feat(sdk): untoggle to force regen

Author: stainless-app[bot]

.stats.yml

@@ -1,4 +1,4 @@
-configured_endpoints: 3
+configured_endpoints: 4
 openapi_spec_url: https://storage.googleapis.com/stainless-sdk-openapi-specs/isaacus%2Fisaacus-30c23c1facb9383eb94d78d16d6a45b7e6afd943caf94cddeb75fd86357294f7.yml
 openapi_spec_hash: 48a6b3192add4f538615ac6f190123c5
-config_hash: 83740a990f84ee8d189fc4071a009a83
+config_hash: 886b5eef0dbd90b8e6686e987a07b816

api.md

@@ -1,3 +1,13 @@
+# Embeddings
+
+Types:
+
+- <code><a href="./src/resources/embeddings.ts">Embedding</a></code>
+
+Methods:
+
+- <code title="post /embeddings">client.embeddings.<a href="./src/resources/embeddings.ts">create</a>({ ...params }) -> Embedding</code>
+
 # Classifications
 
 ## Universal

packages/mcp-server/README.md

@@ -172,7 +172,7 @@ http://localhost:3000?client=cursor&capability=tool-name-length%3D40
 import { server, endpoints, init } from "isaacus-mcp/server";
 
 // import a specific tool
-import createClassificationsUniversal from "isaacus-mcp/tools/classifications/universal/create-classifications-universal";
+import createEmbeddings from "isaacus-mcp/tools/embeddings/create-embeddings";
 
 // initialize the server and all endpoints
 init({ server, endpoints });
@@ -197,13 +197,17 @@ const myCustomEndpoint = {
 };
 
 // initialize the server with your custom endpoints
-init({ server: myServer, endpoints: [createClassificationsUniversal, myCustomEndpoint] });
+init({ server: myServer, endpoints: [createEmbeddings, myCustomEndpoint] });
 ```
 
 ## Available Tools
 
 The following tools are available in this MCP server.
 
+### Resource `embeddings`:
+
+- `create_embeddings` (`write`): Embed legal texts with an Isaacus legal AI embedder.
+
 ### Resource `classifications.universal`:
 
 - `create_classifications_universal` (`write`): Classify the relevance of legal documents to a query with an Isaacus universal legal AI classifier.

packages/mcp-server/src/tools/embeddings/create-embeddings.ts

@@ -0,0 +1,81 @@
+// File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
+
+import { maybeFilter } from 'isaacus-mcp/filtering';
+import { Metadata, asTextContentResult } from 'isaacus-mcp/tools/types';
+
+import { Tool } from '@modelcontextprotocol/sdk/types.js';
+import Isaacus from 'isaacus';
+
+export const metadata: Metadata = {
+  resource: 'embeddings',
+  operation: 'write',
+  tags: [],
+  httpMethod: 'post',
+  httpPath: '/embeddings',
+  operationId: 'CreateEmbeddings',
+};
+
+export const tool: Tool = {
+  name: 'create_embeddings',
+  description:
+    "When using this tool, always use the `jq_filter` parameter to reduce the response size and improve performance.\n\nOnly omit if you're sure you don't need the data.\n\nEmbed legal texts with an Isaacus legal AI embedder.\n\n# Response Schema\n```json\n{\n  $ref: '#/$defs/embedding',\n  $defs: {\n    embedding: {\n      type: 'object',\n      title: 'Embedding response',\n      description: 'Embeddings of legal texts produced by an Isaacus legal AI embedder.',\n      properties: {\n        embeddings: {\n          type: 'array',\n          description: 'The embeddings of the inputs.',\n          items: {\n            type: 'object',\n            title: 'Content embedding',\n            properties: {\n              embedding: {\n                type: 'array',\n                description: 'The embedding of the content represented as an array of floating point numbers.',\n                items: {\n                  type: 'number'\n                }\n              },\n              index: {\n                type: 'integer',\n                description: 'The position of the content in the input array of contents, starting from `0` (and, therefore, ending at the number of contents minus `1`).'\n              }\n            },\n            required: [              'embedding',\n              'index'\n            ]\n          }\n        },\n        usage: {\n          type: 'object',\n          title: 'Embedding usage',\n          description: 'Statistics about the usage of resources in the process of embedding the inputs.',\n          properties: {\n            input_tokens: {\n              type: 'integer',\n              description: 'The number of tokens inputted to the model.'\n            }\n          },\n          required: [            'input_tokens'\n          ]\n        }\n      },\n      required: [        'embeddings',\n        'usage'\n      ]\n    }\n  }\n}\n```",
+  inputSchema: {
+    type: 'object',
+    properties: {
+      model: {
+        type: 'string',
+        description: 'The ID of the [model](https://docs.isaacus.com/models#embedding) to use for embedding.',
+        enum: ['kanon-2-embedder'],
+      },
+      texts: {
+        anyOf: [
+          {
+            type: 'array',
+            items: {
+              type: 'string',
+              title: 'Non-blank string',
+            },
+          },
+          {
+            type: 'string',
+            title: 'Non-blank string',
+          },
+        ],
+        description:
+          'The text or array of texts to embed.\n\nEach text must contain at least one non-whitespace character.\n\nNo more than 1,000 texts can be embedded in a single request.',
+      },
+      dimensions: {
+        type: 'integer',
+        title: 'Positive integer',
+        description: 'A whole number greater than or equal to 1.',
+      },
+      overflow_strategy: {
+        type: 'string',
+        description:
+          "The strategy to employ when content exceeds the model's maximum input length.\n\n`drop_end`, which is the default setting, drops tokens from the end of the content exceeding the limit.\n\nIf `null`, an error will be raised if any content exceeds the model's maximum input length.",
+        enum: ['drop_end'],
+      },
+      task: {
+        type: 'string',
+        description:
+          'The task the embeddings will be used for.\n\n`retrieval/query` is meant for queries and statements, and `retrieval/document` is meant for anything to be retrieved using query embeddings.\n\nIf `null`, which is the default setting, embeddings will not be optimized for any particular task.',
+        enum: ['retrieval/query', 'retrieval/document'],
+      },
+      jq_filter: {
+        type: 'string',
+        title: 'jq Filter',
+        description:
+          'A jq filter to apply to the response to include certain fields. Consult the output schema in the tool description to see the fields that are available.\n\nFor example: to include only the `name` field in every object of a results array, you can provide ".results[].name".\n\nFor more information, see the [jq documentation](https://jqlang.org/manual/).',
+      },
+    },
+    required: ['model', 'texts'],
+  },
+  annotations: {},
+};
+
+export const handler = async (client: Isaacus, args: Record<string, unknown> | undefined) => {
+  const { jq_filter, ...body } = args as any;
+  return asTextContentResult(await maybeFilter(jq_filter, await client.embeddings.create(body)));
+};
+
+export default { metadata, tool, handler };

packages/mcp-server/src/tools/index.ts

@@ -4,6 +4,7 @@ import { Metadata, Endpoint, HandlerFunction } from './types';
 
 export { Metadata, Endpoint, HandlerFunction };
 
+import create_embeddings from './embeddings/create-embeddings';
 import create_classifications_universal from './classifications/universal/create-classifications-universal';
 import create_rerankings from './rerankings/create-rerankings';
 import create_extractions_qa from './extractions/qa/create-extractions-qa';
@@ -14,6 +15,7 @@ function addEndpoint(endpoint: Endpoint) {
   endpoints.push(endpoint);
 }
 
+addEndpoint(create_embeddings);
 addEndpoint(create_classifications_universal);
 addEndpoint(create_rerankings);
 addEndpoint(create_extractions_qa);

src/client.ts

@@ -16,6 +16,7 @@ import * as Errors from './core/error';
 import * as Uploads from './core/uploads';
 import * as API from './resources/index';
 import { APIPromise } from './core/api-promise';
+import { Embedding, EmbeddingCreateParams, Embeddings } from './resources/embeddings';
 import { Reranking, RerankingCreateParams, Rerankings } from './resources/rerankings';
 import { Classifications } from './resources/classifications/classifications';
 import { Extractions } from './resources/extractions/extractions';
@@ -716,18 +717,26 @@ export class Isaacus {
 
   static toFile = Uploads.toFile;
 
+  embeddings: API.Embeddings = new API.Embeddings(this);
   classifications: API.Classifications = new API.Classifications(this);
   rerankings: API.Rerankings = new API.Rerankings(this);
   extractions: API.Extractions = new API.Extractions(this);
 }
 
+Isaacus.Embeddings = Embeddings;
 Isaacus.Classifications = Classifications;
 Isaacus.Rerankings = Rerankings;
 Isaacus.Extractions = Extractions;
 
 export declare namespace Isaacus {
   export type RequestOptions = Opts.RequestOptions;
 
+  export {
+    Embeddings as Embeddings,
+    type Embedding as Embedding,
+    type EmbeddingCreateParams as EmbeddingCreateParams,
+  };
+
   export { Classifications as Classifications };
 
   export {

src/resources/embeddings.ts

@@ -0,0 +1,113 @@
+// File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
+
+import { APIResource } from '../core/resource';
+import { APIPromise } from '../core/api-promise';
+import { RequestOptions } from '../internal/request-options';
+
+export class Embeddings extends APIResource {
+  /**
+   * Embed legal texts with an Isaacus legal AI embedder.
+   *
+   * @example
+   * ```ts
+   * const embedding = await client.embeddings.create({
+   *   model: 'kanon-2-embedder',
+   *   texts: [
+   *     'Are restraints of trade enforceable under English law?',
+   *     'What is a non-compete clause?',
+   *   ],
+   * });
+   * ```
+   */
+  create(body: EmbeddingCreateParams, options?: RequestOptions): APIPromise<Embedding> {
+    return this._client.post('/embeddings', { body, ...options });
+  }
+}
+
+/**
+ * Embeddings of legal texts produced by an Isaacus legal AI embedder.
+ */
+export interface Embedding {
+  /**
+   * The embeddings of the inputs.
+   */
+  embeddings: Array<Embedding.Embedding>;
+
+  /**
+   * Statistics about the usage of resources in the process of embedding the inputs.
+   */
+  usage: Embedding.Usage;
+}
+
+export namespace Embedding {
+  export interface Embedding {
+    /**
+     * The embedding of the content represented as an array of floating point numbers.
+     */
+    embedding: Array<number>;
+
+    /**
+     * The position of the content in the input array of contents, starting from `0`
+     * (and, therefore, ending at the number of contents minus `1`).
+     */
+    index: number;
+  }
+
+  /**
+   * Statistics about the usage of resources in the process of embedding the inputs.
+   */
+  export interface Usage {
+    /**
+     * The number of tokens inputted to the model.
+     */
+    input_tokens: number;
+  }
+}
+
+export interface EmbeddingCreateParams {
+  /**
+   * The ID of the [model](https://docs.isaacus.com/models#embedding) to use for
+   * embedding.
+   */
+  model: 'kanon-2-embedder';
+
+  /**
+   * The text or array of texts to embed.
+   *
+   * Each text must contain at least one non-whitespace character.
+   *
+   * No more than 1,000 texts can be embedded in a single request.
+   */
+  texts: Array<string> | string;
+
+  /**
+   * A whole number greater than or equal to 1.
+   */
+  dimensions?: number | null;
+
+  /**
+   * The strategy to employ when content exceeds the model's maximum input length.
+   *
+   * `drop_end`, which is the default setting, drops tokens from the end of the
+   * content exceeding the limit.
+   *
+   * If `null`, an error will be raised if any content exceeds the model's maximum
+   * input length.
+   */
+  overflow_strategy?: 'drop_end' | null;
+
+  /**
+   * The task the embeddings will be used for.
+   *
+   * `retrieval/query` is meant for queries and statements, and `retrieval/document`
+   * is meant for anything to be retrieved using query embeddings.
+   *
+   * If `null`, which is the default setting, embeddings will not be optimized for
+   * any particular task.
+   */
+  task?: 'retrieval/query' | 'retrieval/document' | null;
+}
+
+export declare namespace Embeddings {
+  export { type Embedding as Embedding, type EmbeddingCreateParams as EmbeddingCreateParams };
+}

src/resources/index.ts

@@ -1,5 +1,6 @@
 // File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
 
 export { Classifications } from './classifications/classifications';
+export { Embeddings, type Embedding, type EmbeddingCreateParams } from './embeddings';
 export { Extractions } from './extractions/extractions';
 export { Rerankings, type Reranking, type RerankingCreateParams } from './rerankings';

tests/api-resources/embeddings.test.ts

@@ -0,0 +1,36 @@
+// File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
+
+import Isaacus from 'isaacus';
+
+const client = new Isaacus({
+  apiKey: 'My API Key',
+  baseURL: process.env['TEST_API_BASE_URL'] ?? 'http://127.0.0.1:4010',
+});
+
+describe('resource embeddings', () => {
+  // Prism tests are disabled
+  test.skip('create: only required params', async () => {
+    const responsePromise = client.embeddings.create({
+      model: 'kanon-2-embedder',
+      texts: ['Are restraints of trade enforceable under English law?', 'What is a non-compete clause?'],
+    });
+    const rawResponse = await responsePromise.asResponse();
+    expect(rawResponse).toBeInstanceOf(Response);
+    const response = await responsePromise;
+    expect(response).not.toBeInstanceOf(Response);
+    const dataAndResponse = await responsePromise.withResponse();
+    expect(dataAndResponse.data).toBe(response);
+    expect(dataAndResponse.response).toBe(rawResponse);
+  });
+
+  // Prism tests are disabled
+  test.skip('create: required and optional params', async () => {
+    const response = await client.embeddings.create({
+      model: 'kanon-2-embedder',
+      texts: ['Are restraints of trade enforceable under English law?', 'What is a non-compete clause?'],
+      dimensions: 1,
+      overflow_strategy: 'drop_end',
+      task: 'retrieval/query',
+    });
+  });
+});