small constructor change and updated notebook (#3426)

small change in the pydantic definitions, same api. 

updated notebook with right constructure and added few shot example

docs/modules/agents/toolkits/examples/powerbi.ipynb

@@ -55,14 +55,16 @@
    },
    "outputs": [],
    "source": [
-    "llm = AzureOpenAI(temperature=0, deployment_name=\"text-davinci-003\", verbose=True)\n",
+    "fast_llm = AzureOpenAI(temperature=0.5, max_tokens=1000, deployment_name=\"gpt-35-turbo\", verbose=True)\n",
+    "smart_llm = AzureOpenAI(temperature=0, max_tokens=100, deployment_name=\"gpt-4\", verbose=True)\n",
+    "\n",
     "toolkit = PowerBIToolkit(\n",
-    "    powerbi=PowerBIDataset(None, \"<dataset_id>\", ['table1', 'table2'], DefaultAzureCredential()), \n",
-    "    llm=llm\n",
+    "    powerbi=PowerBIDataset(dataset_id=\"<dataset_id>\", table_names=['table1', 'table2'], credential=DefaultAzureCredential()), \n",
+    "    llm=smart_llm\n",
     ")\n",
     "\n",
     "agent_executor = create_pbi_agent(\n",
-    "    llm=llm,\n",
+    "    llm=fast_llm,\n",
     "    toolkit=toolkit,\n",
     "    verbose=True,\n",
     ")"
@@ -141,6 +143,56 @@
    "source": [
     "agent_executor.run(\"What unique values are there for dimensions2 in table2\")"
    ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "id": "6fd950e4",
+   "metadata": {},
+   "source": [
+    "## Example: add your own few-shot prompts"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "87d677f9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#fictional example\n",
+    "few_shots = \"\"\"\n",
+    "Question: How many rows are in the table revenue?\n",
+    "DAX: EVALUATE ROW(\"Number of rows\", COUNTROWS(revenue_details))\n",
+    "----\n",
+    "Question: How many rows are in the table revenue where year is not empty?\n",
+    "DAX: EVALUATE ROW(\"Number of rows\", COUNTROWS(FILTER(revenue_details, revenue_details[year] <> \"\")))\n",
+    "----\n",
+    "Question: What was the average of value in revenue in dollars?\n",
+    "DAX: EVALUATE ROW(\"Average\", AVERAGE(revenue_details[dollar_value]))\n",
+    "----\n",
+    "\"\"\"\n",
+    "toolkit = PowerBIToolkit(\n",
+    "    powerbi=PowerBIDataset(dataset_id=\"<dataset_id>\", table_names=['table1', 'table2'], credential=DefaultAzureCredential()), \n",
+    "    llm=smart_llm,\n",
+    "    examples=few_shots,\n",
+    ")\n",
+    "agent_executor = create_pbi_agent(\n",
+    "    llm=fast_llm,\n",
+    "    toolkit=toolkit,\n",
+    "    verbose=True,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "33f4bb43",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "agent_executor.run(\"What was the maximum of value in revenue in dollars in 2022?\")"
+   ]
   }
  ],
  "metadata": {

langchain/utilities/powerbi.py

@@ -33,13 +33,13 @@ class PowerBIDataset(BaseModel):
     If the model is not RLS enabled, this will be ignored.
     """
 
-    group_id: Optional[str]
     dataset_id: str
     table_names: List[str]
+    group_id: Optional[str] = None
     credential: Optional[Union[ChainedTokenCredential, InteractiveCredential]] = None
     token: Optional[str] = None
     impersonated_user_name: Optional[str] = None
-    sample_rows_in_table_info: int = Field(1, gt=0, le=10)
+    sample_rows_in_table_info: int = Field(default=1, gt=0, le=10)
     aiosession: Optional[aiohttp.ClientSession] = None
     schemas: Dict[str, str] = Field(default_factory=dict, init=False)