notilens 0.5.5

NotiLens — send alerts to NotiLens from Python scripts, apps, and AI agents

NotiLens

Send alerts to NotiLens from Python scripts, apps, and AI agents.

Two ways to use it — pick one or both:

• CLI — for shell scripts, Claude Code hooks, bash pipelines
• SDK — for Python projects, with optional AI framework auto-patching

---

---

CLI

Use the CLI in shell scripts, Claude Code hooks, or any terminal workflow.

1. Setup (required, one time)

Get your token and secret from the NotiLens dashboard.

notilens init --name my-app --token YOUR_TOKEN --secret YOUR_SECRET

This saves credentials to ~/.notilens_config.json. All future commands for this agent read from there — no need to pass token/secret again.

Multiple sources (each notifies a different topic):

notilens init --name scraper --token TOKEN_A --secret SECRET_A
notilens init --name mailer  --token TOKEN_B --secret SECRET_B

---

2. Notify

The simplest way to send a notification — no task or run context needed:

notilens notify order.placed    "Order #1234"      --name my-app
notilens notify disk.space.full "Only 2GB left"    --name my-app --level warning
notilens notify report.ready    "Report is ready"  --name my-app --download_url https://example.com/report.pdf

---

3. Commands

--task is a semantic label (e.g. email, report). Each task.start creates an isolated run internally — concurrent executions of the same label never conflict.

Task Lifecycle

notilens queue    --name my-app --task email
notilens start    --name my-app --task email
notilens progress "Fetching data"  --name my-app --task email
notilens loop     "Step 3 of 10"   --name my-app --task email
notilens retry    --name my-app --task email
notilens pause    "Rate limited"   --name my-app --task email
notilens resume   "Resuming"       --name my-app --task email
notilens wait     "Awaiting tool"  --name my-app --task email
notilens stop     --name my-app --task email
notilens complete "All done"       --name my-app --task email
notilens error    "Step 3 failed"  --name my-app --task email
notilens fail     "Unrecoverable"  --name my-app --task email
notilens timeout  "Took too long"  --name my-app --task email
notilens cancel   "User cancelled" --name my-app --task email
notilens terminate "Out of memory" --name my-app --task email

task.start prints the internal run_id to stdout. You can capture it if needed — but for sequential scripts, just use --task LABEL and the SDK handles the rest automatically.

Input / Human-in-the-loop

notilens input.required "Please confirm the output" --name my-app --task email
notilens input.approve  "Confirmed"                 --name my-app --task email
notilens input.reject   "Rejected by user"          --name my-app --task email

Output Events

notilens output.generate "Report ready"     --name my-app --task email
notilens output.fail     "Model unavailable" --name my-app --task email

Metrics

Pass any key=value pairs — numeric values accumulate across calls:

notilens metric tokens=512 cost=0.003 --name my-app --task email
notilens metric records=1500          --name my-app --task email

# Reset one metric
notilens metric.reset tokens --name my-app --task email

# Reset all metrics
notilens metric.reset --name my-app --task email

Custom Events

notilens track user.registered "New signup"      --name my-app
notilens track disk.space.full "Only 2GB left"   --name my-app
notilens track order.placed    "Order #1234"      --name my-app

---

4. Full CLI Example

# Register once
notilens init --name summarizer --token my_token --secret my_secret

# Run a job
notilens start --name summarizer --task report

notilens metric tokens=1024 --name summarizer --task report
notilens metric cost=0.004  --name summarizer --task report

notilens complete "Summary ready" \
  --name summarizer \
  --task report \
  --open_url https://example.com/summary.pdf \
  --meta pages=12

---

5. Claude Code Hooks Example

Register the agent once:

notilens init --name claude-code --token YOUR_TOKEN --secret YOUR_SECRET

Then in ~/.claude/settings.json:

{
  "hooks": {
    "PreToolUse": [{
      "matcher": "",
      "hooks": [{
        "type": "command",
        "command": "notilens progress \"Using tool: $CLAUDE_TOOL_NAME\" --name claude-code --task $CLAUDE_SESSION_ID"
      }]
    }],
    "Stop": [{
      "matcher": "",
      "hooks": [{
        "type": "command",
        "command": "notilens complete \"Session ended\" --name claude-code --task $CLAUDE_SESSION_ID"
      }]
    }]
  }
}

---

CLI Options

Flag	Required	Description
--name NAME	Yes	Name identifying the source (agent, app, service, etc.)
--task LABEL	For task commands	Task label (semantic name, e.g. email, report)
--level	No	Override level: debug info warning error
--meta key=value	No	Custom metadata (repeatable)
--image_url URL	No	Attach an image
--open_url URL	No	Link to open
--download_url URL	No	Link to download
--tags "tag1,tag2"	No	Comma-separated tags
--is_actionable true|false	No	Override actionable flag
--force_send true|false	No	Bypass ML filtering. Default true for notify, fail, timeout, terminate, input.required, output.*

---

---

SDK

Use the SDK in Python projects. Supports manual task lifecycle calls and optional auto-patching of AI frameworks.

1. Setup (required)

import notilens

# token/secret can also come from NOTILENS_TOKEN / NOTILENS_SECRET env vars
nl = notilens.init(
    name="my-app",    # required — name identifying this source
    token="YOUR_TOKEN",  # required — or set NOTILENS_TOKEN env var
    secret="YOUR_SECRET" # required — or set NOTILENS_SECRET env var
)

Via environment variables:

export NOTILENS_TOKEN=your_token
export NOTILENS_SECRET=your_secret

nl = notilens.init(name="my-app")  # reads token+secret from env

All init options:

nl = notilens.init(
    name="my-app",      # required
    token="...",           # required (or env var)
    secret="...",          # required (or env var)
    patch=False,           # optional — auto-patch AI frameworks (default: False)
    state_ttl=86400,       # optional — orphaned state TTL in seconds (default: 86400 / 24h)
    min_level="info",      # optional — minimum event level to send (default: "info")
    call_timeout=30.0,     # optional — alert if AI call exceeds N seconds (default: 30)
    debug=False,           # optional — verbose logging (default: False)
)

---

2. Notify

The simplest way to send a notification — no task or run context needed:

nl.notify("order.placed", "Order #1234")
nl.notify("disk.space.full", "Only 2GB left", level="warning")
nl.notify("report.ready", "Your report is ready",
    download_url="https://example.com/report.pdf",
    meta={"pages": 12},
    tags="report,weekly",
)
# force_send=True by default — pass False to route through ML
nl.notify("low.priority", "FYI only", force_send=False)

Also available on a run, without any run state attached:

run.notify("deploy.done", "Deployed to production",
    open_url="https://example.com/deploy/123",
)

---

3. Task Lifecycle

nl.task(label) creates a Run — an isolated execution context with its own state. Multiple concurrent runs of the same label never conflict.

run = nl.task("email")     # create a run for the "email" task
run.queue()                    # optional — pre-start signal
run.start()                    # begin the run

run.progress("Fetching data")  # mid-run update
run.loop("Processing item 42") # loop iteration marker
run.retry()                    # retry signal

# Pause / resume / wait (non-terminal)
run.pause("Rate limited")
run.resume("Resuming work")
run.wait("Waiting for tool response")

run.stop()                     # non-terminal stop

# Non-terminal error (run continues)
run.error("Step 3 failed, retrying")

# Terminal events — pick one to end the run
run.complete("All done")
run.fail("Unrecoverable error")
run.timeout("Exceeded time limit")
run.cancel("User cancelled")
run.terminate("OOM")

---

4. Input / Human-in-the-loop

run.input_required("Confirm before proceeding")
run.input_approved("User confirmed")
run.input_rejected("User rejected")

---

5. Output Events

run.output_generated("Summary ready")
run.output_failed("Model unavailable")

---

6. Metrics

Track any numeric or string values per run — accumulated automatically and included in every notification.

run.metric("tokens", 350)    # set
run.metric("tokens", 210)    # now 560 (numeric values accumulate)
run.metric("cost", 0.0012)
run.metric("records", 1500)
run.metric("model", "gpt-4") # strings are replaced, not accumulated

run.reset_metrics("tokens")  # reset one metric
run.reset_metrics()           # reset all metrics

---

Automatic Timing

NotiLens automatically tracks task timing. These fields are included in every notification's meta payload when non-zero:

Field	Description
total_duration_ms	Wall-clock time since start
queue_ms	Time between queue and start
pause_ms	Cumulative time spent paused
wait_ms	Cumulative time spent waiting
active_ms	Active time (total − pause − wait)

---

force_send

By default NotiLens routes notifications through ML-based filtering and relevance ranking. Set force_send=True to bypass ML and deliver immediately to the user.

Events/methods that default to force_send=True (high-signal events):

CLI command	SDK method	Default
notilens notify	notify()	True
notilens fail	fail()	True
notilens timeout	timeout()	True
notilens terminate	terminate()	True
notilens input.required	input_required()	True
notilens output.generate	output_generated()	True
notilens output.fail	output_failed()	True
Everything else	Everything else	False

All commands and methods accept force_send as an overridable parameter:

CLI:

# Override to go through ML
notilens fail "Error" --name my-app --task email --force_send false

# Override to bypass ML
notilens progress "Critical step" --name my-app --task email --force_send true

SDK:

# Override a default-True method to go through ML
run.fail("Unrecoverable error", force_send=False)

# Override a default-False method to bypass ML
run.progress("Critical checkpoint", force_send=True)

---

7. Custom Events

run.track("user.registered", "New signup", meta={"plan": "pro"})  # meta optional
run.track("disk.space.full", "Only 2GB left", level="warning")    # level optional
run.track("order.placed", "Order #1234", meta={"amount": 99.99})

---

8. Auto-patching AI Frameworks

Add patch=True to init() — no other changes needed. NotiLens will automatically track every AI call.

import notilens
import openai  # or anthropic, langchain, crewai, pydantic-ai

nl = notilens.init(
    name="my-app",
    token="YOUR_TOKEN",
    secret="YOUR_SECRET",
    patch=True,           # required to enable auto-patching
    call_timeout=30.0,    # optional — alert if any AI call takes longer than 30s
)

# From here, use OpenAI / Anthropic etc. normally.
# NotiLens fires ai.call.start, ai.call.complete, task.error, task.timeout, task.loop automatically.
response = openai.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Summarise this..."}],
)

Multiple agents — only one can own patching:

scraper = notilens.init(name="scraper", token="TOKEN_A", secret="SECRET_A", patch=True)
mailer  = notilens.init(name="mailer",  token="TOKEN_B", secret="SECRET_B")
# patch=True on a second agent raises RuntimeError

---

9. Full SDK Example

import notilens

nl = notilens.init("summarizer", token="my_token", secret="my_secret")
run   = nl.task("report")
run.start()

try:
    run.progress("Fetching PDF")

    result = llm.complete(prompt)
    run.metric("tokens", result.usage.total_tokens)
    run.metric("cost", result.usage.cost)

    run.output_generated("Summary ready")
    run.complete("All done")

except Exception as e:
    run.fail(str(e))

---

---

Events Reference

Event	Default Type	Description
task.queued	info	Task queued
task.started	info	Task began
task.progress	info	Mid-run update
task.loop	warning	Loop iteration
task.retry	warning	Retry attempt
task.completed	success	Task finished successfully
task.stopped	info	Manually stopped
task.failed	urgent	Task failed
task.error	urgent	Non-fatal error
task.timeout	urgent	Exceeded time limit
task.cancelled	warning	Task cancelled
task.terminated	urgent	Force-terminated
task.paused	warning	Task paused
task.resumed	info	Task resumed
task.waiting	warning	Waiting for external response
output.generated	success	Output produced (AI response, report, file, etc.)
output.failed	urgent	Output generation failed
input.required	warning	Waiting for human input
input.approved	success	Input approved
input.rejected	warning	Input rejected

---

Requirements

• Python >= 3.9

License

MIT — notilens.com