[Components] kindo - new action

Author: jcortes

components/kindo/actions/chat/chat.mjs

@@ -0,0 +1,120 @@
+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;
+  },
+};

components/kindo/common/utils.mjs

@@ -0,0 +1,52 @@
+import { ConfigurationError } from "@pipedream/platform";
+
+const parseJson = (input) => {
+  const parse = (value) => {
+    if (typeof(value) === "string") {
+      try {
+        return parseJson(JSON.parse(value));
+      } catch (e) {
+        return value;
+      }
+    } else if (typeof(value) === "object" && value !== null) {
+      return Object.entries(value)
+        .reduce((acc, [
+          key,
+          val,
+        ]) => Object.assign(acc, {
+          [key]: parse(val),
+        }), {});
+    }
+    return value;
+  };
+
+  return parse(input);
+};
+
+function parseArray(value) {
+  try {
+    if (!value) {
+      return [];
+    }
+
+    if (Array.isArray(value)) {
+      return value;
+    }
+
+    const parsedValue = JSON.parse(value);
+
+    if (!Array.isArray(parsedValue)) {
+      throw new Error("Not an array");
+    }
+
+    return parsedValue;
+
+  } catch (e) {
+    throw new ConfigurationError("Make sure the custom expression contains a valid array object");
+  }
+}
+
+export default {
+  parseJson,
+  parseArray: (value) => parseArray(value)?.map(parseJson),
+};

components/kindo/kindo.app.mjs

@@ -1,11 +1,33 @@
+import { axios } from "@pipedream/platform";
+
 export default {
   type: "app",
   app: "kindo",
-  propDefinitions: {},
   methods: {
-    // this.$auth contains connected account data
-    authKeys() {
-      console.log(Object.keys(this.$auth));
+    getUrl(path) {
+      return `https://llm.kindo.ai/v1${path}`;
+    },
+    getHeaders(headers) {
+      return {
+        ...headers,
+        "content-type": "application/json",
+        "api-key": this.$auth.api_key,
+      };
+    },
+    makeRequest({
+      $ = this, path, headers, ...args
+    } = {}) {
+      return axios($, {
+        ...args,
+        url: this.getUrl(path),
+        headers: this.getHeaders(headers),
+      });
+    },
+    post(args = {}) {
+      return this.makeRequest({
+        method: "POST",
+        ...args,
+      });
     },
   },
-};
+};

components/kindo/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@pipedream/kindo",
-  "version": "0.0.1",
+  "version": "0.1.0",
   "description": "Pipedream Kindo Components",
   "main": "kindo.app.mjs",
   "keywords": [
@@ -11,5 +11,8 @@
   "author": "Pipedream <[email protected]> (https://pipedream.com/)",
   "publishConfig": {
     "access": "public"
+  },
+  "dependencies": {
+    "@pipedream/platform": "^3.0.3"
   }
-}
+}