def query_parser(sid, data):
logging.info("inside query parser.....")
logging.info(data)
x = self.get_logical_form(s=data["chat"], model=self.model)
logging.info(x)
payload = {"action_dict": x}
sio.emit("renderActionDict", payload)
def save_command_to_db(sid, postData):
print("in save_command_to_db, got postData: %r" % (postData))
# save the command and fetch all
out = saveAndFetchCommands(self.conn, postData)
if out == "DUPLICATE":
print("Duplicate command not saved.")
else:
print("Saved successfully")
payload = {"commandList": out}
sio.emit("updateSearchList", payload)
def maybe_dump_memory_to_dashboard(self):
if time.time() - self.dashboard_memory_dump_time > MEMORY_DUMP_KEYFRAME_TIME:
self.dashboard_memory_dump_time = time.time()
memories_main = self.memory._db_read("SELECT * FROM Memories")
triples = self.memory._db_read("SELECT * FROM Triples")
reference_objects = self.memory._db_read("SELECT * FROM ReferenceObjects")
named_abstractions = self.memory._db_read("SELECT * FROM NamedAbstractions")
self.dashboard_memory["db"] = {
"memories": memories_main,
"triples": triples,
"reference_objects": reference_objects,
"named_abstractions": named_abstractions,
}
sio.emit("memoryState", self.dashboard_memory["db"])
def log(self, rgb_depth, detections, humans, old_rgb_depth, old_xyz):
"""Log all relevant data from the perceptual models for the dashboard.
All the data here is sent to the dashboard using a socketio emit event. This data
is then used by the dashboard for different debugging visualizations. Add any data
that you would want to fetch on the dashboard here.
Args:
rgb_depth (RGBDepth): the current RGBDepth frame. This frame might be different from
old_rgb_depth, which is the RGBDepth frame for which SlowPerception has been run
detections (list[Detections]): list of all detections
humans (list[Human]): list of all humans detected
old_rgb_depth (RGBDepth): RGBDepth frame for which detections and humans are being sent.
This is the frame for which SlowPerception has been run.
old_xyz (list[floats]): the (x,y,yaw) of the robot at the time of old_rgb_depth
"""
if hasattr(sio, "mock"):
return
sio.emit("image_settings", self.log_settings)
if old_xyz is None:
x, y, yaw = self.agent.mover.get_base_pos_in_canonical_coords()
else:
x, y, yaw = old_xyz
resolution = self.log_settings["image_resolution"]
quality = self.log_settings["image_quality"]
payload = {}
payload["time"] = time.time()
payload["image"] = rgb_depth.to_struct(resolution, quality)
payload["object_image"] = (old_rgb_depth.to_struct(
resolution, quality) if old_rgb_depth is not None else -1)
payload["objects"] = [x.to_struct() for x in detections
] if detections is not None else []
payload["humans"] = [x.to_struct()
for x in humans] if humans is not None else []
payload["x"] = x
payload["y"] = y
payload["yaw"] = yaw
payload["map"] = self.agent.mover.get_obstacles_in_canonical_coords()
sio.emit("sensor_payload", payload)
def send_text_command_to_agent(sid, command):
"""Add the command to agent's incoming chats list and
send back the parse.
Args:
command: The input text command from dashboard player
Returns:
return back a socket emit with parse of command and success status
"""
logging.debug(
"in send_text_command_to_agent, got the command: %r" %
(command))
agent_chat = (
"<dashboard> " + command
) # the chat is coming from a player called "dashboard"
self.dashboard_chat = agent_chat
dialogue_manager = self.dialogue_manager
logical_form = {}
status = ""
try:
logical_form = dialogue_manager.get_logical_form(
s=command, model=dialogue_manager.model)
logging.debug("logical form is : %r" % (logical_form))
status = "Sent successfully"
except:
logging.error("error in sending chat")
status = "Error in sending chat"
# update server memory
self.dashboard_memory["chatResponse"][command] = logical_form
self.dashboard_memory["chats"].pop(0)
self.dashboard_memory["chats"].append({
"msg": command,
"failed": False
})
payload = {
"status": status,
"chat": command,
"chatResponse": self.dashboard_memory["chatResponse"][command],
"allChats": self.dashboard_memory["chats"],
}
sio.emit("setChatResponse", payload)
def send_chat(self, chat: str):
logging.info("Sending chat: {}".format(chat))
# Send the socket event to show this reply on dashboard
sio.emit("showAssistantReply", {'agent_reply' : "Agent: {}".format(chat)})
self.memory.add_chat(self.memory.self_memid, chat)
def update_log_settings(sid, new_values):
self.log_settings["image_resolution"] = new_values["image_resolution"]
self.log_settings["image_quality"] = new_values["image_quality"]
sio.emit("image_settings", self.log_settings)
def objects_in_memory(sid):
objects = loco_memory.DetectedObjectNode.get_all(self.agent.memory)
for o in objects:
del o["feature_repr"]
self.agent.dashboard_memory["objects"] = objects
sio.emit("updateState", {"memory": self.agent.dashboard_memory})
def get_cmds_from_db(sid, postData):
print("in get_cmds_from_db, got postData: %r" % (postData))
out = onlyFetchCommands(self.conn, postData["query"])
payload = {"commandList": out}
sio.emit("updateSearchList", payload)
