Reducing the YouTube response time by 90%

In this blog post, we are going to cover how the audio from Youtube is being used in SUSI Smart Speaker and how we reduced the response time from ~40 seconds to ~4 seconds for an average music video length.

First Approach

Earlier, we were using MPV player’s inbuilt feature to fetch the YouTube music. However, MPV player was a bulky option and the music server had to be started every time before initiating a music video.

video_process = subprocess.Popen([‘mpv’, ‘–no-video’, ‘https://www.youtube.com/watch?v=’ + video_url[4:], ‘–really-quiet’]) # nosec #pylint-disable type: ignore requests.get(‘http://localhost:7070/song/’ + video_url) self.video_process = video_process stopAction.run() stopAction.detector.terminate()

Making it Efficient

To reduce the response time, we created a custom Music Server based on Flask,python-vlc and python-pafy which accepts requests from the main client and instructs the System to play the music with just 90% more efficiency.

app = Flask(__name__)

Instance = vlc.Instance(‘–no-video’)

player = Instance.media_player_new()

url = @app.route(‘/song’, methods=[‘GET’])

def youtube():

    vid = request.args.get(‘vid’)

    url = ‘https://www.youtube.com/watch?v=’ + vid

    video = pafy.new(url)
    streams = video.audiostreams 

    best = streams[3]

    playurl = best.url

    Media = Instance.media_new(playurl)

    Media.get_mrl()

    player.set_media(Media)

    player.play()

    display_message = {“song”:“started”}

    resp = jsonify(display_message)

    resp.status_code = 200

    return resp

However, shifting to this Server removed the ability to process multiple queries and hence we were unable to pause/play/stop the music until it completed the time duration. We wanted to retain the ability to have ‘play/pause/stop’ actions without implementing multiprocessing or multithreading as it would’ve required extensive testing to successfully implement them without creating deadlocks and would’ve been overkill for a simple feature.

Bringing Back the Lost Functionalities

The first Step we took was to remove the vlc-python module and implement a way to obtain an URL that we use in another asynchronous music player.

@app.route(‘/song’, methods=[‘GET’])
def youtube():

    vid = request.args.get(‘vid’)

    streams = video.audiostreams

    best = streams[3]

    playurl = best.url 

    display_message = {“song”: “started”, “url”: playurl}

    resp = jsonify(display_message)

    resp.status_code = 200

    return resp

The next issue was to actually find a way to run the Music Player asynchronously. We used the `subprocess. Popen` method and cvlc to play the songs asynchronously.

try:

    x = requests.get(‘http://localhost:7070/song?vid=’ + video_url[4:])

    data = x.json()

    url = data[‘url’]

    video_process = subprocess.Popen([‘cvlc’, ‘http’ + url[5:], ‘–no-video’])

    self.video_process = video_process

except Exception as e:

    logger.error(e);

And this is how we were able to increase the efficiency of the music player while maintaining the functionalities.

References

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A Workflow of Auto Executing Services on SUSI.AI Smart Speaker

As we plan to create a headless client on RaspberryPi, the requirement was that the SUSI.AI programs should run automatically. To do so, we had to figure out a way to boot up various scripts on startup.

We had the following options to execute the scripts on startup:

  1. Editing Rc.local file
  2. Systemd Rules
  3. Crontab

We decided to proceed with Systemd Rules because using Rc.local and Crontab requires modifying the default system files which in case of any error would make the os functionalities to crash very soon.

We then created the SystemD rules for the following services:

1.factory-daemon.service
2. python-flask.service
3. susi-server.service
4. update-daemon.service
5. susi-linux.service

Now I’ll demonstrate the working and the functionality of each service being implemented.

1. Factory-Daemon Service

This service initiates the factory daemon with the raspberry Pi startup and then keeps it running continuously looking for any input from the GPiO port.

[Unit]
Description=SUSI Linux Factory Daemon
After=multi-user.target

[Service]
Type=simple
ExecStart=/usr/bin/python3 /home/pi/SUSI.AI/susi_linux/factory_reset/factory_reset.py

[Install]
WantedBy=multi-user.target

2. Python-Flask Service

This service starts a python Server to allow handshake between mobile apps and the Smart Speaker which will allow the user to configure SUSI Smart Speaker accordingly.

[Unit]
Description=Python Server for SUSI Linux
After=multi-user.target

[Service]
Type=simple
ExecStart=/usr/bin/python3  /home/pi/SUSI.AI/susi_linux/access_point/server/server.py

[Install]
WantedBy=multi-user.target

3.SUSI-Server Service

This service starts the Local SUSI Server as soon as the Raspberry Pi starts up which in turn allows the SUSI Linux programs to fetch responses of queries very quickly.

[Unit]
Description=Starting SUSI Server for SUSI Linux
After=multi-user.target

[Service]
Type=oneshot
ExecStart=/home/pi/SUSI.AI/susi_linux/susi_server/susi_server/bin/restart.sh

[Install]
WantedBy=multi-user.target

4. Update-Daemon Service

This Service creates a Daemon which starts with the Raspberry Pi and fetches the latest updates from the repository from the upstream branch.

[Unit]
Description=Update Check- SUSI Linux
Wants=network-online.target
After=network-online.target

[Service]
Type=oneshot
ExecStart=/home/pi/SUSI.AI/susi_linux/update_daemon/update_check.sh

[Install]
WantedBy=multi-user.target

5. SUSI-Linux Service

This Service finally runs the main SUSI Linux software after everything has started.

[Unit]
Description=Starting SUSI Linux
Wants=network-online.target
After=network-online.target

[Service]
Type=idle
WorkingDirectory=/home/pi/SUSI.AI/susi_linux/
ExecStart=/usr/bin/python3 -m main

[Install]
WantedBy=multi-user.target

This blog gives a brief workflow of auto-executing services on SUSI Smart Speaker.

Resources

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Configuring LED Lights with SUSI Smart Speaker

To make the SUSI Smart Speaker more interactive and to improve the visual aesthetics, we configured SUSI Smart Speaker’s response with 3 RGB led lights. We have used a new piHat as an external hardware to configure the LEDs.

Now the new hardware specs of the SUSI Smart Speaker are:

  1. Raspberry Pi
  2. ReSpeaker PiHat 2 Mic Array
  3. External Speakers

Using an external PiHat not only added the RGB light functionality but also eliminated the need to use a USB microphone and configured a factory reset button

Configuring the PiHat as the default Audio driver

To Use the PiHat as the default input driver, we use the package called PulseAudio.

And we use the following command in the installation script.

pacmd set-sink-port alsa_output.platform-soc_sound.analog-stereo analog-output-headphones

Configuring PiHat’s GPIO Button with Factory Reset

There is an onboard User Button, which is connected to GPIO17. We use the python library RPi.GPIO to detect the user button. The python script is used in the following way

GPIO.setmode(GPIO.BCM)
GPIO.setup(17,GPIO.IN)
i = 1
while True:
if GPIO.input(17) == 1:
       time.sleep(0.1)
       pass
   elif GPIO.input(17) == 0 :
       start = time.time()
       while GPIO.input(17) == 0 :
           time.sleep(0.1)
       end = time.time()
       total = end – start
       if total >= 7 :
           subprocess.call([‘bash’,‘factory_reset.sh’])  # nosec #pylint-disable type: ignore
       else :
           mixer = alsaaudio.Mixer()
           value = mixer.getvolume()[0]
           if value != 0:
               mixer.setvolume(0)
           else:
               mixer.setvolume(50)
       print(total)
       time.sleep(0.1)

 

This script checks on the button which is configured on GPIO port 17 on the PiHat. If the button is pressed for than 7 secs, the factory reset process takes place, else the device is muted.

Configuring PiHat’s LED with Speaker’s Response

We use a python library called SPIDEV to sync the LED lights with SUSI’s response. SPIDEV is usually used to send a response to the bus devices on the Raspberry Pi.

The first step was installing spidev

sudo pip install spidev

Now we create a class where we store all the methods where we send the signal to the bus port. We treat the LED lights as a circular array and then have a rotation of RGB lights

class LED_COLOR:
    # Constants
   MAX_BRIGHTNESS = 0b11111    LED_START = 0b11100000
    def __init__(self, num_led, global_brightness=MAX_BRIGHTNESS,
                order=‘rgb’, bus=0, device=1, max_speed_hz=8000000):
       self.num_led = num_led
       order = order.lower()
       self.rgb = RGB_MAP.get(order, RGB_MAP[‘rgb’])
       if global_brightness > self.MAX_BRIGHTNESS:
           self.global_brightness = self.MAX_BRIGHTNESS
       else:
           self.global_brightness = global_brightness
        self.leds = [self.LED_START, 0, 0, 0] * self.num_led
       self.spi = spidev.SpiDev()
       self.spi.open(bus, device)
       if max_speed_hz:
           self.spi.max_speed_hz = max_speed_hz
    def clear_strip(self):
        for led in range(self.num_led):
           self.set_pixel(led, 0, 0, 0)
       self.show()
    def set_pixel(self, led_num, red, green, blue, bright_percent=100):
       if led_num < 0:
           return          if led_num >= self.num_led:
           return
       brightness = int(ceil(bright_percent * self.global_brightness / 100.0))
       ledstart = (brightness & 0b00011111) | self.LED_START
        start_index = 4 * led_num
       self.leds[start_index] = ledstart
       self.leds[start_index + self.rgb[0]] = red
       self.leds[start_index + self.rgb[1]] = green
       self.leds[start_index + self.rgb[2]] = blue
    def set_pixel_rgb(self, led_num, rgb_color, bright_percent=100):
       self.set_pixel(led_num, (rgb_color & 0xFF0000) >> 16,
                      (rgb_color & 0x00FF00) >> 8, rgb_color & 0x0000FF, bright_percent)
    def rotate(self, positions=1):
       cutoff = 4 * (positions % self.num_led)
       self.leds = self.leds[cutoff:] + self.leds[:cutoff]
    def show(self):
       data = list(self.leds)
       while data:
           self.spi.xfer2(data[:32])
           data = data[32:]
       self.clock_end_frame()
    def cleanup(self):
       self.spi.close()  # Close SPI port
    def wheel(self, wheel_pos):
       “””Get a color from a color wheel; Green -> Red -> Blue -> Green”””
        if wheel_pos > 255:
           wheel_pos = 255  # Safeguard
       if wheel_pos < 85:  # Green -> Red
           return self.combine_color(wheel_pos * 3, 255 – wheel_pos * 3, 0)
       if wheel_pos < 170:  # Red -> Blue
           wheel_pos -= 85
           return self.combine_color(255 – wheel_pos * 3, 0, wheel_pos * 3)
       wheel_pos -= 170
       return self.combine_color(0, wheel_pos * 3, 255 – wheel_pos * 3)

 

Now we use the threading to create non-blocking code which will allow SUSI to send response as well as change the LED’s simultaneously.

class Lights:
   LIGHTS_N = 3
    def __init__(self):
        self.next = threading.Event()
       self.queue = Queue.Queue()
       self.thread = threading.Thread(target=self._run)
       self.thread.daemon = True
       self.thread.start()
    def wakeup(self, direction=0):
       def f():
           self._wakeup(direction)
        self.next.set()
       self.queue.put(f)
    def listen(self):
       self.next.set()
       self.queue.put(self._listen)
    def think(self):
       self.next.set()
       self.queue.put(self._think)
    def speak(self):
       self.next.set()
       self.queue.put(self._speak)
    def off(self):
       self.next.set()
       self.queue.put(self._off)

This is how LED lights are configured with SUSI’s response

Resources

Additional Resources

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Connecting the Smart Speaker with Mobile Clients

The beauty of SUSI Smart Speaker lies in it being customizable according to the user’s needs. And we allow the user to customize it by providing an interface through the mobile clients. To do so, we create a local server on the Raspberry Pi itself. The Raspberry Pi is started in an Access Point mode and the mobile clients hit the endpoints in a specific order and then the configuration is sent to the server and stored according to the user.

 

The following API’s are required to be executed by the mobile clients

1> /speaker_config

2> /wifi_credentials

3> /auth

4> /config

 

The following is the order of API execution

1. /speaker_config

This endpoint only takes the room name as a parameter. And then send send to the server to store the location of the device under the user’s account

def speaker_config():
   room_name = request.args.get(‘room_name’)
   config = json_config.connect(config_json_folder)
   config[‘room_name’] = rogom_name

 

2. /wifi_credentials

This endpoint takes the wifi ssid and wifi password as the parameters and then stores it in the raspberry Pi wifi config file.

 

def wifi_config():
   wifi_ssid = request.args.get(‘wifissid’)
   wifi_password = request.args.get(‘wifipassd’)
   subprocess.call([‘sudo’, ‘bash’, wifi_search_folder + ‘/wifi_search.sh’, wifi_ssid, wifi_password])
   display_message = {“wifi”:“configured”, “wifi_ssid”:wifi_ssid, “wifi_password”: wifi_password}
   resp = jsonify(display_message)
   resp.status_code = 200
   return resp

 

Now the script wifi_search is called which stores the wifi credentials in the wifi_config file using the following command

 

cat >> /etc/wpa_supplicant/wpa_supplicant.conf <<EOF
network={
   ssid=“$SSID”
   psk=“$PSK”
}
EOF

 

3. /auth

This endpoint takes the SUSI’s login credentials as parameters, i.e. the registered email id and the corresponding password.

 

def login():
   auth = request.args.get(‘auth’)
   email = request.args.get(’email’)
   password = request.args.get(‘password’)
   subprocess.call([‘sudo’, ‘bash’, access_point_folder + ‘/login.sh’, auth, email, password])
   display_message = {“authentication”:“successful”, “auth”: auth, “email”: email, “password”: password}
   resp = jsonify(display_message)
   resp.status_code = 200
   return resp

 

4. /config

Finally, this endpoint takes the stt, tts, hotword detection engine and wake button as the parameters and configures the speaker accordingly.

 

def config():
   stt = request.args.get(‘stt’)
   tts = request.args.get(‘tts’)
   hotword = request.args.get(‘hotword’)
   wake = request.args.get(‘wake’)
   subprocess.Popen([‘sudo’, ‘bash’, access_point_folder + ‘/config.sh ‘, stt, tts, hotword, wake])
   display_message = {“configuration”:“successful”, “stt”: stt, “tts”: tts, “hotword”: hotword, “wake”:wake}
   resp = jsonify(display_message)
   resp.status_code = 200
   return resp

 

Now, this function runs a script called config.sh which in turn runs a script called rwap.sh to convert the Raspberry Pi to normal mode and then finally start SUSI on startup.

 

#!/bin/bash

if [ $EUID -ne 0 ]
then echo “Must be root”
exit
fi

cd /etc/hostapd/
sed -i ‘1,14d’ hostapd.conf

cd /etc/
sed -i ‘57,60d’ dhcpcd.conf

cd /etc/network/
sed -i ‘9,17d’ interfaces

echo “Please reboot”
sudo reboot

 

After successfully hitting all the endpoint from the client, your Smart Speaker would restart and would see the following screen on your client.

 

References

Additional Resources

Tags

fossasia, susi, susi.ai, gsoc, gsoc’18, handshake

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Modifying Finite State Architecture On SUSI Linux to Process Multiple Queries

During the initial stages of SUSI Linux: As the code base grew, it was getting very difficult to manage code, so we opted to implement a Finite State Architecture in our repo. But, as there were new features implemented in the Repo, we realized that we couldn’t process more than one query at a time which restricted a lot of features. eg. The smart speaker was converted to a simple Bluetooth speaker since no response regarding playing/pausing were accepted.

To solve this issue, we made a slight modification in the architecture.

Brief About SUSI States

SUSI is working as a Finite State Machine and is present in 3 states namely IDLE state, Recognising state and Busy state. The State Machine executes in the following order.

  1. IDLE State:
    When the SUSI state Machine is in this State, SUSI is searching for the hotword “SUSI”, waiting to trigger the complete Machine.
  2. Recognizing State

In this State , the State Machine has started the STT client. After recognition, SUSI sends the query to the Server awaiting the response

  1. Busy State

After the response has been received, the TTS client is triggered and the answer is given out by SUSI

Adding a Second Hotword Recognition Class

Now, to allow SUSI to process the second query, The State machine must be triggered while SUSI is giving out the first response and to trigger the State Machine, we must have hotword recognition while SUSI is speaking the answer to the previous query. Hence, a hotword recognition engine is now initiated every time the State Machine enters the busy state.

We will be using Snowboy as Hotword Detection Engine.

 

import os
TOP_DIR = os.path.dirname(os.path.abspath(__file__))
RESOURCE_FILE = os.path.join(TOP_DIR, “susi.pmdl”)
class StopDetector():
   “””This implements the Stop Detection with Snowboy Hotword Detection Engine.”””
    def __init__(self, detection) -> None:
       super().__init__()
       self.detector = snowboydecoder.HotwordDetector(
           RESOURCE_FILE, sensitivity=0.6)
       self.detection = detection
    def run(self):
       “”” Implementation of run abstract method in HotwordDetector. This method is called when thread is
started for the first time. We start the Snowboy detection and declare detected callback as
       detection_callback method declared ina parent class.
       “””
       self.detector.start(detected_callback=self.detection)

 

Now, this class takes the Callback function as a parameter which is passed when the transition to busy state takes place from the recognition state.

 

Modifying the State Machine Architecture

After declaring a second hotword recognition engine , we must modify how the transitions take place between the States of the SUSI State Machine.

Hence the callback that will be triggered is passed from the busy state.

 

def detection(self):
       “””This callback is fired when a Hotword Detector detects a hotword.
       :return: None
       “””
       if hasattr(self, ‘video_process’):
           self.video_process.send_signal(signal.SIGSTOP)
           lights.wakeup()
           subprocess.Popen([‘play’, str(self.components.config[‘detection_bell_sound’])])
           lights.off()
           self.transition(self.allowedStateTransitions.get(‘recognizing’))
           self.video_process.send_signal(signal.SIGCONT)
       if hasattr(self, ‘audio_process’):
           self.audio_process.send_signal(signal.SIGSTOP)  
           lights.wakeup()
           subprocess.Popen([‘play’, str(self.components.config[‘detection_bell_sound’])])
           lights.wakeup()
           self.transition(self.allowedStateTransitions.get(‘recognizing’))
           self.audio_process.send_signal(signal.SIGCONT)

 

As soon as the hotword is detected ,the state machine makes transitions to the Recognition State while pausing the current Music and resumes the Music after the second query has been completed.

 

This is how SUSI processes multiple queries simultaneously while still maintaining finite state archi.

 

Additional Resources

Tags

gsoc, gsoc’18, finite_state_machine, susi_linux, multiple_query, susi.ai, susi

 

Continue ReadingModifying Finite State Architecture On SUSI Linux to Process Multiple Queries

Creating a Factory Reset Daemon for SUSI.AI Smart Speaker

In our constantly evolving SUSI.AI Smart Speaker project, we require regular updates for our devices. And imagine a scenario that during a crucial update, there is a crash or an internet disconnection which stops the SUSI.AI Linux program from booting up. We’ll require a reset method for that. So, we have added a button in SUSI smart speaker that works as a factory reset switch. This daemon was accomplished by using python scripting, bash scripting, and Raspbian’s systemd rules.

Approach followed

We have created a python script that detects the button presses on GPIO port 17. The script is run as soon as the Raspberry Pi is booted using the systemd rules and checks for the device inputs. And if the button press is for more than 7 seconds, the factory_reset.sh script is run which deletes all the contents of the repo and clones it again.

 

#! /bin/bash
# To be executed using a physical button

SCRIPT_PATH=$(realpath $0)
DIR_PATH=$(dirname $SCRIPT_PATH)

cd $DIR_PATH/../..
pwd
mv susi_linux/ susi_temp
git clone https://github.com/fossasia/susi_linux #while testing change to personal repo
pwd
ls
cd susi_linux

rm -rf ../susi_temp

./install.sh

 

Detecting the Button Press

We have Used the library RPi.GPIO to detect button click on raspberry Pi.

while True:
       if GPIO.input(17) == 1:
           pass
       elif GPIO.input(17) == 0 :
           start = time.time()
          while GPIO.input(17) == 0 :
               print(“on”)
               time.sleep(0.1)
          end = time.time()
           total = end – start
           if total >= 7 :
              subprocess.call([‘bash’,‘factory_reset.sh’])
          else :
               mixer = alsaaudio.Mixer()
               value = mixer.getvolume()[0]
              if value != 0:
                  mixer.setvolume(0)
               else:
                   mixer.setvolume(50)
           print(total)
           time.sleep(0.1)

 

If the button press is greater than 7 seconds, factory reset process will start and if the press is less than 7 seconds, the button will function as mute button

 

Auto Booting The program

 

For the script to autorun everytime the raspberry pi started. We create systemd file which will allow the program to start as soon as the device has started

 

[Unit]
Description=SUSI Linux Factory Daemon
After=multi-user.target

[Service]
Type=simple
ExecStart=/usr/bin/python3 /home/pi/SUSI.AI/susi_linux/factory_reset/factory_reset.py

[Install]
WantedBy=multi-user.target

 

This runs the factory reset script to boot up as soon as the Raspberry Pi starts

References

Tags

susi, factory_daemon, factory_reset, gsoc, gsoc’18,susi_linux , fossasia

Continue ReadingCreating a Factory Reset Daemon for SUSI.AI Smart Speaker

Creating a Custom Raspbian Image containing SUSI.AI Linux Libraries

Installing Raspbian and SUSI Linux on your Raspberry Pi can be a long process and if your raspberry Pi crashes due to some bug, you have to repeat the process again and again.

It wastes a lot of valuable time. So, we will discuss a method in which we will have to install the SUSI Linux repo only once and can use it again in case of any issues.

First, we’ll go through the requirements for f installing SUSI Linux on our hardware

Hardware Requirements

1> Raspberry Pi

2> Micro SD card (16GB or greater)

3> USB Mic

4> USB Mouse and USB Keyboard

5> HDMI Monitor

6> ReSpeaker Pi Hat 2 Mic Array(optional)

7> 3.5 mm Jack Headphones / Speaker

 

Step 1: Preparing SD for Installation

1> To format your SD card

  • You can use softwares like SDCardformater to do so.

2> To install Raspbian

  • Download raspbian official build from here
  • Now mount the Image using software like Etcher or win32diskimager

 

Step 2: Installing SUSI Linux on your Pi

1> Navigate to the folder `/home/pi` and make a folder called SUSI.AI

 

cd /home/pi
mkdir SUSI.AI
cd SUSI.AI

 

2> Clone the SUSI Linux repo from here and navigate in the repo

 

git clone http://github.com/fossasia/susi_linux

cd susi_linux/

 

3> Run the installation script by using the command `./install.sh`

 

./install.sh

 

4> Run the configuration script by using the following command

`python3 config_generator.py <stt> <tts> <hotword> <wake>`

 

5> Run SUSI linux with the following command

`python3 -m main`

‘log’

If it plays a bell after you say ‘SUSI’ , it means that your software has been successfully installed

Step 3: Creating the image

1> Now that you have successfully installed SUSI Linux on your raspberry Pi , we will make a backup of the current stage of the system and use it for future references

 

2>Turn off the raspberry Pi , and remove the SD card from the Pi and insert it in your system.

 

3> To create the custom Image , use something like win32 imager and follow the steps below

  • In the text box , create a custom where you want your image to exist
  • Click on read button
  • And voila

 

References

https://www.raspberrypi.org/downloads/raspbian/

Tags

Fossasia, gsoc’18, SUSI.AI , susi_linux , gsoc, SUSI HW, installation

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Implementing Volume Action in SUSI Smart Speaker

We all know that a Smart Speaker to excel above its competitors has to excel in first being a good “Speaker” and a speaker has a basic and essential feature which is “volume control”. But things get better if you can control your volume with your voice.

So, we have implemented a feature that allows the user to control the volume of the audio with his/her voice.

Below are the steps we had to follow to implement this feature

 

Step 1: Creating the Skills

The skills required to implement the ‘volume-action’ is implemented in the SUSI Server repo itself.

The skill is located in

susi_server/conf/system_skills/general/en/en_0001_foundation.txt

 

And below are the skills required

 

set audio volume to *|set audio volume to * percent|set audio volume to * points|set volume to *|set volume to * percent|set volume to * points
!console:Audio volume is now $1$ percent.
{“actions”:[
{“type”:“audio_volume”, “volume”:$1$}
]}
eol

 

We get the following response from the server

 

“actions”: [
     {
       “volume”: “80”,
       “type”: “audio_volume”
     },
     {
       “type”: “answer”,
       “expression”: “Audio volume is now 80 percent.”
     }

 

Step 2: Finding Volume Action in the server response

Now that our Server responds to our queries regarding the voice change action , we must implement it in our Smart Speaker Client.


We first create a custom class in our in the SUSI API Wrapper repo which has only one member

 

class VolumeAction(BaseAction):
   def __init__(self , volume):
       super().__init__()
       self.volume = volume

 

We check through the actions in the server’s response

 

elif isinstance(action, VolumeAction):
           result[‘volume’] = action.volume

 

Step 3: Implementing it in the client

Now to implement the action in our client we use a library called ‘alsaaudio’ to control the master volume of our RaspberryPi

 

              m = alsaaudio.Mixer()
               m.setvolume(int(reply[‘volume’]))
               os.system(‘play {0} &’.format(self.components.config[‘detection_bell_sound’]))  # nosec #pylint-disable type: ignore                m = alsaaudio.Mixer()
               m.setvolume(int(reply[‘volume’]))
               os.system(‘play {0} &’.format(self.components.config[‘detection_bell_sound’]))  # nosec #pylint-disable type: ignore

 

Now the user can easily change the speaker using the voice commands

References

 

Tags

GSoC, GSoC’18, SUSI.AI, SUSI Linux, Smart Speaker , SUSI API Wrapper, SUSI Server, FOSSASIA, Volume Action

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Using a Flask Server to Connect to SUSI smart speaker

A smart speaker becomes significantly smarter when it is connected to a Smart-Phone.

So, we added a way to connect the Smart-Phone to the Smart Speaker and initiate the first way towards a Smart Home.

Use a simple HTTP connection protocol and deploy a light-weight server on the Raspberry Pi to allow connection from a mobile phone.

Step 1: Setting Up the server

Use flask to deploy a light-weight server on the raspberry pi. We’ll install flask using raspbian repos.

 

1>Install Flask by using the following command

sudo apt-get install python3-flask

 

2> Setting up the boilerplate code.

Open the terminal and type the following commands

`

mkdir server_app
cd server_app

touch app.py

`

 

Add the following code to your app.py file. This create a server at localhost:5000

 

from flask import Flask

app = Flask(__name__)

@app.route(‘/’)
def index():
   return ‘Hello world’

if __name__ == ‘__main__’:
   app.run(debug=False, host=‘0.0.0.0’)  #This will allow the server to be accessible on all devices

 

Step 2: Adding Endpoints

Now , add endpoints which will trigger the scripts during initialisation of the raspberry Pi. This will trigger the respective endpoints

@app.route(‘/auth/<auth>/<email>/<passwd>’)
def login(auth, email, passwd):
os.system(‘sudo ./login.sh {} {} {}’.format(auth, email,passwd)) #nosec #pylint-disable type: ignore
return ‘Authenticated’ # pylint-enable@app.route(‘/wifi_credentials/<wifissid>/<wifipassd>’)
def wifi_config(wifissid,wifipassd):
wifi_ssid = wifissid
wifi_password = wifipassd
os.system(‘sudo ./home/pi/SUSI.AI/susi_linux/access_point/wifi_search.sh {} {}’.format(wifi_ssid,wifi_password))  #nosec #pylint-disable type: ignore
return ‘Wifi Configured’ # pylint-enable

 

Step 3: Connecting to the endpoints

Now, try and hit the API endpoints to get the response.

eg.As shown in the above example, you will be getting a single line response and will execute a bash script behind the scenes

Now you can access the other endpoints and configure the clients with the SUSI Smart Speaker

References

 

Tags

fossasia,GSoC,Python, Flask , raspberryPi, SUSI,smart-speaker,FOSSASIA

Continue ReadingUsing a Flask Server to Connect to SUSI smart speaker

Displaying SUSI Smart speaker under Devices while logging in

The user should be given an ability to access all his devices on one page(Smart Speaker, IOS Device, WebClient and the Android Device). The user was previously allowed to access his/her web app account, the IOS app, Android App. But not the Smart Speaker. Now, this feature will allow the user to easily manage the Smart Speaker devices without many hassles.

In this post, we will be talking about the API’s that we have used to send the details of the Smart-Speaker to the server.

About the API’s

  1. Below is the API endpoint which will return the list of all devices present under the user’s account

We use the following endpoint

/aaa/ListUserSettings.json?/access_token=access_token

 

Below is sample response :

“devices”: {
“8C-39-45-cc-eb-95”: {
“name”: “Device 1”,
“room”: “Room 1”,
“geolocation”: {
“latitude”: “52.34567”,
“longitude”: “62.34567”
}
 }
}

 

  1. The second endpoint that we will be using is to add a new Device under the devices section

API Endpoint

/aaa/addNewDevice.json?

 

This endpoint has the following parameters

  • macid (Mac address of the device)
  • name (Name of the device)
  • room (Room info of the device)
  • latitude (Latitude info of the device)
  • longitude (Longitude info of the device)

 

After successfully hitting the endpoint , you’ll get the following response

 

{
“accepted”: true,
“message”: “You have successfully added the device!”,
“session”: {“identity”: {
“type”: “email”,
“name”: “sansyrox@gmail.com”,
“anonymous”: false
}}
}

 

Implementing the API’s

  1. First, we check the server for existing devices. This step is implemented primarily to check weather our current Smart Speaker is already configured or not.
get_device_info = api_endpoint + ‘/aaa/listUserSettings.json?’

param1 = {
       ‘access_token’:access_token
   }

   # print(access_token)

   if access_token is not None:
       device_info_response = requests.get(get_device_info,param1)
       device_info = device_info_response.json()

   # print(device_info)

If the current device is not already configured on Server, we proceed to next step.

  1. Now we will configure the device with the server and then post the device settings there.
    We will implement the API in the following way:

 

if device_info is not None:
   device = device_info[‘devices’] # list of existing mac ids
   print(device)
   session = device_info[‘session’] # session info
   identity = session[‘identity’]
   name = identity[‘name’]
   
   params2 = {
   ‘macid’: macid,
   ‘name’: name,
   ‘device’: ‘Smart Speaker’,
   ‘access_token’: access_token
   }

   for dev in device:
       if dev == macid:
           print(‘Device already configured’)
           return
       else :
           adding_device = requests.post(add_device_url, params2)
           print(adding_device.url)

 

To extract the mac address from the speaker and pass it as the params , we use a python library called UUID and this is how SUSI Smart Speaker is displayed on the web client(chat.susi.ai).

Resources

Tags

 

Continue ReadingDisplaying SUSI Smart speaker under Devices while logging in