Chat with Kindo API on New Requests from HTTP / Webhook API

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New Requests from the HTTP / Webhook API

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Getting Started#

This integration creates a workflow with a HTTP / Webhook trigger and Kindo action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Select this integration
Configure the New Requests trigger
1. Optional- Configure Body Only
2. Optional- Configure Response Status Code
3. Optional- Configure Response Content-Type
4. Optional- Configure Response Body
5. Connect your HTTP / Webhook account
Configure the Chat action
1. Connect your Kindo account
2. Configure Model
3. Configure Messages
4. Optional- Configure Max Tokens
5. Optional- Configure Temperature
6. Optional- Configure Top P
7. Optional- Configure N
8. Optional- Configure Stop
9. Optional- Configure Presence Penalty
10. Optional- Configure Frequency Penalty
11. Optional- Configure Additional Parameters
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 Requests on HTTP / Webhook

Description:Get a URL and emit the full HTTP event on every request (including headers and query parameters). You can also configure the HTTP response code, body, and more.

Version:0.1.1

Key:http-new-requests

View on GitHub

HTTP / Webhook Overview#

Build, test, and send HTTP requests without code using your Pipedream workflows. The HTTP / Webhook action is a tool to build HTTP requests with a Postman-like graphical interface.

Point and click HTTP requests

Define the target URL, HTTP verb, headers, query parameters, and payload body without writing custom code.

$A screenshot of Pipedream's HTTP Request Configuration interface with a GET request type selected. The request URL is set to 'https://api.openai.com/v1/models'. The 'Auth' tab is highlighted, indicating that authentication is required for this request. In the headers section, there are two headers configured: 'User-Agent' is set to 'pipedream/1', and 'Authorization' is set to 'Bearer {{openai_api_key}}', showing how the OpenAI account's API key is dynamically inserted into the headers to handle authentication automatically.$

Here's an example workflow that uses the HTTP / Webhook action to send an authenticated API request to OpenAI.

Focus on integrating, not authenticating

This action can also use your connected accounts with third-party APIs. Selecting an integrated app will automatically update the request’s headers to authenticate with the app properly, and even inject your token dynamically.

Pipedream integrates with thousands of APIs, but if you can’t find a Pipedream integration simply use Environment Variables in your request headers to authenticate with.

Compatible with no code actions or Node.js and Python

The HTTP/Webhook action exports HTTP response data for use in subsequent workflow steps, enabling easy data transformation, further API calls, database storage, and more.

Response data is available for both coded (Node.js, Python) and no-code steps within your workflow.

Trigger Code#

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

// Core HTTP component
export default {
  key: "http-new-requests",
  name: "New Requests",
  description: "Get a URL and emit the full HTTP event on every request (including headers and query parameters). You can also configure the HTTP response code, body, and more.",
  version: "0.1.1",
  type: "source",
  props: {
    httpInterface: {
      type: "$.interface.http",
      customResponse: true,
    },
    emitBodyOnly: {
      type: "boolean",
      label: "Body Only",
      description: "This source emits an event representing the full HTTP request by default. Select `true` to emit the body only.",
      optional: true,
      default: false,
    },
    resStatusCode: {
      type: "string",
      label: "Response Status Code",
      description: "The status code to return in the HTTP response",
      optional: true,
      default: "200",
    },
    resContentType: {
      type: "string",
      label: "Response Content-Type",
      description: "The `Content-Type` of the body returned in the HTTP response",
      optional: true,
      default: "application/json",
    },
    resBody: {
      type: "string",
      label: "Response Body",
      description: "The body to return in the HTTP response",
      optional: true,
      default: "{ \"success\": true }",
    },
    http,
  },
  async run(event) {
    const summary = `${event.method} ${event.path}`;

    this.httpInterface.respond({
      status: this.resStatusCode,
      body: this.resBody,
      headers: {
        "content-type": this.resContentType,
      },
    });

    if (this.emitBodyOnly) {
      this.$emit(event.body, {
        summary,
      });
    } else {
      this.$emit(event, {
        summary,
      });
    }
  },
};

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
N/A	`httpInterface`	`$.interface.http`	This component uses `$.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.
Body Only	`emitBodyOnly`	`boolean`	This source emits an event representing the full HTTP request by default. Select `true` to emit the body only.
Response Status Code	`resStatusCode`	`string`	The status code to return in the HTTP response
Response Content-Type	`resContentType`	`string`	The `Content-Type` of the body returned in the HTTP response
Response Body	`resBody`	`string`	The body to return in the HTTP response
HTTP / Webhook	`http`	`app`	This component uses the HTTP / Webhook app.

Trigger Authentication#

The HTTP / Webhook API does not require authentication.

About HTTP / Webhook#

Get a unique URL where you can send HTTP or webhook requests

Action#

Chat on Kindo

Description:Creates a model response for the given chat conversation using Kindo's API. [See the documentation](https://app.kindo.ai/settings/api) for more information.

Version:0.0.1

Key:kindo-chat

View on GitHub

Action Code#

import app from "../../kindo.app.mjs";
import utils from "../../common/utils.mjs";

export default {
  key: "kindo-chat",
  name: "Chat",
  description: "Creates a model response for the given chat conversation using Kindo's API. [See the documentation](https://app.kindo.ai/settings/api) for more information.",
  version: "0.0.1",
  type: "action",
  props: {
    app,
    model: {
      type: "string",
      label: "Model",
      description: "The model name from Kindo's available models",
    },
    messages: {
      type: "string[]",
      label: "Messages",
      description: "A list of messages comprising the conversation so far. Depending on the [model](https://app.kindo.ai/settings/api) you use, different message types (modalities) are supported, like [text](https://platform.openai.com/docs/guides/text-generation), [images](https://platform.openai.com/docs/guides/vision), and [audio](https://platform.openai.com/docs/guides/audio). [See the documentation](https://platform.openai.com/docs/api-reference/chat/create#chat-create-messages) for more information. Eg. `[{\"role\": \"user\", \"content\": \"Hello, world!\"}]",
    },
    maxTokens: {
      type: "integer",
      label: "Max Tokens",
      description: "The maximum number of [tokens](https://beta.openai.com/tokenizer) to generate in the completion.",
      optional: true,
    },
    temperature: {
      type: "string",
      label: "Temperature",
      description: "**Optional**. What [sampling temperature](https://towardsdatascience.com/how-to-sample-from-language-models-682bceb97277) to use. Higher values means the model will take more risks. Try `0.9` for more creative applications, and `0` (argmax sampling) for ones with a well-defined answer.",
      optional: true,
    },
    topP: {
      type: "string",
      label: "Top P",
      description: "An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So `0.1` means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or `temperature` but not both.",
      optional: true,
    },
    n: {
      type: "integer",
      label: "N",
      description: "How many completions to generate for each prompt",
      optional: true,
    },
    stop: {
      type: "string[]",
      label: "Stop",
      description: "Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.",
      optional: true,
    },
    presencePenalty: {
      type: "string",
      label: "Presence Penalty",
      description: "Number between `-2.0` and `2.0`. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.",
      optional: true,
    },
    frequencyPenalty: {
      type: "string",
      label: "Frequency Penalty",
      description: "Number between `-2.0` and `2.0`. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.",
      optional: true,
    },
    additionalParameters: {
      type: "object",
      label: "Additional Parameters",
      description: "Additional parameters to pass to the API.",
      optional: true,
    },
  },
  methods: {
    chat(args = {}) {
      return this.app.post({
        path: "/chat/completions",
        ...args,
      });
    },
  },
  async run({ $ }) {
    const {
      chat,
      model,
      messages,
      maxTokens,
      temperature,
      topP,
      n,
      stop,
      presencePenalty,
      frequencyPenalty,
      additionalParameters,
    } = this;

    const response = await chat({
      $,
      data: {
        model,
        messages: utils.parseArray(messages),
        max_tokens: maxTokens,
        ...(temperature && {
          temperature: +temperature,
        }),
        ...(topP && {
          top_p: +topP,
        }),
        n,
        stop,
        ...(presencePenalty && {
          presence_penalty: +presencePenalty,
        }),
        ...(frequencyPenalty && {
          frequency_penalty: +frequencyPenalty,
        }),
        ...additionalParameters,
      },
    });
    $.export("$summary", "Successfully created model response");
    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
Kindo	`app`	`app`	This component uses the Kindo app.
Model	`model`	`string`	The model name from Kindo's available models
Messages	`messages`	`string[]`	A list of messages comprising the conversation so far. Depending on the model you use, different message types (modalities) are supported, like text, images, and audio. See the documentation for more information. Eg. `[{"role": "user", "content": "Hello, world!"}]
Max Tokens	`maxTokens`	`integer`	The maximum number of tokens to generate in the completion.
Temperature	`temperature`	`string`	Optional. What sampling temperature to use. Higher values means the model will take more risks. Try `0.9` for more creative applications, and `0` (argmax sampling) for ones with a well-defined answer.
Top P	`topP`	`string`	An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So `0.1` means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or `temperature` but not both.
N	`n`	`integer`	How many completions to generate for each prompt
Stop	`stop`	`string[]`	Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.
Presence Penalty	`presencePenalty`	`string`	Number between `-2.0` and `2.0`. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.
Frequency Penalty	`frequencyPenalty`	`string`	Number between `-2.0` and `2.0`. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.
Additional Parameters	`additionalParameters`	`object`	Additional parameters to pass to the API.

Action Authentication#

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

About Kindo#

Enterpise-Ready Agentic Security

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