Create Vector Store with OpenAI (ChatGPT) API

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

Trigger workflow on

HTTP requests, schedules and app events

Next, do this

Create Vector Store with the OpenAI (ChatGPT) API

No credit card required

▶

Watch us build a workflow

8 min

Watch now ➜

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

Developers ♥ Pipedream

Getting Started#

Create a workflow to Create Vector Store with the OpenAI (ChatGPT) API. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Configure the Create Vector Store action
1. Connect your OpenAI (ChatGPT) account
2. Optional- Select one or more File IDs
3. Optional- Configure Name
4. Optional- Configure Expiration Days
5. Optional- Configure Metadata
Select a trigger to run your workflow on HTTP requests, schedules or app events
Deploy the workflow
Send a test event to validate your setup
Turn on the trigger

Integrations#

Create Vector Store with OpenAI (ChatGPT) API on New Requests (Payload Only) from HTTP / Webhook API

HTTP / Webhook + OpenAI (ChatGPT)

Try it

Create Vector Store with OpenAI (ChatGPT) API on New Submission from Typeform API

Typeform + OpenAI (ChatGPT)

Try it

Create Vector Store with OpenAI (ChatGPT) API on New Submission (Instant) from Jotform API

Jotform + OpenAI (ChatGPT)

Try it

Create Vector Store with OpenAI (ChatGPT) API on New Scheduled Tasks from Pipedream API

Pipedream + OpenAI (ChatGPT)

Try it

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

npm + OpenAI (ChatGPT)

Try it

Details#

This is a pre-built, source-available component from Pipedream's GitHub repo. The component is 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.

Create Vector Store on OpenAI (ChatGPT)

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

Version:0.0.5

Key:openai-create-vector-store

View on GitHub

Code#

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

export default {
  key: "openai-create-vector-store",
  name: "Create Vector Store",
  description: "Create a vector store. [See the documentation](https://platform.openai.com/docs/api-reference/vector-stores/create)",
  version: "0.0.5",
  type: "action",
  props: {
    openai,
    fileIds: {
      propDefinition: [
        openai,
        "fileId",
      ],
      type: "string[]",
      label: "File IDs",
      description: "An array of File IDs that the vector store should use",
      optional: true,
      reloadProps: true,
    },
    name: {
      type: "string",
      label: "Name",
      description: "Name of the vector store",
      optional: true,
    },
    expiryDays: {
      type: "integer",
      label: "Expiration Days",
      description: "The number of days after the `last_active_at` time that the vector store will expire",
      optional: true,
    },
    metadata: {
      type: "object",
      label: "Metadata",
      description: "Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format",
      optional: true,
    },
  },
  additionalProps() {
    const props = {};
    if (!this.fileIds?.length) {
      return props;
    }

    props.chunkingStrategy = {
      type: "string",
      label: "Chunking Strategy",
      description: "The chunking strategy used to chunk the file(s)",
      options: [
        "auto",
        "static",
      ],
      optional: true,
      reloadProps: true,
    };

    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.createVectorStore({
      $,
      data: {
        file_ids: this.fileIds,
        name: this.name,
        expires_after: this.expiryDays && {
          anchor: "last_active_at",
          days: this.expiryDays,
        },
        chunking_strategy: this.chunkingStrategy && {
          type: this.chunkingStrategy,
          static: this.chunkingStrategy === "static"
            ? {
              max_chunk_size_tokens: this.maxChunkSizeTokens,
              chunk_overlap_tokens: this.chunkOverlapTokens,
            }
            : undefined,
        },
        metadata: this.metadata,
      },
    });
    $.export("$summary", `Successfully created vector store with ID: ${response.id}`);
    return response;
  },
};

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.
File IDs	`fileIds`	`string[]`	Select a value from the drop down menu.
Name	`name`	`string`	Name of the vector store
Expiration Days	`expiryDays`	`integer`	The number of days after the `last_active_at` time that the vector store will expire
Metadata	`metadata`	`object`	Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format