Render an agent response as a visualization

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This page shows how to use the Python SDK to render a visualization from the chart specifications that are provided within a Conversational Analytics API response. The sample code extracts the chart specification (in the Vega-Lite format) from the response's chart field and uses the Vega-Altair library to render the chart, save it as an image, and display it.

Note: This guide assumes that you're working in an environment like Colaboratory. This guide also builds on the setup in Build a data agent using the Python SDK, which shows how to authenticate and initialize the required client, inline_context, and messages variables.

Example: Render a bar chart from an API

This example shows how to render a bar chart from a Conversational Analytics API agent response. The example sends a request with the following prompt:

"Create a bar graph that shows the top five states by the total number of airports."

The sample code defines the following helper functions:

• render_chart_response: Extracts the Vega-Lite configuration from the chart message, converts it to a format that can be used by the Vega-Altair library, renders the chart, saves it to chart.png, and displays it.
• chat: Sends a request to the Conversational Analytics API using the inline_context variable and the current messages list, processes the streaming response, and if a chart is returned, calls render_chart_response to display it.

To use the following sample code, replace the following:

• sqlgen-testing: The ID of your billing project that has the required APIs enabled.
• Create a bar graph that shows the top five states by the total number of airports: The prompt that you want to send to the Conversational Analytics API.

from google.cloud import geminidataanalytics
from google.protobuf.json_format import MessageToDict
import altair as alt
import proto

# Helper function for rendering chart response
def render_chart_response(resp):
  def _convert(v):
    if isinstance(v, proto.marshal.collections.maps.MapComposite):
      return {k: _convert(v) for k, v in v.items()}
    elif isinstance(v, proto.marshal.collections.RepeatedComposite):
      return [_convert(el) for el in v]
    elif isinstance(v, (int, float, str, bool)):
      return v
    else:
      return MessageToDict(v)

  vega_config = _convert(resp.result.vega_config)
  chart = alt.Chart.from_dict(vega_config)
  chart.save('chart.png')
  chart.display()

# Helper function for calling the API
def chat(q: str):
  billing_project = "sqlgen-testing"

  input_message = geminidataanalytics.Message(
      user_message=geminidataanalytics.UserMessage(text=q)
  )

  client = geminidataanalytics.DataChatServiceClient()
  request = geminidataanalytics.ChatRequest(
      inline_context=inline_context,
      parent=f"projects/{billing_project}/locations/global",
      messages=messages,
  )

  # Make the request
  stream = client.chat(request=request)

  for reply in stream:
    if "chart" in reply.system_message:
      # ChartMessage includes `query` for generating a chart and `result` with the generated chart.
      if "result" in reply.system_message.chart:
        render_chart_response(reply.system_message.chart)

# Send the prompt to make a bar graph
chat("Create a bar graph that shows the top five states by the total number of airports.")