Example: Telegram LLM Bot

A minimal ready-to-run kdeps workflow that connects a Telegram bot to a local Ollama LLM.

Files

telegram-bot/
├── workflow.yaml
└── resources/
    ├── llm.yaml
    └── reply.yaml

workflow.yaml

apiVersion: kdeps.io/v1
kind: Workflow

metadata:
  name: telegram-llm-bot
  description: Telegram bot that answers messages with an LLM
  version: "1.0.0"
  targetActionId: reply

settings:
  agentSettings:
    timezone: Etc/UTC
    installOllama: true
    models:
      - llama3.2:3b

  input:
    sources: [bot]
    bot:
      executionType: polling
      telegram:
        botToken: "{{ env('TELEGRAM_BOT_TOKEN') }}"
        pollIntervalSeconds: 1

resources/llm.yaml

apiVersion: kdeps.io/v1
kind: Resource

metadata:
  actionId: llm
  name: LLM Response

run:
  chat:
    backend: ollama
    model: llama3.2:3b
    messages:
      - role: user
        content: "{{ input('message') }}"

resources/reply.yaml

apiVersion: kdeps.io/v1
kind: Resource

metadata:
  actionId: reply
  name: Reply

dependencies:
  - llm

run:
  botReply:
    text: "{{ get('llm') }}"

Running

export TELEGRAM_BOT_TOKEN="1234567890:AAH..."
kdeps run workflow.yaml

See Also

• Bot Tutorial — Step-by-step walkthrough
• Input Sources — Full platform config reference