[ACTION] [COHERE] Chat

components/cohere_platform/actions/chat/chat.mjs

@@ -0,0 +1,99 @@
+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;
+  },
+};

components/cohere_platform/actions/classify-text/classify-text.mjs

@@ -1,44 +1,46 @@
-import coherePlatform from "../../cohere_platform.app.mjs";
+import app from "../../cohere_platform.app.mjs";
+import { clearObj } from "../../common/utils.mjs";
 
 export default {
   key: "cohere_platform-classify-text",
   name: "Classify Text",
-  version: "0.0.1",
-  description: "This action makes a prediction about which label fits the specified text inputs best. [See the docs here](https://docs.cohere.com/reference/classify)",
+  version: "0.1.0",
+  description: "This action makes a prediction about which label fits the specified text inputs best. [See the documentation](https://docs.cohere.com/reference/classify-1)",
   type: "action",
   props: {
-    coherePlatform,
+    app,
     inputs: {
       type: "string[]",
       label: "Inputs",
       description: "Represents a list of queries to be classified, each entry must not be empty. The maximum is 96 inputs.",
     },
-    classifyModel: {
+    model: {
       propDefinition: [
-        coherePlatform,
+        app,
         "classifyModel",
       ],
     },
     preset: {
       propDefinition: [
-        coherePlatform,
+        app,
         "preset",
       ],
     },
     truncate: {
       propDefinition: [
-        coherePlatform,
+        app,
         "truncate",
       ],
     },
     numExamples: {
       type: "integer",
       label: "Number of Examples",
-      description: "To make a prediction, Classify uses provided examples of text + label pairs. Specify the number of examples to provide. Each example is a text string and its associated label/class. At least 2 labels must be provided.",
+      description: "To make a prediction, Classify uses provided examples of text + label pairs. Specify the number of examples to provide. Each example is a text string and its associated label/class. At least 2 unique labels must be provided and each label should have at least 2 different examples.",
+      default: 4,
       reloadProps: true,
     },
   },
-  async additionalProps() {
+  additionalProps() {
     const props = {};
 
     for (let i = 0; i < this.numExamples; i++) {
@@ -56,28 +58,40 @@ export default {
 
     return props;
   },
+  methods: {
+    getExamples() {
+      const examples = [];
+      for (let i = 0; i < this.numExamples; i++) {
+        examples.push({
+          text: this[`text_${i}`],
+          label: this[`label_${i}`],
+        });
+      }
+      return examples;
+    },
+    classifyText(data) {
+      return this.app.client().classify(data);
+    },
+  },
   async run({ $ }) {
-    const examples = [];
-    for (let i = 0; i < this.numExamples; i++) {
-      examples.push({
-        text: this[`text_${i}`],
-        label: this[`label_${i}`],
-      });
-    }
-
-    const response = await this.coherePlatform.classifyText({
-      inputs: this.inputs,
-      model: this.model,
-      preset: this.preset,
-      truncate: this.truncate,
-      examples,
-    });
+    const {
+      classifyText,
+      inputs,
+      model,
+      preset,
+      truncate,
+      getExamples,
+    } = this;
 
-    if (response.statusCode != "200") {
-      throw new Error(response.body.message);
-    }
+    const response = await classifyText(clearObj({
+      inputs,
+      model,
+      preset,
+      truncate,
+      examples: getExamples(),
+    }));
 
-    $.export("$summary", "The text was successfully classified.");
+    $.export("$summary", `The text was successfully classified with ID \`${response.id}\``);
     return response;
   },
 };