feat: refactor image captioning tests and add ESLint configuration

Author: LightCyan01

.eslintrc.json

@@ -0,0 +1 @@
+Subproject commit ebf414ea497a020da0f82df3913e5b6cb8e9663a

backend/llama-joycaption-beta-one-hf-llava

@@ -1,16 +1,28 @@
 import pytest
 from unittest.mock import MagicMock, patch
-from service.image_captioning import ImageCaptioning
+from pathlib import Path
+from service.image_captioning import ImageCaptioningService
 
 @pytest.fixture
-def dummy_captioner():
+def dummy_captioner(tmp_path):
     with patch('service.image_captioning.LlavaForConditionalGeneration.from_pretrained') as mock_model, \
          patch('service.image_captioning.AutoProcessor.from_pretrained') as mock_processor:
         mock_model.return_value = MagicMock()
         processor_instance = MagicMock()
-        # Set the processor mock to return our processor_instance
         mock_processor.return_value = processor_instance
-        captioner = ImageCaptioning("dummy-model")
+        
+        load_path = tmp_path / "load"
+        save_path = tmp_path / "save"
+        load_path.mkdir()
+        save_path.mkdir()
+        
+        captioner = ImageCaptioningService(
+            model=Path("dummy-model"),
+            load_path=load_path,
+            save_path=save_path,
+            prompt="Describe this image."
+        )
+        
         # Mock methods used in the pipeline
         captioner._model.generate = MagicMock(return_value=[[1, 2, 3, 4]])
         processor_instance.apply_chat_template = MagicMock(return_value="prompt")
@@ -19,7 +31,6 @@ def dummy_captioner():
             "pixel_values": MagicMock()
         }
         processor_instance.tokenizer.decode = MagicMock(return_value="A cat on a mat.")
-        # Make sure the processor mock is used for __call__
         captioner._processor = processor_instance
         return captioner
 
@@ -28,7 +39,7 @@ def test_image_inputs(dummy_captioner, tmp_path):
     img_path = tmp_path / "test.jpg"
     from PIL import Image
     Image.new("RGB", (10, 10)).save(img_path)
-    inputs = dummy_captioner._image_inputs(img_path, "Describe this image.")
+    inputs = dummy_captioner._image_inputs(img_path)
     assert "input_ids" in inputs
 
 def test_generate_caption(dummy_captioner):
@@ -44,7 +55,7 @@ def test_save_caption(dummy_captioner, tmp_path):
     img_path = tmp_path / "test.jpg"
     img_path.touch()
     caption = "A cat on a mat."
-    output_file = dummy_captioner.save_caption(caption, img_path)
+    output_file = dummy_captioner.save_caption(caption, img_path, tmp_path)
     assert output_file.exists()
     with open(output_file, "r", encoding="utf-8") as f:
         assert f.read() == caption

backend/tests/test_image_captioning.py

@@ -0,0 +1,50 @@
+import eslint from "@eslint/js";
+import tseslint from "@typescript-eslint/eslint-plugin";
+import tsparser from "@typescript-eslint/parser";
+import importPlugin from "eslint-plugin-import";
+
+export default [
+  {
+    ignores: [
+      "node_modules/**",
+      ".vite/**",
+      "out/**",
+      "dist/**",
+      "backend/**",
+      "*.js",
+    ],
+  },
+  eslint.configs.recommended,
+  {
+    files: ["**/*.ts", "**/*.tsx"],
+    languageOptions: {
+      parser: tsparser,
+      parserOptions: {
+        ecmaVersion: "latest",
+        sourceType: "module",
+      },
+      globals: {
+        console: "readonly",
+        process: "readonly",
+        __dirname: "readonly",
+        Buffer: "readonly",
+        setTimeout: "readonly",
+        clearTimeout: "readonly",
+        fetch: "readonly",
+        window: "readonly",
+        document: "readonly",
+        MAIN_WINDOW_VITE_DEV_SERVER_URL: "readonly",
+        MAIN_WINDOW_VITE_NAME: "readonly",
+      },
+    },
+    plugins: {
+      "@typescript-eslint": tseslint,
+      import: importPlugin,
+    },
+    rules: {
+      ...tseslint.configs.recommended.rules,
+      "@typescript-eslint/no-unused-vars": ["warn", { argsIgnorePattern: "^_" }],
+      "@typescript-eslint/no-explicit-any": "warn",
+    },
+  },
+];