Document Question Answering with Hugging Face API on New Message Updates (Instant) from Telegram Bot API

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New Message Updates (Instant) from the Telegram Bot API

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Document Question Answering with the Hugging Face API

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Getting Started#

This integration creates a workflow with a Telegram Bot trigger and Hugging Face action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Select this integration
Configure the New Message Updates (Instant) trigger
1. Connect your Telegram Bot account
Configure the Document Question Answering action
1. Connect your Hugging Face account
2. Select a Model ID
3. Configure Image URL
4. Configure Question
Deploy the workflow
Send a test event to validate your setup
Turn on the trigger

Details#

This integration uses pre-built, source-available components from Pipedream's GitHub repo. These components are developed by Pipedream and the community, and verified and maintained by Pipedream.

To contribute an update to an existing component or create a new component, create a PR on GitHub. If you're new to Pipedream component development, you can start with quickstarts for trigger span and action development, and then review the component API reference.

Trigger#

New Message Updates (Instant) on Telegram Bot

Description:Emit new event each time a Telegram message is created or updated.

Version:0.1.5

Key:telegram_bot_api-message-updates

View on GitHub

Telegram Bot Overview#

The Telegram Bot API allows you to build bots that can interact with users on the Telegram platform. Using Pipedream, you can automate messaging, handle commands, and trigger actions based on conversations or alerts. Pipedream's serverless execution model enables you to create complex workflows involving Telegram messages without managing any infrastructure. With Pipedream's integration, you can process inbound messages, send outbound notifications, and connect the Telegram Bot API with numerous other services to create powerful automation solutions.

Trigger Code#

import base from "../common/webhooks.mjs";
import sampleEmit from "./test-event.mjs";

export default {
  ...base,
  key: "telegram_bot_api-message-updates",
  name: "New Message Updates (Instant)",
  description: "Emit new event each time a Telegram message is created or updated.",
  version: "0.1.5",
  type: "source",
  dedupe: "unique",
  methods: {
    ...base.methods,
    getMeta(event, message) {
      return {
        id: event.update_id,
        summary: message.text,
        ts: new Date(message.edit_date ?? message.date),
      };
    },
    getEventTypes() {
      return [
        "message",
        "edited_message",
      ];
    },
    processEvent(event) {
      const message = event.edited_message ?? event.message;
      this.$emit(event, this.getMeta(event, message));
    },
  },
  sampleEmit,
};

Trigger Configuration#

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI and CLI.

Label	Prop	Type	Description
Telegram Bot	`telegramBotApi`	`app`	This component uses the Telegram Bot app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
N/A	`http`	`$.interface.http`	This component uses `$.interface.http` to generate a unique URL when the component is first instantiated. Each request to the URL will trigger the `run()` method of the component.

Trigger Authentication#

Telegram Bot uses API keys for authentication. When you connect your Telegram Bot account, Pipedream securely stores the keys so you can easily authenticate to Telegram Bot APIs in both code and no-code steps.

To use the Telegram Bot API, you must first create a new bot by chatting with the BotFather.

After you create your bot, copy the bot token and add it below.

About Telegram Bot#

Telegram, is a cloud-based, cross-platform, encrypted instant messaging (IM) service.

Action#

Document Question Answering on Hugging Face

Description:Want to have a nice know-it-all bot that can answer any question?. This action allows you to ask a question and get an answer from a trained model. [See the docs](https://huggingface.co/docs/huggingface.js/inference/classes/HfInference#questionanswer).

Version:0.0.1

Key:hugging_face-document-question-answering

View on GitHub

Hugging Face Overview#

The Hugging Face API provides access to a vast range of machine learning models, primarily for natural language processing (NLP) tasks like text classification, translation, summarization, and question answering. It lets you leverage pre-trained models and fine-tune them on your data. Using the API within Pipedream, you can automate workflows that involve language processing, integrate AI insights into your apps, or respond to events with AI-generated content.

Action Code#

import app from "../../hugging_face.app.mjs";
import tag from "../common/tag.mjs";

export default {
  key: "hugging_face-document-question-answering",
  name: "Document Question Answering",
  description: "Want to have a nice know-it-all bot that can answer any question?. This action allows you to ask a question and get an answer from a trained model. [See the docs](https://huggingface.co/docs/huggingface.js/inference/classes/HfInference#questionanswer).",
  type: "action",
  version: "0.0.1",
  props: {
    app,
    modelId: {
      propDefinition: [
        app,
        "modelId",
        () => ({
          tagFilter: tag.DOCUMENT_QUESTION_ANSWERING,
        }),
      ],
    },
    imageUrl: {
      description: "The image url to use for answering the question.",
      propDefinition: [
        app,
        "imageUrl",
      ],
    },
    question: {
      type: "string",
      label: "Question",
      description: "The question to ask.",
    },
  },
  async run({ $: step }) {
    const {
      modelId,
      imageUrl,
      question,
    } = this;

    const image = await this.app.getBinaryFromUrl(imageUrl);

    const response = await this.app.inference({
      step,
      modelId,
      data: {
        inputs: {
          image,
          question,
        },
      },
    });

    step.export("$summary", `Successfully answered question with score ${response[0].score}`);

    return response;
  },
};

Action Configuration#

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI.

Label	Prop	Type	Description
Hugging Face	`app`	`app`	This component uses the Hugging Face app.
Model ID	`modelId`	`string`	Select a value from the drop down menu.
Image URL	`imageUrl`	`string`	The image url to use for answering the question.
Question	`question`	`string`	The question to ask.

Action Authentication#

Hugging Face uses API keys for authentication. When you connect your Hugging Face account, Pipedream securely stores the keys so you can easily authenticate to Hugging Face APIs in both code and no-code steps.

To retrieve your Access Tokens,