cohere-ai - npm Package Compare versions

Comparing version 3.2.0 to 4.0.0

dist/cohere.d.ts

 import * as models from './models';
 interface CohereService {
     init(key: string, version?: string): void;
-    generate(model: string, config: models.generate): Promise<models.cohereResponse<models.text>>;
-    embed(model: string, config: models.embed): Promise<models.cohereResponse<models.embeddings>>;
-    chooseBest(model: string, config: models.chooseBest): Promise<models.cohereResponse<models.scores>>;
-    extract(model: string, config: models.extract): Promise<models.cohereResponse<models.extraction[]>>;
+    generate(config: models.generate): Promise<models.cohereResponse<models.text>>;
+    embed(config: models.embed): Promise<models.cohereResponse<models.embeddings>>;
+    extract(config: models.extract): Promise<models.cohereResponse<models.extraction[]>>;
 }
@@ -15,3 +14,3 @@ declare class Cohere implements CohereService {
      */
-    generate(model: string, config: models.generate): Promise<models.cohereResponse<models.text>>;
+    generate(config: models.generate): Promise<models.cohereResponse<models.text>>;
     /** Returns text embeddings. An embedding is a list of floating point numbers that captures semantic
@@ -21,21 +20,13 @@ * information about the text that it represents.
      */
-    embed(model: string, config: models.embed): Promise<models.cohereResponse<models.embeddings>>;
-    /**  Uses likelihood to perform classification. Given a query text that you'd like to classify between
-     * a number of options, Choose Best will return a score between the query and each option.
-     * See: https://docs.cohere.ai/choose-best-reference
-     */
+    embed(config: models.embed): Promise<models.cohereResponse<models.embeddings>>;
     /**
-     * @deprecated Will be deleted in favor of 'classify'.
-     */
-    chooseBest(model: string, config: models.chooseBest): Promise<models.cohereResponse<models.scores>>;
-    /**
      * Classifies text as one of the given labels. Returns a confidence score for each label.
      */
-    classify(model: string, config: models.classify): Promise<models.cohereResponse<models.classifications>>;
+    classify(config: models.classify): Promise<models.cohereResponse<models.classifications>>;
     /**
      * Extract text from texts, with examples
      */
-    extract(model: string, config: models.extract): Promise<models.cohereResponse<models.extraction[]>>;
+    extract(config: models.extract): Promise<models.cohereResponse<models.extraction[]>>;
 }
 declare const cohere: Cohere;
 export = cohere;

dist/cohere.js

@@ -38,3 +38,2 @@ (function webpackUniversalModuleDefinition(root, factory) {
     ENDPOINT["EMBED"] = "/embed";
-    ENDPOINT["CHOOSE_BEST"] = "/choose-best";
     ENDPOINT["CLASSIFY"] = "/classify";
@@ -50,4 +49,4 @@ ENDPOINT["EXTRACT"] = "/extract";
     };
-    Cohere.prototype.makeRequest = function (model, endpoint, data) {
-        return api_service_1.default.post("/" + model + endpoint, data);
+    Cohere.prototype.makeRequest = function (endpoint, data) {
+        return api_service_1.default.post(endpoint, data);
     };
@@ -57,4 +56,4 @@ /** Generates realistic text conditioned on a given input.
      */
-    Cohere.prototype.generate = function (model, config) {
-        return this.makeRequest(model, ENDPOINT.GENERATE, config);
+    Cohere.prototype.generate = function (config) {
+        return this.makeRequest(ENDPOINT.GENERATE, config);
     };
@@ -65,3 +64,3 @@ /** Returns text embeddings. An embedding is a list of floating point numbers that captures semantic
      */
-    Cohere.prototype.embed = function (model, config) {
+    Cohere.prototype.embed = function (config) {
         var _this = this;
@@ -83,3 +82,3 @@ var createBatches = function (array) {
         return Promise.all(createBatches(config.texts).map(function (texts) {
-            return _this.makeRequest(model, ENDPOINT.EMBED, __assign(__assign({}, config), { texts: texts }));
+            return _this.makeRequest(ENDPOINT.EMBED, __assign(__assign({}, config), { texts: texts }));
         })).then(function (results) {
@@ -97,17 +96,7 @@ var embeddings = [];
     };
-    /**  Uses likelihood to perform classification. Given a query text that you'd like to classify between
-     * a number of options, Choose Best will return a score between the query and each option.
-     * See: https://docs.cohere.ai/choose-best-reference
-     */
     /**
-     * @deprecated Will be deleted in favor of 'classify'.
-     */
-    Cohere.prototype.chooseBest = function (model, config) {
-        return this.makeRequest(model, ENDPOINT.CHOOSE_BEST, config);
-    };
-    /**
      * Classifies text as one of the given labels. Returns a confidence score for each label.
      */
-    Cohere.prototype.classify = function (model, config) {
-        return this.makeRequest(model, ENDPOINT.CLASSIFY, config);
+    Cohere.prototype.classify = function (config) {
+        return this.makeRequest(ENDPOINT.CLASSIFY, config);
     };
@@ -117,4 +106,4 @@ /**
      */
-    Cohere.prototype.extract = function (model, config) {
-        return this.makeRequest(model, ENDPOINT.EXTRACT, config);
+    Cohere.prototype.extract = function (config) {
+        return this.makeRequest(ENDPOINT.EXTRACT, config);
     };
@@ -121,0 +110,0 @@ return Cohere;

dist/models/index.ts

@@ -8,2 +8,4 @@ export interface cohereResponse<T> {
 export interface generate {
+  /** Denotes the model to be used. Defaults to the best performing model */
+  model?: string;
   /** Represents the prompt or text to be completed. */
@@ -48,2 +50,4 @@ prompt: string;
 export interface embed {
+  /** Denotes the model to be used. Defaults to the best performing model */
+  model?: string;
   /** An array of strings for the model to embed. */
@@ -55,14 +59,5 @@ texts: string[];
 
-export interface chooseBest {
-  /** Used to query the options. */
-  query: string;
-  /** Each string concatenates to the query. */
-  options: string[];
-  /** One of PREPEND_OPTION|APPEND_OPTION to specify where the option string will be placed and
-   * how to compute the log-likelihood.
-   */
-  mode: 'PREPEND_OPTION' | 'APPEND_OPTION';
-}
-
 export interface classify {
+  /** Denotes the model to be used. Defaults to the best performing model */
+  model?: string;
   /** An array of strings that you would like to classify. */
@@ -78,3 +73,3 @@ inputs: string[];
 
-export type cohereParameters = generate | embed | chooseBest | classify | extract;
+export type cohereParameters = generate | embed | classify | extract;
 
@@ -81,0 +76,0 @@ /* -- responses -- */

package.json

 {
   "name": "cohere-ai",
-  "version": "3.2.0",
+  "version": "4.0.0",
   "description": "A Node.js SDK with TypeScript support for the Cohere API.",
@@ -12,3 +12,4 @@ "homepage": "https://docs.cohere.ai",
     "dev": "webpack --progress --env development --env nodemon",
-    "test": "npm run build && mocha -r ts-node/register test/test.ts"
+    "test": "npm run build && mocha -r ts-node/register test/test.ts",
+    "publish": "npm run build && npm publish"
   },
@@ -15,0 +16,0 @@ "files": [

README.md

@@ -40,3 +40,2 @@ # Welcome to the Cohere AI Node.js SDK.
 /generate  | cohere.generate()
-/choose-best | cohere.chooseBest()
 /embed | cohere.embed()
@@ -100,3 +99,3 @@
 
-## Local development instructions
-To tinker with the package library itself, please check the development instructions [readme](https://github.com/cohere-ai/cohere-node/blob/main/DEV.md).
+## cohere-node package readme
+If you'd like to help contribute to the package library itself or modify it locally, please check the development instructions [readme](https://github.com/cohere-ai/cohere-node/blob/main/DEV.md).

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Worsened metrics

Total package byte prevSize

36393

decreased by-5.1%

Lines of code

456

decreased by-5%

Number of lines in readme file

99

decreased by-1.98%

Number of medium supply chain risk alerts

2

increased by100%

No dependency changes