.add_err_response(stored_request,
search_info.err_msg)
return search_info
print('make_search_solutions_call 2')
search_info_json = json_loads(search_info.result_obj)
if not search_info_json.success:
StoredResponse.add_err_response(stored_request,
search_info_json.err_msg)
return search_info_json
search_info_data = search_info_json.result_obj
print('search_info_data', json_dumps(search_info_data)[1])
print('make_search_solutions_call 3')
if not ta2_static.KEY_SEARCH_ID in search_info_data:
user_msg = 'searchId not found in the SearchSolutionsResponse'
StoredResponse.add_err_response(stored_request, user_msg)
return err_resp(user_msg)
search_id = search_info_data['searchId']
StoredResponse.add_success_response(stored_request,
search_info_data,
search_id=search_id)
# Async task to run GetSearchSolutionsResults
#
extra_params = {SESSION_KEY: session_key}
SearchSolutionsHelper.kick_off_solution_results.delay(\
search_id, websocket_id, user_id,
all_search_params=all_params,
**extra_params)
# Back to the UI, looking good
#
return ok_resp(search_info_data)
def run_get_score_solution_responses(self, request_id):
"""(2) Run GetScoreSolutionResults"""
if self.has_error():
return
if not request_id:
self.send_websocket_err_msg(ta2_static.GET_SCORE_SOLUTION_RESULTS,
'request_id must be set')
return
# -----------------------------------
# (1) make GRPC request object
# -----------------------------------
params_dict = {ta2_static.KEY_REQUEST_ID: request_id}
params_info = json_dumps(params_dict)
try:
grpc_req = Parse(params_info.result_obj,
core_pb2.GetScoreSolutionResultsRequest())
except ParseError as err_obj:
err_msg = ('Failed to convert JSON to gRPC: %s') % (err_obj)
self.send_websocket_err_msg(ta2_static.GET_SCORE_SOLUTION_RESULTS,
err_msg)
return
# --------------------------------
# (2) Save the request to the db
# --------------------------------
stored_request = StoredRequest(\
user=self.user_object,
request_type=ta2_static.GET_SCORE_SOLUTION_RESULTS,
search_id=self.search_id,
pipeline_id=self.pipeline_id,
is_finished=False,
request=params_dict)
stored_request.save()
# --------------------------------
# (2a) Behavioral logging
# --------------------------------
log_data = dict(session_key=self.session_key,
feature_id=ta2_static.GET_SCORE_SOLUTION_RESULTS,
activity_l1=bl_static.L1_MODEL_SELECTION,
activity_l2=bl_static.L2_MODEL_SUMMARIZATION,
other=params_dict)
LogEntryMaker.create_ta2ta3_entry(self.user_object, log_data)
# --------------------------------
# (3) Make the gRPC request
# --------------------------------
core_stub, err_msg = TA2Connection.get_grpc_stub()
if err_msg:
return err_resp(err_msg)
msg_cnt = 0
try:
# -----------------------------------------
# Iterate through the streaming responses
# Note: The StoredResponse.id becomes the pipeline id
# -----------------------------------------
for reply in core_stub.GetScoreSolutionResults(\
grpc_req, timeout=settings.TA2_GRPC_LONG_TIMEOUT):
msg_cnt += 1
stored_response = None # to hold a StoredResponse object
# -----------------------------------------------
# Parse the response into JSON + store response
# -----------------------------------------------
msg_json_str = message_to_json(reply)
msg_json_info = json_loads(msg_json_str)
if not msg_json_info.success:
err_msg = ('Failed to convert JSON to gRPC: %s') % \
(err_obj,)
StoredResponse.add_stream_err_response(
stored_request, user_msg)
self.send_websocket_err_msg(\
ta2_static.GET_SCORE_SOLUTION_RESULTS,
err_msg)
# Wait for next response....
continue
result_json = msg_json_info.result_obj
# -----------------------------------------
# Looks good, save the response
# -----------------------------------------
stored_resp_info = StoredResponse.add_stream_success_response(\
stored_request, result_json)
# -----------------------------------------
# Make sure the response was saved (probably won't happen)
# -----------------------------------------
if not stored_resp_info.success:
# Not good but probably won't happen
# send a message to the user...
#
self.send_websocket_err_msg(\
ta2_static.GET_SCORE_SOLUTION_RESULTS,
stored_resp_info.err_msg)
#
StoredResponse.add_stream_err_response(\
stored_request, stored_resp_info.err_msg)
#
continue
# ---------------------------------------------
# Looks good! Get the StoredResponse
# - send responses back to WebSocket
# ---------------------------------------------
stored_response = stored_resp_info.result_obj
stored_response.set_pipeline_id(self.pipeline_id)
# ---------------------------------------------
# If progress is complete,
# send response back to WebSocket
# ---------------------------------------------
progress_val = get_dict_value(\
result_json,
[ta2_static.KEY_PROGRESS,
ta2_static.KEY_PROGRESS_STATE])
if (not progress_val.success) or \
(progress_val.result_obj != ta2_static.KEY_PROGRESS_COMPLETED):
user_msg = 'GetScoreSolutionResultsResponse is not yet complete'
LOGGER.info(user_msg)
# wait for next message...
continue
ws_msg = WebsocketMessage.get_success_message(\
ta2_static.GET_SCORE_SOLUTION_RESULTS,
'it worked',
msg_cnt=msg_cnt,
data=stored_response.as_dict())
LOGGER.info('ws_msg: %s' % ws_msg)
#print('ws_msg', ws_msg.as_dict())
ws_msg.send_message(self.websocket_id)
# stored_response.mark_as_sent_to_user()
except grpc.RpcError as err_obj:
stored_request.set_error_status(str(err_obj))
return
except Exception as err_obj:
stored_request.set_error_status(str(err_obj))
return
StoredRequestUtil.set_finished_ok_status(stored_request.id)
def run_process(self):
"""(1) Run ScoreSolution"""
if self.has_error():
return
# ----------------------------------
# Create the input
# ----------------------------------
LOGGER.info('ScoreSolutionHelper.run_process 2')
json_str_info = json_dumps(self.score_params)
if not json_str_info.success:
self.add_err_msg(json_str_info.err_msg)
return
json_str_input = json_str_info.result_obj
# ----------------------------------
# (2) Save the request
# ----------------------------------
stored_request = StoredRequest(\
user=self.user_object,
search_id=self.search_id,
pipeline_id=self.pipeline_id,
workspace='(not specified)',
request_type=ta2_static.SCORE_SOLUTION,
is_finished=False,
request=self.score_params)
stored_request.save()
# --------------------------------
# (2a) Behavioral logging
# --------------------------------
log_data = dict(session_key=self.session_key,
feature_id=ta2_static.SCORE_SOLUTION,
activity_l1=bl_static.L1_MODEL_SELECTION,
activity_l2=bl_static.L2_MODEL_SUMMARIZATION,
other=self.score_params)
LogEntryMaker.create_ta2ta3_entry(self.user_object, log_data)
# ----------------------------------
# Run ScoreSolution
# ----------------------------------
LOGGER.info('run ScoreSolution: %s', json_str_input)
fit_info = score_solution(json_str_input)
if not fit_info.success:
print('ScoreSolution err_msg: ', fit_info.err_msg)
StoredResponse.add_err_response(stored_request, fit_info.err_msg)
self.send_websocket_err_msg(ta2_static.SCORE_SOLUTION,
fit_info.err_msg)
return
# ----------------------------------
# Parse the ScoreSolutionResponse
# ----------------------------------
response_info = json_loads(fit_info.result_obj)
if not response_info.success:
print('ScoreSolution grpc err_msg: ', response_info.err_msg)
StoredResponse.add_err_response(stored_request,
response_info.err_msg)
self.send_websocket_err_msg(ta2_static.SCORE_SOLUTION,
response_info.err_msg)
return
result_json = response_info.result_obj
# ----------------------------------
# Get the requestId
# ----------------------------------
if not ta2_static.KEY_REQUEST_ID in result_json:
user_msg = (' "%s" not found in response to JSON: %s') % \
(ta2_static.KEY_REQUEST_ID, result_json)
StoredResponse.add_err_response(stored_request, user_msg)
self.send_websocket_err_msg(ta2_static.SCORE_SOLUTION, user_msg)
return
StoredResponse.add_success_response(stored_request, result_json)
self.run_get_score_solution_responses(
result_json[ta2_static.KEY_REQUEST_ID])
def solution_export3(user, raven_json, **kwargs):
"""
Send a SolutionExportRequest to the SolutionExport command
"""
if not isinstance(user, User):
err_msg = '"user" must be a User object'
return err_resp(err_msg)
if not isinstance(raven_json, dict):
err_msg = 'raven_dict must be a python dict'
return err_resp(err_msg)
if not ta2_static.KEY_SEARCH_ID in raven_json:
err_msg = (f'Key: "{ta2_static.KEY_SEARCH_ID}" not found in the'
f' "raven_json" dict. (solution_export3)')
return err_resp(err_msg)
search_id = raven_json.pop(
ta2_static.KEY_SEARCH_ID) # not needed for GRPC call
session_key = kwargs.get(SESSION_KEY, '')
# --------------------------------
# Convert dict to string
# --------------------------------
raven_json_info = json_dumps(raven_json)
if not raven_json_info.success:
return err_resp(raven_json_info.err_msg)
raven_json_str = raven_json_info.result_obj
# --------------------------------
# convert the JSON string to a gRPC request
# --------------------------------
try:
req = Parse(raven_json_str, core_pb2.SolutionExportRequest())
except ParseError as err_obj:
err_msg = 'Failed to convert JSON to gRPC: %s' % (err_obj)
return err_resp(err_msg)
# In test mode, return canned response
#
if settings.TA2_STATIC_TEST_MODE:
resp = core_pb2.SolutionExportResponse()
return ok_resp(message_to_json(resp))
core_stub, err_msg = TA2Connection.get_grpc_stub()
if err_msg:
return err_resp(err_msg)
# --------------------------------
# Save the request to the db
# --------------------------------
stored_request = StoredRequest(\
user=user,
search_id=search_id,
workspace='(not specified)',
request_type=ta2_static.SOLUTION_EXPORT,
is_finished=False,
request=raven_json)
stored_request.save()
# --------------------------------
# Behavioral logging
# --------------------------------
log_data = dict(session_key=session_key,
feature_id=ta2_static.SOLUTION_EXPORT,
activity_l1=bl_static.L1_MODEL_SELECTION,
activity_l2=bl_static.L2_MODEL_EXPORT,
other=raven_json)
LogEntryMaker.create_ta2ta3_entry(user, log_data)
# --------------------------------
# Send the gRPC request
# --------------------------------
try:
reply = core_stub.SolutionExport(\
req,
timeout=settings.TA2_GRPC_SHORT_TIMEOUT)
except Exception as err_obj:
user_msg = f'Error: {err_obj}'
StoredResponse.add_err_response(stored_request, user_msg)
return err_resp(user_msg)
# --------------------------------
# Convert the reply to JSON and send it back
# --------------------------------
resp_json_str = message_to_json(reply)
resp_json_dict_info = json_loads(resp_json_str)
if not resp_json_dict_info.success:
user_msg = (f'Failed to convert GRPC response to JSON:'
f' {resp_json_dict_info.err_msg}')
StoredResponse.add_err_response(stored_request, user_msg)
return err_resp(user_msg)
StoredResponse.add_success_response(stored_request,
resp_json_dict_info.result_obj)
return ok_resp(resp_json_str)
def run_process(self):
"""(1) Run ProduceSolution"""
if self.has_error():
return
# ----------------------------------
# Create the input
# ----------------------------------
json_str_info = json_dumps(self.produce_params)
if not json_str_info.success:
self.add_err_msg(json_str_info.err_msg)
return
json_str_input = json_str_info.result_obj
# --------------------------------
# (2) Save the request to the db
# --------------------------------
req_type = ta2_static.PRODUCE_SOLUTION
stored_request = StoredRequest(\
user=self.user_object,
request_type=req_type,
pipeline_id=self.pipeline_id,
search_id=self.search_id,
is_finished=False,
request=self.produce_params)
stored_request.save()
# --------------------------------
# (2a) Behavioral logging
# --------------------------------
log_data = dict(session_key=self.session_key,
feature_id=ta2_static.PRODUCE_SOLUTION,
activity_l1=bl_static.L1_MODEL_SELECTION,
activity_l2=bl_static.L2_MODEL_EXPLANATION,
other=self.produce_params)
LogEntryMaker.create_ta2ta3_entry(self.user_object, log_data)
# ----------------------------------
# Run FitSolution
# ----------------------------------
produce_info = produce_solution(json_str_input)
if not produce_info.success:
StoredResponse.add_err_response(stored_request,
produce_info.err_msg)
self.send_websocket_err_msg(ta2_static.PRODUCE_SOLUTION,
produce_info.err_msg)
return
# ----------------------------------
# Parse the ProduceSolutionResponse
# ----------------------------------
response_info = json_loads(produce_info.result_obj)
if not response_info.success:
StoredResponse.add_err_response(stored_request,
response_info.err_msg)
self.send_websocket_err_msg(ta2_static.PRODUCE_SOLUTION,
response_info.err_msg)
return
result_json = response_info.result_obj
# ----------------------------------
# Get the requestId
# ----------------------------------
if not ta2_static.KEY_REQUEST_ID in result_json:
user_msg = (' "%s" not found in response to JSON: %s') % \
(ta2_static.KEY_REQUEST_ID, result_json)
#
StoredResponse.add_err_response(stored_request,
user_msg)
#
self.send_websocket_err_msg(ta2_static.PRODUCE_SOLUTION, user_msg)
return
# Store success response
#
StoredResponse.add_success_response(stored_request, result_json)
print('produce 3')
self.run_get_produce_solution_responses(result_json[ta2_static.KEY_REQUEST_ID])