added longText as default text and fixed a bug in MetricResult

Author: jjmachan

nbs/backends/ragas_api_client.ipynb

@@ -704,25 +704,7 @@
    "outputs": [],
    "source": [
     "#| export\n",
-    "from enum import Enum"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#| export\n",
-    "class ColumnType(str, Enum):\n",
-    "    NUMBER = \"number\"\n",
-    "    TEXT = \"text\"\n",
-    "    LONG_TEXT = \"longText\"\n",
-    "    SELECT = \"select\"\n",
-    "    DATE = \"date\"\n",
-    "    MULTI_SELECT = \"multiSelect\"\n",
-    "    CHECKBOX = \"checkbox\"\n",
-    "    CUSTOM = \"custom\""
+    "from ragas_experimental.typing import ColumnType"
    ]
   },
   {

nbs/dataset.ipynb

@@ -261,7 +261,7 @@
     {
      "data": {
       "text/plain": [
-       "Dataset(name=TestModel, model=TestModel, len=0)"
+       "Dataset(name=TestModel_with_long_text, model=TestModel, len=0)"
       ]
      },
      "execution_count": null,
@@ -271,7 +271,7 @@
    ],
    "source": [
     "p = Project(project_id=\"1ef0843b-231f-4a2c-b64d-d39bcee9d830\", ragas_app_client=ragas_api_client)\n",
-    "test_dataset = p.create_dataset(name=\"TestModel\", model=TestModel)\n",
+    "test_dataset = p.create_dataset(name=\"TestModel_with_long_text\", model=TestModel)\n",
     "test_dataset"
    ]
   },
@@ -283,11 +283,11 @@
     {
      "data": {
       "text/plain": [
-       "{'id': '9375149c-20ce-4f07-9b2e-ebca6d00ea0c',\n",
-       " 'name': 'TestModel',\n",
+       "{'id': 'a7bd8b1f-dc29-4ae0-b1e5-24f0dfb76f7a',\n",
+       " 'name': 'TestModel_with_long_text',\n",
        " 'description': None,\n",
-       " 'created_at': '2025-04-15T19:02:22.275691+00:00',\n",
-       " 'updated_at': '2025-04-15T19:02:22.275691+00:00',\n",
+       " 'created_at': '2025-04-16T00:02:58.149112+00:00',\n",
+       " 'updated_at': '2025-04-16T00:02:58.149112+00:00',\n",
        " 'version_counter': 0,\n",
        " 'project_id': '1ef0843b-231f-4a2c-b64d-d39bcee9d830'}"
       ]
@@ -306,6 +306,31 @@
     "test_dataset"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'items': [],\n",
+       " 'pagination': {'offset': 0,\n",
+       "  'limit': 50,\n",
+       "  'total': 0,\n",
+       "  'order_by': 'created_at',\n",
+       "  'sort_dir': 'asc'}}"
+      ]
+     },
+     "execution_count": null,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "await ragas_api_client.list_dataset_rows(project_id=TEST_PROJECT_ID, dataset_id=TEST_DATASET_ID)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -325,11 +350,11 @@
     {
      "data": {
       "text/plain": [
-       "{'id': 'g01hEImX5RLW',\n",
-       " 'name': 'eBUi7lksCjTg',\n",
-       " 'description': 'cCax9o3Mv6vQ',\n",
-       " 'result': 'dJMynwKvhdaj',\n",
-       " 'result_reason': 'dxuafEzCImGW'}"
+       "{'id': 'eCYjJtBbLSDL',\n",
+       " 'name': '1sfEb8iJ1TUg',\n",
+       " 'description': 'gYsqmPXHbOyy',\n",
+       " 'result': 'cAZanmY0CwWT',\n",
+       " 'result_reason': 'e7IgZXICkmhA'}"
       ]
      },
      "execution_count": null,
@@ -395,7 +420,7 @@
     {
      "data": {
       "text/plain": [
-       "2"
+       "1"
       ]
      },
      "execution_count": null,

nbs/metric/result.ipynb

@@ -303,15 +303,26 @@
     "        \"reason\": self.reason,\n",
     "    }\n",
     "\n",
-    "# Add Pydantic compatibility methods\n",
     "@patch(cls_method=True)\n",
     "def __get_pydantic_core_schema__(\n",
     "    cls: MetricResult, \n",
     "    _source_type: t.Any, \n",
     "    _handler: GetCoreSchemaHandler\n",
     ") -> core_schema.CoreSchema:\n",
-    "    \"\"\"Generate a Pydantic core schema for MetricResult.\"\"\"\n",
-    "    # Create a schema that handles both validation and serialization\n",
+    "    \"\"\"Generate a Pydantic core schema for MetricResult.\n",
+    "    \n",
+    "    This custom schema handles different serialization behaviors:\n",
+    "    - For model_dump(): Returns the original MetricResult instance\n",
+    "    - For model_dump_json(): Converts to a JSON-compatible dict using __json__\n",
+    "    \"\"\"\n",
+    "    def serializer_function(instance, info):\n",
+    "        \"\"\"Handle different serialization modes for MetricResult.\"\"\"\n",
+    "        # For JSON serialization (model_dump_json), use __json__ method\n",
+    "        if getattr(info, 'mode', None) == 'json':\n",
+    "            return instance.__json__()\n",
+    "        # For Python serialization (model_dump), return the instance itself\n",
+    "        return instance\n",
+    "    \n",
     "    return core_schema.union_schema([\n",
     "        # First schema: handles validation of MetricResult instances\n",
     "        core_schema.is_instance_schema(MetricResult),\n",
@@ -324,15 +335,9 @@
     "            ),\n",
     "        ]),\n",
     "    ], serialization=core_schema.plain_serializer_function_ser_schema(\n",
-    "        # This function handles serialization\n",
-    "        lambda instance: instance.__json__()\n",
-    "    ))\n",
-    "\n",
-    "\n",
-    "@patch\n",
-    "def model_dump(self: MetricResult):\n",
-    "    \"\"\"Support Pydantic's model_dump method.\"\"\"\n",
-    "    return self.to_dict()"
+    "        serializer_function,\n",
+    "        info_arg=True  # Explicitly specify that we're using the info argument\n",
+    "    ))"
    ]
   },
   {
@@ -381,7 +386,7 @@
     {
      "data": {
       "text/plain": [
-       "{'result': 1, 'reason': 'test'}"
+       "{'response': 'test', 'grade': 1, 'faithfulness': 1}"
       ]
      },
      "execution_count": null,
@@ -390,13 +395,13 @@
     }
    ],
    "source": [
-    "m.grade.model_dump()"
+    "m.model_dump()"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "27f9bc1c",
+   "id": "0bc2a1ec",
    "metadata": {},
    "outputs": [
     {
@@ -411,9 +416,7 @@
     }
    ],
    "source": [
-    "mt = TestModel(response=\"test\", grade=MetricResult(result=1, reason=\"test\"), faithfulness=MetricResult(result=1, reason=\"test\"))\n",
-    "\n",
-    "mt.model_dump_json()"
+    "m.model_dump_json()"
    ]
   }
  ],