Creating an AI-Powered Video Conferencing App with Next.js and Stream

In
a
recent
tutorial,
developers
can
now
learn
to
build
a
sophisticated
video
conferencing
app
using
Next.js,
Stream,
and
AssemblyAI,
according
to

AssemblyAI.
This
app
supports
video
calls,
live
transcriptions,
and
an
AI-powered
meeting
assistant,
integrating
modern
technologies
to
enhance
user
experience.

Project
Overview

The
tutorial
walks
through
the
creation
of
a
video
conferencing
app
leveraging
Next.js
for
the
front-end,
Stream
Video
SDK
for
video
call
functionality,
and
AssemblyAI
for
real-time
transcriptions
and
language
model
(LLM)
powered
interactions.
By
the
end
of
the
tutorial,
users
will
have
a
functional
app
capable
of
handling
multiple
participants,
providing
live
transcriptions,
and
integrating
an
AI
assistant
to
answer
questions
during
calls.

Setting
Up
the
Project

The
tutorial
provides
a
starter
template
for
a
Next.js
project
that
includes
the
setup
for
the
Stream
React
SDK.
Users
are
guided
to
clone
the
starter
project
from
GitHub,
configure
environment
variables
with
API
keys
from
Stream
and
AssemblyAI,
and
install
project
dependencies
using
npm
or
yarn.
Once
set
up,
the
app
can
be
run
locally,
enabling
users
to
start
video
calls
and
test
the
app’s
features.

App
Architecture

The
app’s
architecture
is
meticulously
explained,
detailing
the
folder
structure
and
key
files
such
as

app/page.tsx,

app/api/token/route.tsx,
and
various
components
handling
the
UI
and
state
management.
The
video
call
functionality
is
implemented
using
the
Stream
React
Video
SDK,
which
ensures
low
latency
and
high
reliability
through
Stream’s
global
edge
network.

Real-Time
Transcriptions

For
real-time
transcription,
the
tutorial
employs
the
AssemblyAI
Node
SDK.
Users
are
guided
to
create
a
microphone
recorder
to
capture
audio
data,
which
is
then
transcribed
in
real-time
using
AssemblyAI’s
Streaming
Speech-to-Text
service.
The
setup
involves
creating
helper
functions
to
manage
audio
data
and
integrating
these
functionalities
into
the
app.

Implementing
the
AI
Assistant

The
AI
assistant,
powered
by
AssemblyAI’s
LeMUR,
is
designed
to
respond
to
user
queries
during
video
calls.
The
tutorial
describes
setting
up
a
Next.js
route
to
handle
API
calls
to
LeMUR,
processing
user
prompts,
and
integrating
the
assistant
into
the
app.
A
trigger
word
mechanism
is
implemented
to
activate
the
AI
assistant,
which
then
processes
the
user’s
query
and
provides
responses
in
real-time.

UI
Integration

The
final
steps
involve
integrating
the
transcription
and
AI
assistant
functionalities
into
the
app’s
UI.
The
tutorial
provides
detailed
instructions
on
adding
UI
elements
to
display
live
transcriptions
and
AI
responses.
Users
are
shown
how
to
create
state
properties
to
manage
transcribed
text
and
AI
responses,
and
how
to
initialize
and
manage
the
transcription
and
AI
services
through
the
UI.

Conclusion

By
following
this
comprehensive
tutorial,
developers
can
build
a
powerful
video
conferencing
app
with
advanced
features
like
live
transcriptions
and
AI-powered
assistance.
The
app
is
ready
for
deployment,
enabling
other
users
to
join
meetings
and
utilize
its
functionalities.
For
more
details,
refer
to
the
full
tutorial
on

AssemblyAI.

Image
source:
Shutterstock