Build your first skill - search & discovery
This guide will take you through the development of your first skill. It will teach you, how to connect the AEA to the digital world, register the AEA and search for other AEAs.
Although one can imagine scenarios where a single AEA pursues its goals in isolation without interacting with other AEAs, there is no doubt that by working together, AEAs can achieve much more. To do so, an AEA must be seen and found by other AEAs so that they can trade and do other useful things. Fetch.ai’s search-and-discovery mechanism, the simple OEF (or SOEF, for short) lets your agents register, be discovered, and find other agents. You can then negotiate using the AEA framework’s peer-to-peer network (ACN) and trade. This guide covers getting your AEA connected to the SOEF, and describing your AEA to make itself visible.
Registering your AEA with the SOEF involves setting a name, a genus (a high-level description of what the agent represents, e.g. vehicle, building or service), a classification (for example infrastructure.railway.train) and other descriptors to further fine-tune the kind of service your AEA offers (for example, the agent's position, whether it buys or sells, and other descriptive items).
The more you describe your AEA, the easier it is for others to find it using specific filters.
Dependencies (Required)¶
Follow the Preliminaries and Installation sections from the AEA quick start.
Step 1: Setup¶
We will first create an AEA and add a scaffold skill, which we call my_search.
In the following steps, we replace the scaffolded Behaviour and Handler in my_aea/skills/my_search with our implementation. We will build a simple skill which lets the AEA send a search query to the SOEF search node and process the resulting response.
Step 2: Develop a Behaviour¶
A Behaviour class contains the business logic specific to actions initiated by the AEA rather than reactions to other events.
In this example, we implement a simple search behaviour. Each time, act() gets called by the main agent loop, we will send a search request to the SOEF search node via the P2P communication network.
from typing import cast
from aea.helpers.search.models import Constraint, ConstraintType, Location, Query
from aea.skills.behaviours import TickerBehaviour
from packages.fetchai.protocols.oef_search.message import OefSearchMessage
from packages.fetchai.skills.my_search.dialogues import OefSearchDialogues
DEFAULT_LOCATION = {"longitude": 0.1270, "latitude": 51.5194}
DEFAULT_SEARCH_QUERY = {
"search_key": "seller_service",
"search_value": "generic_service",
"constraint_type": "==",
}
DEFAULT_SEARCH_RADIUS = 5.0
class MySearchBehaviour(TickerBehaviour):
"""This class provides a simple search behaviour."""
def __init__(self, **kwargs):
"""Initialize the search behaviour."""
search_query = kwargs.pop("search_query", DEFAULT_SEARCH_QUERY)
location = kwargs.pop("location", DEFAULT_LOCATION)
agent_location = Location(latitude=location["latitude"], longitude=location["longitude"])
radius = kwargs.pop("search_radius", DEFAULT_SEARCH_RADIUS)
close_to_my_service = Constraint(
"location", ConstraintType("distance", (agent_location, radius))
)
service_key_filter = Constraint(
search_query["search_key"],
ConstraintType(
search_query["constraint_type"], search_query["search_value"],
),
)
self.query = Query([close_to_my_service, service_key_filter])
super().__init__(**kwargs)
self.sent_search_count = 0
def setup(self) -> None:
"""
Implement the setup.
:return: None
"""
self.context.logger.info(
"setting up MySearchBehaviour"
)
def act(self) -> None:
"""
Implement the act.
:return: None
"""
self.sent_search_count += 1
oef_search_dialogues = cast(
OefSearchDialogues, self.context.oef_search_dialogues
)
self.context.logger.info(
"sending search request to OEF search node, search_count={}".format(
self.sent_search_count
)
)
search_request, _ = oef_search_dialogues.create(
counterparty=self.context.search_service_address,
performative=OefSearchMessage.Performative.SEARCH_SERVICES,
query=self.query,
)
self.context.outbox.put_message(message=search_request)
def teardown(self) -> None:
"""
Implement the task teardown.
:return: None
"""
self.context.logger.info(
"tearing down MySearchBehaviour"
)
Searches are proactive and, as such, well placed in a Behaviour. Specifically, we subclass the TickerBehaviour as it allows us to repeatedly search at a defined tick interval.
We place this code in my_aea/skills/my_search/behaviours.py. Ensure you replace the fetchai author in this line from packages.fetchai.skills.my_search.dialogues import OefSearchDialogues with your author handle (run aea init to set or check the author name).
Note
Note that the import paths to agent packages, for example packages.fetchai.skills.my_search.dialogues above, are not actual paths. Package files always reside in your AEA's folder, either under a specific package directory (e.g. connection, protocol, skill) if the package is custom built, or under vendor if it is pulled from the registry. These paths are virtual and created automatically when an AEA is run. See this page for more details.
Step 3: Develop a Handler¶
So far, we have tasked the AEA with sending search requests to the SOEF search node. However, we have no way of handling the responses sent to the AEA by the SOEF search node at the moment. The AEA would simply respond to the SOEF search node via the default error skill which sends all unrecognised envelopes back to the sender.
Let us now implement a Handler to deal with the incoming search responses.
from typing import Optional, cast
from aea.protocols.base import Message
from aea.skills.base import Handler
from packages.fetchai.protocols.oef_search.message import OefSearchMessage
from packages.fetchai.skills.my_search.dialogues import (
OefSearchDialogue,
OefSearchDialogues,
)
class MySearchHandler(Handler):
"""This class provides a simple search handler."""
SUPPORTED_PROTOCOL = OefSearchMessage.protocol_id
def __init__(self, **kwargs):
"""Initialize the handler."""
super().__init__(**kwargs)
self.received_search_count = 0
def setup(self) -> None:
"""Set up the handler."""
self.context.logger.info(
"setting up MySearchHandler"
)
def handle(self, message: Message) -> None:
"""
Implement the reaction to a message.
:param message: the message
:return: None
"""
oef_search_msg = cast(OefSearchMessage, message)
# recover dialogue
oef_search_dialogues = cast(
OefSearchDialogues, self.context.oef_search_dialogues
)
oef_search_dialogue = cast(
Optional[OefSearchDialogue], oef_search_dialogues.update(oef_search_msg)
)
if oef_search_dialogue is None:
self._handle_unidentified_dialogue(oef_search_msg)
return
# handle message
if oef_search_msg.performative is OefSearchMessage.Performative.OEF_ERROR:
self._handle_error(oef_search_msg, oef_search_dialogue)
elif oef_search_msg.performative is OefSearchMessage.Performative.SEARCH_RESULT:
self._handle_search(oef_search_msg, oef_search_dialogue)
else:
self._handle_invalid(oef_search_msg, oef_search_dialogue)
def _handle_unidentified_dialogue(self, oef_search_msg: OefSearchMessage) -> None:
"""
Handle an unidentified dialogue.
:param msg: the message
"""
self.context.logger.info(
"received invalid oef_search message={}, unidentified dialogue.".format(
oef_search_msg
)
)
def _handle_error(
self, oef_search_msg: OefSearchMessage, oef_search_dialogue: OefSearchDialogue
) -> None:
"""
Handle an oef search message.
:param oef_search_msg: the oef search message
:param oef_search_dialogue: the dialogue
:return: None
"""
self.context.logger.info(
"received oef_search error message={} in dialogue={}.".format(
oef_search_msg, oef_search_dialogue
)
)
def _handle_search(
self, oef_search_msg: OefSearchMessage, oef_search_dialogue: OefSearchDialogue
) -> None:
"""
Handle the search response.
:param agents: the agents returned by the search
:return: None
"""
self.received_search_count += 1
nb_agents_found = len(oef_search_msg.agents)
self.context.logger.info(
"found number of agents={}, received search count={}".format(
nb_agents_found, self.received_search_count
)
)
self.context.logger.info(
"number of search requests sent={} vs. number of search responses received={}".format(
self.context.behaviours.my_search_behaviour.sent_search_count,
self.received_search_count,
)
)
def _handle_invalid(
self, oef_search_msg: OefSearchMessage, oef_search_dialogue: OefSearchDialogue
) -> None:
"""
Handle an oef search message.
:param oef_search_msg: the oef search message
:param oef_search_dialogue: the dialogue
:return: None
"""
self.context.logger.warning(
"cannot handle oef_search message of performative={} in dialogue={}.".format(
oef_search_msg.performative, oef_search_dialogue,
)
)
def teardown(self) -> None:
"""
Teardown the handler.
:return: None
"""
self.context.logger.info(
"tearing down MySearchHandler"
)
We create a handler which is registered for the oef_search protocol. Whenever it receives a search result, we log the number of agents returned in the search - the agents matching the search query - and update the counter of received searches.
We also implement a trivial check on the difference between the amount of search requests sent and responses received.
Note, how the handler simply reacts to incoming events (i.e. messages). It could initiate further actions, however, they are still reactions to the upstream search event.
Also note, how we have access to other objects in the skill via self.context, the SkillContext.
We place this code in my_aea/skills/my_search/handlers.py. Ensure you replace the fetchai author in this line from packages.fetchai.skills.my_search.dialogues import ( with your author handle (run aea init to set or check the author name).
Step 4: Add dialogues model¶
We have implemented a behaviour and a handler. We now implement a Model, in particular we implement the Dialogue and Dialogues classes. These ensure that the message flow satisfies the fetchai/oef_search:1.0.0 protocol and keep track of the individual messages being sent and received.
from aea.protocols.base import Message
from aea.protocols.dialogue.base import Dialogue as BaseDialogue
from aea.skills.base import Address, Model
from packages.fetchai.protocols.oef_search.dialogues import (
OefSearchDialogue as BaseOefSearchDialogue,
)
from packages.fetchai.protocols.oef_search.dialogues import (
OefSearchDialogues as BaseOefSearchDialogues,
)
OefSearchDialogue = BaseOefSearchDialogue
class OefSearchDialogues(Model, BaseOefSearchDialogues):
"""This class keeps track of all oef_search dialogues."""
def __init__(self, **kwargs) -> None:
"""
Initialize dialogues.
:param agent_address: the address of the agent for whom dialogues are maintained
:return: None
"""
Model.__init__(self, **kwargs)
def role_from_first_message( # pylint: disable=unused-argument
message: Message, receiver_address: Address
) -> BaseDialogue.Role:
"""Infer the role of the agent from an incoming/outgoing first message
:param message: an incoming/outgoing first message
:param receiver_address: the address of the receiving agent
:return: The role of the agent
"""
return BaseOefSearchDialogue.Role.AGENT
BaseOefSearchDialogues.__init__(
self,
self_address=str(self.skill_id),
role_from_first_message=role_from_first_message,
)
We add this code in the file my_aea/skills/my_search/my_model.py, replacing its original content. We then rename my_aea/skills/my_search/my_model.py to my_aea/skills/my_search/dialogues.py.
Step 5: Create the configuration file¶
Based on our skill components above, we create the following configuration file.
name: my_search
author: fetchai
version: 0.1.0
type: skill
description: A simple search skill utilising the SOEF search node.
license: Apache-2.0
aea_version: '>=1.0.0, <2.0.0'
fingerprint: {}
fingerprint_ignore_patterns: []
connections: []
contracts: []
protocols:
- fetchai/oef_search:1.1.2
skills: []
behaviours:
my_search_behaviour:
args:
location:
latitude: 51.5194
longitude: 0.127
search_query:
constraint_type: ==
search_key: seller_service
search_value: generic_service
search_radius: 5.0
tick_interval: 5
class_name: MySearchBehaviour
handlers:
my_search_handler:
args: {}
class_name: MySearchHandler
models:
oef_search_dialogues:
args: {}
class_name: OefSearchDialogues
dependencies:
aea-ledger-fetchai:
version: <2.0.0,>=1.0.0
is_abstract: false
Ensure, you replace the author field with your author name! (Run aea init to set or check the author name.)
Importantly, the keys my_search_behaviour and my_search_handler are used in the above handler to access these skill components at runtime via the context. We also set the tick_interval of the TickerBehaviour to 5 seconds.
We place this code in my_aea/skills/my_search/skill.yaml.
Similarly, we replace my_aea/skills/my_search/__init__.py as follows:
# -*- coding: utf-8 -*-
# ------------------------------------------------------------------------------
#
# Copyright 2018-2019 Fetch.AI Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# ------------------------------------------------------------------------------
"""This module contains the implementation of the error skill."""
from aea.configurations.base import PublicId
PUBLIC_ID = PublicId.from_str("fetchai/my_search:0.1.0")
Step 6: Update fingerprint¶
To run an AEA with new or modified code, you need to update the fingerprint of the new/modified components. In this case, we need to fingerprint our skill:
Ensure, you use the correct author name to reference your skill (here we usefetchai as the author.)
Step 7: Add the OEF protocol and connection¶
Our AEA does not have the OEF protocol yet so let's add it.
This adds the protocol to our AEA and makes it available on the path packages.fetchai.protocols....
At this point we need to add the SOEF and P2P connections to allow the AEA to communicate with the SOEF node and other AEAs, install the AEA's dependencies, and configure the AEA:
aea add connection fetchai/soef:0.27.2
aea add connection fetchai/p2p_libp2p:0.27.1
aea install
aea build
aea config set agent.default_connection fetchai/p2p_libp2p:0.27.1
aea config set --type dict agent.default_routing \
'{
"fetchai/oef_search:1.1.2": "fetchai/soef:0.27.2"
}'
The last command will ensure that search requests are processed by the correct connection.
Step 8: Run a service provider AEA¶
In order for this AEA to find another AEA when searching, the second AEA (let's call it the service provider AEA) must exist and have been registered with the SOEF.
From a different terminal window, we fetch a finished service provider AEA and install its Python dependencies:
aea fetch fetchai/simple_service_registration:0.32.1 && cd simple_service_registration && aea install && aea build
This AEA will simply register a location service on the SOEF search node so we can search for it.
We first create the private key for the service provider AEA based on the network you want to transact. To generate and add a private-public key pair for Fetch.ai Dorado use:
Next, create a private key used to secure the AEA's communications:
aea generate-key fetchai fetchai_connection_private_key.txt
aea add-key fetchai fetchai_connection_private_key.txt --connection
Finally, certify the key for use by the connections that request that:
Then we run the AEA:
Once you see a message of the form To join its network use multiaddr: ['SOME_ADDRESS'] take note of the address. (Alternatively, use aea get-multiaddress fetchai -c -i fetchai/p2p_libp2p:0.27.1 -u public_uri to retrieve the address.) This is the entry peer address for the local agent communication network created by the simple_service_registration (service provider) AEA.
Click here to see full code and guide for this AEA
We use a TickerBehaviour to update the service registration at regular intervals. The following code is placed in behaviours.py.
from typing import Any, Optional, cast
from aea.helpers.search.models import Description
from aea.skills.behaviours import TickerBehaviour
from packages.fetchai.protocols.oef_search.message import OefSearchMessage
from packages.fetchai.skills.simple_service_registration.dialogues import (
OefSearchDialogues,
)
from packages.fetchai.skills.simple_service_registration.strategy import Strategy
DEFAULT_MAX_SOEF_REGISTRATION_RETRIES = 5
DEFAULT_SERVICES_INTERVAL = 30.0
class ServiceRegistrationBehaviour(TickerBehaviour):
"""This class implements a behaviour."""
def __init__(self, **kwargs: Any) -> None:
"""Initialise the behaviour."""
services_interval = kwargs.pop(
"services_interval", DEFAULT_SERVICES_INTERVAL
) # type: int
self._max_soef_registration_retries = kwargs.pop(
"max_soef_registration_retries", DEFAULT_MAX_SOEF_REGISTRATION_RETRIES
) # type: int
super().__init__(tick_interval=services_interval, **kwargs)
self.failed_registration_msg = None # type: Optional[OefSearchMessage]
self._nb_retries = 0
def setup(self) -> None:
"""
Implement the setup.
:return: None
"""
self._register_agent()
def act(self) -> None:
"""
Implement the act.
:return: None
"""
self._retry_failed_registration()
def teardown(self) -> None:
"""
Implement the task teardown.
:return: None
"""
self._unregister_service()
self._unregister_agent()
def _retry_failed_registration(self) -> None:
"""
Retry a failed registration.
:return: None
"""
if self.failed_registration_msg is not None:
self._nb_retries += 1
if self._nb_retries > self._max_soef_registration_retries:
self.context.is_active = False
return
oef_search_dialogues = cast(
OefSearchDialogues, self.context.oef_search_dialogues
)
oef_search_msg, _ = oef_search_dialogues.create(
counterparty=self.failed_registration_msg.to,
performative=self.failed_registration_msg.performative,
service_description=self.failed_registration_msg.service_description,
)
self.context.outbox.put_message(message=oef_search_msg)
self.context.logger.info(
f"Retrying registration on SOEF. Retry {self._nb_retries} out of {self._max_soef_registration_retries}."
)
self.failed_registration_msg = None
def _register(self, description: Description, logger_msg: str) -> None:
"""
Register something on the SOEF.
:param description: the description of what is being registered
:param logger_msg: the logger message to print after the registration
:return: None
"""
oef_search_dialogues = cast(
OefSearchDialogues, self.context.oef_search_dialogues
)
oef_search_msg, _ = oef_search_dialogues.create(
counterparty=self.context.search_service_address,
performative=OefSearchMessage.Performative.REGISTER_SERVICE,
service_description=description,
)
self.context.outbox.put_message(message=oef_search_msg)
self.context.logger.info(logger_msg)
def _register_agent(self) -> None:
"""
Register the agent's location.
:return: None
"""
strategy = cast(Strategy, self.context.strategy)
description = strategy.get_location_description()
self._register(description, "registering agent on SOEF.")
def register_service(self) -> None:
"""
Register the agent's service.
:return: None
"""
strategy = cast(Strategy, self.context.strategy)
description = strategy.get_register_service_description()
self._register(description, "registering agent's service on the SOEF.")
def register_genus(self) -> None:
"""
Register the agent's personality genus.
:return: None
"""
strategy = cast(Strategy, self.context.strategy)
description = strategy.get_register_personality_description()
self._register(
description, "registering agent's personality genus on the SOEF."
)
def register_classification(self) -> None:
"""
Register the agent's personality classification.
:return: None
"""
strategy = cast(Strategy, self.context.strategy)
description = strategy.get_register_classification_description()
self._register(
description, "registering agent's personality classification on the SOEF."
)
def _unregister_service(self) -> None:
"""
Unregister service from the SOEF.
:return: None
"""
strategy = cast(Strategy, self.context.strategy)
description = strategy.get_unregister_service_description()
oef_search_dialogues = cast(
OefSearchDialogues, self.context.oef_search_dialogues
)
oef_search_msg, _ = oef_search_dialogues.create(
counterparty=self.context.search_service_address,
performative=OefSearchMessage.Performative.UNREGISTER_SERVICE,
service_description=description,
)
self.context.outbox.put_message(message=oef_search_msg)
self.context.logger.info("unregistering service from SOEF.")
def _unregister_agent(self) -> None:
"""
Unregister agent from the SOEF.
:return: None
"""
strategy = cast(Strategy, self.context.strategy)
description = strategy.get_location_description()
oef_search_dialogues = cast(
OefSearchDialogues, self.context.oef_search_dialogues
)
oef_search_msg, _ = oef_search_dialogues.create(
counterparty=self.context.search_service_address,
performative=OefSearchMessage.Performative.UNREGISTER_SERVICE,
service_description=description,
)
self.context.outbox.put_message(message=oef_search_msg)
self.context.logger.info("unregistering agent from SOEF.")
Model type strategy class and place it in strategy.py. We use a generic data model to register the service. As part of the registration we register a location and a key pair describing our service.
from typing import Any
from aea.exceptions import enforce
from aea.helpers.search.generic import (
AGENT_LOCATION_MODEL,
AGENT_PERSONALITY_MODEL,
AGENT_REMOVE_SERVICE_MODEL,
AGENT_SET_SERVICE_MODEL,
)
from aea.helpers.search.models import Description, Location
from aea.skills.base import Model
DEFAULT_LOCATION = {"longitude": 0.1270, "latitude": 51.5194}
DEFAULT_SERVICE_DATA = {"key": "seller_service", "value": "generic_service"}
DEFAULT_PERSONALITY_DATA = {"piece": "genus", "value": "data"}
DEFAULT_CLASSIFICATION = {"piece": "classification", "value": "seller"}
class Strategy(Model):
"""This class defines a strategy for the agent."""
def __init__(self, **kwargs: Any) -> None:
"""
Initialize the strategy of the agent.
:return: None
"""
location = kwargs.pop("location", DEFAULT_LOCATION)
self._agent_location = {
"location": Location(
latitude=location["latitude"], longitude=location["longitude"]
)
}
self._set_personality_data = kwargs.pop(
"personality_data", DEFAULT_PERSONALITY_DATA
)
enforce(
len(self._set_personality_data) == 2
and "piece" in self._set_personality_data
and "value" in self._set_personality_data,
"personality_data must contain keys `key` and `value`",
)
self._set_classification = kwargs.pop("classification", DEFAULT_CLASSIFICATION)
enforce(
len(self._set_classification) == 2
and "piece" in self._set_classification
and "value" in self._set_classification,
"classification must contain keys `key` and `value`",
)
self._set_service_data = kwargs.pop("service_data", DEFAULT_SERVICE_DATA)
enforce(
len(self._set_service_data) == 2
and "key" in self._set_service_data
and "value" in self._set_service_data,
"service_data must contain keys `key` and `value`",
)
self._remove_service_data = {"key": self._set_service_data["key"]}
super().__init__(**kwargs)
def get_location_description(self) -> Description:
"""
Get the location description.
:return: a description of the agent's location
"""
description = Description(
self._agent_location, data_model=AGENT_LOCATION_MODEL,
)
return description
def get_register_service_description(self) -> Description:
"""
Get the register service description.
:return: a description of the offered services
"""
description = Description(
self._set_service_data, data_model=AGENT_SET_SERVICE_MODEL,
)
return description
def get_register_personality_description(self) -> Description:
"""
Get the register personality description.
:return: a description of the personality
"""
description = Description(
self._set_personality_data, data_model=AGENT_PERSONALITY_MODEL,
)
return description
def get_register_classification_description(self) -> Description:
"""
Get the register classification description.
:return: a description of the classification
"""
description = Description(
self._set_classification, data_model=AGENT_PERSONALITY_MODEL,
)
return description
def get_unregister_service_description(self) -> Description:
"""
Get the unregister service description.
:return: a description of the to be removed service
"""
description = Description(
self._remove_service_data, data_model=AGENT_REMOVE_SERVICE_MODEL,
)
return description
Model type dialogue class and place it in dialogues.py. These classes ensure that the message flow satisfies the fetchai/oef_search:1.0.0 protocol and keep track of the individual messages being sent and received.
from typing import Any
from aea.protocols.base import Address, Message
from aea.protocols.dialogue.base import Dialogue as BaseDialogue
from aea.skills.base import Model
from packages.fetchai.protocols.oef_search.dialogues import (
OefSearchDialogue as BaseOefSearchDialogue,
)
from packages.fetchai.protocols.oef_search.dialogues import (
OefSearchDialogues as BaseOefSearchDialogues,
)
OefSearchDialogue = BaseOefSearchDialogue
class OefSearchDialogues(Model, BaseOefSearchDialogues):
"""This class keeps track of all oef_search dialogues."""
def __init__(self, **kwargs: Any) -> None:
"""
Initialize dialogues.
:param agent_address: the address of the agent for whom dialogues are maintained
:return: None
"""
Model.__init__(self, **kwargs)
def role_from_first_message( # pylint: disable=unused-argument
message: Message, receiver_address: Address
) -> BaseDialogue.Role:
"""Infer the role of the agent from an incoming/outgoing first message
:param message: an incoming/outgoing first message
:param receiver_address: the address of the receiving agent
:return: The role of the agent
"""
return BaseOefSearchDialogue.Role.AGENT
BaseOefSearchDialogues.__init__(
self,
self_address=str(self.skill_id),
role_from_first_message=role_from_first_message,
)
handlers.py. The handler deals with handling any error messages which might occur during service registration:
from typing import Optional, cast
from aea.configurations.base import PublicId
from aea.protocols.base import Message
from aea.skills.base import Handler
from packages.fetchai.protocols.oef_search.message import OefSearchMessage
from packages.fetchai.skills.simple_service_registration.behaviours import (
ServiceRegistrationBehaviour,
)
from packages.fetchai.skills.simple_service_registration.dialogues import (
OefSearchDialogue,
OefSearchDialogues,
)
class OefSearchHandler(Handler):
"""This class implements an OEF search handler."""
SUPPORTED_PROTOCOL = OefSearchMessage.protocol_id # type: Optional[PublicId]
def setup(self) -> None:
"""Call to setup the handler."""
def handle(self, message: Message) -> None:
"""
Implement the reaction to a message.
:param message: the message
:return: None
"""
oef_search_msg = cast(OefSearchMessage, message)
# recover dialogue
oef_search_dialogues = cast(
OefSearchDialogues, self.context.oef_search_dialogues
)
oef_search_dialogue = cast(
Optional[OefSearchDialogue], oef_search_dialogues.update(oef_search_msg)
)
if oef_search_dialogue is None:
self._handle_unidentified_dialogue(oef_search_msg)
return
# handle message
if oef_search_msg.performative == OefSearchMessage.Performative.SUCCESS:
self._handle_success(oef_search_msg, oef_search_dialogue)
elif oef_search_msg.performative == OefSearchMessage.Performative.OEF_ERROR:
self._handle_error(oef_search_msg, oef_search_dialogue)
else:
self._handle_invalid(oef_search_msg, oef_search_dialogue)
def teardown(self) -> None:
"""
Implement the handler teardown.
:return: None
"""
def _handle_unidentified_dialogue(self, oef_search_msg: OefSearchMessage) -> None:
"""
Handle an unidentified dialogue.
:param msg: the message
"""
self.context.logger.info(
"received invalid oef_search message={}, unidentified dialogue.".format(
oef_search_msg
)
)
def _handle_success(
self,
oef_search_success_msg: OefSearchMessage,
oef_search_dialogue: OefSearchDialogue,
) -> None:
"""
Handle an oef search message.
:param oef_search_success_msg: the oef search message
:param oef_search_dialogue: the dialogue
:return: None
"""
self.context.logger.info(
"received oef_search success message={} in dialogue={}.".format(
oef_search_success_msg, oef_search_dialogue
)
)
target_message = cast(
OefSearchMessage,
oef_search_dialogue.get_message_by_id(oef_search_success_msg.target),
)
if (
target_message.performative
== OefSearchMessage.Performative.REGISTER_SERVICE
):
description = target_message.service_description
data_model_name = description.data_model.name
registration_behaviour = cast(
ServiceRegistrationBehaviour, self.context.behaviours.service,
)
if "location_agent" in data_model_name:
registration_behaviour.register_service()
elif "set_service_key" in data_model_name:
registration_behaviour.register_genus()
elif (
"personality_agent" in data_model_name
and description.values["piece"] == "genus"
):
registration_behaviour.register_classification()
elif (
"personality_agent" in data_model_name
and description.values["piece"] == "classification"
):
self.context.logger.info(
"the agent, with its genus and classification, and its service are successfully registered on the SOEF."
)
else:
self.context.logger.warning(
f"received soef SUCCESS message as a reply to the following unexpected message: {target_message}"
)
def _handle_error(
self,
oef_search_error_msg: OefSearchMessage,
oef_search_dialogue: OefSearchDialogue,
) -> None:
"""
Handle an oef search message.
:param oef_search_error_msg: the oef search message
:param oef_search_dialogue: the dialogue
:return: None
"""
self.context.logger.info(
"received oef_search error message={} in dialogue={}.".format(
oef_search_error_msg, oef_search_dialogue
)
)
target_message = cast(
OefSearchMessage,
oef_search_dialogue.get_message_by_id(oef_search_error_msg.target),
)
if (
target_message.performative
== OefSearchMessage.Performative.REGISTER_SERVICE
):
registration_behaviour = cast(
ServiceRegistrationBehaviour, self.context.behaviours.service,
)
registration_behaviour.failed_registration_msg = target_message
def _handle_invalid(
self, oef_search_msg: OefSearchMessage, oef_search_dialogue: OefSearchDialogue
) -> None:
"""
Handle an oef search message.
:param oef_search_msg: the oef search message
:param oef_search_dialogue: the dialogue
:return: None
"""
self.context.logger.warning(
"cannot handle oef_search message of performative={} in dialogue={}.".format(
oef_search_msg.performative, oef_search_dialogue,
)
)
skill.yaml is:
name: simple_service_registration
author: fetchai
version: 0.20.0
type: skill
description: The simple service registration skills is a skill to register a service.
license: Apache-2.0
aea_version: '>=1.0.0, <2.0.0'
fingerprint:
README.md: QmUgCcR7sDBQeeCBRKwDT7tPBTi3t4zSibyEqR3xdQUKmh
__init__.py: QmZd48HmYDr7FMxNaVeGfWRvVtieEdEV78hd7h7roTceP2
behaviours.py: QmQHf6QL5aBtLJ34D2tdcbjJLbzom9gaA3HWgRn3rWyigM
dialogues.py: QmTT9dvFhWt6qvxjwBfMFDTrgEtgWbvgANYafyRg2BXwcR
handlers.py: QmZqPt8toGbJgTT6NZBLxjkusrQCZ8GmUEwcmqZ1sd7DpG
strategy.py: QmVXfQpk4cjDw576H2ELE12tEiN5brPkwvffvcTeMbsugA
fingerprint_ignore_patterns: []
connections: []
contracts: []
protocols:
- fetchai/oef_search:1.1.2
skills: []
behaviours:
service:
args:
max_soef_registration_retries: 5
services_interval: 30
class_name: ServiceRegistrationBehaviour
handlers:
oef_search:
args: {}
class_name: OefSearchHandler
models:
oef_search_dialogues:
args: {}
class_name: OefSearchDialogues
strategy:
args:
classification:
piece: classification
value: seller
location:
latitude: 51.5194
longitude: 0.127
personality_data:
piece: genus
value: data
service_data:
key: seller_service
value: generic_service
class_name: Strategy
dependencies: {}
is_abstract: false
Step 9: Run the Search AEA¶
First, create the private key for the search AEA based on the network you want to transact. To generate and add a private-public key pair for Fetch.ai Dorado use:
Next, create a private key used to secure the AEA's communications:
aea generate-key fetchai fetchai_connection_private_key.txt
aea add-key fetchai fetchai_connection_private_key.txt --connection
Finally, certify the key for use by the connections that request that:
Then, in the search AEA, run this command (replace SOME_ADDRESS with the correct value as described above):
aea config set --type dict vendor.fetchai.connections.p2p_libp2p.config \
'{
"delegate_uri": "127.0.0.1:11001",
"entry_peers": ["/dns4/127.0.0.1/tcp/9000/p2p/16Uiu2HAm1uJpFsqSgHStJdtTBPpDme1fo8uFEvvY182D2y89jQuj"],
"local_uri": "127.0.0.1:9001",
"log_file": "libp2p_node.log",
"public_uri": "127.0.0.1:9001"
}'
We can then launch our AEA.
We can see that the AEA sends search requests to the SOEF search node and receives search responses from the SOEF search node. The search response returns one or more agents (the service provider and potentially other agents which match the query).
We stop the AEA with CTRL + C.
Next steps¶
Recommended¶
We recommend you continue with the next step in the 'Getting Started' series:
Relevant deep-dives¶
This guide goes through a more elaborate scenario than the one on this page, where after finding each other, the two AEAs negotiate and trade via a ledger.