> ## Documentation Index
> Fetch the complete documentation index at: https://docs.lyzr.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Get query results

> API reference for the DataAnalyzr `ask` method

```python theme={null}
DataAnalyzr.ask(
    user_input: str = None,
    outputs: list = None,
    plot_path: str = None,
    recommendations_params: dict = None,
    counts: dict = None,
    context: dict = None,
    **kwargs,
) -> dict
```

This method orchestrates the analysis process and generates visualization, insights, recommendations, and tasks based on the specified inputs and parameters.
It is the recommended method to use for generating visualization, insights, recommendations, and tasks.

1. The method coordinates the analysis process and generates visualisation, insights, recommendations, and tasks based on the specified parameters.
2. Uses the `analysis`, `visualisation`, `insights`, `recommendations`, and `tasks` methods internally.
3. It allows for customization of outputs, analysis rerun, insights usage, recommendations format, output type, and counts.
4. The generated outputs are returned as a dictionary.

## Parameters

<ParamField path="user_input" type="string" required>
  The input string provided by the user for generating outputs.

  ```python theme={null}
  user_input = "What are the insights for the dataset?"
  ```
</ParamField>

<ParamField path="outputs" type="list">
  List of outputs to generate. Possible values are `visualisation`, `insights`, `recommendations`, and `tasks`.
  Defaults to `["visualisation", "insights", "recommendations", "tasks"]`.

  ```python theme={null}
  outputs = ["insights", "recommendations"]
  ```
</ParamField>

<ParamField path="plot_path" type="string">
  Path to save the generated plot. Only relevant when `outputs` includes `visualisation`.
  Defaults to `generated_plots/<random-plot-name>.png`.

  ```python theme={null}
  plot_path = "path/to/save/plot.png"
  ```
</ParamField>

<ParamField path="recommendations_params" type="dictionary">
  Parameters for generating recommendations. Includes `from_insights`, `output_type` and `json_format`.

  ```python theme={null}
  recommendations_params = {
      "from_insights": True,
      "output_type": "json",
      "json_format": {
          "Recommendation": "Recommendation text",
          "Reason": "Reason for the recommendation",
          "Impact": "Impact of the recommendation",
      },
  }
  ```

  <Expandable title="details">
    <ParamField path="from_insights" type="boolean">
      Whether to generate recommendations from insights. Default is True.
    </ParamField>

    <ParamField path="output_type" type="Literal['json', 'text']">
      Type of output for recommendations. Default is `json`.
    </ParamField>

    <ParamField path="json_format" type="dictionary">
      Format for the JSON output of recommendations.
    </ParamField>
  </Expandable>
</ParamField>

<ParamField path="counts" type="dictionary">
  Dictionary containing the counts of insights, recommendations, and tasks to generate.

  ```python theme={null}
  counts = {
      "insights": 3,
      "recommendations": 3,
      "tasks": 5,
  }
  ```

  <Expandable title="details">
    <ParamField path="insights" type="integer">
      Number of insights to generate. Default is 3.
    </ParamField>

    <ParamField path="recommendations" type="integer">
      Number of recommendations to generate. Default is 3.
    </ParamField>

    <ParamField path="tasks" type="integer">
      Number of tasks to generate. Default is 5.
    </ParamField>
  </Expandable>
</ParamField>

<ParamField path="context" type="dictionary">
  Context dictionary for the analysis. Includes `analysis`, `visualisation`, `insights`, `recommendations`, and `tasks`.

  ```python theme={null}
  context = {
      "analysis": "Analyze sales data",
      "visualisation": "Context for visualisation",
      "insights": "Context for insights",
      "recommendations": "Improve sales performance",
      "tasks": "Analyze sales data",
  }
  ```

  <Expandable title="details">
    <ParamField path="analysis" type="string">
      Context for the analysis method.
    </ParamField>

    <ParamField path="visualisation" type="string">
      Context for the visualisation method.
    </ParamField>

    <ParamField path="insights" type="string">
      Context for the insights method.
    </ParamField>

    <ParamField path="recommendations" type="string">
      Context for the recommendations method.
    </ParamField>

    <ParamField path="tasks" type="string">
      Context for the tasks method.
    </ParamField>
  </Expandable>
</ParamField>

<ParamField path="rerun_analysis" type="boolean">
  Whether to rerun the analysis before generating outputs. Default is True.

  ```python theme={null}
  rerun_analysis = True
  ```
</ParamField>

<ParamField path="max_retries" type="integer">
  Maximum number of retries for generating outputs. Default is 10.

  ```python theme={null}
  max_retries = 5
  ```
</ParamField>

<ParamField path="time_limit" type="integer">
  Time limit in seconds for generating outputs. Default is 45 for analysis and 60 for visualization.

  ```python theme={null}
  time_limit = 60
  ```
</ParamField>

<ParamField path="auto_train" type="boolean">
  Whether to automatically add questions with their SQL query or Python code to the vector store. Default is True.

  ```python theme={null}
  auto_train = True
  ```
</ParamField>

## Returns

<ResponseField name="response" type="dictionary">
  Dictionary containing the generated outputs. Includes `visualisation`, `insights`, `recommendations`, and `tasks`.

  ```python theme={null}
  response = {
      "visualisation": "path/to/plot.png",
      "insights": "-Insight 1\n-Insight 2\n-Insight 3",
      "recommendations": "Recommendation 1\nRecommendation 2\nRecommendation 3",
      "tasks": "Task 1\nTask 2\nTask 3\nTask 4\nTask 5",
  }
  ```

  <Expandable title="details">
    <ParamField path="visualisation" type="string">
      Path to the generated plot.
    </ParamField>

    <ParamField path="insights" type="string">
      Insights generated based on the analysis output.
    </ParamField>

    <ParamField path="recommendations" type="string">
      Recommendations generated based on the analysis output.
    </ParamField>

    <ParamField path="tasks" type="string">
      Tasks generated based on the analysis output.
    </ParamField>
  </Expandable>
</ResponseField>

## Example usage

```python theme={null}
# Ask for visualisation, insights, recommendations, and tasks
response = data_analyzr.ask(
    user_input="What are the insights for the dataset?",
    outputs=["visualisation", "insights", "recommendations", "tasks"],
    plot_path="path/to/plot.png",
    recommendations_params={
        "from_insights": True,
        "output_type": "json",
        "json_format": {
            "Recommendation": "Recommendation text",
            "Reason": "Reason for the recommendation",
            "Impact": "Impact of the recommendation",
        },
    },
    counts={
        "insights": 3,
        "recommendations": 3,
        "tasks": 5,
    },
    context={
        "analysis": "Analyze sales data",
        "visualisation": "Context for visualisation",
        "insights": "Context for insights",
        "recommendations": "Improve sales performance",
        "tasks": "Analyze sales data",
    },
    rerun_analysis=True,
    max_retries=5,
    time_limit=60,
    auto_train=True,
)

# Display the visualisation
from PIL import Image
Image.open(response["visualisation"]).show()

# Print insights
print(response["insights"])

# Print recommendations
print(response["recommendations"])

# Print tasks
print(response["tasks"])
```