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2026-01-26 15:17:54 +01:00
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# System
.DS_Store
Thumbs.db
# Config and Secrets
.env
.env.*
!.env.example
data/config.json
data/*.lock
data/*.signal
# Runtime Data
data/*.madeline
data/*.madeline.*
data/*.mp3
data/*.wav
data/*.log
redis_data/
# Dependencies (if installed locally)
vendor/
composer.lock
# IDE
.idea/
.vscode/

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FROM php:8.2-cli
# Install dependencies
RUN apt-get update && apt-get install -y \
ffmpeg \
libffi-dev \
libgmp-dev \
libxml2-dev \
espeak \
libcurl4-openssl-dev \
libssl-dev \
libonig-dev \
git \
unzip \
&& docker-php-ext-install ffi gmp simplexml dom curl sockets mbstring
# Install Composer
COPY --from=composer:latest /usr/bin/composer /usr/bin/composer
# Set working directory
WORKDIR /app
# Copy source code
COPY . /app
COPY piper /app/piper
# Expose Web Port
EXPOSE 8000
# Entrypoint
RUN chmod +x start.sh
CMD ["./start.sh"]

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# Telemovris 2.0 - Telegram TTS Call Bot
A dockerized application that converts text to audio (using Piper Neural TTS) and calls a Telegram user to play the message. Includes a modern Web Dashboard for management.
## Features
* **High Quality TTS**: Uses [Piper](https://github.com/rhasspy/piper) with `es_ES-sharvard-medium` model for human-like speech.
* **Web Dashboard**: Manage queue, view history, and test voices via browser.
* **Web-based Login**: Log in to your Telegram account directly from the UI (supports 2FA).
* **Web-based Configuration**: Set `API_ID` and `API_HASH` without touching config files.
* **Real-time Queue**: Redis-backed queue with history and error reporting.
* **Smart Dialing**: Waits for the user to answer before playing audio.
* **Legacy API Support**: Compatible with simple GET requests.
## Prerequisites
* Docker & Docker Compose
## Installation
1. **Clone the repository**:
```bash
git clone https://gitlab.com/your/telemovris2.git
cd telemovris2
```
2. **Ensure Piper binaries are present**:
The project expects the Piper TTS binary and model in the `piper/` directory.
* `piper/piper/piper` (Executable)
* `piper/es_ES-sharvard-medium.onnx` (Model)
* `piper/es_ES-sharvard-medium.onnx.json` (Config)
3. **Start the container**:
```bash
docker compose up -d --build
```
## Configuration & Usage
### 1. Initial Setup
1. Open your browser and navigate to `http://localhost:8234`.
2. You will be prompted to enter your **Telegram API ID** and **API Hash**.
* Get these from [my.telegram.org](https://my.telegram.org).
3. Click **Save Configuration**. The worker will restart.
### 2. Login
1. After configuration, the dashboard will show a **Login Now** button.
2. Enter your **Phone Number** (international format, e.g., `+34...`).
3. Scan the **QR Code** using your Telegram Mobile App (Settings > Devices > Link Desktop Device).
* *Note: If the QR code expires or fails, check `docker logs telemovris_app` for details.*
### 3. Sending Messages
* **Via Dashboard**: Use the "Queue New Task" form.
* **Via Legacy API**:
```
GET http://localhost:8234/sendmessage?user=@username&message=Hello+World&audio=yes
```
## Development
* **Reset Config**: If you need to change accounts or keys, click the "Reset Config" button in the dashboard (when disconnected).
* **Logs**: Check worker logs for debugging:
```bash
docker logs -f telemovris_app
```
## Persistence
* **Session**: Telegram session is stored in `./data/session.madeline`.
* **Redis**: Job queue and history are persisted in `./redis_data`.
* **Config**: API credentials are stored in `./data/config.json`.
## License
MIT

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services:
redis:
image: redis:alpine
container_name: telemovris_redis
restart: always
command: redis-server --appendonly yes
volumes:
- ./redis_data:/data
app:
build: .
container_name: telemovris_app
ports:
- "8234:8000"
volumes:
- ./src:/app/src
- ./data:/app/data
env_file:
- .env
environment:
- REDIS_HOST=redis
dns:
- 8.8.8.8
- 1.1.1.1
depends_on:
- redis
restart: always

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{
"audio": {
"sample_rate": 22050,
"quality": "medium"
},
"espeak": {
"voice": "es"
},
"inference": {
"noise_scale": 0.667,
"length_scale": 1,
"noise_w": 0.8
},
"phoneme_type": "espeak",
"phoneme_map": {},
"phoneme_id_map": {
"_": [
0
],
"^": [
1
],
"$": [
2
],
" ": [
3
],
"!": [
4
],
"'": [
5
],
"(": [
6
],
")": [
7
],
",": [
8
],
"-": [
9
],
".": [
10
],
":": [
11
],
";": [
12
],
"?": [
13
],
"a": [
14
],
"b": [
15
],
"c": [
16
],
"d": [
17
],
"e": [
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],
"f": [
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],
"h": [
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],
"i": [
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],
"j": [
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],
"k": [
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],
"l": [
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],
"m": [
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],
"n": [
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],
"o": [
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],
"p": [
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],
"q": [
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],
"r": [
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],
"s": [
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],
"t": [
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],
"u": [
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],
"v": [
34
],
"w": [
35
],
"x": [
36
],
"y": [
37
],
"z": [
38
],
"æ": [
39
],
"ç": [
40
],
"ð": [
41
],
"ø": [
42
],
"ħ": [
43
],
"ŋ": [
44
],
"œ": [
45
],
"ǀ": [
46
],
"ǁ": [
47
],
"ǂ": [
48
],
"ǃ": [
49
],
"ɐ": [
50
],
"ɑ": [
51
],
"ɒ": [
52
],
"ɓ": [
53
],
"ɔ": [
54
],
"ɕ": [
55
],
"ɖ": [
56
],
"ɗ": [
57
],
"ɘ": [
58
],
"ə": [
59
],
"ɚ": [
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],
"ɛ": [
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],
"ɜ": [
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],
"ɞ": [
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],
"ɟ": [
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],
"ɠ": [
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],
"ɡ": [
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],
"ɢ": [
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],
"ɣ": [
68
],
"ɤ": [
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],
"ɥ": [
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],
"ɦ": [
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],
"ɧ": [
72
],
"ɨ": [
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],
"ɪ": [
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],
"ɫ": [
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],
"ɬ": [
76
],
"ɭ": [
77
],
"ɮ": [
78
],
"ɯ": [
79
],
"ɰ": [
80
],
"ɱ": [
81
],
"ɲ": [
82
],
"ɳ": [
83
],
"ɴ": [
84
],
"ɵ": [
85
],
"ɶ": [
86
],
"ɸ": [
87
],
"ɹ": [
88
],
"ɺ": [
89
],
"ɻ": [
90
],
"ɽ": [
91
],
"ɾ": [
92
],
"ʀ": [
93
],
"ʁ": [
94
],
"ʂ": [
95
],
"ʃ": [
96
],
"ʄ": [
97
],
"ʈ": [
98
],
"ʉ": [
99
],
"ʊ": [
100
],
"ʋ": [
101
],
"ʌ": [
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],
"ʍ": [
103
],
"ʎ": [
104
],
"ʏ": [
105
],
"ʐ": [
106
],
"ʑ": [
107
],
"ʒ": [
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],
"ʔ": [
109
],
"ʕ": [
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],
"ʘ": [
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],
"ʙ": [
112
],
"ʛ": [
113
],
"ʜ": [
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],
"ʝ": [
115
],
"ʟ": [
116
],
"ʡ": [
117
],
"ʢ": [
118
],
"ʲ": [
119
],
"ˈ": [
120
],
"ˌ": [
121
],
"ː": [
122
],
"ˑ": [
123
],
"˞": [
124
],
"β": [
125
],
"θ": [
126
],
"χ": [
127
],
"ᵻ": [
128
],
"ⱱ": [
129
],
"0": [
130
],
"1": [
131
],
"2": [
132
],
"3": [
133
],
"4": [
134
],
"5": [
135
],
"6": [
136
],
"7": [
137
],
"8": [
138
],
"9": [
139
],
"̧": [
140
],
"̃": [
141
],
"̪": [
142
],
"̯": [
143
],
"̩": [
144
],
"ʰ": [
145
],
"ˤ": [
146
],
"ε": [
147
],
"↓": [
148
],
"#": [
149
],
"\"": [
150
],
"↑": [
151
],
"̺": [
152
],
"̻": [
153
]
},
"num_symbols": 256,
"num_speakers": 2,
"speaker_id_map": {
"M": 0,
"F": 1
},
"piper_version": "1.0.0",
"language": {
"code": "es_ES",
"family": "es",
"region": "ES",
"name_native": "Español",
"name_english": "Spanish",
"country_english": "Spain"
},
"dataset": "sharvard"
}

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name Vietnamese (Northern)
language vi
words 1 2
pitch 95 175
tone 100 225 800 100 2000 50 5400 75 8000 200

9
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name Vietnamese (Central)
language vi-vn-x-central
phonemes vi-hue
dictrules 1
words 1
pitch 82 118 //80 118
voicing 90 //18
flutter 20

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piper/piper/espeak-ng-data/lang/aav/vi-VN-x-south Normal file
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name Vietnamese (Southern)
language vi-vn-x-south
phonemes vi-sgn
dictrules 2
words 1
pitch 82 118 //80 118
voicing 90 //18
flutter 20

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name Esperanto
language eo
apostrophe 2

2
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name Interlingua
language ia

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name Ido
language io
phonemes eo
status testing

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name Lojban
language jbo
speed 80 // speed adjustment, percentage

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name Lingua Franca Nova
language lfn
phonemes base2
l_unpronouncable 0
numbers 2 3
stressLength 150 140 180 180 0 0 200 200

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name Klingon
language piqd
status testing
stressRule 3

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name Pyash
language py
maintainer Logan Streondj <logan@liberit.ca>
status testing
speed 80 // speed adjustment, percentage
stressRule 0

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name Lang Belta
language qdb
numbers 4 3
replace 1 t ?

4
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name Quenya
language qya
stressRule 2
// rule=penultimate, with qya_rules for light penultimate syllables to move primary stress to the preceding (antepenultimate) syllable

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name Sindarin
language sjn
stressRule 2
// rule=penultimate, with sjn_rules for light penultimate syllables to move primary stress to the preceding (antepenultimate) syllable

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name Nahuatl (Classical)
language nci
intonation 3
stressRule 2
stressLength 190 190 200 200 0 0 220 240

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name Lithuanian
language lt

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name Latgalian
language ltg
maintainer Valdis Vitolins <valdis.vitolins@odo.lv>
status testing
phonemes lv
dictionary lv
dictrules 2 // Setting for Latgalian pronunciation
words 0 2
pitch 64 118
tone 60 150 204 100 400 255 700 10 3000 255
stressAmp 12 10 8 8 0 0 15 16
stressLength 160 140 200 140 0 0 240 160

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name Latvian
language lv
maintainer Valdis Vitolins <valdis.vitolins@odo.lv>
status mature
words 0 2
pitch 67 123
tone 60 150 204 100 400 255 700 10 3000 255
stressAmp 11 8 11 9 0 0 14 12
stressLength 160 120 200 130 0 0 230 180

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name Swahili
language sw
status testing

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name Setswana
language tn
status testing

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name Georgian
language ka
lowercaseSentence // A period followed by a lowercase letter is considered a sentence (mkhedruli)

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name Welsh
language cy
intonation 4

4
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name Gaelic (Irish)
language ga
dictrules 1 // fix for eclipsis

4
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name Gaelic (Scottish)
language gd
status testing

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name Oromo
language om
status testing

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name Kannada
language kn
intonation 2
//consonants 80

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name Malayalam
language ml
intonation 2
//consonants 80

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name Tamil
language ta
intonation 2
consonants 80

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name Telugu
language te
status testing
intonation 2
//consonants 80

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name Greenlandic
language kl

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name Basque
language eu
status testing
stressRule 15

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name Danish
language da
tunes s2 c2 q2 e2

2
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name Icelandic
language is

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name Norwegian Bokmål
language nb
language no
phonemes no
dictionary no
intonation 4

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