Create Vector Store File with OpenAI (ChatGPT) API on New Download Counts from npm API

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New Download Counts from the npm API

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Create Vector Store File with the OpenAI (ChatGPT) API

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Getting Started#

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

Select this integration
Configure the New Download Counts trigger
1. Connect your npm account
2. Configure timer
3. Select a Period
4. Optional- Configure Package
Configure the Create Vector Store File action
1. Connect your OpenAI (ChatGPT) account
2. Select a Vector Store ID
3. Select a File ID
4. Optional- Select a Chunking Strategy
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 Download Counts on npm

Description:Emit new event with the latest count of downloads for an npm package. [See the documentation](https://github.com/npm/registry/blob/main/docs/download-counts.md).

Version:0.1.0

Key:npm-download-counts

View on GitHub

Trigger Code#

import app from "../../npm.app.mjs";

export default {
  key: "npm-download-counts",
  name: "New Download Counts",
  description: "Emit new event with the latest count of downloads for an npm package. [See the documentation](https://github.com/npm/registry/blob/main/docs/download-counts.md).",
  version: "0.1.0",
  type: "source",
  props: {
    app,
    db: "$.service.db",
    timer: {
      type: "$.interface.timer",
      description: "One day interval time is recommended because NPM only update metrics once a day. [See the documentation](https://github.com/npm/registry/blob/main/docs/download-counts.md#data-source).",
      default: {
        intervalSeconds: 60 * 60 * 24,
      },
    },
    period: {
      type: "string",
      label: "Period",
      description: "Select last-day, last-week or last-month.",
      optional: false,
      default: "last-day",
      options: [
        "last-day",
        "last-week",
        "last-month",
      ],
    },
    packageName: {
      type: "string",
      label: "Package",
      description: "Enter an npm package name. Leave blank for all",
      optional: true,
    },
  },
  methods: {
    getDownloadCounts({
      period, packageName, ...args
    } = {}) {
      const basePath = `/downloads/point/${encodeURIComponent(period)}`;
      return this.app.makeRequest({
        path: packageName
          ? `${basePath}/${encodeURIComponent(packageName)}`
          : basePath,
        ...args,
      });
    },
  },
  async run({ timestamp: ts }) {
    const {
      getDownloadCounts,
      period,
      packageName,
    } = this;

    const response = await getDownloadCounts({
      period,
      packageName,
    });

    this.$emit(response, {
      id: ts,
      summary: `New Download Count ${response.downloads}`,
      ts,
    });
  },
};

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
npm	`app`	`app`	This component uses the npm app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
	`timer`	`$.interface.timer`	One day interval time is recommended because NPM only update metrics once a day. See the documentation
Period	`period`	`string`	Select a value from the drop down menu:`last-daylast-weeklast-month`
Package	`packageName`	`string`	Enter an npm package name. Leave blank for all

Trigger Authentication#

The npm API does not require authentication.

About npm#

Node package manager

Action#

Create Vector Store File on OpenAI (ChatGPT)

Description:Create a vector store file. [See the documentation](https://platform.openai.com/docs/api-reference/vector-stores-files/createFile)

Version:0.0.5

Key:openai-create-vector-store-file

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:

Action Code#

import openai from "../../openai.app.mjs";

export default {
  key: "openai-create-vector-store-file",
  name: "Create Vector Store File",
  description: "Create a vector store file. [See the documentation](https://platform.openai.com/docs/api-reference/vector-stores-files/createFile)",
  version: "0.0.5",
  type: "action",
  props: {
    openai,
    vectorStoreId: {
      propDefinition: [
        openai,
        "vectorStoreId",
      ],
    },
    fileId: {
      propDefinition: [
        openai,
        "fileId",
      ],
    },
    chunkingStrategy: {
      type: "string",
      label: "Chunking Strategy",
      description: "The chunking strategy used to chunk the file",
      options: [
        "auto",
        "static",
      ],
      optional: true,
      reloadProps: true,
    },
  },
  additionalProps() {
    const props = {};

    if (this?.chunkingStrategy === "static") {
      props.maxChunkSizeTokens = {
        type: "integer",
        label: "Max Chunk Size Tokens",
        description: "The maximum number of tokens in each chunk. The default value is `800`. The minimum value is `100` and the maximum value is `4096`.",
        default: 800,
        optional: true,
      };
      props.chunkOverlapTokens = {
        type: "integer",
        label: "Chunk Overlap Tokens",
        description: "The number of tokens that overlap between chunks. The default value is `400`. Note that the overlap must not exceed half of max_chunk_size_tokens.",
        default: 400,
        optional: true,
      };
    }

    return props;
  },
  async run({ $ }) {
    const response = await this.openai.createVectorStoreFile({
      $,
      vectorStoreId: this.vectorStoreId,
      data: {
        file_id: this.fileId,
        chunking_strategy: this.chunkingStrategy && {
          type: this.chunkingStrategy,
          static: this.chunkingStrategy === "static"
            ? {
              max_chunk_size_tokens: this.maxChunkSizeTokens,
              chunk_overlap_tokens: this.chunkOverlapTokens,
            }
            : undefined,
        },
      },
    });
    $.export("$summary", `Successfully created vector store file with ID: ${response.id}`);
    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
OpenAI (ChatGPT)	`openai`	`app`	This component uses the OpenAI (ChatGPT) app.
Vector Store ID	`vectorStoreId`	`string`	Select a value from the drop down menu.
File ID	`fileId`	`string`	Select a value from the drop down menu.
Chunking Strategy	`chunkingStrategy`	`string`	Select a value from the drop down menu:`autostatic`

Create Vector Store File with OpenAI (ChatGPT) API on New Download Counts from npm API

Pipedream makes it easy to connect APIs for OpenAI (ChatGPT), npm and 2,500+ other apps remarkably fast.

Trusted by 1,000,000+ developers from startups to Fortune 500 companies

Developers ♥ Pipedream

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