how to deploy my app in my own ec2

Thanks for reaching out, Sajjad. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.

i want to deploy my agent on ec2

Great — I can help you deploy your agent on EC2. A few quick questions so I give exact steps: • Which language/runtime is your agent written in (Node/Python/other)? • Do you want to run it in Docker containers or directly on the VM? • Planned instance type (e.g., t3.micro, m5.large) and OS/AMI (Ubuntu version)? • Will the agent need inbound ports exposed or just outbound connections to LiveKit? • Do you already have LiveKit credentials (

LIVEKIT_API_KEY

,

LIVEKIT_API_SECRET

) and a LiveKit URL? Once you confirm, I’ll provide a tailored step‑by‑step: EC2 launch + security group settings, Dockerfile (if Docker), systemd or Docker run commands, environment variable handling, and graceful shutdown configuration. , with interactive elements

when i deply my agent on an ec2 how will I manage to get observability?

Thanks — helpful question. I’ll cover what’s available and what you should set up for observability when running an agent on EC2. Quick clarification: are your agents connecting to LiveKit Cloud or are you also self‑hosting the LiveKit server? That changes what built‑in observability you can use. What you can do • If your agent connects to LiveKit Cloud ◦ Enable Agent Observability in your project’s settings to get session traces, audio/transcripts, and agent logs in the dashboard (data retained 30 days). Ensure you use a supported SDK version (Python v1.3+ or Node v1.0.18+). ◦ You can still forward logs to external APMs (Datadog, Sentry, New Relic) if desired. • If you self‑host the LiveKit server (agent on EC2 + self‑hosted server) ◦ Agent Observability in the LiveKit dashboard is not available. You must collect and forward logs/metrics yourself. Practical observability setup for agents on EC2 • Logs ◦ Emit structured logs from the agent (stdout/stderr) using your language’s logger. ◦ Run a log forwarder on the instance: AWS CloudWatch Agent, Fluent Bit, or Logstash to ship logs to CloudWatch/Datadog/S3/ELK. ◦ Capture agent lifecycle events (startup, SIGTERM, errors) and include session IDs in logs for correlation. • Metrics & health ◦ Export application metrics (request durations, active sessions, error counts) via Prometheus client libs or push metrics to CloudWatch/Datadog. ◦ Expose a /health or /metrics HTTP endpoint and monitor it with your monitoring system and an ALARM for failed health checks. • Tracing ◦ Add OpenTelemetry instrumentation for traces (span per session/operation) and export to your tracing backend (Jaeger/Zipkin/CloudTrace/Datadog APM). • Containers & orchestration ◦ If running in Docker, bake logging/metrics agents into the host or sidecar containers. Pre-download models during image build to reduce cold starts. ◦ Use graceful shutdown handling (SIGTERM) so ongoing conversations drain. Configure a long grace period for voice workloads. • Alerts & retention ◦ Create alerts for high error rates, CPU/memory spikes, and failed health checks. ◦ Choose appropriate log/metric retention and privacy settings for session data. Debugging tips (quick commands) • View logs: journalctl -u your-agent.service or docker logs container • Check processes: systemctl status your-agent.service • Tail forwarder logs: tail -f /var/log/amazon-cloudwatch/ or Fluent Bit logs If you want, I can: • Provide a sample Dockerfile + systemd unit or ECS task definition for your agent • Give a CloudWatch Agent / Fluent Bit config to forward logs • Show an OpenTelemetry snippet for your language Tell me which of the above you want first (CloudWatch vs Datadog, Docker vs VM, Node vs Python), and I’ll send step‑by‑step configs. Sources: Why is my Agent insights data missing? | LiveKit | Streamline troubleshooting with Agent Observability | LiveKit | Where to find your Agent Logs | LiveKit | Where to find your Agent Logs | LiveKit | Server options | LiveKit Documentation, with interactive elements

my agent is on ec2 and is connected to livekit cloud

Great — since your agent runs on EC2 and connects to LiveKit Cloud, you can use LiveKit’s Agent Observability plus your own host-level monitoring. Below is a concise, actionable plan and sample configs you can apply now. What you get immediately • Enable Agent Observability in your LiveKit Cloud project settings to see session traces, synced audio/transcripts, and agent logs in the dashboard (data retained 30 days). • Use a supported SDK version (Python v1.3+ or Node v1.0.18+) so observability data is sent correctly. Recommended observability stack (minimal, effective) • Logs: structured stdout/stderr from the agent → forward with CloudWatch Agent or Fluent Bit to CloudWatch/Datadog/S3. • Metrics: expose Prometheus metrics or push custom metrics to CloudWatch/Datadog. • Tracing: instrument with OpenTelemetry and export to your tracing backend (Jaeger, Datadog, etc.). • Health: expose a /health endpoint and monitor it with CloudWatch alarms. • Alerts: create alarms for high error rates, high latency, and unhealthy health checks. Practical steps 1) Agent logging • Emit structured logs with session IDs. • Run CloudWatch Agent or Fluent Bit on the EC2 host to forward logs. ◦ CloudWatch Agent picks up journalctl or files. ◦ Fluent Bit can parse JSON and send to many backends. 2) Metrics & health • Add a Prometheus client or push CloudWatch metrics for: ◦ active sessions ◦ request durations ◦ error rates • Expose /metrics and /health endpoints; create CloudWatch or Datadog monitors. 3) Tracing • Add OpenTelemetry SDK to the agent, create spans per session/operation, and export to your tracing backend. 4) Graceful shutdown • Ensure agent handles SIGTERM to stop accepting new jobs and drain existing conversations (configure 10+ minute grace for voice). Quick sample snippets • Dockerfile (minimal)

FROM python:3.11-slim
WORKDIR /app
COPY . /app
RUN pip install -r requirements.txt
ENV LIVEKIT_API_KEY=your_key
ENV LIVEKIT_API_SECRET=your_secret
CMD ["python", "agent.py"]

• systemd unit (if running directly on VM)

[Unit]
Description=livekit-agent
After=network.target

[Service]
User=ubuntu
WorkingDirectory=/opt/agent
EnvironmentFile=/opt/agent/.env
ExecStart=/usr/bin/python3 /opt/agent/agent.py
TimeoutStopSec=600
KillMode=process
Restart=on-failure

[Install]
WantedBy=multi-user.target

• CloudWatch Agent JSON (logs)

{
  "logs": {
    "logs_collected": {
      "files": {
        "collect_list": [
          {
            "file_path": "/var/log/agent/agent.log",
            "log_group_name": "/livekit/agent",
            "log_stream_name": "{instance_id}"
          }
        ]
      }
    }
  }
}

Debug & verification • Verify LiveKit Agent Observability appears in the dashboard (Agent insights). • Check forwarded logs in CloudWatch/Datadog. • Query traces in your tracing backend. • Use

journalctl -u livekit-agent

or

docker logs <container>

for local troubleshooting. If you want, I can now: • Provide a Fluent Bit config to forward JSON logs to CloudWatch or Datadog, • Give an OpenTelemetry snippet for Node or Python, • Or produce a complete step‑by‑step EC2 setup (user data, security group, CloudWatch Agent install). Which of those should I send next? , with interactive elements

when i deply my agent app on livekit cloud do i need to provive secrets

Short answer: yes — you must provide the secrets your agent needs (LiveKit API key/secret and any third‑party credentials) when deploying to LiveKit Cloud. What to provide • LiveKit credentials:

LIVEKIT_API_KEY

,

LIVEKIT_API_SECRET

, and

LIVEKIT_URL

(or the equivalent values your agent expects). • Any other secrets your agent uses: API keys for external services, model credentials, DB passwords, etc. How they’re supplied (summary) • Add secrets via the LiveKit Cloud deployment UI or the deployment’s environment/secret section so they are injected as environment variables at runtime. • Secrets are not hardcoded into your image; store them in the Cloud deployment’s secret store or env settings. Best practices • Put only needed secrets in the Cloud secret store; keep long‑lived credentials rotated. • Do not bake secrets into your Docker image or commit them to source control. • Limit secret scope (least privilege) and rotate periodically. • Use environment variables and read them from a

.env

loader or process env in your agent code. If you want, I can: • Give exact steps/screenshots for adding secrets in the LiveKit Cloud deployment UI, or • Provide example code in Node or Python showing how to read the injected environment variables. Which one would you like? , with interactive elements

LOCALLY MY APP IS Working but after deploying not working

Sorry that happened — I can help. Quick checklist of the most common causes and then a couple short diagnostics so I can pinpoint the issue. Common causes when it works locally but fails after deployment • Missing or incorrect environment variables / secrets (LIVEKIT_API_KEY, LIVEKIT_API_SECRET, LIVEKIT_URL, third‑party keys). • SDK/version mismatch or unmet dependency in the deployed image. • Agent not registering with LiveKit (network or credential issue). • Agent crashes before a session completes (so no observability data appears). • Runtime differences (Python/Node version, file paths, permissions). • Health check or container timeouts and improper SIGTERM handling. Please run these checks and share results 1. Logs: From LiveKit Cloud use

lk agent logs

or check Agent insights logs; paste the last 20–50 lines (or any errors). 2. Env: Confirm which secrets/env vars you set in the deployment and that

LIVEKIT_API_KEY

,

LIVEKIT_API_SECRET

, and

LIVEKIT_URL

are present. 3. SDK: Tell me your agent runtime and SDK version (Node or Python + version). 4. Registration: Look for a log line like

registered worker

— do you see it? 5. Crash timing: Does the agent start then crash immediately, or does it run but fail to join sessions? If you paste the log excerpt and the answers to 2–4 I’ll give exact next steps (env fixes, Dockerfile or image changes, or a log-forwarder/health-check tweak). Sources: Self-hosted deployments | LiveKit Documentation | Running LiveKit on AWS | LiveKit | Server startup modes | LiveKit Documentation | Where to find your Agent Logs | LiveKit | Build Your First AI Voice Agent in Python: Complete Tutorial | LiveKit, with interactive elements

Using project [suno-app] Using agent [CA_SfPUF9aPPzpJ] INFOlivekit.agentsstarting worker INFOlivekit.agentsplugin registered {"message": "starting worker", "level": "INFO", "name": "livekit.agents", "version": "1.5.8", "rtc-version": "1.1.7", "timestamp": "2026-05-08T110547.611162+00:00"} INFOlivekit.agentsplugin registered {"message": "plugin registered", "level": "INFO", "name": "livekit.agents", "plugin": "livekit.plugins.silero", "version": "1.5.8", "timestamp": "2026-05-08T110547.611379+00:00"} {"message": "plugin registered", "level": "INFO", "name": "livekit.agents", "plugin": "livekit.plugins.turn_detector.base", "version": "1.5.8", "timestamp": "2026-05-08T110547.611575+00:00"} INFOlivekit.agentspreloading plugins {"message": "preloading plugins", "level": "INFO", "name": "livekit.agents", "packages": ["livekit.plugins.silero", "livekit.plugins.turn_detector", "av"], "timestamp": "2026-05-08T110547.611652+00:00"} INFOlivekit.agentsHTTP server listening on :8081 {"message": "HTTP server listening on :8081", "level": "INFO", "name": "livekit.agents", "timestamp": "2026-05-08T110547.637520+00:00"} INFOlivekit.agentsinitializing process {"message": "initializing process", "level": "INFO", "name": "livekit.agents", "pid": 77, "timestamp": "2026-05-08T110549.545435+00:00"} INFOlivekit.agentsinitializing process {"message": "initializing process", "level": "INFO", "name": "livekit.agents", "pid": 80, "timestamp": "2026-05-08T110549.568862+00:00"} INFOlivekit.agentsprocess initialized {"message": "process initialized", "level": "INFO", "name": "livekit.agents", "pid": 77, "elapsed_time": 0.22, "timestamp": "2026-05-08T110549.769646+00:00"} INFOlivekit.agentsprocess initialized {"message": "process initialized", "level": "INFO", "name": "livekit.agents", "pid": 80, "elapsed_time": 0.21, "timestamp": "2026-05-08T110549.776402+00:00"} INFOlivekit.agentsregistered worker {"message": "registered worker", "level": "INFO", "name": "livekit.agents", "agent_name": "voice_assistant", "id": "CAW_hXvgyrA8kx5q", "url": "https://suno-app-nqv74rl9.livekit.cloud", "region": "US East B", "protocol": 17, "timestamp": "2026-05-08T110549.818904+00:00"}

Thanks — I can see from the logs your agent starts, preloads plugins, and successfully registers ("registered worker"). That means runtime and LiveKit credentials look correct. Let's focus on why it still isn't working after deployment. Quick checks — please confirm these and paste results where applicable: 1. Are any errors shown after the "registered worker" lines in the agent logs or in Agent insights? If so, paste the next 50 lines. 2. Did you configure all required secrets in the LiveKit Cloud deployment (e.g., OpenAI/Anthropic keys, model creds, any third‑party APIs the agent uses)? Missing external secrets is a common cause. 3. SDK/runtime: Which agent runtime and SDK version are you using in deployment (Python 1.5.8 shown in logs is OK; confirm any other libs)? Any difference from local versions? 4. Does the agent receive tasks/sessions? Check Agent insights → sessions or look for logs indicating a session start or "session assigned" type message. 5. If the agent crashes or exits, do you see an exit code or stack trace in logs (or

lk agent logs

output)? If everything above looks normal, try these immediate diagnostics: • Reproduce a session and stream logs while reproducing (live tail of the agent logs). Paste errors you see. • Verify environment variables present at runtime by having the agent log a masked subset of env vars on startup (not full secrets). • Confirm the agent can reach external services from the deployment environment (e.g., curl the external API endpoints from the container/instance). I can next: • Inspect the next 50–100 log lines after registration if you paste them, • Provide steps to add missing secrets to the LiveKit Cloud deployment, • Give a minimal health-check/diagnostic snippet to log env and outbound connectivity. Which of those do you want me to do first? , with interactive elements

how to verify the env variabled

Good question — here are safe, practical ways to verify the env vars your agent sees at runtime. Pick the method that matches your deployment (LiveKit Cloud or EC2/Docker). 1) From LiveKit Cloud UI / CLI • UI: Open your LiveKit Cloud project → Deployment → Environment / Secrets and confirm the variables are present. • CLI: Run

lk app env -w

(or

lk agent env -w

) to write the deployment env to a local

.env.local

file and inspect it. 2) Quick runtime check inside the container/VM • If you have shell access to the instance or container: ◦ VM: SSH in and run

printenv | grep LIVEKIT

or

printenv

to list env vars. ◦ Docker container:

docker exec -it <container> /bin/sh -c 'printenv | grep LIVEKIT'

. 3) Safe in‑app debug (recommended) • Add a masked env log at startup to avoid leaking secrets. Only log non‑secret names or masked values. • Python example:

import os
def masked(v):
    return v[:4]+"..." if v else "<missing>"

for k in ("LIVEKIT_API_KEY","LIVEKIT_API_SECRET","LIVEKIT_URL","OPENAI_API_KEY"):
    print(f"{k}={masked(os.environ.get(k))}")

• Node example:

const mask = v => v ? v.slice(0,4)+'...' : '<missing>';
["LIVEKIT_API_KEY","LIVEKIT_API_SECRET","LIVEKIT_URL","OPENAI_API_KEY"]
  .forEach(k => console.log(`${k}=${mask(process.env[k])}`));

4) Health / diagnostic endpoint • Add a temporary

/diag

or

/health

HTTP endpoint that returns presence (not values) of required env vars: ◦ Example JSON: { "LIVEKIT_URL": true, "OPENAI_API_KEY": false } 5) If you use LiveKit Cloud secrets • Ensure secrets were added in the deployment secret store (not baked into image). • After updating secrets, redeploy or trigger a rollout so the runtime picks them up. What I need from you to help further • Tell me which method you prefer (UI/CLI, SSH, container, or in‑app logging), and whether you want the exact CLI commands or a code snippet you can paste into your agent., with interactive elements

image.png

Thanks — I can see your agent is RUNNING and registered but shows 0% uptime/load, which means it hasn't processed sessions. To confirm env vars and find the blocker, do this next (pick 1–2 to run now): 1) Check deployed env via LiveKit CLI • Run:

lk app env -w

This writes the deployment env to

.env.local

so you can inspect presence of

LIVEKIT_API_KEY

,

LIVEKIT_API_SECRET

,

LIVEKIT_URL

, and any model/API keys. 2) Tail agent logs while reproducing • Run:

lk agent logs -w

(or use Agent Insights → Logs) and then trigger a test session with "Test in Console". Paste any error lines you see after the "registered worker" message. 3) Add a safe masked env check in startup (temporary) • Python:

import os
def m(v): return v[:4]+"..." if v else "<missing>"
print("LIVEKIT_API_KEY=", m(os.getenv("LIVEKIT_API_KEY")))
print("OPENAI_API_KEY=", m(os.getenv("OPENAI_API_KEY")))

• Node:

const m = v => v ? v.slice(0,4)+'...' : '<missing>';
console.log('LIVEKIT_API_KEY=', m(process.env.LIVEKIT_API_KEY));
console.log('OPENAI_API_KEY=', m(process.env.OPENAI_API_KEY));

4) Verify secrets in Cloud UI • Project → Agents → your agent → Secrets — confirm all required secrets are present and deployed. 5) Confirm network/access • From the running container, verify outbound access:

curl -I https://api.openai.com

(or your provider) to ensure no firewall blocks. If you run 1–3 and paste the log output (especially the next 50 lines after "registered worker") I’ll pinpoint the fix and provide exact changes to your deployment. Which step would you like to do now? , with interactive elements

athar@athar-computer:~/python_projects/WORKSHOP_DEMO/livekit-voice-agent$ lk app env -w Using project [suno-app]

Thanks — I can see the agent is RUNNING but uptime/load are 0% and your Secrets table shows only

GOOGLE_API_KEY

. That strongly suggests missing runtime secrets are preventing sessions from being served. Do this now (fastest path to fix) 1. In the LiveKit Cloud UI go to Project → Agents → your agent → Secrets → + and add any required secrets your agent uses (at minimum confirm you’ve added

LIVEKIT_API_KEY

,

LIVEKIT_API_SECRET

, and

LIVEKIT_URL

, plus any AI/provider keys like

OPENAI_API_KEY

or

ANTHROPIC_API_KEY

). 2. Redeploy the current version (Versions → your version → Redeploy) so the new secrets are injected. 3. Tail logs while reproducing: run

lk agent logs -w

and then click “Test in Console” in the UI. Paste any error lines after the existing “registered worker” log if it still fails. If you want to verify env vars inside the runtime first, add this masked startup snippet and redeploy (safe to log partial values): • Python:

import os
def m(v): return v[:4]+"..." if v else "<missing>"
for k in ("LIVEKIT_API_KEY","LIVEKIT_API_SECRET","LIVEKIT_URL","OPENAI_API_KEY"):
    print(f"{k}={m(os.getenv(k))}")

• Node:

const m=v=>v?v.slice(0,4)+'...':'<missing>';
["LIVEKIT_API_KEY","LIVEKIT_API_SECRET","LIVEKIT_URL","OPENAI_API_KEY"].forEach(k=>console.log(`${k}=${m(process.env[k])}`));

Tell me which secrets you added and paste the next 50 log lines after "registered worker" (or the errors from

lk agent logs -w

) and I’ll pinpoint the fix. , with interactive elements

image.png

Thanks — useful info. Your screenshots show only

GOOGLE_API_KEY

is set and the agent uptime/load are 0%, so the most likely cause is missing runtime secrets. Quick next steps (pick one to run now): 1) Add required secrets in Cloud UI • Project → Agents → your agent → Secrets → + • Add at minimum:

LIVEKIT_API_KEY

,

LIVEKIT_API_SECRET

,

LIVEKIT_URL

and any AI/third‑party keys your agent needs (e.g.,

OPENAI_API_KEY

,

ANTHROPIC_API_KEY

). • Redeploy the current version after adding secrets. 2) Verify env with CLI • Run:

lk app env -w

then open the created

.env.local

and confirm those variables appear. 3) Safe runtime check (temporary) • Add a masked startup log to your agent to confirm presence (does not print full secrets). Use the Python or Node snippet I shared earlier and redeploy. 4) Tail logs while testing • Run

lk agent logs -w

, click “Test in Console”, and paste the next 50 log lines after the existing “registered worker” message if it still fails. Which would you like me to walk you through first — adding secrets in the UI, the CLI env check, or adding the masked startup log? , with interactive elements

how to set secrets

Thanks — here’s exactly how to add secrets for your agent in LiveKit Cloud, both via the UI and CLI, plus how to verify them at runtime. UI (quick) 1. Open LiveKit Cloud → Project → Agents → select your agent. 2. Scroll to the Secrets section and click + (Add). 3. Choose Kind: Environment, enter the KEY and VALUE (e.g., OPENAI_API_KEY) and save. 4. After adding secrets, redeploy the current version (Versions → your version → Redeploy) so the new secrets are injected. Notes:

LIVEKIT_API_KEY

,

LIVEKIT_API_SECRET

, and

LIVEKIT_URL

are auto‑injected by LiveKit — don’t add them manually. CLI • Create/deploy with a secrets file: a. Create a file

.env

with lines: KEY=VALUE b. Run:

lk agent create . --secrets-file .env

• Deploy with inline secrets:

lk agent deploy . --secrets "OPENAI_API_KEY=sk...,GOOGLE_API_KEY=..."

• Update secrets without changing code:

lk agent update-secrets --secrets OPENAI_API_KEY=newkey --overwrite

• List secret keys (values hidden):

lk agent secrets

• Write runtime env to local file for inspection:

lk app env -w
  # opens/creates .env.local with injected vars (values for LiveKit creds will be present)

Safe verification at runtime • Add a masked startup log (doesn’t print full secrets). Example — Python:

import os
def m(v): return v[:4]+"..." if v else "<missing>"
for k in ("OPENAI_API_KEY","GOOGLE_API_KEY"):
    print(f"{k}={m(os.getenv(k))}")

Node:

const m=v=>v?v.slice(0,4)+'...':'<missing>';
["OPENAI_API_KEY","GOOGLE_API_KEY"].forEach(k=>console.log(`${k}=${m(process.env[k])}`));

• Or run

lk app env -w

and inspect

.env.local

locally to confirm keys are present. After you add secrets and redeploy: • Tail logs while testing:

lk agent logs -w

and trigger a session (Test in Console). Paste any error lines if the agent still fails. Tell me which secret(s) you want to add (e.g., OPENAI_API_KEY), and I’ll give the exact UI field values or the CLI command you should run. Sources: Agent Builder | LiveKit Documentation | https://docs.livekit.io/agents/deploy/| | Build a salary negotiation coach with a LemonSlice avatar | LiveKit, with interactive elements

look I elete the deploer agen and create anew one guide me

Okay — I’ll walk you through recreating and deploying a new agent step‑by‑step. I’ll assume you have your agent project locally and the

lk

CLI installed. Tell me if you want UI steps instead of CLI. 1) Prepare secrets • Create a file

.env

in your project with required keys (example): ◦ LIVEKIT_API_KEY=leave blank; LiveKit injects this automatically ◦ LIVEKIT_API_SECRET=leave blank; LiveKit injects this automatically ◦ LIVEKIT_URL=leave blank; LiveKit injects this automatically ◦ OPENAI_API_KEY=sk_... ◦ GOOGLE_API_KEY=... ◦ (add any other provider keys your agent needs) • Save

.env

. 2) Register & deploy the agent (CLI) • From your agent project directory run: ◦ To create and deploy using the secrets file: lk agent create . --secrets-file .env • Or to deploy an existing agent directory: lk agent deploy . --secrets-file .env • To pass inline secrets instead: lk agent deploy . --secrets "OPENAI_API_KEY=sk...,GOOGLE_API_KEY=..." 3) Verify deployment • Check status: lk agent status • Tail logs live: lk agent logs -w • Verify the agent registers (look for log line: "registered worker"). 4) If you need to add or update secrets later (no code redeploy) • Update secrets: lk agent update-secrets --secrets OPENAI_API_KEY=newkey --overwrite • List secret keys (values hidden): lk agent secrets 5) Quick runtime verification (safe) • Locally write runtime env to inspect: lk app env -w This creates

.env.local

with injected vars you can inspect. • Or add a masked startup log in your agent to confirm presence of keys (prints only first 4 chars). 6) Test the agent • In Cloud UI: Project → Agents → your agent → click “Test in Console”. • While testing, tail logs (

lk agent logs -w

) and paste any errors you see. If you want, I can: • Provide the exact

.env

template for your agent, • Give a sample

livekit.toml

/ Dockerfile if you need, • Or walk through the UI flow to create the agent instead. Which would you like me to do next? Sources: https://docs.livekit.io/agents/deploy/| | Voice AI quickstart | LiveKit Documentation | Server startup modes | LiveKit Documentation | Introduction | LiveKit Documentation, with interactive elements

(livekit-voice-agent) athar@athar-computer:~/python_projects/WORKSHOP_DEMO/livekit-voice-agent$ lk agent create . --secrets-file .env Using project [suno-app] Using agent configuration [livekit.toml] Creating new agent deployment open .env: no such file or directory

That error means

lk agent create . --secrets-file .env

couldn't find a

.env

file in your current directory. Create the file with the secrets your agent needs, then re-run the command. Quick steps: 1) Create

.env

in your project root: • Recommended contents (replace values):

# leave LiveKit core creds blank — they are auto‑injected
OPENAI_API_KEY=sk_...
GOOGLE_API_KEY=your_google_key
ANTHROPIC_API_KEY=your_anthropic_key
OTHER_SECRET=...

2) Save the file and run:

lk agent create . --secrets-file .env

Alternative (inline) if you prefer not to store a file:

lk agent create . --secrets "OPENAI_API_KEY=sk_...,GOOGLE_API_KEY=..."

3) After create/deploy: • Tail logs:

lk agent logs -w

• Verify registration: look for

registered worker

• If sessions still fail, run

lk app env -w

to write

.env.local

and confirm the deployed env, or add the masked startup log snippet I shared to check runtime vars. If you want, paste your intended

.env

keys (no values) and I’ll confirm which ones you must include. , with interactive elements

i have .env.local

Nice — since you already have

.env.local

, the CLI is just looking for

.env

. You have three quick options: • Rename the file: mv .env.local .env then run: lk agent create . --secrets-file .env • Or point the CLI at the existing file: lk agent create . --secrets-file .env.local • Or pass secrets inline (no file): lk agent create . --secrets "OPENAI_API_KEY=sk...,GOOGLE_API_KEY=..." If you want, paste the keys (not values) from your

.env.local

and I’ll confirm which ones you must include for deployment. , with interactive elements

it is being deployed

Nice — deployment is in progress. Do these next steps: 1. Wait for the build to finish, then check status: ◦ lk agent status 1. Tail logs while testing: ◦ lk agent logs -w ◦ Then click “Test in Console” in the dashboard and watch for errors or a "registered worker" + session logs. 1. If it fails, paste the next 50 log lines after "registered worker" and I’ll diagnose. Important security step (urgent): • I see API keys in your editor screenshot. Remove those from source, add `.env`/`.env.local` and

.env*

to

.gitignore

, and rotate any exposed keys immediately. Tell me the lk status output or paste logs when ready and I’ll guide the fix. , with interactive elements

ye or NO

Yes — that build log shows the image built and the agent is being deployed. Do these next two quick checks: 1) Confirm status: • Run:

lk agent status

◦ Look for the agent in RUNNING state and note the version. 2) Tail logs and test: • Run:

lk agent logs -w

• In the Cloud UI click Test in Console and reproduce the failure. • Paste any error lines after the existing “registered worker” log (or tell me if you see session start messages). Also important: rotate any API keys you exposed in your editor and add

.env*

to

.gitignore

. Do you want me to walk through reading the status output or pasting the logs here? , with interactive elements

nex?

Next: run these two commands and paste their output. 1) Check status: lk agent status 2) Tail logs and test: lk agent logs -w Then in the Cloud UI click “Test in Console” (or trigger a session) and paste any error lines you see after "registered worker". If status shows RUNNING and logs show sessions starting, confirm uptime in the dashboard. If you see errors, paste the log excerpt (50–100 lines) and I’ll diagnose. , with interactive elements

is it finished, or i should let it finished?

Let it finish building/deploying — then run these two checks: 1) Verify status: lk agent status 2) Tail logs and test: lk agent logs -w Then click “Test in Console” (or trigger a session) and watch for a "registered worker" log and session logs. If you paste the outputs (status and any error lines after "registered worker"), I’ll tell you the exact next fix. , with interactive elements

at this condition

Deployment is still running — wait for the build to finish (you’ll see the command return and a final success message). When it completes, run these two commands: 1) Check status: lk agent status 2) Tail logs and test: lk agent logs -w Then trigger a session via Cloud UI "Test in Console" and watch for "registered worker" and session logs. If you paste the outputs (status and any error lines after "registered worker"), I’ll diagnose the next steps. , with interactive elements

i has been quite a time

Sorry it’s taking long — let’s check what’s happening and get it unstuck. Quick checks (pick one — do them in a new terminal if your current build is blocked): 1) Is the build still running in the terminal? • If yes, wait for it to finish. If it’s hung >10–15 minutes, press Ctrl+C to cancel and retry the

lk agent create

command. 2) Check deployment status: • Run:

lk agent status

◦ If it shows a running deployment/version, proceed to logs. ◦ If no deployment or error, paste the

lk agent status

output here. 3) Tail logs while reproducing: • Run:

lk agent logs -w

• Then trigger a test session in the Cloud UI (“Test in Console”) and paste any error lines you see (especially after “registered worker”). 4) If the CLI build failed earlier, re-run create with verbose output: •

lk agent create . --secrets-file .env.local --verbose

◦ Paste the final lines or any error messages. If you want, I can guide you through cancelling and retrying the build, or troubleshoot any error lines you paste. Which step would you like to run now? , with interactive elements

ehere to run this

lk agent status

Run

lk agent status

in a terminal on your local machine inside the agent project directory (the same folder where you ran

lk agent create

and where `livekit.toml`/`Dockerfile` live). Steps: 1. Open a terminal. 2. cd to your project root (e.g.,

cd ~/python_projects/WORKSHOP_DEMO/livekit-voice-agent

). 3. Activate your virtual env if used (e.g.,

source .venv/bin/activate

). 4. Run: lk agent status If you get a permission or login error, run

lk login

first. Paste the command output here and I’ll interpret it. , with interactive elements

image.png

Great — your

lk agent status

shows the agent is Running. Next steps: 1. Tail logs while you test: ◦ Run:

lk agent logs -w

◦ In the Cloud UI click Test in Console (or trigger a session). 1. Watch for: ◦ A "registered worker" message (agent ready). ◦ Session assignment/start logs and any error lines after those messages. 1. If it still fails, paste the log excerpt (50–100 lines) containing errors after "registered worker" and I’ll diagnose. Quick reminders: • Confirm required secrets (OPENAI/ANTHROPIC/GOOGLE, etc.) are set in the agent Secrets and redeployed. • Rotate any API keys you accidentally committed. Tell me what the logs show after you run step 1–2. , with interactive elements

(livekit-voice-agent) athar@athar-computer:~/python_projects/WORKSHOP_DEMO/livekit-voice-agent$ lk agent logs -w Incorrect Usage: flag provided but not defined: -w flag provided but not defined: -w

Good catch — the

-w

flag isn't valid. Run this to stream logs for the current agent: • lk agent logs If you need to specify an agent ID: • lk agent logs --id CA_yourAgentID While logs stream, trigger a session with “Test in Console” in the Cloud UI and paste any error lines you see after the "registered worker" message. Sources: Where to find your Agent Logs | LiveKit | Deployment reliability on LiveKit Cloud | LiveKit | Where to find your Agent Logs | LiveKit | https://docs.livekit.io/agents/deploy/|, with interactive elements

how to test this

Great — here’s a concise, step‑by‑step way to test your deployed agent. 1) Stream the agent logs (in your project dir) • Run:

lk agent logs

(Or:

lk agent logs --id <AGENT_ID>

) 2) Open the Agent Console in the Cloud UI • Go to LiveKit Cloud → Project → Agents → select your agent → click “Test in Console” (or open the Agent Console link). 3) Start a test session • In the Console: choose the agent name, click “Save and start session.” • Grant the browser microphone permission when prompted. • Speak or use the text input in the Console. 4) Watch logs and dashboard • In the terminal streaming logs, look for: ◦ "registered worker" — agent is ready ◦ Session assignment/start logs (session id, participant joins) ◦ Any error messages or stack traces • In the Console you should see transcripts, responses, and audio activity. 5) If nothing happens • Confirm required secrets are set in the agent (OPENAI/GOOGLE/ANTHROPIC, etc.) and redeploy. • Confirm the agent shows RUNNING:

lk agent status

• Verify browser mic permissions and network access. • Paste the log lines you see after "registered worker" here and I’ll help debug. Want me to walk you through the Console UI now or to interpret your logs if you paste them? Sources: Google AI and LiveKit | LiveKit Documentation | Build Your First AI Voice Agent in Python: Complete Tutorial | LiveKit | Where to find your Agent Logs | LiveKit | Testing and evaluation | LiveKit Documentation, with interactive elements

it is talking in console

Nice — glad it’s speaking in the Console! Great signs your agent is running and connected. Next recommended steps (short): • Verify sessions in Agent Insights: open Project → Agents → your agent → Agent Insights / Sessions to confirm transcripts, audio, and logs are appearing. • Confirm uptime/load: check the dashboard’s Uptime and Average Load; session counts should increase when you test. • Review logs for errors: keep

lk agent logs

open while testing to catch any warnings or stack traces. • Confirm secrets & env: ensure all provider keys are set in Secrets (OPENAI/GOOGLE/ANTHROPIC, etc.) and rotate any keys you exposed earlier. • Prepare for production: add health/metrics endpoints, set alerts for errors/latency, and scale replicas if needed. If you want, I can: • Fetch and interpret the latest session logs for you, • Provide a CloudWatch/Fluent Bit config to forward logs, • Or walk through scaling and graceful shutdown settings. Which of those would you like next? , with interactive elements

i want to run in sandbox and connt using web

Great — here’s a short step‑by‑step to run your agent in sandbox/dev mode and connect from the web (Agent Console or sandbox frontend). 1) Start the agent in dev mode (in your project dir) • Python: uv run agent.py dev • Node: pnpm dev Wait for the console to show: "registered worker". 2) Open the Agent Console (web) • Go to LiveKit Cloud → Project → Agents → select your agent → click "Test in Console" (or open the Agent Console link shown in the UI). • Ensure the agent name matches the registered agent. 3) Start a sandbox session • In the Console click “Save and start session.” • Grant microphone permission when prompted. • Speak or use the text input to interact. 4) Use the sandbox frontend (optional) • In Agent Builder / Project UI, click “Test Agent” or create a sandbox app: ◦ Install CLI: curl -sSL https://get.livekit.io/cli | bash ◦ Bootstrap: lk app create --sandbox sandbox-id • This gives a shareable web frontend that connects to your running agent. 5) Troubleshooting quick checks • Confirm "registered worker" appears in agent logs. • Stream logs locally: lk agent logs (or watch your local console). • Check browser mic permissions. • Verify required secrets are set (OPENAI/GOOGLE/etc.) in the deployment or your local .env. • If no audio, confirm audio devices and browser output. Tell me whether you want the exact Agent Console URL for your project, the sandbox bootstrap command with your sandbox id, or a quick snippet to add a /diag HTTP endpoint for env verification. Which one now? Sources: Voice AI quickstart | LiveKit Documentation | Build Your First AI Voice Agent in Python: Complete Tutorial | LiveKit | Agent Builder | LiveKit Documentation, with interactive elements

listen i can launch it in sand box do i need to run in dev mode

Short answer: No — you only need dev mode if the agent process is running on your local machine. If you deployed the agent to LiveKit Cloud (a hosted deployment) and want to test via the sandbox/web Console, you do NOT need to run dev mode locally. When to use each: • Run in dev mode (e.g.,

uv run agent.py dev

or

pnpm dev

) when: ◦ You want to test a local agent instance and make live code changes. ◦ You need to debug locally while using the Agent Console or sandbox frontend to connect to your machine. • Don’t run dev mode when: ◦ You have deployed the agent to LiveKit Cloud and want the Cloud instance to handle sessions. Just use the Cloud “Test in Console” / sandbox frontend — it will connect to the deployed worker. If you tell me which you want (test locally in dev mode, or test the deployed Cloud agent), I’ll give the exact command(s) and the next steps. , with interactive elements

sandbox frontend

Great — to test your deployed agent using the sandbox frontend, follow these steps. 1) Ensure the agent is deployed and running • Confirm with:

lk agent status

(agent should show Running and 1/1 replicas). • Required secrets (OPENAI/GOOGLE/ANTHROPIC, etc.) must be set in the agent Secrets. 2) Create/boot a sandbox frontend (CLI) • Install CLI if needed: curl -sSL https://get.livekit.io/cli | bash • Bootstrap sandbox app (replace sandbox-id with the sandbox identifier shown in the UI): lk app create --sandbox sandbox-id • This builds and deploys a small web frontend pointing at your project’s LiveKit URL. 3) Open the sandbox web URL • After bootstrap completes the CLI prints a URL. Or open Project → Sandbox in the Cloud UI and click the sandbox link. • The sandbox frontend connects to LiveKit Cloud and will route sessions to your deployed agent (no local dev mode required). 4) Test the agent in the browser • Open the sandbox URL, click start, and grant microphone permission. • Interact with the agent; you should see audio/transcripts in the UI. 5) Monitor logs and sessions • Stream agent logs while you test: lk agent logs • Inspect sessions and Agent Insights in the Cloud UI (Project → Agents → Sessions). If you want, I can: • Provide the exact

lk app create

command with the sandbox id from your UI, or • Walk you through the Project → Sandbox UI steps. Which do you want? , with interactive elements

where to find sandbox id

You’ll find the sandbox ID in the LiveKit Cloud dashboard. Steps: 1. Open LiveKit Cloud → select your Project. 2. In the left menu click Sandbox (or Project → Sandbox). 3. The Sandbox page shows the sandbox entry and its ID (displayed as the sandbox identifier/token). If none exists, click Create / Regenerate test app and the page will show the new sandbox ID. Once you have the sandbox ID I can give the exact

lk app create --sandbox <sandbox-id>

command or the TokenSource code snippet to connect the web frontend. Which do you want? Sources: Build agent experiences faster with Session APIs | LiveKit | Agent Builder | LiveKit Documentation | Build a salary negotiation coach with a LemonSlice avatar | LiveKit | Build a salary negotiation coach with a LemonSlice avatar | LiveKit, with interactive elements

image.png

I can help — your screenshot shows the Sandbox settings page. To get the sandbox ID, create or open a sandbox app there. Two quick options: UI: 1. LiveKit Cloud → Project → Settings → Sandbox. 2. Under “Get started” click a starter (e.g., “Web Voice Agent”) or “Create / Regenerate test app.” 3. After creation, the page will display the sandbox entry and its sandbox ID/token. CLI: 1. Install CLI if needed: curl -sSL https://get.livekit.io/cli | bash 1. Bootstrap a sandbox app (replace sandbox-id with the ID once you have it): lk app create --sandbox sandbox-id If you want, I can: • Walk you through creating the sandbox in the UI step‑by‑step, or • Once you create it, give the exact

lk app create

command using your sandbox ID. Which would you like? , with interactive elements

image.png

Yes — select "Yes" to install dependencies. After that completes: 1. The CLI will finish provisioning the sandbox app and print a sandbox URL. 2. Open the sandbox URL in your browser, click Start, and grant mic permission to test your agent. 3. While testing, stream agent logs with

lk agent logs

and check Agent Insights for sessions. If you see any errors during installation or after opening the URL, paste the CLI output or the log lines and I’ll help debug. , with interactive elements

image.png

Run commands in a terminal on your local machine in the agent project directory (where your agent’s files like

livekit.toml

and

Dockerfile

are). Steps: 1. Open a terminal. 2. cd into your project directory, e.g.: cd ~/python_projects/WORKSHOP_DEMO/livekit-voice-agent 1. Activate your virtualenv if you use one, e.g.: source .venv/bin/activate 1. Run the command there: lk agent status or lk agent logs or lk app create --sandbox sandbox-id If you want I can give the exact command for your current project path — confirm your project folder name and whether you use a virtualenv. Sources: Voice AI quickstart | LiveKit Documentation | Debug voice agents in real time with Agent Console | LiveKit | Build Your First AI Voice Agent in Python: Complete Tutorial | LiveKit | Agent Builder | LiveKit Documentation | https://docs.livekit.io/agents/deploy/|, with interactive elements

please

Okay — I’ll give exact steps to run the sandbox app you created and test your agent from the web. Run these in a terminal on your machine. 1) Open the project folder and activate env • Replace path if different: cd ~/python_projects/WORKSHOP_DEMO/livekit-voice-agent source .venv/bin/activate (or on Windows: .venv\Scripts\activate) 2) Complete the sandbox bootstrap prompt • If

lk app create --sandbox <id>

is waiting and asking to install dependencies, choose Yes. • If it finished, note the URL printed by the CLI (it shows the sandbox frontend URL). 3) If the CLI created a local frontend project, start it • Change into the frontend folder it created (CLI prints path), then: ◦ If package.json uses pnpm: pnpm install pnpm dev • If npm: npm install npm run dev • If yarn: yarn install yarn dev • The CLI output will show a local URL (e.g., http//localhost3000) or the deployed sandbox preview URL. 4) Open the sandbox frontend in your browser • Use the URL from the CLI or open Project → Sandbox in LiveKit Cloud and click the sandbox link. • Click Start / Join and grant microphone permission. 5) While testing, monitor your agent • Stream agent logs: lk agent logs • Confirm agent is Running: lk agent status • Check Agent Insights → Sessions in the Cloud UI for transcripts/audio. If you don’t see the sandbox URL in the CLI output, paste the final CLI output here (or tell me the folder name the CLI created) and I’ll point to the exact file & start command. , with interactive elements