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Documentation Index

Fetch the complete documentation index at: https://docs.emergence.ai/llms.txt

Use this file to discover all available pages before exploring further.

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Visualizations

The Data Insights solution generates interactive Plotly visualizations as part of the conversational analytics pipeline. When a user’s question benefits from a visual answer, the Insights Agent automatically selects and generates the appropriate chart type.

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How Visualizations Are Generated

The Insights Agent determines when a visualization would enhance the answer and generates it as part of the agentic loop:
1

Question analysis

The Insights Agent evaluates whether the question implies a visual answer. Questions about trends, comparisons, distributions, or proportions typically trigger visualization.
2

Data retrieval

The Text2SQL Agent generates and executes a query to retrieve the data needed for the visualization.
3

Chart type selection

The LLM selects the most appropriate chart type based on the data shape, question intent, and number of dimensions:
Data PatternChart Type
Trends over timeLine chart
Category comparisonBar chart
Part-to-wholePie / Donut chart
DistributionHistogram
CorrelationScatter plot
Multi-dimensionalGrouped / Stacked bar
4

Code generation

The Insights Agent generates Python code using Plotly to create the visualization:
import plotly.express as px

fig = px.bar(
    df,
    x="product_category",
    y="revenue",
    title="Revenue by Product Category",
    color="region",
    barmode="group"
)
fig.update_layout(
    xaxis_title="Category",
    yaxis_title="Revenue ($)"
)
5

Rendering and delivery

The chart is rendered and delivered as an artifact via the A2A protocol. The frontend renders it as an interactive Plotly chart with hover tooltips, zoom, and pan capabilities.

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Supported Chart Types

ChartWhen UsedPlotly Function
LineTime series, trendspx.line()
BarCategory comparisonpx.bar()
Pie / DonutProportions (< 8 categories)px.pie()
ScatterCorrelations, distributionspx.scatter()
HistogramValue distributionspx.histogram()
AreaCumulative trendspx.area()

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Interactive Features

Plotly charts rendered in the frontend support full interactivity:
  • Hover tooltips: View exact values for each data point
  • Zoom and pan: Focus on specific regions of the chart
  • Legend toggle: Show/hide individual series by clicking the legend
  • Download: Export as PNG or SVG directly from the chart toolbar
  • Responsive sizing: Charts adapt to the container width

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Chart Generation Examples

Question: “Show me the monthly revenue trend for the past year”The Insights Agent generates a line chart with months on the x-axis and revenue on the y-axis, including trend annotations for significant changes.
Question: “Compare sales across product categories by region”The agent generates a grouped bar chart with categories on the x-axis, sales on the y-axis, and color-coded bars for each region.
Question: “What does the distribution of order values look like?”The agent generates a histogram showing the frequency distribution of order values, with optional statistics overlay (mean, median, standard deviation).
Question: “What percentage of revenue comes from each channel?”The agent generates a pie or donut chart showing revenue proportions by channel, with percentage labels.

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Artifact Storage

Generated visualizations are stored as session artifacts in the Talk2Data database:
Artifact ComponentStorage
Chart specificationPlotly JSON stored in the artifacts table
Underlying dataQuery results stored alongside the chart
Python codeGeneration code preserved for reproducibility
MetadataChart type, title, axes, timestamp
Artifacts persist for the duration of the session and can be referenced in follow-up questions (“Make that a line chart instead” or “Add a trend line”).

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Customization in Follow-Up Questions

Users can refine visualizations through natural-language follow-ups:
RequestResult
”Make that a bar chart”Chart type changed
”Show only the top 5”Data filtered, chart updated
”Add a trend line”Trend line overlay added
”Use a logarithmic scale”Y-axis scale changed
”Split by region”Color dimension added
”Show as a percentage”Values converted to proportions

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Next Steps

Chat With Data

See the full conversational pipeline that produces visualizations.

Text-to-SQL

Understand how data is retrieved before visualization.

Analysis Agent

Learn about the reasoning engine that selects chart types.

Data Source Setup

Connect a database to start visualizing your data.