AI Data Extraction with Scrapfly API on New File Created from OpenAI (ChatGPT) API

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New File Created from the OpenAI (ChatGPT) API

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AI Data Extraction with the Scrapfly API

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Getting Started#

This integration creates a workflow with a OpenAI (ChatGPT) trigger and Scrapfly action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Select this integration
Configure the New File Created trigger
1. Connect your OpenAI (ChatGPT) account
2. Configure timer
3. Optional- Select a Purpose
Configure the AI Data Extraction action
1. Connect your Scrapfly account
2. Configure Body
3. Select a Content Type
4. Configure URL
5. Optional- Configure Charset
6. Optional- Configure Extraction Template
7. Optional- Configure Extraction Prompt
8. Optional- Configure Extraction Model
9. Optional- Configure Webhook Name
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 File Created on OpenAI (ChatGPT)

Description:Emit new event when a new file is created in OpenAI. [See the documentation](https://platform.openai.com/docs/api-reference/files/list)

Version:0.0.10

Key:openai-new-file-created

View on GitHub

OpenAI (ChatGPT) Overview#

OpenAI provides a suite of powerful AI models through its API, enabling developers to integrate advanced natural language processing and generative capabilities into their applications. Here’s an overview of the services offered by OpenAI's API:

Use Python or Node.js code to make fully authenticated API requests with your OpenAI account:

Trigger Code#

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

export default {
  ...common,
  key: "openai-new-file-created",
  name: "New File Created",
  description: "Emit new event when a new file is created in OpenAI. [See the documentation](https://platform.openai.com/docs/api-reference/files/list)",
  version: "0.0.10",
  type: "source",
  dedupe: "unique",
  props: {
    ...common.props,
    purpose: {
      propDefinition: [
        common.props.openai,
        "purpose",
      ],
      description: "If specified, events will only be emitted for files with the specified purpose.",
      optional: true,
    },
  },
  methods: {
    ...common.methods,
    getData() {
      return this.openai.listFiles({
        purpose: this.purpose,
      });
    },
    getMeta(item) {
      return {
        id: item.id,
        summary: `New File: ${item.filename}`,
        ts: item.created_at * 1000,
      };
    },
  },
  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
OpenAI (ChatGPT)	`openai`	`app`	This component uses the OpenAI (ChatGPT) app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
	`timer`	`$.interface.timer`
Purpose	`purpose`	`string`	Select a value from the drop down menu:`fine-tuneassistantsvisionbatch`

Trigger Authentication#

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

About OpenAI (ChatGPT)#

OpenAI is an AI research and deployment company with the mission to ensure that artificial general intelligence benefits all of humanity. They are the makers of popular models like ChatGPT, DALL-E, and Whisper.

Action#

AI Data Extraction on Scrapfly

Description:Automate content extraction from any text-based source using AI, LLM, and custom parsing. [See the documentation](https://scrapfly.io/docs/extraction-api/getting-started)

Version:0.0.1

Key:scrapfly-ai-data-extraction

View on GitHub

Action Code#

import { ConfigurationError } from "@pipedream/platform";
import fs from "fs";
import { checkTmp } from "../../common/utils.mjs";
import scrapfly from "../../scrapfly.app.mjs";

export default {
  key: "scrapfly-ai-data-extraction",
  name: "AI Data Extraction",
  description: "Automate content extraction from any text-based source using AI, LLM, and custom parsing. [See the documentation](https://scrapfly.io/docs/extraction-api/getting-started)",
  version: "0.0.1",
  type: "action",
  props: {
    scrapfly,
    body: {
      propDefinition: [
        scrapfly,
        "body",
      ],
    },
    contentType: {
      propDefinition: [
        scrapfly,
        "contentType",
      ],
    },
    url: {
      propDefinition: [
        scrapfly,
        "url",
      ],
    },
    charset: {
      type: "string",
      label: "Charset",
      description: "Charset of the document pass in the body. If you are not sure, you can use the `auto` value and we will try to detect it. Bad charset can lead to bad extraction, so it's important to set it correctly. **The most common charset is `utf-8` for text document and `ascii` for binary**. The symptom of a bad charset is that the text is not correctly displayed (accent, special characters, etc).",
      default: "auto",
      optional: true,
    },
    extractionTemplate: {
      type: "string",
      label: "Extraction Template",
      description: "Define an extraction template to get structured data. Use an ephemeral template (declared on the fly on the API call) or a stored template (declared in the dashboard) by using the template name.",
      optional: true,
    },
    extractionPrompt: {
      type: "string",
      label: "Extraction Prompt",
      description: "Instruction to extract data or ask a question on the scraped content with an LLM (Large Language Model). [Must be url encoded](https://scrapfly.io/web-scraping-tools/urlencode).",
      optional: true,
    },
    extractionModel: {
      type: "string",
      label: "Extraction Model",
      description: "AI Extraction to auto parse document to get structured data. E.g., `product`, `review`, `real-estate`, `article`.",
      optional: true,
    },
    webhookName: {
      type: "string",
      label: "Webhook Name",
      description: "Queue you scrape request and redirect API response to a provided webhook endpoint. You can create a webhook endpoint from your `dashboard`, it takes the name of the webhook. Webhooks are scoped to the given project/env.",
      optional: true,
    },
  },
  async run({ $ }) {
    if (!this.extractionTemplate && !this.extractionPrompt && !this.extractionModel) {
      throw new ConfigurationError("You must provide at least **Extraction Template**, **Extraction Prompt** or **Extraction Model**");
    }
    const response = await this.scrapfly.automateContentExtraction({
      $,
      headers: {
        "content-type": this.contentType,
      },
      maxBodyLength: Infinity,
      params: {
        url: this.url,
        charset: this.charset,
        extraction_template: this.extractionTemplate,
        extraction_prompt: this.extractionPrompt,
        extraction_model: this.extractionModel,
        webhook_name: this.webhookName,
      },
      data: fs.readFileSync(checkTmp(this.body)).toString(),
    });

    $.export("$summary", "Successfully extracted content");
    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
Scrapfly	`scrapfly`	`app`	This component uses the Scrapfly app.
Body	`body`	`string`	The request body must contain the content of the page you want to extract data from. The content must be in the format specified by the `content-type` header or via the `content_type` HTTP parameter. Provide a file from `/tmp`. To upload a file to `/tmp` folder, please follow the doc here
Content Type	`contentType`	`string`	Select a value from the drop down menu:`application/jsonapplication/jsonldapplication/xmltext/plaintext/htmltext/markdowntext/csvapplication/xhtml+xml`
URL	`url`	`string`	This URL is used to transform any relative URLs in the document into absolute URLs automatically. It can be either the base URL or the exact URL of the document. Must be url encoded.
Charset	`charset`	`string`	Charset of the document pass in the body. If you are not sure, you can use the `auto` value and we will try to detect it. Bad charset can lead to bad extraction, so it's important to set it correctly. The most common charset is `utf-8` for text document and `ascii` for binary. The symptom of a bad charset is that the text is not correctly displayed (accent, special characters, etc).
Extraction Template	`extractionTemplate`	`string`	Define an extraction template to get structured data. Use an ephemeral template (declared on the fly on the API call) or a stored template (declared in the dashboard) by using the template name.
Extraction Prompt	`extractionPrompt`	`string`	Instruction to extract data or ask a question on the scraped content with an LLM (Large Language Model). Must be url encoded.
Extraction Model	`extractionModel`	`string`	AI Extraction to auto parse document to get structured data. E.g., `product`, `review`, `real-estate`, `article`.
Webhook Name	`webhookName`	`string`	Queue you scrape request and redirect API response to a provided webhook endpoint. You can create a webhook endpoint from your `dashboard`, it takes the name of the webhook. Webhooks are scoped to the given project/env.