Katia Configuration

You can configure Katia with different parameters that will allow you to create different assistants with different behaviours.

Docker configuration

If you are running in local kafka, using the associated tutorial, you can customize some aspects of kafka deployment.

Zookeeper configuration

ZOOKEEPER_CLIENT_PORT:

Instructs ZooKeeper where to listen for connections by clients such as Apache Kafka®.
ZOOKEEPER_TICK_TIME:

This is only required when running in clustered mode. Sets the server ID in the myid file, which consists of a single line that contains only the text of that machine’s ID. For example, the myid of server 1 would only contain the text “1”. The ID must be unique within the ensemble and should have a value between 1 and 255.

Kafka configuration

KAFKA_ZOOKEEPER_CONNECT:

Instructs Kafka how to get in touch with ZooKeeper.
KAFKA_LISTENER_SECURITY_PROTOCOL_MAP:

Defines key/value pairs for the security protocol to use, per listener name. This is equivalent to the listener.security.protocol.map configuration parameter in the server properties file (<path-to-confluent>/etc/kafka/server.properties).
KAFKA_ADVERTISED_LISTENERS:

A comma-separated list of listeners with their the host/IP and port. This is the metadata that is passed back to clients. This is equivalent to the advertised.listeners configuration parameter in the server properties file (<path-to-confluent>/etc/kafka/server.properties).
KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR:

This setting defines the replication factor of the topic used to store the consumers offset. In the default case this is set to 1. So the consumer offsets for a particular topic will only be present on a single node. If that node goes down, consumers will lose track of where they are, since they can’t update the consumer offsets.
KAFKA_TRANSACTION_STATE_LOG_MIN_ISR:

The minimum ISR for this topic. This is equivalent to the transaction.state.log.min.isr configuration parameter in the server properties file (<path-to-confluent>/etc/kafka/server.properties).
KAFKA_TRANSACTION_STATE_LOG_REPLICATION_FACTOR:

The replication factor for the transaction topic (set higher to ensure availability). Internal topic creation will fail until the cluster size meets this replication factor requirement. This is equivalent to the transaction.state.log.replication.factor configuration parameter in the server properties file (<path-to-confluent>/etc/kafka/server.properties).
KAFKA_GROUP_INITIAL_REBALANCE_DELAY_MS:

The amount of time the group coordinator will wait for more consumers to join a new group before performing the first rebalance. A longer delay means potentially fewer rebalances, but increases the time until processing begins. This is equivalent to the group.initial.rebalance.delay.ms configuration parameter in the server properties file (<path-to-confluent>/etc/kafka/server.properties).

Katia service configuration

Kafka configuration

Both this configuration fields are mandatory, and Katia will not work unless she can connect to a kafka broker. As Katia is based on an architecture centered in kafka communication between services.

KAFKA_BROKER_URL: MANDATORY

This is your kafka url.
KAFKA_BROKER_PORT: MANDATORY

This is your kafka port.

General configuration

KATIA_LANGUAGE:
Language for Katia. You can use the standard codes for languages from ISO 639-1 and from ISO 3166-1.
en-US en-EN es-ES ...
KATIA_MAIN_NAME:

The name of the interpreter. It is used to generate the interpreter personality. As it will be the name used to define itself. We like Katia, but you can configure with the name you want for your assistant 🙂
KATIA_VALID_NAMES:

Sometimes the recognizer does not recognize well the name of the assistant, so here you can add the different valid pronunciations/names for your assistant. For example, for Katia should be also valid this list: "['katia', 'catia', 'catya', 'katya', 'cati', 'katy', 'caty', 'kati']"

Extra prompt

By default the prompt form Katia is very easy: You are a assistant called {name}.. But, you can add extra things to this prompt, like adjectives for the assistant, or extra text.

For that purpose you can use the following configurations:

KATIA_ADJECTIVES:

This will be a list of adjectives that will be placed before the assistant word in the initial prompt. So, for example "['funny', 'helpful', 'kind']" will produce the following prompt: You are a funny, helpful and kind assistant called {name}.
KATIA_EXTRA_DESCRIPTION:

This is parameter you want if you want to add extra behaviours for your assistant. It is a free text and you can add things like: You will always be very concise. and it will produce the following prompt: You are a assistant called {name}. You will always be very concise.

You can add very complex (and funny) things, like for example: You will always speak in verse with assonant rhyme., or you're always rapping like you're from a fucked up neighborhood, saying a lot of swear words..

We do not encourage to set up this last prompt if you are going to show Katia to your granny, unless your granny is a very tough granny. 👵

Recognizer configuration

RECOGNIZER_ENERGY_THRESHOLD:

This is the minimum audio energy to consider for recording. Under ‘ideal’ conditions
(such as in a quiet room), values between 0 and 100 are considered silent or ambient, and values 300 to about 3500 are considered speech.
RECOGNIZER_DYNAMIC_ENERGY_THRESHOLD:

With RECOGNIZER_DYNAMIC_ENERGY_THRESHOLD set to 'True', Katia will continuously try to re-adjust the energy threshold to match the environment based on the ambient noise level at that time.
RECOGNIZER_PAUSE_THRESHOLD:

Seconds of non-speaking audio before a phrase is considered complete for Katia.
RECOGNIZER_PHRASE_THRESHOLD:

Minimum seconds of speaking audio before we consider the speaking audio a phrase - values below this are ignored (for filtering out clicks and pops).
RECOGNIZER_NON_SPEAKING_DURATION:

Seconds of non-speaking audio to keep on both sides of the recording.
RECOGNIZER_STOPPER_EXTRA_WORDS:

List of words that can be added to the stopper sentences. This field is complementary to RECOGNIZER_STOPPER_SENTENCES. And it is ment to work together.
RECOGNIZER_STOPPER_SENTENCES:
List of sentences to use for katia to stop talking. This field is complementary to RECOGNIZER_STOPPER_EXTRA_WORDS. For example, you can use this values:
RECOGNIZER_STOPPER_EXTRA_WORDS="['hey', 'please']" RECOGNIZER_STOPPER_SENTENCES="['stop talking', 'shut up']"
And if you say something like: Hey Katia, stop talking please it will stop. But for something like Hey catia, can you shut up now please? it will not work. You should add can, you and now to RECOGNIZER_STOPPER_EXTRA_WORDS.
RECOGNIZER_CONTINUE_CONVERSATION_DELAY_IN_SECONDS:

Seconds to wait for the recognizer to stop conversation flux (so you have to call again the assistant). This is not since start talking but since Katia stopped talking.
RECOGNIZER_GAP_CONTINUE_CONVERSATION_IN_SECONDS:

Gap between when Katia stopped talking and before your next iteration with Katia. You can configure it to 0, but, the recognizer maybe get the Katia response as one of your answers, and Katia will start talking with herself.

In future this should be removed if using voice recognition instead of speech recognition.

Interpreter configuration

OPENAI_KEY: MANDATORY

This is your API key from openai. You can follow the tutorial about how to get one in the OPENAI setup tutorial

If the API key is not valid or if it is not set at all you will se an exception.
OPENAI_MODEL:

This is the model you want to use for chatgpt. You can check which ones you can use in the official documentation of OPENAI.

Speaker configuration

AWS_PROFILE_NAME:

This is your AWS profile for the speaker. You can follow the tutorial to get this well configured.
AWS_VOICE_NAME:

This is the model you want to use from Polly for your voice. You can pick one of the available ones provided by AWS Polly. (Name/ID value)

Remember that some of the voices does not support neural voice, so make sure you configure this value according to the AWS_ENGINE
AWS_ENGINE:

This is the type of engine you want to use for AWS Polly. The two values accepted are neural or standard. You can check the differences here.