Chat with Cohere API on New Item in Feed from RSS API

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New Item in Feed from the RSS API

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Chat with the Cohere API

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Getting Started#

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

Select this integration
Configure the New Item in Feed trigger
1. Connect your RSS account
2. Configure timer
3. Configure Feed URL
4. Configure Published After
Configure the Chat action
1. Connect your Cohere account
2. Configure Message
3. Optional- Select a Model
4. Optional- Configure Temperature
5. Optional- Configure Max Tokens
6. Optional- Configure K
7. Optional- Configure P
8. Optional- Configure Stop Sequences
9. Optional- Configure Frequency Penalty
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 Item in Feed on RSS

Description:Emit new items from an RSS feed

Version:1.2.7

Key:rss-new-item-in-feed

View on GitHub

RSS Overview#

The RSS app allows users to automatically fetch and parse updates from web feeds. This functionality is pivotal for staying abreast of content changes or updates from websites, blogs, and news outlets that offer RSS feeds. With Pipedream, you can harness the RSS API to trigger workflows that enable a broad range of automations, like content aggregation, monitoring for specific keywords, notifications, and data synchronization across platforms.

Trigger Code#

import { defineSource } from "@pipedream/types";
import rss from "../../app/rss.app.mjs";
import rssCommon from "../common/common.mjs";
export default defineSource({
    ...rssCommon,
    key: "rss-new-item-in-feed",
    name: "New Item in Feed",
    description: "Emit new items from an RSS feed",
    version: "1.2.7",
    type: "source",
    dedupe: "unique",
    props: {
        ...rssCommon.props,
        url: {
            propDefinition: [
                rss,
                "url",
            ],
        },
        publishedAfter: {
            type: "string",
            label: "Published After",
            description: "Emit items published after the specified date in ISO 8601 format .e.g `2022-12-07T12:57:10+07:00`",
            default: new Date(Date.now() - 24 * 60 * 60 * 1000).toISOString(), // default to one day ago
        },
    },
    hooks: {
        async activate() {
            // Try to parse the feed one time to confirm we can fetch and parse.
            // The code will throw any errors to the user.
            await this.rss.fetchAndParseFeed(this.url);
        },
    },
    methods: {
        ...rssCommon.methods,
        generateMeta: function (item) {
            return {
                id: this.rss.itemKey(item),
                summary: item.title,
                ts: Date.now(),
            };
        },
    },
    async run() {
        const items = await this.rss.fetchAndParseFeed(this.url);
        for (const item of items.reverse()) {
            const publishedAfter = +new Date(this.publishedAfter);
            const ts = this.rss.itemTs(item);
            if (Number.isNaN(publishedAfter) || publishedAfter > ts) {
                continue;
            }
            const meta = this.generateMeta(item);
            this.$emit(item, meta);
        }
    },
});

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
RSS	`rss`	`app`	This component uses the RSS app.
	`timer`	`$.interface.timer`	How often you want to poll the feed for new items
Feed URL	`url`	`string`	Enter the URL for any public RSS feed
Published After	`publishedAfter`	`string`	Emit items published after the specified date in ISO 8601 format .e.g `2022-12-07T12:57:10+07:00`

Trigger Authentication#

The RSS API does not require authentication.

About RSS#

Real Simple Syndication

Action#

Chat on Cohere

Description:Generates a text response to a user message. [See the documentation](https://docs.cohere.com/reference/chat)

Version:0.0.1

Key:cohere_platform-chat

View on GitHub

Cohere Overview#

The Cohere API enables the development of apps with advanced natural language understanding capabilities. Utilizing machine learning, it can help with tasks like text generation, summarization, sentiment analysis, and more. On Pipedream, you can seamlessly integrate Cohere's features into serverless workflows, triggering actions based on text input, processing large volumes of data, or even enhancing chatbots with more human-like responses.

Action Code#

import app from "../../cohere_platform.app.mjs";
import { clearObj } from "../../common/utils.mjs";

export default {
  key: "cohere_platform-chat",
  name: "Chat",
  version: "0.0.1",
  description: "Generates a text response to a user message. [See the documentation](https://docs.cohere.com/reference/chat)",
  type: "action",
  props: {
    app,
    message: {
      propDefinition: [
        app,
        "message",
      ],
    },
    model: {
      propDefinition: [
        app,
        "model",
      ],
    },
    temperature: {
      propDefinition: [
        app,
        "temperature",
      ],
    },
    maxTokens: {
      propDefinition: [
        app,
        "maxTokens",
      ],
    },
    k: {
      propDefinition: [
        app,
        "k",
      ],
    },
    p: {
      propDefinition: [
        app,
        "p",
      ],
    },
    stopSequences: {
      propDefinition: [
        app,
        "stopSequences",
      ],
    },
    frequencyPenalty: {
      propDefinition: [
        app,
        "frequencyPenalty",
      ],
    },
  },
  methods: {
    chat(data) {
      return this.app.client().chat(data);
    },
  },
  async run({ $ }) {
    const {
      chat,
      message,
      model,
      temperature,
      maxTokens,
      k,
      p,
      stopSequences,
      frequencyPenalty,

    } = this;
    const response = await chat(clearObj({
      message,
      model,
      ...(temperature && {
        temperature: parseFloat(temperature),
      }),
      maxTokens,
      k,
      ...(p && {
        p: parseFloat(p),
      }),
      stopSequences,
      ...(frequencyPenalty && {
        frequencyPenalty: parseFloat(frequencyPenalty),
      }),
    }));

    $.export("$summary", `The message was successfully responded with ID \`${response.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
Cohere	`app`	`app`	This component uses the Cohere app.
Message	`message`	`string`	Text input for the model to respond to. Compatible Deployments: Cohere Platform, Azure, AWS Sagemaker, Private Deployments
Model	`model`	`string`	Select a value from the drop down menu:`command-r-pluscommand-rcommandcommand-nightlycommand-lightcommand-light-nightlyembed-english-v3.0embed-english-light-v3.0embed-multilingual-v3.0embed-multilingual-light-v3.0embed-english-v2.0embed-english-light-v2.0embed-multilingual-v2.0rerank-english-v3.0rerank-multilingual-v3.0rerank-english-v2.0rerank-multilingual-v2.0`
Temperature	`temperature`	`string`	Must be between 0 and 1.0 inclusive that tunes the degree of randomness in generation. Lower temperatures mean less random generations, and higher temperatures mean more random generations. Randomness can be further maximized by increasing the value of the P parameter. Compatible Deployments: Cohere Platform, Azure, AWS Sagemaker, Private Deployments See Temperature for more details.
Max Tokens	`maxTokens`	`integer`	The maximum number of tokens the model will generate as part of the response. Note: Setting a low value may result in incomplete generations. Compatible Deployments: Cohere Platform, Azure, AWS Sagemaker, Private Deployments. See BPE Tokens for more details.
K	`k`	`integer`	Ensures only the top K most likely tokens are considered for generation at each step. Defaults to `0`, min value of `0`, max value of `500`. Compatible Deployments: Cohere Platform, Azure, AWS Sagemaker, Private Deployments
P	`p`	`string`	Ensures that only the most likely tokens, with total probability mass of P, are considered for generation at each step. If both K and P are enabled, P acts after K. Defaults to `0.75`. min value of `0.01`, max value of `0.99`. Compatible Deployments: Cohere Platform, Azure, AWS Sagemaker, Private Deployments
Stop Sequences	`stopSequences`	`string[]`	A list of up to 5 strings that the model will use to stop generation. If the model generates a string that matches any of the strings in the list, it will stop generating tokens and return the generated text up to that point not including the stop sequence. Compatible Deployments: Cohere Platform, Azure, AWS Sagemaker, Private Deployments
Frequency Penalty	`frequencyPenalty`	`string`	Defaults to `0.0`, min value of `0.0`, max value of `1.0`. Used to reduce repetitiveness of generated tokens. The higher the value, the stronger a penalty is applied to previously present tokens, proportional to how many times they have already appeared in the prompt or prior generation. Compatible Deployments: Cohere Platform, Azure, AWS Sagemaker, Private Deployments