feat: add finetune endpoints

package.json

@@ -1,6 +1,6 @@
 {
   "name": "vlmrun",
-  "version": "0.2.5",
+  "version": "0.2.6",
   "description": "The official TypeScript library for the VlmRun API",
   "author": "VlmRun <[email protected]>",
   "main": "dist/index.js",
@@ -28,6 +28,7 @@
     "dotenv": "^16.4.7",
     "path": "^0.12.7",
     "zod": "~3.24.2",
+    "mime-types": "^2.1.35",
     "zod-to-json-schema": "~3.24.1"
   },
   "devDependencies": {

src/client/fine_tuning.ts

@@ -0,0 +1,181 @@
+import { Client, APIRequestor } from "./base_requestor";
+import { FinetuningResponse, FinetuningProvisionResponse, FinetuningGenerateParams, FinetuningListParams, PredictionResponse, FinetuningCreateParams, FinetuningProvisionParams } from "./types";
+import { encodeImage, processImage } from "../utils";
+
+export class Finetuning {
+  private requestor: APIRequestor;
+
+  constructor(client: Client) {
+    this.requestor = new APIRequestor({
+      ...client,
+      baseURL: `${client.baseURL}/fine_tuning`,
+    });
+  }
+
+  /**
+   * Create a fine-tuning job
+   * @param {Object} params - Fine-tuning parameters
+   * @param {string} params.model - Base model to fine-tune
+   * @param {string} params.training_file_id - File ID for training data
+   * @param {string} [params.validation_file_id] - File ID for validation data
+   * @param {number} [params.num_epochs=1] - Number of epochs
+   * @param {number|string} [params.batch_size="auto"] - Batch size for training
+   * @param {number} [params.learning_rate=2e-4] - Learning rate for training
+   * @param {string} [params.suffix] - Suffix for the fine-tuned model
+   * @param {string} [params.wandb_api_key] - Weights & Biases API key
+   * @param {string} [params.wandb_base_url] - Weights & Biases base URL
+   * @param {string} [params.wandb_project_name] - Weights & Biases project name
+   */
+  async create(params: FinetuningCreateParams): Promise<FinetuningResponse> {
+    if (params.suffix) {
+      // Ensure suffix contains only alphanumeric, hyphens or underscores
+      if (!/^[a-zA-Z0-9_-]+$/.test(params.suffix)) {
+        throw new Error(
+          "Suffix must be alphanumeric, hyphens or underscores without spaces"
+        );
+      }
+    }
+
+    const [response] = await this.requestor.request<FinetuningResponse>(
+      "POST",
+      "create",
+      undefined,
+      {
+        callback_url: params.callbackUrl,
+        model: params.model,
+        training_file: params.trainingFile,
+        validation_file: params.validationFile,
+        num_epochs: params.numEpochs ?? 1,
+        batch_size: params.batchSize ?? 1,
+        learning_rate: params.learningRate ?? 2e-4,
+        suffix: params.suffix,
+        wandb_api_key: params.wandbApiKey,
+        wandb_base_url: params.wandbBaseUrl,
+        wandb_project_name: params.wandbProjectName,
+      }
+    );
+
+    return response;
+  }
+
+  /**
+   * Provision a fine-tuning model
+   * @param {Object} params - Provisioning parameters
+   * @param {string} params.model - Model to provision
+   * @param {number} [params.duration=600] - Duration for the provisioned model (in seconds)
+   * @param {number} [params.concurrency=1] - Concurrency for the provisioned model
+   */
+  async provision(params: FinetuningProvisionParams): Promise<FinetuningProvisionResponse> {
+    const [response] = await this.requestor.request<FinetuningProvisionResponse>(
+      "POST",
+      "provision",
+      undefined,
+      {
+        model: params.model,
+        duration: params.duration ?? 600, // 10 minutes default
+        concurrency: params.concurrency ?? 1,
+      }
+    );
+
+    return response;
+  }
+
+  /**
+   * Generate a prediction using a fine-tuned model
+   * @param {FinetuningGenerateParams} params - Generation parameters
+   */
+  async generate(params: FinetuningGenerateParams): Promise<PredictionResponse> {
+    if (!params.jsonSchema) {
+      throw new Error("JSON schema is required for fine-tuned model predictions");
+    }
+
+    if (!params.prompt) {
+      throw new Error("Prompt is required for fine-tuned model predictions");
+    }
+
+    if (params.domain) {
+      throw new Error("Domain is not supported for fine-tuned model predictions");
+    }
+
+    if (params.detail && params.detail !== "auto") {
+      throw new Error("Detail level is not supported for fine-tuned model predictions");
+    }
+
+    if (params.batch) {
+      throw new Error("Batch mode is not supported for fine-tuned models");
+    }
+
+    if (params.callbackUrl) {
+      throw new Error("Callback URL is not supported for fine-tuned model predictions");
+    }
+
+    const [response] = await this.requestor.request<PredictionResponse>(
+      "POST",
+      "generate",
+      undefined,
+      {
+        images: params.images.map((image) => processImage(image)),
+        model: params.model,
+        config: {
+          prompt: params.prompt,
+          json_schema: params.jsonSchema,
+          detail: params.detail ?? "auto",
+          response_model: params.responseModel,
+          confidence: params.confidence ?? false,
+          grounding: params.grounding ?? false,
+          max_retries: params.maxRetries ?? 3,
+          max_tokens: params.maxTokens ?? 4096,
+        },
+        max_new_tokens: params.maxNewTokens ?? 1024,
+        temperature: params.temperature ?? 0.0,
+        metadata: {
+          environment: params?.environment ?? "dev",
+          session_id: params?.sessionId,
+          allow_training: params?.allowTraining ?? true,
+        },
+        batch: params.batch ?? false,
+        callback_url: params.callbackUrl,
+      }
+    );
+
+    return response;
+  }
+
+  /**
+   * List all fine-tuning jobs
+   * @param {FinetuningListParams} params - List parameters
+   */
+  async list(params?: FinetuningListParams): Promise<FinetuningResponse[]> {
+    const [response] = await this.requestor.request<FinetuningResponse[]>(
+      "GET",
+      "jobs",
+      {
+        skip: params?.skip ?? 0,
+        limit: params?.limit ?? 10,
+      }
+    );
+
+    return response;
+  }
+
+  /**
+   * Get fine-tuning job details
+   * @param {string} jobId - ID of job to retrieve
+   */
+  async get(jobId: string): Promise<FinetuningResponse> {
+    const [response] = await this.requestor.request<FinetuningResponse>(
+      "GET",
+      `jobs/${jobId}`
+    );
+
+    return response;
+  }
+
+  /**
+   * Cancel a fine-tuning job
+   * @param {string} jobId - ID of job to cancel
+   */
+  async cancel(jobId: string): Promise<Record<string, any>> {
+    throw new Error("Not implemented");
+  }
+}

src/client/types.ts

@@ -174,6 +174,79 @@ export interface WebPredictionParams extends PredictionGenerateParams {
   mode: "fast" | "accurate";
 }
 
+export interface FinetuningResponse {
+  id: string;
+  created_at: string;
+  completed_at?: string;
+  status: JobStatus;
+  model: string;
+  training_file_id: string;
+  validation_file_id?: string;
+  num_epochs: number;
+  batch_size: number | string;
+  learning_rate: number;
+  suffix?: string;
+  wandb_url?: string;
+  message?: string;
+}
+
+export interface FinetuningProvisionResponse {
+  id: string;
+  created_at: string;
+  model: string;
+  duration: number;
+  concurrency: number;
+  status: JobStatus;
+  message?: string;
+}
+
+export interface FinetuningCreateParams {
+  callbackUrl?: string;
+  model: string;
+  trainingFile: string;
+  validationFile?: string;
+  numEpochs?: number;
+  batchSize?: number | string;
+  learningRate?: number;
+  suffix?: string;
+  wandbApiKey?: string;
+  wandbBaseUrl?: string;
+  wandbProjectName?: string;
+}
+
+export interface FinetuningGenerateParams {
+  images: string[];
+  model: string;
+  prompt?: string;
+  domain?: string;
+  jsonSchema?: Record<string, any>;
+  maxNewTokens?: number;
+  temperature?: number;
+  detail?: "auto" | "hi" | "lo";
+  batch?: boolean;
+  metadata?: Record<string, any>;
+  callbackUrl?: string;
+  maxRetries?: number;
+  maxTokens?: number;
+  confidence?: boolean;
+  grounding?: boolean;
+  environment?: string;
+  sessionId?: string;
+  allowTraining?: boolean;
+  responseModel?: string;  
+}
+
+export interface FinetuningProvisionParams {
+  model: string;
+  duration?: number;
+  concurrency?: number;
+}
+
+export interface FinetuningListParams {
+  skip?: number;
+  limit?: number;
+}
+
 export class APIError extends Error {
   constructor(
     message: string,

src/index.ts

@@ -10,13 +10,15 @@ import {
   WebPredictions,
 } from "./client/predictions";
 import { Feedback } from "./client/feedback";
+import { Finetuning } from "./client/fine_tuning";
 
 export * from "./client/types";
 export * from "./client/base_requestor";
 export * from "./client/models";
 export * from "./client/files";
 export * from "./client/predictions";
 export * from "./client/feedback";
+export * from "./client/fine_tuning";
 
 export * from "./utils";
 
@@ -36,6 +38,7 @@ export class VlmRun {
   readonly video: ReturnType<typeof VideoPredictions>;
   readonly web: WebPredictions;
   readonly feedback: Feedback;
+  readonly finetuning: Finetuning;
 
   constructor(config: VlmRunConfig) {
     this.client = {
@@ -50,7 +53,8 @@ export class VlmRun {
     this.document = DocumentPredictions(this.client);
     this.audio = AudioPredictions(this.client);
     this.video = VideoPredictions(this.client);
-    this.feedback = new Feedback(this.client);
     this.web = new WebPredictions(this.client);
+    this.feedback = new Feedback(this.client);
+    this.finetuning = new Finetuning(this.client);
   }
 }

src/utils/file.ts

@@ -2,17 +2,18 @@ export const readFileFromPathAsFile = async (filePath: string): Promise<File> =>
     try {
         if (typeof window === 'undefined') {
             const fs = require("fs/promises");
-            const path = require('path');
+            const path = require("path");
+            const mime = require("mime-types");
 
             const fileBuffer = await fs.readFile(filePath);
             const fileName = path.basename(filePath);
-            return new File([fileBuffer], fileName, {
-                type: 'application/pdf',
-            });
+            const mimeType = mime.lookup(fileName) || "application/octet-stream";
+
+            return new File([fileBuffer], fileName, { type: mimeType });
         } else {
-            throw new Error('File reading is not supported in the browser');
+            throw new Error("File reading is not supported in the browser");
         }
     } catch (error: any) {
         throw new Error(`Error reading file at ${filePath}: ${error.message}`);
     }
-}
+};