Logger Bot

A Telegram bot that accepts voice messages, transcribes them, and parses workout data (exercise, reps, weight) for logging to a csv or database.

Architecture

flowchart LR
    user([User])
    telegram(Telegram Bot)
    server([Server])
    extractor([Speech2Text + parsing])
    logger([Logger])
    db([Database])

    user -- voice --> telegram
    telegram -- webhook --> server
    server -- audio --> extractor
    extractor -- text --> server
    server -- text --> logger
    logger --entry--> db

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Requirements

• uv package manager
• A Telegram bot token (from @BotFather)

Setup your bot server using uv

1. Configure the bot token Create a bot using Telegram's @BotFather. Grab your token and create a .env file in the project root with it like this:

TELEGRAM_API_TOKEN=your_telegram_bot_token_here

2. Launch Server Make sure you have uv installed in your machine.

Run this on your terminal (at project root level):

./run_server.sh

That will set up the venv, install dependencies and launch the server that communicates with your telegram bot.

You can healthcheck the server typing /health on your telegram bot chat.

Using the bot

The bot will listen for voice, messages and commands (start with /).

You can send a voice message describing your workout. The bot transcribes it, parses the result, and logs it into the database/csv file.

The bot understands natural language, for example:

• "Press de banca, 10 repeticiones, 80 kilos, categoría pecho"
• "Sentadilla 5 reps 100 kg"
• "Shoulder press 8 repetitions 60 lbs"

Bot Commands

These are the commands

• /last <exercise>: Returns the most recent logged set for a given exercise, as a JSON code block, for example /last sentadilla.
• /sql <query>: Runs a SQL query against log.db and returns the results as a JSON code block. The connection is read-only, so only SELECT statements work, for example:

/sql
SELECT * FROM logs 
where exercise like "%press%"
order by date desc
LIMIT 10

Launch the database view You can visualize your database and run queries against it using a UI. Run this command to launch the UI:

./launch_db_view.sh

This script:

• Imports your latest log.csv into a SQLite database called log.db (table: logs).
• Starts a local Datasette server.

Open your browser on http://127.0.0.1:8001 — you'll see your workouts as an interactive table.