flet-stt 0.1.2

Speech-to-text for Flet apps via OS-native recognition (Android/iOS)

flet-stt

Speech-to-text for Flet apps via OS-native recognition (Android/iOS).

Install

pip install flet-stt

App pyproject.toml setup

Three things are required in your app's pyproject.toml for APK builds:

[project]
dependencies = ["flet>=0.82.0", "flet-stt"]

# 1. microphone permission
[tool.flet.android.permission]
"android.permission.RECORD_AUDIO" = true

# 2. prevent source shadowing in APK
[tool.flet.app]
exclude = ["flet_stt"]

# 3. extension discovery
[tool.flet.dev_packages]
flet-stt = "flet_stt"

All three are needed. Missing any one causes silent failures or build errors.

Quick start

import json
import flet as ft
from flet_stt import FletStt

def main(page: ft.Page):
    stt = FletStt()  # do NOT add to page.overlay or page.controls

    def on_result(e):
        data = json.loads(e.data)
        if data["final"]:
            print(f"Recognized: {data['text']}")

    stt.on_result = on_result

    async def start(e):
        await stt.initialize()
        await stt.listen(listen_mode="dictation")

    page.add(ft.Button(content="Listen", on_click=start))

ft.run(main)

More examples in examples/.

Common pitfalls

1. Do not add FletStt to page.overlay or page.controls

FletStt is a service, not a visual control. It registers itself automatically. Adding it to page.overlay, page.controls, or page.add() causes a red crash screen on Android with no useful error message.

# WRONG - causes crash
stt = FletStt()
page.overlay.append(stt)

# CORRECT - just instantiate
stt = FletStt()

2. Always uninstall before reinstalling APK

Flet's serious_python caches the extracted Python environment. adb install -r silently runs old code.

adb uninstall com.yourapp.package
adb install build/apk/app-release.apk

3. on_device=True may silently produce no results

On-device speech models may not be installed on the device. Recognition starts, status says "listening", but no results come back and no error fires. The default is on_device=False (cloud) which includes a 15-second timeout that fires a cloud_recognition_timeout error if nothing comes back.

API

FletStt()

Instantiate once. Assign event handlers before calling listen().

Events

Event	e.data	Description
on_result	{"text": "...", "final": true, "confidence": 0.95, "alternates": [...]}	Recognition result. final=false for partial results.
on_error	{"error": "...", "permanent": false}	Error. Includes cloud_recognition_timeout when cloud returns nothing.
on_status	{"status": "listening"}	Status: "listening", "notListening", "done".
on_sound_level	{"level": -6.5}	Mic dB level during listening.

Methods

await initialize() -> bool - initialize recognizer, request mic permission. Call before listen().

await listen(...)

Parameter	Default	Description
locale_id	""	BCP-47 locale (e.g. "en_US"). Empty = system default.
listen_for_seconds	0	Max duration. 0 = platform default (~60s).
pause_for_seconds	0	Silence before auto-stop. 0 = platform default.
partial_results	True	Fire on_result for partial results.
on_device	False	Use on-device recognition. Default is cloud.
cancel_on_error	False	Cancel on error instead of continuing.
sample_rate	0	Hz. 0 = platform default.
listen_mode	"confirmation"	"confirmation", "search", or "dictation".

await stop() - stop and get final result.

await cancel() - stop without final result.

await locales() -> list[dict] - available locales.

await system_locale() -> dict - system default locale.

await is_listening() -> bool / await has_permission() -> bool

Platform notes

• Android: Google Speech Services. On-device for ~50 languages. Auto-stops after ~5s silence / ~60s total. Requires RECORD_AUDIO.
• iOS: Apple SFSpeechRecognizer. On-device since iOS 15 for major languages. Needs NSSpeechRecognitionUsageDescription and NSMicrophoneUsageDescription in Info.plist.
• Desktop: instantiates without error but recognition won't work (no native plugin).

Building APK

flet build apk -v

On Windows, set PYTHONIOENCODING=utf-8 before building to avoid Unicode crashes.

License

MIT