feat(api): api update

Author: stainless-app[bot]

.stats.yml

@@ -1,4 +1,4 @@
-configured_endpoints: 24
-openapi_spec_url: https://storage.googleapis.com/stainless-sdk-openapi-specs/lemma%2Flemma-398e43f06821a461846ebae030851faf308afa99a9c2340530a21272e5ae67a9.yml
-openapi_spec_hash: 624c26645898fdc2cd6db3670dc3f1ec
+configured_endpoints: 9
+openapi_spec_url: https://storage.googleapis.com/stainless-sdk-openapi-specs/lemma%2Flemma-d740cae5b0014320a9b81a06cf19be4740aa75451b68cd041eddc6fe332b0282.yml
+openapi_spec_hash: 8ca9bdc602442861e7a4db790e2fa0c7
 config_hash: 017a31b2ac0856f4d4152a5173e6fa18

README.md

@@ -29,9 +29,11 @@ const client = new Lemma({
   apiKey: process.env['LEMMA_API_KEY'], // This is the default and can be omitted
 });
 
-const dataset = await client.datasets.create({ name: '<NAME>' });
-
-console.log(dataset.id);
+const response = await client.datasets.generateDataset({
+  dataset_id: 'dataset_id',
+  entries_required: 0,
+  schema: { foo: 'bar' },
+});
 ```
 
 ### Request & Response types
@@ -46,8 +48,12 @@ const client = new Lemma({
   apiKey: process.env['LEMMA_API_KEY'], // This is the default and can be omitted
 });
 
-const params: Lemma.DatasetCreateParams = { name: 'name' };
-const dataset: Lemma.Dataset = await client.datasets.create(params);
+const params: Lemma.DatasetGenerateDatasetParams = {
+  dataset_id: 'dataset_id',
+  entries_required: 0,
+  schema: { foo: 'bar' },
+};
+const response: Lemma.DatasetGenerateDatasetResponse = await client.datasets.generateDataset(params);
 ```
 
 Documentation for each method, request param, and response field are available in docstrings and will appear on hover in most modern editors.
@@ -89,15 +95,17 @@ a subclass of `APIError` will be thrown:
 
 <!-- prettier-ignore -->
 ```ts
-const dataset = await client.datasets.create({ name: 'name' }).catch(async (err) => {
-  if (err instanceof Lemma.APIError) {
-    console.log(err.status); // 400
-    console.log(err.name); // BadRequestError
-    console.log(err.headers); // {server: 'nginx', ...}
-  } else {
-    throw err;
-  }
-});
+const response = await client.datasets
+  .generateDataset({ dataset_id: 'dataset_id', entries_required: 0, schema: { foo: 'bar' } })
+  .catch(async (err) => {
+    if (err instanceof Lemma.APIError) {
+      console.log(err.status); // 400
+      console.log(err.name); // BadRequestError
+      console.log(err.headers); // {server: 'nginx', ...}
+    } else {
+      throw err;
+    }
+  });
 ```
 
 Error codes are as follows:
@@ -129,7 +137,7 @@ const client = new Lemma({
 });
 
 // Or, configure per-request:
-await client.datasets.create({ name: 'name' }, {
+await client.datasets.generateDataset({ dataset_id: 'dataset_id', entries_required: 0, schema: { foo: 'bar' } }, {
   maxRetries: 5,
 });
 ```
@@ -146,7 +154,7 @@ const client = new Lemma({
 });
 
 // Override per-request:
-await client.datasets.create({ name: 'name' }, {
+await client.datasets.generateDataset({ dataset_id: 'dataset_id', entries_required: 0, schema: { foo: 'bar' } }, {
   timeout: 5 * 1000,
 });
 ```
@@ -169,13 +177,17 @@ Unlike `.asResponse()` this method consumes the body, returning once it is parse
 ```ts
 const client = new Lemma();
 
-const response = await client.datasets.create({ name: 'name' }).asResponse();
+const response = await client.datasets
+  .generateDataset({ dataset_id: 'dataset_id', entries_required: 0, schema: { foo: 'bar' } })
+  .asResponse();
 console.log(response.headers.get('X-My-Header'));
 console.log(response.statusText); // access the underlying Response object
 
-const { data: dataset, response: raw } = await client.datasets.create({ name: 'name' }).withResponse();
+const { data: response, response: raw } = await client.datasets
+  .generateDataset({ dataset_id: 'dataset_id', entries_required: 0, schema: { foo: 'bar' } })
+  .withResponse();
 console.log(raw.headers.get('X-My-Header'));
-console.log(dataset.id);
+console.log(response);
 ```
 
 ### Logging
@@ -255,7 +267,7 @@ parameter. This library doesn't validate at runtime that the request matches the
 send will be sent as-is.
 
 ```ts
-client.datasets.create({
+client.datasets.generateDataset({
   // ...
   // @ts-expect-error baz is not yet public
   baz: 'undocumented option',

api.md

@@ -3,20 +3,12 @@
 Types:
 
 - <code><a href="./src/resources/datasets/datasets.ts">Dataset</a></code>
-- <code><a href="./src/resources/datasets/datasets.ts">DatasetListResponse</a></code>
-- <code><a href="./src/resources/datasets/datasets.ts">DatasetDeleteResponse</a></code>
-- <code><a href="./src/resources/datasets/datasets.ts">DatasetCreateDownloadURLResponse</a></code>
 - <code><a href="./src/resources/datasets/datasets.ts">DatasetGenerateDatasetResponse</a></code>
 - <code><a href="./src/resources/datasets/datasets.ts">DatasetGenerateSchemaResponse</a></code>
 - <code><a href="./src/resources/datasets/datasets.ts">DatasetGenerateValidatorsResponse</a></code>
 
 Methods:
 
-- <code title="post /datasets">client.datasets.<a href="./src/resources/datasets/datasets.ts">create</a>({ ...params }) -> Dataset</code>
-- <code title="get /datasets/{dataset_id}">client.datasets.<a href="./src/resources/datasets/datasets.ts">retrieve</a>(datasetID) -> Dataset</code>
-- <code title="get /datasets/">client.datasets.<a href="./src/resources/datasets/datasets.ts">list</a>() -> DatasetListResponse</code>
-- <code title="delete /datasets/{dataset_id}">client.datasets.<a href="./src/resources/datasets/datasets.ts">delete</a>(datasetID) -> DatasetDeleteResponse</code>
-- <code title="get /datasets/{dataset_id}/create-download-url">client.datasets.<a href="./src/resources/datasets/datasets.ts">createDownloadURL</a>(datasetID) -> string</code>
 - <code title="post /datasets/generate-dataset">client.datasets.<a href="./src/resources/datasets/datasets.ts">generateDataset</a>({ ...params }) -> DatasetGenerateDatasetResponse</code>
 - <code title="post /datasets/generate-schema">client.datasets.<a href="./src/resources/datasets/datasets.ts">generateSchema</a>({ ...params }) -> DatasetGenerateSchemaResponse</code>
 - <code title="post /datasets/generate-validators">client.datasets.<a href="./src/resources/datasets/datasets.ts">generateValidators</a>({ ...params }) -> DatasetGenerateValidatorsResponse</code>
@@ -62,27 +54,12 @@ Methods:
 Types:
 
 - <code><a href="./src/resources/prompts/prompts.ts">Prompt</a></code>
-- <code><a href="./src/resources/prompts/prompts.ts">PromptListResponse</a></code>
-- <code><a href="./src/resources/prompts/prompts.ts">PromptDeleteResponse</a></code>
-
-Methods:
-
-- <code title="post /prompts">client.prompts.<a href="./src/resources/prompts/prompts.ts">create</a>({ ...params }) -> Prompt</code>
-- <code title="get /prompts/{prompt_id}">client.prompts.<a href="./src/resources/prompts/prompts.ts">retrieve</a>(promptID) -> Prompt</code>
-- <code title="get /prompts">client.prompts.<a href="./src/resources/prompts/prompts.ts">list</a>() -> PromptListResponse</code>
-- <code title="delete /prompts/{prompt_id}">client.prompts.<a href="./src/resources/prompts/prompts.ts">delete</a>(promptID) -> PromptDeleteResponse</code>
 
 ## Iterations
 
 Types:
 
 - <code><a href="./src/resources/prompts/iterations.ts">PromptIteration</a></code>
-- <code><a href="./src/resources/prompts/iterations.ts">IterationListResponse</a></code>
-
-Methods:
-
-- <code title="post /prompts/{prompt_id}/iterations">client.prompts.iterations.<a href="./src/resources/prompts/iterations.ts">create</a>(promptID, { ...params }) -> PromptIteration</code>
-- <code title="get /prompts/{prompt_id}/iterations">client.prompts.iterations.<a href="./src/resources/prompts/iterations.ts">list</a>(promptID) -> IterationListResponse</code>
 
 # Evaluators
 
@@ -91,14 +68,3 @@ Types:
 - <code><a href="./src/resources/evaluators.ts">Evaluator</a></code>
 - <code><a href="./src/resources/evaluators.ts">RubricCriterion</a></code>
 - <code><a href="./src/resources/evaluators.ts">RubricExample</a></code>
-- <code><a href="./src/resources/evaluators.ts">EvaluatorRetrieveResponse</a></code>
-- <code><a href="./src/resources/evaluators.ts">EvaluatorUpdateResponse</a></code>
-- <code><a href="./src/resources/evaluators.ts">EvaluatorListResponse</a></code>
-- <code><a href="./src/resources/evaluators.ts">EvaluatorCreateRubricResponse</a></code>
-
-Methods:
-
-- <code title="get /evaluators/{evaluator_id}">client.evaluators.<a href="./src/resources/evaluators.ts">retrieve</a>(evaluatorID) -> EvaluatorRetrieveResponse</code>
-- <code title="put /evaluators/{evaluator_id}">client.evaluators.<a href="./src/resources/evaluators.ts">update</a>(evaluatorID, { ...params }) -> EvaluatorUpdateResponse</code>
-- <code title="get /evaluators">client.evaluators.<a href="./src/resources/evaluators.ts">list</a>() -> EvaluatorListResponse</code>
-- <code title="post /evaluators/rubric">client.evaluators.<a href="./src/resources/evaluators.ts">createRubric</a>({ ...params }) -> EvaluatorCreateRubricResponse</code>

packages/mcp-server/README.md

@@ -40,7 +40,7 @@ For clients with a configuration JSON, it might look something like this:
   "mcpServers": {
     "lemma_api": {
       "command": "node",
-      "args": ["/path/to/local/lemma-typescript/packages/mcp-server", "--client=claude", "--tools=dynamic"],
+      "args": ["/path/to/local/lemma-typescript/packages/mcp-server", "--client=claude", "--tools=all"],
       "env": {
         "LEMMA_API_KEY": "My API Key"
       }
@@ -187,7 +187,7 @@ http://localhost:3000?client=cursor&capability=tool-name-length%3D40
 import { server, endpoints, init } from "lemma-mcp/server";
 
 // import a specific tool
-import createDatasets from "lemma-mcp/tools/datasets/create-datasets";
+import generateDatasetDatasets from "lemma-mcp/tools/datasets/generate-dataset-datasets";
 
 // initialize the server and all endpoints
 init({ server, endpoints });
@@ -212,7 +212,7 @@ const myCustomEndpoint = {
 };
 
 // initialize the server with your custom endpoints
-init({ server: myServer, endpoints: [createDatasets, myCustomEndpoint] });
+init({ server: myServer, endpoints: [generateDatasetDatasets, myCustomEndpoint] });
 ```
 
 ## Available Tools
@@ -221,32 +221,6 @@ The following tools are available in this MCP server.
 
 ### Resource `datasets`:
 
-- `create_datasets` (`write`): Create a new dataset.
-
-  Creates a new dataset with the specified name and optional description.
-  The dataset will be associated with the current user's tenant.
-
-- `retrieve_datasets` (`read`): Get a dataset by ID.
-
-  Retrieves a specific dataset by its ID. The dataset must belong to the
-  current user's tenant.
-
-- `list_datasets` (`read`): List all datasets for the current tenant.
-
-  Retrieves all datasets that belong to the current user's tenant.
-  This includes datasets created by any user within the same tenant.
-
-- `delete_datasets` (`write`): Delete a dataset by ID.
-
-  Permanently deletes a dataset and all its associated data. This action
-  cannot be undone. The dataset must belong to the current user's tenant.
-
-- `create_download_url_datasets` (`read`): Create a download URL for a dataset.
-
-  Creates a secure, time-limited download URL that allows downloading
-  the dataset data. The URL can be used to access the dataset file
-  without requiring authentication.
-
 - `generate_dataset_datasets` (`write`): Generate a dataset using AI.
 
   Initiates the generation of a dataset based on the provided schema and
@@ -298,61 +272,3 @@ The following tools are available in this MCP server.
 ### Resource `playground`:
 
 - `run_playground` (`write`): Run a playground experiment with a prompt and optional evaluator.
-
-### Resource `prompts`:
-
-- `create_prompts` (`write`): Create a new prompt.
-
-  Creates a new prompt with the specified ID and optional description.
-  If a seed_prompt is provided, it will create the first iteration of the prompt.
-  Returns the created prompt object with metadata.
-
-- `retrieve_prompts` (`read`): Get a specific prompt by ID.
-
-  Retrieves a single prompt with all its details. The prompt must
-  belong to the current user's tenant.
-
-- `list_prompts` (`read`): List all prompts for the current user.
-
-  Retrieves all prompts belonging to the current user's tenant.
-  Results are ordered by creation date (newest first).
-
-- `delete_prompts` (`write`): Delete a prompt by ID.
-
-  Permanently deletes a prompt and all its iterations. This action
-  cannot be undone. The prompt must belong to the current user's tenant.
-
-### Resource `prompts.iterations`:
-
-- `create_prompts_iterations` (`write`): Create a new prompt iteration.
-
-  Creates a new version/iteration of an existing prompt with updated content.
-  Each iteration represents a specific version of the prompt that can be
-  used for testing and comparison.
-
-- `list_prompts_iterations` (`read`): List all iterations for a specific prompt.
-
-  Retrieves all iterations/versions of a prompt, ordered by version
-  number (newest first). The prompt must belong to the current user's tenant.
-
-### Resource `evaluators`:
-
-- `retrieve_evaluators` (`read`): Get a specific evaluator by ID.
-
-  Retrieves detailed information about a specific evaluator.
-  The evaluator must belong to the current user's tenant.
-
-- `update_evaluators` (`write`): Update an existing evaluator.
-
-  Updates the configuration and settings of an existing evaluator.
-  The evaluator must belong to the current user's tenant.
-
-- `list_evaluators` (`read`): List all evaluators for the current tenant.
-
-  Retrieves all evaluators that belong to the current user's tenant.
-  Evaluators are used to assess the quality of AI model outputs.
-
-- `create_rubric_evaluators` (`write`): Create a new rubric for evaluation.
-
-  Creates a new rubric that defines how to evaluate AI model outputs.
-  Rubrics provide structured criteria for assessment.