Tutorial: Run ClawBio Skills via a Telegram Bot

Production bot available: If you want the full-featured bot with Claude-powered reasoning, medication photo detection, and the RoboTerri persona, see bot/roboterri.py and its README. The tutorial below builds a simpler version from scratch for learning purposes.

This tutorial walks you through building a Telegram bot that runs ClawBio skills. By the end, you'll be able to send a genetic data file to your bot and receive a pharmacogenomics report, equity score, or genome comparison — all running locally on your machine.

Time: ~20 minutes | Difficulty: Intermediate | Prerequisites: Python 3.11+, a Telegram account

Overview
Prerequisites
Clone and Install ClawBio
Create a Telegram Bot
Get Your Telegram Chat ID
Set Up Your API Key
Build the Bot
Run It
Test It
Next Steps
Troubleshooting

1. Overview

You (Telegram)  →  Your bot (your machine)  →  ClawBio skills (local)
      ↑                                              │
      └──────── report + figures ←───────────────────┘

The bot you'll build:

Accepts messages and genetic data files in Telegram
Routes to the correct ClawBio skill via the CLI
Runs the analysis locally — no genetic data leaves your machine
Sends back a summary, report, and figures directly in Telegram

2. Prerequisites

Requirement	Version	Check
Python	3.11+	`python3 --version`
pip	latest	`pip3 install --upgrade pip`
Git	any	`git --version`
Telegram	account + app	telegram.org

macOS

brew install python@3.11

Linux (Ubuntu/Debian)

sudo apt update && sudo apt install python3.11 python3.11-venv python3-pip

3. Clone and Install ClawBio

git clone https://github.com/ClawBio/ClawBio.git
cd ClawBio
pip3 install -r requirements.txt

Verify it works:

python3 clawbio.py list
python3 clawbio.py run pharmgx --demo

You should see a pharmacogenomics report generated in under 1 second.

4. Create a Telegram Bot

Open Telegram and search for @BotFather
Send /newbot
Choose a name (e.g., "My ClawBio Agent")
Choose a username (must end in bot, e.g., my_clawbio_bot)
BotFather replies with your bot token — save it securely

Security: Never share your bot token or commit it to Git. Treat it like a password.

Optional: Set bot commands

Still in the BotFather chat, send /setcommands, select your bot, then paste:

start - Start the bot
demo - Run a ClawBio demo skill

5. Get Your Telegram Chat ID

Restrict your bot so only you can use it. To find your chat ID:

Start a conversation with your new bot (press Start)
Send any message (e.g., "hello")
Open this URL in your browser (replace YOUR_BOT_TOKEN):

https://api.telegram.org/botYOUR_BOT_TOKEN/getUpdates

Look for "chat":{"id":123456789} — that number is your chat ID

Alternatively, search for @userinfobot on Telegram and send /start.

6. Set Up Your API Key

Install the Telegram bot library:

pip3 install "python-telegram-bot[job-queue]"

Create a file called .env in the ClawBio directory:

TELEGRAM_BOT_TOKEN=your-bot-token-here
TELEGRAM_CHAT_ID=your-chat-id-here

Add .env to your .gitignore so it never gets committed:

echo ".env" >> .gitignore

7. Build the Bot

Create a file called telegram_bot.py in the ClawBio directory:

#!/usr/bin/env python3
"""Minimal Telegram bot that runs ClawBio skills."""

import os
import subprocess
import tempfile
from pathlib import Path

from dotenv import load_dotenv
from telegram import Update
from telegram.ext import (
    Application,
    CommandHandler,
    ContextTypes,
    MessageHandler,
    filters,
)

load_dotenv()

BOT_TOKEN = os.environ["TELEGRAM_BOT_TOKEN"]
ALLOWED_CHAT_ID = int(os.environ["TELEGRAM_CHAT_ID"])
CLAWBIO = Path(__file__).parent / "clawbio.py"


def is_authorised(update: Update) -> bool:
    return update.effective_chat.id == ALLOWED_CHAT_ID


async def start(update: Update, ctx: ContextTypes.DEFAULT_TYPE):
    if not is_authorised(update):
        return
    await update.message.reply_text(
        "ClawBio Telegram Bot\n\n"
        "Commands:\n"
        "  /demo <skill>  — Run a demo (pharmgx, equity, nutrigx, compare)\n"
        "  /list           — List available skills\n\n"
        "Or send a genetic data file (.txt, .csv, .vcf) to analyse it."
    )


async def list_skills(update: Update, ctx: ContextTypes.DEFAULT_TYPE):
    if not is_authorised(update):
        return
    result = subprocess.run(
        ["python3", str(CLAWBIO), "list"],
        capture_output=True, text=True, timeout=30,
    )
    await update.message.reply_text(f"```\n{result.stdout}\n```", parse_mode="Markdown")


async def demo(update: Update, ctx: ContextTypes.DEFAULT_TYPE):
    if not is_authorised(update):
        return
    skill = ctx.args[0] if ctx.args else "pharmgx"
    await update.message.reply_text(f"Running {skill} demo...")

    with tempfile.TemporaryDirectory() as tmpdir:
        cmd = ["python3", str(CLAWBIO), "run", skill, "--demo", "--output", tmpdir]
        result = subprocess.run(cmd, capture_output=True, text=True, timeout=300)

        if result.returncode != 0:
            await update.message.reply_text(f"Error:\n```\n{result.stderr[:2000]}\n```", parse_mode="Markdown")
            return

        # Send stdout summary
        if result.stdout.strip():
            for chunk in [result.stdout[i:i+4000] for i in range(0, len(result.stdout), 4000)]:
                await update.message.reply_text(chunk)

        # Send generated files (reports, figures)
        output = Path(tmpdir)
        for md_file in sorted(output.rglob("*.md")):
            await update.message.reply_document(document=open(md_file, "rb"))
        for img_file in sorted(output.rglob("*.png")):
            await update.message.reply_photo(photo=open(img_file, "rb"))


async def handle_file(update: Update, ctx: ContextTypes.DEFAULT_TYPE):
    """Auto-detect genetic file and run the appropriate skill."""
    if not is_authorised(update):
        return
    doc = update.message.document
    if not doc:
        return

    await update.message.reply_text(f"Received {doc.file_name}. Analysing...")

    # Download file
    tg_file = await doc.get_file()
    with tempfile.TemporaryDirectory() as tmpdir:
        local_path = Path(tmpdir) / doc.file_name
        await tg_file.download_to_drive(local_path)

        # Detect skill by extension
        ext = local_path.suffix.lower()
        if ext in (".txt", ".csv"):
            skill = "pharmgx"
        elif ext == ".vcf":
            skill = "equity"
        else:
            await update.message.reply_text(f"Unsupported file type: {ext}")
            return

        out_dir = Path(tmpdir) / "output"
        out_dir.mkdir()
        cmd = ["python3", str(CLAWBIO), "run", skill, "--input", str(local_path), "--output", str(out_dir)]
        result = subprocess.run(cmd, capture_output=True, text=True, timeout=300)

        if result.returncode != 0:
            await update.message.reply_text(f"Error:\n```\n{result.stderr[:2000]}\n```", parse_mode="Markdown")
            return

        if result.stdout.strip():
            for chunk in [result.stdout[i:i+4000] for i in range(0, len(result.stdout), 4000)]:
                await update.message.reply_text(chunk)

        for md_file in sorted(out_dir.rglob("*.md")):
            await update.message.reply_document(document=open(md_file, "rb"))
        for img_file in sorted(out_dir.rglob("*.png")):
            await update.message.reply_photo(photo=open(img_file, "rb"))


def main():
    app = Application.builder().token(BOT_TOKEN).build()
    app.add_handler(CommandHandler("start", start))
    app.add_handler(CommandHandler("list", list_skills))
    app.add_handler(CommandHandler("demo", demo))
    app.add_handler(MessageHandler(filters.Document.ALL, handle_file))
    print("Bot is running. Press Ctrl+C to stop.")
    app.run_polling()


if __name__ == "__main__":
    main()

This is a self-contained bot (~100 lines) that:

Restricts access to your chat ID only
Runs /demo pharmgx, /demo equity, /demo compare etc.
Auto-detects genetic file types when you send a document
Sends back reports and figures

8. Run It

python3 telegram_bot.py

You should see:

Bot is running. Press Ctrl+C to stop.

Run in the background (optional)

# Using nohup
nohup python3 telegram_bot.py > bot.log 2>&1 &

# Or using screen
screen -S clawbio-bot
python3 telegram_bot.py
# Detach: Ctrl+A, then D
# Reattach: screen -r clawbio-bot

9. Test It

Open your Telegram bot and try:

List skills

You: /list
Bot: Available skills:
       pharmgx    Pharmacogenomics reporter ...
       equity     HEIM equity scorer ...
       ...

Run a demo

You: /demo pharmgx
Bot: Running pharmgx demo...
     CYP2D6 *4/*4 — Poor Metabolizer → 10 drugs AVOID
     [report.md attached]
     [figures attached]

Send your own genetic data

Export your 23andMe raw data (Settings > 23andMe Data > Download Raw Data)
Send the .txt file to the bot
The bot auto-detects the format and runs PharmGx Reporter

You: [attach 23andMe_raw_data.txt]
Bot: Received 23andMe_raw_data.txt. Analysing...
     CYP2C19 *1/*2 — Intermediate Metabolizer
     ...

10. Next Steps

Add more skills: Extend handle_file() to route .fastq to metagenomics, or add keyword detection
Add Claude reasoning: Use the Anthropic SDK to add conversational AI around the skill results
Build your own skill: See CONTRIBUTING.md and the skill template
Explore the architecture: See docs/architecture.md
Watch the demo: ClawBio at UK AI Agent Hack

11. Troubleshooting

"ModuleNotFoundError: No module named 'telegram'"

pip3 install "python-telegram-bot[job-queue]"

Bot doesn't respond

Verify your chat ID matches what's in .env
Check the bot token is correct (no extra spaces or quotes)
Send /start to your bot first

ClawBio skill fails

Run it standalone to isolate the issue:

python3 clawbio.py run pharmgx --demo

Permission denied

Make sure clawbio.py is executable or invoke it via python3:

python3 clawbio.py run pharmgx --demo

ClawBio is a research and educational tool. It is not a medical device and does not provide clinical diagnoses. Consult a healthcare professional before making any medical decisions.

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Tutorial: Run ClawBio Skills via a Telegram Bot

Table of Contents

1. Overview

2. Prerequisites

macOS

Linux (Ubuntu/Debian)

3. Clone and Install ClawBio

4. Create a Telegram Bot

Optional: Set bot commands

5. Get Your Telegram Chat ID

6. Set Up Your API Key

7. Build the Bot

8. Run It

Run in the background (optional)

9. Test It

List skills

Run a demo

Send your own genetic data

10. Next Steps

11. Troubleshooting

"ModuleNotFoundError: No module named 'telegram'"

Bot doesn't respond

ClawBio skill fails

Permission denied

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Tutorial: Run ClawBio Skills via a Telegram Bot

Table of Contents

1. Overview

2. Prerequisites

macOS

Linux (Ubuntu/Debian)

3. Clone and Install ClawBio

4. Create a Telegram Bot

Optional: Set bot commands

5. Get Your Telegram Chat ID

6. Set Up Your API Key

7. Build the Bot

8. Run It

Run in the background (optional)

9. Test It

List skills

Run a demo

Send your own genetic data

10. Next Steps

11. Troubleshooting

"ModuleNotFoundError: No module named 'telegram'"

Bot doesn't respond

ClawBio skill fails

Permission denied