Add all utility classes and their code samples

.github/workflows/_test-code-samples.yml

@@ -4,6 +4,15 @@ on:
   workflow_call:
   workflow_dispatch:
 
+env:
+  MINDEE_API_KEY: ${{ secrets.MINDEE_API_KEY_SE_TESTS }}
+  MINDEE_V2_API_KEY: ${{ secrets.MINDEE_V2_SE_TESTS_API_KEY }}
+  MINDEE_V2_SE_TESTS_FINDOC_MODEL_ID: ${{ secrets.MINDEE_V2_SE_TESTS_FINDOC_MODEL_ID }}
+  MINDEE_V2_SE_TESTS_CLASSIFICATION_MODEL_ID: ${{ secrets.MINDEE_V2_SE_TESTS_CLASSIFICATION_MODEL_ID }}
+  MINDEE_V2_SE_TESTS_CROP_MODEL_ID: ${{ secrets.MINDEE_V2_SE_TESTS_CROP_MODEL_ID }}
+  MINDEE_V2_SE_TESTS_SPLIT_MODEL_ID: ${{ secrets.MINDEE_V2_SE_TESTS_SPLIT_MODEL_ID }}
+  MINDEE_V2_SE_TESTS_OCR_MODEL_ID: ${{ secrets.MINDEE_V2_SE_TESTS_OCR_MODEL_ID }}
+
 jobs:
   build:
     name: Run Tests
@@ -33,7 +42,10 @@ jobs:
       - name: Build
         run: npm run build-for-dist
 
-      - name: Tests sample code
+      - name: Tests v2 sample code
         run: |
-          ./tests/test_code_samples.sh ${{ secrets.MINDEE_ACCOUNT_SE_TESTS }} ${{ secrets.MINDEE_ENDPOINT_SE_TESTS }} ${{ secrets.MINDEE_API_KEY_SE_TESTS }} ${{ secrets.MINDEE_V2_SE_TESTS_API_KEY }} ${{ secrets.MINDEE_V2_SE_TESTS_FINDOC_MODEL_ID }}
+          ./tests/test_v2_code_samples.sh
 
+      - name: Tests v1 sample code
+        run: |
+          ./tests/test_v1_code_samples.sh ${{ secrets.MINDEE_ACCOUNT_SE_TESTS }} ${{ secrets.MINDEE_ENDPOINT_SE_TESTS }}

.github/workflows/_test-integrations.yml

@@ -7,6 +7,17 @@ on:
   workflow_call:
   workflow_dispatch:
 
+env:
+  MINDEE_API_KEY: ${{ secrets.MINDEE_API_KEY_SE_TESTS }}
+  WORKFLOW_ID: ${{ secrets.WORKFLOW_ID_SE_TESTS }}
+  MINDEE_V2_API_KEY: ${{ secrets.MINDEE_V2_SE_TESTS_API_KEY }}
+  MINDEE_V2_SE_TESTS_BLANK_PDF_URL: ${{ secrets.MINDEE_V2_SE_TESTS_BLANK_PDF_URL }}
+  MINDEE_V2_SE_TESTS_FINDOC_MODEL_ID: ${{ secrets.MINDEE_V2_SE_TESTS_FINDOC_MODEL_ID }}
+  MINDEE_V2_SE_TESTS_CLASSIFICATION_MODEL_ID: ${{ secrets.MINDEE_V2_SE_TESTS_CLASSIFICATION_MODEL_ID }}
+  MINDEE_V2_SE_TESTS_CROP_MODEL_ID: ${{ secrets.MINDEE_V2_SE_TESTS_CROP_MODEL_ID }}
+  MINDEE_V2_SE_TESTS_SPLIT_MODEL_ID: ${{ secrets.MINDEE_V2_SE_TESTS_SPLIT_MODEL_ID }}
+  MINDEE_V2_SE_TESTS_OCR_MODEL_ID: ${{ secrets.MINDEE_V2_SE_TESTS_OCR_MODEL_ID }}
+
 jobs:
   run-tests:
     name: Run Integration Tests
@@ -56,10 +67,4 @@ jobs:
         run: npm run build
 
       - name: Test code
-        env:
-          MINDEE_API_KEY: ${{ secrets.MINDEE_API_KEY_SE_TESTS }}
-          WORKFLOW_ID: ${{ secrets.WORKFLOW_ID_SE_TESTS }}
-          MINDEE_V2_API_KEY: ${{ secrets.MINDEE_V2_SE_TESTS_API_KEY }}
-          MINDEE_V2_FINDOC_MODEL_ID: ${{ secrets.MINDEE_V2_SE_TESTS_FINDOC_MODEL_ID }}
-          MINDEE_V2_SE_TESTS_BLANK_PDF_URL: ${{ secrets.MINDEE_V2_SE_TESTS_BLANK_PDF_URL }}
         run: npm run test-integration

docs/code_samples/v2_classification.txt

@@ -0,0 +1,33 @@
+import * as mindee from "mindee";
+// If you're on CommonJS:
+// const mindee = require("mindee");
+
+const apiKey = "MY_API_KEY";
+const filePath = "/path/to/the/file.ext";
+const modelId = "MY_CLASSIFICATION_MODEL_ID";
+
+// Init a new client
+const mindeeClient = new mindee.Client(
+  { apiKey: apiKey }
+);
+
+// Set product parameters
+const params = {
+  modelId: modelId,
+};
+
+// Load a file from disk
+const inputSource = new mindee.PathInput({ inputPath: filePath });
+
+// Send for processing
+const response = await mindeeClient.enqueueAndGetResult(
+  mindee.v2.product.Classification,
+  inputSource,
+  params,
+);
+
+// print a string summary
+console.log(response.inference.toString());
+
+// Access the classification result
+const classification = response.inference.result.classification;

docs/code_samples/v2_crop.txt

@@ -0,0 +1,33 @@
+import * as mindee from "mindee";
+// If you're on CommonJS:
+// const mindee = require("mindee");
+
+const apiKey = "MY_API_KEY";
+const filePath = "/path/to/the/file.ext";
+const modelId = "MY_CROP_MODEL_ID";
+
+// Init a new client
+const mindeeClient = new mindee.Client(
+  { apiKey: apiKey }
+);
+
+// Set product parameters
+const params = {
+  modelId: modelId,
+};
+
+// Load a file from disk
+const inputSource = new mindee.PathInput({ inputPath: filePath });
+
+// Send for processing
+const response = await mindeeClient.enqueueAndGetResult(
+  mindee.v2.product.Crop,
+  inputSource,
+  params,
+);
+
+// print a string summary
+console.log(response.inference.toString());
+
+// Access the result crops
+const crops = response.inference.result.crops;

docs/code_samples/v2_default.txt → docs/code_samples/v2_extraction.txt

@@ -1,6 +1,6 @@
-const mindee = require("mindee");
-// for TS or modules:
-// import * as mindee from "mindee";
+import * as mindee from "mindee";
+// If you're on CommonJS:
+// const mindee = require("mindee");
 
 const apiKey = "MY_API_KEY";
 const filePath = "/path/to/the/file.ext";
@@ -11,8 +11,8 @@ const mindeeClient = new mindee.Client(
   { apiKey: apiKey }
 );
 
-// Set inference parameters
-const extractionParams = {
+// Set product parameters
+const params = {
   modelId: modelId,
 
   // Options: set to `true` or `false` to override defaults
@@ -32,14 +32,14 @@ const extractionParams = {
 const inputSource = new mindee.PathInput({ inputPath: filePath });
 
 // Send for processing
-const response = mindeeClient.enqueueAndGetResult(
+const response = await mindeeClient.enqueueAndGetResult(
   mindee.v2.product.Extraction,
   inputSource,
-  extractionParams
+  params,
 );
 
-// Handle the response Promise
-response.then((resp) => {
-  // print a string summary
-  console.log(resp.inference.toString());
-});
+// print a string summary
+console.log(response.inference.toString());
+
+// Access the result fields
+const fields = response.inference.result.fields;

docs/code_samples/v2_ocr.txt

@@ -0,0 +1,33 @@
+import * as mindee from "mindee";
+// If you're on CommonJS:
+// const mindee = require("mindee");
+
+const apiKey = "MY_API_KEY";
+const filePath = "/path/to/the/file.ext";
+const modelId = "MY_OCR_MODEL_ID";
+
+// Init a new client
+const mindeeClient = new mindee.Client(
+  { apiKey: apiKey }
+);
+
+// Set product parameters
+const params = {
+  modelId: modelId,
+};
+
+// Load a file from disk
+const inputSource = new mindee.PathInput({ inputPath: filePath });
+
+// Send for processing
+const response = await mindeeClient.enqueueAndGetResult(
+  mindee.v2.product.Ocr,
+  inputSource,
+  params,
+);
+
+// print a string summary
+console.log(response.inference.toString());
+
+// Access the result OCR pages
+const crops = response.inference.result.pages;

docs/code_samples/v2_split.txt

@@ -0,0 +1,33 @@
+import * as mindee from "mindee";
+// If you're on CommonJS:
+// const mindee = require("mindee");
+
+const apiKey = "MY_API_KEY";
+const filePath = "/path/to/the/file.ext";
+const modelId = "MY_SPLIT_MODEL_ID";
+
+// Init a new client
+const mindeeClient = new mindee.Client(
+  { apiKey: apiKey }
+);
+
+// Set product parameters
+const params = {
+  modelId: modelId,
+};
+
+// Load a file from disk
+const inputSource = new mindee.PathInput({ inputPath: filePath });
+
+// Send for processing
+const response = await mindeeClient.enqueueAndGetResult(
+  mindee.v2.product.Split,
+  inputSource,
+  params,
+);
+
+// print a string summary
+console.log(response.inference.toString());
+
+// Access the result splits
+const crops = response.inference.result.splits;

src/v2/cli.ts

@@ -14,7 +14,6 @@ import {
 
 const program = new Command();
 
-
 //
 // EXECUTE THE COMMANDS
 //

src/v2/parsing/inference/baseInference.ts

@@ -21,4 +21,13 @@ export abstract class BaseInference {
     this.model = new InferenceModel(serverResponse["model"]);
     this.file = new InferenceFile(serverResponse["file"]);
   }
+
+  toString(): string {
+    return (
+      "Inference\n" +
+      "#########\n" +
+      this.model.toString() + "\n" +
+      this.file.toString() + "\n"
+    );
+  }
 }

src/v2/product/classification/classificationClassifier.ts

@@ -0,0 +1,16 @@
+import { StringDict } from "@/parsing/index.js";
+
+/**
+ * Document level classification.
+ */
+export class ClassificationClassifier {
+  documentType: string;
+
+  constructor(serverResponse: StringDict) {
+    this.documentType = serverResponse["document_type"];
+  }
+
+  toString(): string {
+    return `Document Type: ${this.documentType}`;
+  }
+}

src/v2/product/classification/classificationInference.ts

@@ -1,23 +1,21 @@
 import { StringDict } from "@/parsing/index.js";
 import { BaseInference } from "@/v2/parsing/inference/baseInference.js";
+import { ClassificationResult } from "./classificationResult.js";
 
 export class ClassificationInference extends BaseInference {
   /**
    * Result of a classification inference.
    */
-  result: any;
+  result: ClassificationResult;
 
   constructor(serverResponse: StringDict) {
     super(serverResponse);
-    this.result = serverResponse["result"];
+    this.result = new ClassificationResult(serverResponse["result"]);
   }
 
   toString(): string {
     return (
-      "Inference\n" +
-      "#########\n" +
-      this.model.toString() + "\n" +
-      this.file.toString() + "\n" +
+      super.toString() +
       this.result.toString() + "\n"
     );
   }

src/v2/product/classification/classificationResult.ts

@@ -0,0 +1,17 @@
+import { StringDict } from "@/parsing/stringDict.js";
+import { ClassificationClassifier } from "./classificationClassifier.js";
+
+export class ClassificationResult {
+  /**
+   * Fields contained in the inference.
+   */
+  public classification: ClassificationClassifier;
+
+  constructor(serverResponse: StringDict) {
+    this.classification = new ClassificationClassifier(serverResponse["classification"]);
+  }
+
+  toString(): string {
+    return `Classification\n==============\n${this.classification}`;
+  }
+}

src/v2/product/classification/index.ts

@@ -2,3 +2,5 @@ export { Classification } from "./classification.js";
 export { ClassificationParameters } from "./classificationParameters.js";
 export { ClassificationResponse } from "./classificationResponse.js";
 export { ClassificationInference } from "./classificationInference.js";
+export { ClassificationResult } from "./classificationResult.js";
+export { ClassificationClassifier } from "./classificationClassifier.js";

src/v2/product/crop/cropInference.ts

@@ -15,10 +15,7 @@ export class CropInference extends BaseInference {
 
   toString(): string {
     return (
-      "Inference\n" +
-      "#########\n" +
-      this.model.toString() + "\n" +
-      this.file.toString() + "\n" +
+      super.toString() +
       this.result.toString() + "\n"
     );
   }

src/v2/product/extraction/extractionInference.ts

@@ -21,10 +21,7 @@ export class ExtractionInference extends BaseInference {
 
   toString(): string {
     return (
-      "Inference\n" +
-      "#########\n" +
-      this.model.toString() + "\n" +
-      this.file.toString() + "\n" +
+      super.toString() +
       this.activeOptions.toString() + "\n" +
       this.result.toString() + "\n"
     );

src/v2/product/extraction/extractionResponse.ts

@@ -3,7 +3,6 @@ import { StringDict } from "@/parsing/stringDict.js";
 import { BaseResponse } from "@/v2/parsing/index.js";
 
 export class ExtractionResponse extends BaseResponse {
-
   /**
    * The inference result for an extraction request.
    */

src/v2/product/ocr/ocrInference.ts

@@ -1,15 +1,16 @@
 import { StringDict } from "@/parsing/index.js";
 import { BaseInference } from "@/v2/parsing/inference/baseInference.js";
+import { OcrResult } from "@/v2/product/ocr/ocrResult.js";
 
 export class OcrInference extends BaseInference {
   /**
    * Result of an OCR inference.
    */
-  result: any;
+  result: OcrResult;
 
   constructor(serverResponse: StringDict) {
     super(serverResponse);
-    this.result = serverResponse["result"];
+    this.result = new OcrResult(serverResponse["result"]);
   }
 
   toString(): string {