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Alexa Client SDK v0.4
This release of the Alexa Client SDK for C++ provides components for authentication and communications with the Alexa Voice Service (AVS), specifically AuthDelegate, Alexa Communications Library (ACL), Alexa Directive Sequencer Library (ADSL), Activity Focus Manager Library (AFML), Audio Input Manager (AIP), Wake Word Detector (WWD), and associated APIs.
Additionally, this release includes SpeechSynthesizer
, an implementation of the SpeechRecognizer
capability agent, and a reference implementation of MediaPlayer
based on GStreamer for audio playback.
Native components for the following capability agents are not included in this release and will be added in future releases: Alerts
, AudioPlayer
, PlaybackController
, Speaker
, Settings
, and System
. However, it's important to note, this release does support directives from the referenced interfaces.
Overview
The Alexa Client SDK provides a modern C++ (11 or later) interface for AVS that allows developers to add intelligent voice control to connected products. It is modular and abstracted, providing components to handle discrete functionality such as speech capture, audio processing, and communications, with each component exposing APIs that you can use and customize for your integration.
Common Terms
- Interface - A collection of logically grouped messages called directives and events, which correspond to client functionality, such speech recognition, audio playback, and volume control.
- Directives - Messages sent from AVS that instruct your product to take action.
- Events - Messages sent from your product to AVS notifying AVS something has occurred.
- Downchannel - A stream you create in your HTTP/2 connection, which is used to deliver directives from AVS to your product. The downchannel remains open in a half-closed state from the device and open from AVS for the life of the connection. The downchannel is primarily used to send cloud-initiated directives to your product.
- Cloud-initiated Directives - Directives sent from AVS to your product. For example, when a user adjusts device volume from the Amazon Alexa App, a directive is sent to your product without a corresponding voice request.
SDK Components
This architecture diagram illustrates the data flows between components that comprise the Alexa Client SDK.
Audio Signal Processor (ASP) - Applies signal processing algorithms to both input and output audio channels. The applied algorithms are designed to produce clean audio data and include, but are not limited to: acoustic echo cancellation (AEC), beam forming (fixed or adaptive), voice activity detection (VAD), and dynamic range compression (DRC). If a multi-microphone array is present, the ASP constructs and outputs a single audio stream for the array.
Shared Data Stream (SDS) - A single producer, multi-consumer buffer that allows for the transport of any type of data between a single writer and one or more readers. SDS performs two key tasks: 1) it passes audio data between the audio front end (or Audio Signal Processor), the wake word engine, and the Alexa Communications Library (ACL) before sending to AVS; 2) it passes data attachments sent by AVS to specific capability agents via the ACL.
SDS is implemented atop a ring buffer on a product-specific memory segment (or user-specified), which allows it to be used for in-process or interprocess communication. Keep in mind, the writer and reader(s) may be in different threads or processes.
Wake Word Engine (WWE) - Spots wake words in an input stream. It is comprised of two binary interfaces. The first handles wake word spotting (or detection), and the second handles specific wake word models (in this case "Alexa"). Depending on your implementation, the WWE may run on the system on a chip (SOC) or dedicated chip, like a digital signal processor (DSP).
Audio Input Processor (AIP) - Handles audio input that is sent to AVS via the ACL. These include on-device microphones, remote microphones, an other audio input sources.
The AIP also includes the logic to switch between different audio input sources. Only one audio input source can be sent to AVS at a given time.
Alexa Communications Library (ACL) - Serves as the main communications channel between a client and AVS. The Performs two key functions:
- Establishes and maintains long-lived persistent connections with AVS. ACL adheres to the messaging specification detailed in Managing an HTTP/2 Conncetion with AVS.
- Provides message sending and receiving capabilities, which includes support JSON-formatted text, and binary audio content. For additional information, see Structuring an HTTP/2 Request to AVS.
Alexa Directive Sequencer Library (ADSL): Manages the order and sequence of directives from AVS, as detailed in the AVS Interaction Model. This component manages the lifecycle of each directive, and informs the Directive Handler (which may or may not be a Capability Agent) to handle the message.
See Appendix B for a diagram of the directive lifecycle.
Activity Focus Manager Library (AFML): Provides centralized management of audiovisual focus for the device. Focus is based on channels, as detailed in the AVS Interaction Model, which are used to govern the prioritization of audiovisual inputs and outputs.
Channels can either be in the foreground or background. At any given time, only one channel can be in the foreground and have focus. If multiple channels are active, you need to respect the following priority order: Dialog > Alerts > Content. When a channel that is in the foreground becomes inactive, the next active channel in the priority order moves into the foreground.
Focus management is not specific to Capability Agents or Directive Handlers, and can be used by non-Alexa related agents as well. This allows all agents using the AFML to have a consistent focus across a device.
Capability Agents: Handle Alexa-driven interactions; specifically directives and events. Each capability agent corresponds to a specific interface exposed by the AVS API. These interfaces include:
- SpeechRecognizer - The interface for speech capture.
- SpeechSynthesizer - The interface for Alexa speech output.
- Alerts - The interface for setting, stopping, and deleting timers and alarms.
- AudioPlayer - The interface for managing and controlling audio playback.
- PlaybackController - The interface for navigating a playback queue via GUI or buttons.
- Speaker - The interface for volume control, including mute and unmute.
- System - The interface for communicating product status/state to AVS.
Minimum Requirements and Dependencies
- C++ 11 or later
- GNU Compiler Collection (GCC) 4.8.5 or later OR Clang 3.3 or later
- CMake 3.0 or later
- libcurl 7.50.2 or later
- nghttp2 1.0 or later
- OpenSSL 1.0.2 or later
- Doxygen 1.8.13 or later (required to build API documentation)
Building the reference implementation of the MediaPlayerInterface
(the class MediaPlayer
) is optional, but requires:
- GStreamer 1.8 or later and the following GStreamer plug-ins:
- GStreamer Base Plugins 1.8 or later.
- GStreamer Good Plugins 1.8 or later.
- Installation of PulseAudio, including development libraries (except on MacOS where
osxaudiosink
is used, instead).
Prerequisites
Before you create your build, you'll need to install some software that is required to run AuthServer
. AuthServer
is a minimal authorization server built in Python using Flask. It provides an easy way to obtain your first refresh token, which will be used for integration tests and obtaining access token that are required for all interactions with AVS.
IMPORTANT NOTE: AuthServer
is for testing purposed only. A commercial product is expected to obtain Login with Amazon (LWA) credentials using the instructions provided on the Amazon Developer Portal for Remote Authorization and Local Authorization. For additional information, see AVS Authorization.
Step 1: Install pip
If pip
isn't installed on your system, follow the detailed install instructions here.
Step 2: Install flask
and requests
For Windows run this command:
pip install flask requests
For Unix/Mac run this command:
pip install --user flask requests
Step 3: Obtain Your Device Type ID, Cliend ID, and Client Secret
If you haven't already, follow these instructions to register a product and create a security profile.
Make sure you note the following, you'll need these later when you configure AuthServer
:
- Device Type ID
- Client ID
- Client Secret
IMPORTANT NOTE: Make sure that you've set your Allowed Origins and Allowed Return URLs in the Web Settings Tab:
- Allowed Origins: http://localhost:3000
- Allowed Return URLs: http://localhost:3000/authresponse
Create an Out-of-Source Build
The following instructions assume that all requirements and dependencies are met and that you have cloned the repository (or saved the tarball locally).
CMake Build Types and Options
The following build types are supported:
DEBUG
- Shows debug logs with-g
compiler flag.RELEASE
- Adds-O2
flag and removes-g
flag.MINSIZEREL
- Compiles withRELEASE
flags and optimizations (-O
s) for a smaller build size.
To specify a build type, use this command in place of step 4 below (see Build for Generic Linux or Build for macOS):
cmake <path-to-source> -DCMAKE_BUILD_TYPE=<build-type>
Build with the KITT.ai Wake Word Detector
These options are required to build with the KITT.ai wake word detector:
-DKITTAI_KEY_WORD_DETECTOR=<ON or OFF>
- Specifies whether to build and enable the KITT.ai wake word detector.-DKITTAI_KEY_WORD_DETECTOR_LIB_PATH=<path-to-kittai-lib>
- The path to the KITT.ai library.-DKITTAI_KEY_WORD_DETECTOR_INCLUDE_DIR=<path-to-kittai-include-dir>
- The path to the KITT.ai include directory.
This is an example cmake
command:
cmake <path-to-source> -DKITTAI_KEY_WORD_DETECTOR=ON -DKITTAI_KEY_WORD_DETECTOR_LIB_PATH=.../snowboy-1.2.0/lib/libsnowboy-detect.a -DKITTAI_KEY_WORD_DETECTOR_INCLUDE_DIR=.../snowboy-1.2.0/include
NOTE: A matrix calculation library, known as BLAS, is required to use KITT.ai. The following are sample commands to install this library:
- Generic Linux -
apt-get install libatlas-base-dev
- macOS -
brew install homebrew/science/openblas
Note: To list all available CMake options, use the following command: -LH
.
Build with an implementation of MediaPlayer
MediaPlayer
(the reference implementation of the MediaPlayerInterface
) is based upon GStreamer, and is not built by default. To build 'MediaPlayer' the -DGSTREAMER_MEDIA_PLAYER=ON
option must be specified to CMake. Here is an example cmake command:
cmake <path-to-source> -DGSTREAMER_MEDIA_PLAYER=ON.
NOTE: If GStreamer is not installed and detected by CMake, the MediaPlayer
build is skipped even if the
-DGSTREAMER_MEDIA_PLAYER=ON
option is specified. see **Minimum Requirements and Dependencies ** for details.
Build for Generic Linux
To create an out-of-source build for Linux:
- Clone the repository (or download and extract the tarball).
- Create a build directory out-of-source. Important: The directory cannot be a subdirectory of the source folder.
cd
into your build directory.- From your build directory, run
cmake
on the source directory to generate make files for the SDK:cmake <path-to-source-code>
. - After you've successfully run
cmake
, you should see the following message:-- Please fill <path-to-build-directory>/Integration/AlexaClientSDKConfig.json before you execute integration tests.
. OpenIntegration/AlexaClientSDKConfig.json
with your favorite text editor and fill in your product information (which you got from the developer portal when registering a product and creating a security profile). It should look like this:
NOTE: The{ "authDelegate":{ "deviceTypeId":"<Device Type ID for your device on the Developer portal>", "clientId":"<ClientID for the security profile of the device>", "clientSecret":"<ClientSecret for the security profile of the device>", "deviceSerialNumber":"<a unique number for your device>" } }
deviceSerialNumber
is a unique identifier that you create. It is not provided by Amazon. - From the build directory, run
make
to build the SDK.
Build for macOS
Building for macOS requires some additional setup. Specifically, you need to ensure that you are running the latest version of cURL and that cURL is linked to nghttp2 (the default installation does not).
To recompile cURL, follow these instructions:
- Install Homebrew, if you haven't done so already.
- Install cURL with HTTP2 support:
brew install curl --with-nghttp2
- Force cURL to explicitly link to the updated binary:
brew link curl --force
- Close and reopen terminal.
- Confirm version and source with this command:
brew info curl
To create an out-of-source build for macOS:
- Clone the repository (or download and extract the tarball).
- Create a build directory out-of-source. Important: The directory cannot be a subdirectory of the source folder.
cd
into your build directory.- From your build directory, run
cmake
on the source directory to generate make files for the SDK:cmake <path-to-source-code>
. - After you've successfully run
cmake
, you should see the following message:-- Please fill <path-to-build-directory>/Integration/AlexaClientSDKConfig.json before you execute integration tests.
. OpenIntegration/AlexaClientSDKConfig.json
with your favorite text editor and fill in your product information (which you got from the developer portal when registering a product and creating a security profile). It should look like this:
NOTE: The{ "authDelegate":{ "deviceTypeId":"<Device Type ID for your device on the Developer portal>", "clientId":"<ClientID for the security profile of the device>", "clientSecret":"<ClientSecret for the security profile of the device>", "deviceSerialNumber":"<a unique number for your device>" } }
deviceSerialNumber
is a unique identifier that you create. It is not provided by Amazon. - From the build directory, run
make
to build the SDK.
Run AuthServer
After you've created your out-of-source build, the next step is to run AuthServer
to retrieve a valid refresh token from LWA.
- Run this command to start
AuthServer
:
You should see a message that indicates the server is running.python AuthServer/AuthServer.py
- Open your favorite browser and navigate to:
http://localhost:3000
- Follow the on-screen instructions.
- After you've entered your credentials, the server should terminate itself, and
Integration/AlexaClientSDKConfig.json
will be populated with your refresh token. - Before you proceed, it's important that you make sure the refresh token is in
Integration/AlexaClientSDKConfig.json
.
Run Unit Tests
Unit tests for the Alexa Client SDK use the Google Test framework. Ensure that the Google Test is installed, then run the following command:
make all test
Ensure that all tests are passed before you begin integration testing.
Note: In order to run unit tests for the KITT.ai wake word detector, the following files must be downloaded from GitHub and placed in KWD/inputs/KittAiModels
:
common.res
alexa.umdl
- It's important that you download thealexa.umdl
inresources/alexa/alexa-avs-sample-app
for the KITT.ai unit tests to run properly.
Run Integration Tests
Integration tests ensure that your build can make a request and receive a response from AVS. All requests to AVS require auth credentials.
Important: Integration tests reference an AlexaClientSDKConfig.json
file, which you must create.
See the Create the AlexaClientSDKConfig.json file
section (above), if you have not already done this.
To exercise the integration tests run this command:
make all integration
Note: If the project was built with the KITT.ai wake word detector, the following files must be downloaded from GitHub and placed in Integration/inputs/KittAiModels
for the integration tests to run properly:
common.res
alexa.umdl
- It's important that you download thealexa.umdl
inresources/alexa/alexa-avs-sample-app
for the KITT.ai integration tests to run properly.
Alexa Client SDK API Documentation
To build the Alexa Client SDK API documentation, run this command from your build directory: make doc
.
Resources and Guides
- Step-by-step instructions to optimize libcurl for size in
*nix
systems. - Step-by-step instructions to build libcurl with mbed TLS and nghttp2 for
*nix
systems.
Appendix A: Memory Profile
This appendix provides the memory profiles for various modules of the Alexa Client SDK. The numbers were observed running integration tests on a machine running Ubuntu 16.04.2 LTS.
Module | Source Code Size (Bytes) | Library Size RELEASE Build (libxxx.so) (Bytes) | Library Size MINSIZEREL Build (libxxx.so) (Bytes) |
---|---|---|---|
ACL | 300 KB | 245 KB | 227 KB |
ADSL | 188 KB | 180 KB | 169 KB |
AFML | 100 KB | 114 KB | 109 KB |
Runtime Memory
Unique size set (USS) and proportional size set (PSS) were measured by SMEM while integration tests were run.
Runtime Memory | Max USS (Bytes) | Max PSS (Bytes) |
---|---|---|
ACL | 22 MB | 23 MB |
ADSL + ACL | 26 MB | 27 MB |
Definitions
- USS: The amount of memory that is private to the process and not shared with any other processes.
- PSS: The amount of memory shared with other processes; divided by the number of processes sharing each page.
Appendix B: Directive Lifecycle Diagram
Appendix C: Runtime Configuration of path to CA Certificates
By default libcurl is built with paths to a CA bundle and a directory containing CA certificates. You can direct the Alexa Client SDK to configure libcurl to use an additional path to directories containing CA certificates via the CURLOPT_CAPATH setting. This is done by adding a "libcurlUtils/CURLOPT_CAPATH"
entry to the AlexaClientSDKConfig.json
file. Here is an example:
{
"authDelegate" : {
"clientId" : "INSERT_YOUR_CLIENT_ID_HERE",
"refreshToken" : "INSERT_YOUR_REFRESH_TOKEN_HERE",
"clientSecret" : "INSERT_YOUR_CLIENT_SECRET_HERE"
},
"libcurlUtils" : {
"CURLOPT_CAPATH" : "INSERT_YOUR_CA_CERTIFICATE_PATH_HERE"
}
}
Note If you want to assure that libcurl is only using CA certificates from this path you may need to reconfigure libcurl with the --without-ca-bundle
and --without-ca-path
options and rebuild it to suppress the default paths. See The libcurl documention for more information.
Release Notes
v0.4 updated 5/31/2017:
- Added
AuthServer
, an authorization server implementation used to retrieve refresh tokens from LWA.
v0.4 release 5/24/2017:
- Added the
SpeechSynthesizer
, an implementation of theSpeechRecognizer
capability agent. - Implemented a reference
MediaPlayer
based on GStreamer for audio playback.- Added the
MediaPlayerInterface
that allows you to implement your own media player.
- Added the
- Updated
ACL
to support asynchronous receipt of audio attachments from AVS. - Bug Fixes:
- Some intermittent unit test failures were fixed.
- Known Issues:
ACL
's asynchronous receipt of audio attachments may manage resources poorly in scenarios where attachments are received but not consumed.- When an
AttachmentReader
does not deliver data for prolonged periodsMediaPlayer
may not resume playing the delayed audio.
v0.3 released 5/17/2017:
- Added the
CapabilityAgent
base class that is used to build capability agent implementations. - Added the
ContextManager
class that allows multiple Capability Agents to store and access state. These events includecontext
, which is used to communicate the state of each capability agent to AVS: - Implemented the
SharedDataStream
(SDS) to asynchronously communicate data between a local reader and writer. - Added
AudioInputProcessor
(AIP), an implementation of aSpeechRecognizer
capability agent. - Added the WakeWord Detector (WWD), which recognizes keywords in audio streams. v0.3 implements a wrapper for KITT.ai.
- Added a new implementation of
AttachmentManager
and associated classes for use with SDS. - Updated the
ACL
to support asynchronously sending audio to AVS.
v0.2.1 released 5/3/2017:
- Replaced the configuration file
AuthDelegate.config
withAlexaClientSDKConfig.json
. - Added the ability to specify a
CURLOPT_CAPATH
value to be used when libcurl is used by ACL and AuthDelegate. See Appendix C for details. - Changes to ADSL interfaces:
The v0.2 interface for registering directive handlers (
DirectiveSequencer::setDirectiveHandlers()
) was problematic because it canceled the ongoing processing of directives and dropped further directives until it completed. The revised API makes the operation immediate without canceling or dropping any handling. However, it does create the possibility thatDirectiveHandlerInterface
methodspreHandleDirective()
andhandleDirective()
may be called on different handlers for the same directive.DirectiveSequencerInterface::setDirectiveHandlers()
was replaced byaddDirectiveHandlers()
andremoveDirectiveHandlers()
.DirectiveHandlerInterface::shutdown()
was replaced withonDeregistered()
.DirectiveHandlerInterface::preHandleDirective()
now takes astd::unique_ptr
instead of astd::shared_ptr
toDirectiveHandlerResultInterface
.DirectiveHandlerInterface::handleDirective()
now returns a bool indicating if the handler recognizes themessageId
.
- Bug fixes:
- ACL and AuthDelegate now require TLSv1.2.
onDirective()
now sendsExceptionEncountered
for unhandled directives.DirectiveSequencer::shutdown()
no longer sendsExceptionEncountered()
for queued directives.
v0.2 updated 3/27/2017:
- Added memory profiling for ACL and ADSL. See Appendix A.
- Added command to build API documentation.
v0.2 released 3/9/2017:
- Alexa Client SDK v0.2 released.
- Architecture diagram has been updated to include the ADSL and AMFL.
- CMake build types and options have been updated.
- New documentation for libcurl optimization included.
v0.1 released 2/10/2017:
- Alexa Client SDK v0.1 released.