Add Generative Graphs UI and Data Analysis Tool #464
Conversation
- Integrated Recharts for data visualization - Added dataAnalysis tool with Zod schema for chart configuration - Extended chat file uploads to support CSV and JSON files - Updated researcher agent with guidelines for data visualization - Integrated MapQueryHandler for geospatial data in analysis results - Ensured real-time UI streaming for chart components Co-authored-by: ngoiyaeric <115367894+ngoiyaeric@users.noreply.github.com>
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WalkthroughAdds a data analysis/visualization feature: new GraphSection component, dataAnalysis tool, schema/type, agent prompt/tool integration, UI wiring to render graphs (and trigger map queries from geospatial results), plus CSV/JSON file input support and removal of drawnFeatures streaming. Changes
Sequence DiagramsequenceDiagram
participant User
participant Agent
participant DataAnalysisTool
participant UIStream
participant GraphSection
participant MapQueryHandler
User->>Agent: Request visualization / provide data
Agent->>DataAnalysisTool: select + execute(dataAnalysis)
DataAnalysisTool->>UIStream: create streamable value
DataAnalysisTool->>GraphSection: append GraphSection bound to stream
DataAnalysisTool->>UIStream: complete stream with DataAnalysisResult
UIStream->>GraphSection: deliver resolved data
GraphSection->>GraphSection: render chart (bar/line/area/pie/scatter)
GraphSection->>Agent: expose geospatial points (if present)
Agent->>MapQueryHandler: send MAP_QUERY_TRIGGER constructed from first geospatial item
GraphSection->>User: display visualization
Estimated code review effort🎯 4 (Complex) | ⏱️ ~45 minutes Possibly related PRs
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There was a problem hiding this comment.
Main blockers are in components/graph-section.tsx: conditional hook usage (useStreamableValue) is a Rules of Hooks violation and can break rendering, and unguarded JSON.parse can crash the UI. There are also correctness gaps in chart rendering (pie assumes series[0], scatter duplicates identical series), and the tool’s “streaming” path currently adds complexity without actual incremental streaming. Consider tightening the dataAnalysisSchema to reduce runtime failures from malformed model output.
Additional notes (1)
- Performance |
app/actions.tsx:298-308
The file ingestion now treatsapplication/jsonuploads as plain text and prepends the entire file content into the model prompt. Large JSON/CSV files can easily blow prompt limits and degrade model performance or cause failures.
At minimum, implement size caps and/or truncation/summarization before injecting into messageParts, and consider attaching metadata (filename, row count) rather than full raw content by default.
Summary of changes
What this PR changes
- Adds a new
dataAnalysistool (lib/agents/tools/data-analysis.tsx) backed by a Zod schema (lib/schema/data-analysis.tsx) to generate structured chart specs. - Introduces
GraphSectionUI (components/graph-section.tsx) using Recharts to render bar/line/area/pie/scatter charts, including support for streamed tool output. - Extends file uploads to accept
text/csvandapplication/jsonin the chat UI (components/chat-panel.tsx) and server action parsing (app/actions.tsx). - Updates AI → UI mapping (
app/actions.tsx) to renderGraphSectionfordataAnalysistool results and trigger map updates when geospatial points are present. - Updates researcher agent instructions (
lib/agents/researcher.tsx) to include a decision path fordataAnalysis. - Adds dependency:
rechartsinpackage.json. - Adds a new exported type
DataAnalysisResult(lib/types/index.ts).
components/graph-section.tsx
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| const chartData: DataAnalysisResult | undefined = typeof data === 'string' | ||
| ? JSON.parse(data) | ||
| : data as DataAnalysisResult | ||
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There was a problem hiding this comment.
JSON.parse(data) is performed without any error handling. If the AI/tool ever emits a partial string (streaming), malformed JSON, or a plain-text error message, this will throw during render and crash the client subtree.
This is especially risky given the component explicitly supports streamed and string inputs.
Suggestion
Guard JSON.parse with a try/catch and render a safe fallback UI (or return null) if parsing fails.
let chartData: DataAnalysisResult | undefined
if (typeof data === 'string') {
try {
chartData = JSON.parse(data)
} catch {
chartData = undefined
}
} else {
chartData = data as DataAnalysisResult
}Optionally show a small CardDescription like “Unable to render chart: invalid data” for debuggability.
Reply with "@CharlieHelps yes please" if you'd like me to add a commit with this change.
components/graph-section.tsx
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| const [streamData, error, pending] = useStreamableValue(isStreamable ? (result as any) : undefined) | ||
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| const data = isStreamable ? streamData : result; | ||
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| const chartData: DataAnalysisResult | undefined = typeof data === 'string' | ||
| ? JSON.parse(data) | ||
| : data as DataAnalysisResult | ||
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| if (pending && !chartData) { | ||
| return ( | ||
| <Section className="py-2"> | ||
| <div className="animate-pulse flex space-y-4 flex-col"> | ||
| <div className="h-4 bg-muted rounded w-3/4"></div> | ||
| <div className="h-64 bg-muted rounded"></div> | ||
| </div> | ||
| </Section> | ||
| ) | ||
| } | ||
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| if (!chartData) return null |
There was a problem hiding this comment.
The error value returned by useStreamableValue is computed but ignored. If the stream errors, the user will just see an empty section or partial UI with no explanation.
Also, pending && !chartData only handles the initial loading state; if the stream errors, you should surface that explicitly.
Suggestion
Handle the error case explicitly and render an error state.
if (error) {
return (
<Section className="py-2">
<Card>
<CardHeader className="pb-2">
<CardTitle className="text-lg font-medium">Chart unavailable</CardTitle>
<CardDescription>{String(error)}</CardDescription>
</CardHeader>
</Card>
</Section>
)
}Reply with "@CharlieHelps yes please" if you'd like me to add a commit with this error handling.
components/graph-section.tsx
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| case 'pie': | ||
| return ( | ||
| <PieChart> | ||
| <Pie | ||
| data={plotData} | ||
| dataKey={config.series[0].key} | ||
| nameKey={config.xAxisKey} | ||
| cx="50%" | ||
| cy="50%" | ||
| outerRadius={80} | ||
| label | ||
| > | ||
| {plotData.map((entry, index) => ( | ||
| <Cell key={`cell-${index}`} fill={COLORS[index % COLORS.length]} /> | ||
| ))} | ||
| </Pie> | ||
| <Tooltip /> | ||
| <Legend /> | ||
| </PieChart> |
There was a problem hiding this comment.
pie rendering assumes config.series[0] always exists. If the tool returns an empty series array, this will throw and crash rendering.
Even if the schema intends series to exist, model output can still be inconsistent at runtime.
Suggestion
Add a defensive guard for series.length === 0 and render a fallback message.
case 'pie': {
const first = config.series[0]
if (!first) return <div>Missing series configuration for pie chart.</div>
// ...use `first.key`
}Reply with "@CharlieHelps yes please" if you'd like me to add a commit with this guard.
components/graph-section.tsx
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| case 'scatter': | ||
| return ( | ||
| <ScatterChart> | ||
| <CartesianGrid strokeDasharray="3 3" /> | ||
| <XAxis type="number" dataKey={config.xAxisKey} name={config.xAxisKey} /> | ||
| <YAxis type="number" dataKey={config.yAxisKey} name={config.yAxisKey} /> | ||
| <Tooltip cursor={{ strokeDasharray: '3 3' }} /> | ||
| <Legend /> | ||
| {config.series.map((s, i) => ( | ||
| <Scatter key={s.key} name={s.name} data={plotData} fill={s.color || COLORS[i % COLORS.length]} /> | ||
| ))} | ||
| </ScatterChart> | ||
| ) |
There was a problem hiding this comment.
scatter rendering currently maps config.series but each <Scatter ... data={plotData} /> uses the same plotData and does not use s.key at all. This likely renders duplicated scatter series with identical points, and the legend will be misleading.
If the intention is to support multiple series, each series should typically point to a different dataKey / shape, or you should render a single <Scatter> and use config for axes only.
Suggestion
Either:
- Render a single scatter series:
case 'scatter':
return (
<ScatterChart>
...
<Scatter name={config.series[0]?.name ?? 'Series'} data={plotData} fill={...} />
</ScatterChart>
)or 2) If you need multi-series scatter, change the schema/transform so each series references a distinct dataset (e.g. series[i].dataKey or separate arrays).
Reply with "@CharlieHelps yes please" if you'd like me to add a commit implementing option (1) with basic guards.
| export const dataAnalysisTool = ({ uiStream }: ToolProps) => ({ | ||
| description: 'Analyze data and generate a structured representation for visualization in a graph or chart. Use this tool when the user asks for a chart, graph, or data visualization, or when you have structured data (like from a CSV or search results) that would be better understood visually.', | ||
| parameters: dataAnalysisSchema, | ||
| execute: async (result: DataAnalysisResult) => { | ||
| const streamResults = createStreamableValue<DataAnalysisResult>() | ||
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| uiStream.append(<GraphSection result={streamResults.value} />) | ||
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| streamResults.done(result) | ||
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| return result | ||
| } |
There was a problem hiding this comment.
dataAnalysisTool.execute creates a streamable value, appends <GraphSection result={streamResults.value} />, and then immediately calls streamResults.done(result). This doesn’t actually stream incremental updates; it just publishes a single final payload.
If the intent is real-time rendering, this should either:
- append a placeholder and update it over time, or
- stream partial results (e.g.,
streamResults.update(...)as analysis progresses).
As-is, the extra stream plumbing adds complexity without benefit.
Suggestion
If you don’t plan to stream partial chart specs, simplify:
- remove
createStreamableValueusage - append
<GraphSection result={result} />directly
execute: async (result: DataAnalysisResult) => {
uiStream.append(<GraphSection result={result} />)
return result
}If you do plan to stream, change the tool to progressively update the streamable value with intermediate states.
Reply with "@CharlieHelps yes please" if you'd like me to add a commit with the simplification.
| case 'dataAnalysis': | ||
| return { | ||
| id, | ||
| component: ( | ||
| <> | ||
| <GraphSection result={searchResults.value} /> | ||
| {toolOutput.geospatial && toolOutput.geospatial.length > 0 && ( | ||
| <MapQueryHandler | ||
| toolOutput={{ | ||
| type: 'MAP_QUERY_TRIGGER', | ||
| originalUserInput: JSON.stringify(toolOutput.geospatial[0]), | ||
| timestamp: new Date().toISOString(), | ||
| mcp_response: { | ||
| location: { | ||
| latitude: toolOutput.geospatial[0].latitude, | ||
| longitude: toolOutput.geospatial[0].longitude, | ||
| place_name: toolOutput.geospatial[0].label | ||
| } | ||
| } | ||
| }} | ||
| /> | ||
| )} |
There was a problem hiding this comment.
This constructs a MAP_QUERY_TRIGGER with originalUserInput: JSON.stringify(toolOutput.geospatial[0]) and uses only the first geospatial point. If multiple points are returned, the map will ignore all but one.
Also, this code is doing a lot of ad-hoc shaping of a map tool payload inside UI-state mapping logic, which makes the contract fragile and hard to evolve.
Suggestion
At minimum, consider passing the entire geospatial array through and letting MapQueryHandler decide what to do, or explicitly document that only the first point is supported.
If MapQueryHandler expects a single location, add a small helper function (in this file) to build the payload so the shape is centralized and testable.
Reply with "@CharlieHelps yes please" if you'd like me to add a commit that factors payload creation into a helper and (optionally) uses the first item explicitly with a comment.
| export const dataAnalysisSchema = z.object({ | ||
| title: z.string().describe('The title of the chart'), | ||
| description: z.string().optional().describe('A brief description of the chart'), | ||
| chartType: z.enum(['bar', 'line', 'pie', 'area', 'scatter']).describe('The type of chart to render'), | ||
| data: z.array(z.record(z.any())).describe('The data points for the chart'), | ||
| config: z.object({ | ||
| xAxisKey: z.string().describe('The key in the data object to use for the X axis'), | ||
| yAxisKey: z.string().optional().describe('The key in the data object to use for the Y axis (for scatter charts)'), | ||
| series: z.array(z.object({ | ||
| key: z.string().describe('The key in the data object for this series'), | ||
| name: z.string().describe('The display name for this series'), | ||
| color: z.string().optional().describe('Optional hex color for this series') | ||
| })).describe('The series to be plotted') | ||
| }).describe('Configuration for the chart layout'), | ||
| geospatial: z.array(z.object({ | ||
| latitude: z.number(), | ||
| longitude: z.number(), | ||
| label: z.string().optional() | ||
| })).optional().describe('Optional geospatial data points to be displayed on a map') | ||
| }) |
There was a problem hiding this comment.
DataAnalysisResult uses any[] and z.record(z.any()) in the schema. This makes the tool output effectively untyped and pushes failures into runtime rendering (e.g., missing keys for axes/series).
Given this is a core integration point between the model and UI, it’s worth tightening validation at least around required keys (xAxisKey, series keys existing in data, etc.).
Suggestion
Improve runtime robustness by refining the schema:
- use
z.record(z.unknown())instead ofz.any()to avoid implicitany - add
min(1)ondataandconfig.series - add a
superRefinethat verifiesxAxisKeyand eachseries.keyappear in at least one data row
data: z.array(z.record(z.unknown())).min(1),
config: z.object({
xAxisKey: z.string(),
series: z.array(...).min(1),
}).superRefine((cfg, ctx) => { /* validate keys */ })Reply with "@CharlieHelps yes please" if you'd like me to add a commit that tightens the schema with min(1) and z.unknown() (and optionally key checks).
| export const dataAnalysisSchema = z.object({ | ||
| title: z.string().describe('The title of the chart'), | ||
| description: z.string().optional().describe('A brief description of the chart'), | ||
| chartType: z.enum(['bar', 'line', 'pie', 'area', 'scatter']).describe('The type of chart to render'), | ||
| data: z.array(z.record(z.any())).describe('The data points for the chart'), | ||
| config: z.object({ | ||
| xAxisKey: z.string().describe('The key in the data object to use for the X axis'), | ||
| yAxisKey: z.string().optional().describe('The key in the data object to use for the Y axis (for scatter charts)'), | ||
| series: z.array(z.object({ | ||
| key: z.string().describe('The key in the data object for this series'), | ||
| name: z.string().describe('The display name for this series'), | ||
| color: z.string().optional().describe('Optional hex color for this series') | ||
| })).describe('The series to be plotted') | ||
| }).describe('Configuration for the chart layout'), | ||
| geospatial: z.array(z.object({ | ||
| latitude: z.number(), | ||
| longitude: z.number(), | ||
| label: z.string().optional() | ||
| })).optional().describe('Optional geospatial data points to be displayed on a map') | ||
| }) |
There was a problem hiding this comment.
dataAnalysisSchema uses z.array(z.record(z.any())) for data. This forces the model/tool pipeline to accept arbitrarily-shaped values and makes it easy to return non-serializable objects (Dates, nested functions, etc.) or huge payloads.
Since the UI expects Recharts-friendly JSON, you should constrain this to JSON-serializable primitives (e.g., string | number | boolean | null) and objects/arrays thereof, or at least z.record(z.union([z.string(), z.number(), z.boolean(), z.null()])) for flat chart rows. This reduces runtime render errors and payload bloat.
Suggestion
Tighten the data schema to JSON-serializable and ideally flat row records.
Example (flat rows):
const cell = z.union([z.string(), z.number(), z.boolean(), z.null()])
export const dataAnalysisSchema = z.object({
// ...
data: z.array(z.record(cell)).describe('Flat row records for the chart')
// ...
})If you need nested structures, model them explicitly rather than any.
Reply with "@CharlieHelps yes please" if you'd like me to add a commit with this suggestion.
| export type DataAnalysisResult = { | ||
| title: string; | ||
| description?: string; | ||
| chartType: 'bar' | 'line' | 'pie' | 'area' | 'scatter'; | ||
| data: any[]; | ||
| config: { | ||
| xAxisKey: string; | ||
| yAxisKey?: string; | ||
| series: { | ||
| key: string; | ||
| name: string; | ||
| color?: string; | ||
| }[]; | ||
| }; | ||
| geospatial?: { | ||
| latitude: number; | ||
| longitude: number; | ||
| label?: string; | ||
| }[]; | ||
| }; |
There was a problem hiding this comment.
DataAnalysisResult in lib/types/index.ts uses any[] for data. This is type-valid but defeats type safety across the rendering surface and makes it easy to accidentally pass non-JSON/non-Recharts-friendly values into the chart components.
Given you already have a Zod schema for the tool, consider deriving the TS type from Zod (z.infer<typeof dataAnalysisSchema>) or at least using a safer record type (Record<string, string | number | boolean | null>).
Suggestion
Prefer deriving DataAnalysisResult from the Zod schema to keep runtime/compile-time aligned.
Example:
// lib/types/index.ts
import type { z } from 'zod'
import { dataAnalysisSchema } from '@/lib/schema/data-analysis'
export type DataAnalysisResult = z.infer<typeof dataAnalysisSchema>Or if you want to avoid importing schema into types, at least replace any[] with Array<Record<string, string | number | boolean | null>>.
Reply with "@CharlieHelps yes please" if you'd like me to add a commit with this suggestion.
![coderabbitai[bot]](https://avatars.githubusercontent.com/in/347564?s=60&v=4){kind=small}
There was a problem hiding this comment.
Actionable comments posted: 6
Caution
Some comments are outside the diff and can’t be posted inline due to platform limitations.
⚠️ Outside diff range comments (1)
lib/agents/researcher.tsx (1)
24-75:⚠️ Potential issue | 🟠 MajorResolve conflict between “Geospatial Priority” and the new dataAnalysis step.
The prompt says any location query must use
geospatialQueryTool, but the decision flow now prioritizesdataAnalysisfor charts. For location‑based charts, the model may pick the wrong tool. Clarify precedence (e.g., “chart requests → dataAnalysis; maps/directions/places → geospatialQueryTool”) to keep behavior deterministic.
🤖 Fix all issues with AI agents
In `@components/graph-section.tsx`:
- Around line 35-60: GraphSection currently ignores the error returned from
useStreamableValue and calls JSON.parse without try/catch; update the component
to first check the error from useStreamableValue (variable error) and render an
appropriate fallback (null or an error UI) when error exists, then wrap the
JSON.parse logic that produces chartData in a try/catch to safely handle
malformed strings and set chartData to undefined (or an error state) on parse
failure, and ensure pending logic still uses the safe chartData variable;
reference symbols: GraphSection, useStreamableValue, streamData, error, pending,
chartData, JSON.parse.
In `@lib/agents/tools/data-analysis.tsx`:
- Around line 10-18: The execute function should be made resilient by wrapping
the UI and stream operations in a try-catch: inside execute (which uses
createStreamableValue(), uiStream.append(<GraphSection ...>) and
streamResults.done(result)), wrap the uiStream.append and streamResults.done
calls in a try block and in the catch log the error (e.g., processLogger.error
or console.error) and call streamResults.error or streamResults.done with a safe
fallback to ensure the stream is completed; finally return the original result
(or a safe fallback) so the caller does not receive an unhandled exception.
In `@lib/schema/data-analysis.tsx`:
- Around line 4-23: Update dataAnalysisSchema to enforce non-empty series and
conditional yAxisKey rules: ensure config.series uses z.array(...).min(1) so
charts that access config.series[0].key (e.g., pie handling) cannot be empty,
and make chartType a discriminated union or add a z.refine on dataAnalysisSchema
that when chartType === 'scatter' requires config.yAxisKey to be
present/non-empty; reference dataAnalysisSchema, chartType, config.series, and
config.yAxisKey when implementing the min(1) and conditional requirement so
runtime accesses are safe.
- Line 25: The current type alias PartialDataAnalysis applies DeepPartial to the
schema instance instead of the inferred data shape; change the alias to apply
DeepPartial to the inferred type by using z.infer on dataAnalysisSchema (e.g.,
update PartialDataAnalysis to DeepPartial<z.infer<typeof dataAnalysisSchema>>),
referencing the existing dataAnalysisSchema and PartialDataAnalysis identifiers
so the type represents the actual data structure.
In `@lib/types/index.ts`:
- Around line 42-46: Rename the optional text field in the geospatial array to
match the MapData.markers interface: change geospatial's label?: string to
title?: string so it aligns with MapData.markers (referencing geospatial and
MapData.markers, and the label?/title? property names) and update any usages or
types that reference geospatial to use title instead of label.
- Line 32: The type declaration uses data: any[] which loses type safety; change
the DataAnalysisResult type to use a safer type such as data: Record<string,
unknown>[] or make it generic (e.g., export type DataAnalysisResult<T extends
Record<string, unknown> = Record<string, unknown>> = { ... data: T[]; ... }) and
update usages of DataAnalysisResult to pass the concrete T where appropriate
(refer to the DataAnalysisResult type name and the data property to locate the
change).
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📒 Files selected for processing (9)
app/actions.tsxcomponents/chat-panel.tsxcomponents/graph-section.tsxlib/agents/researcher.tsxlib/agents/tools/data-analysis.tsxlib/agents/tools/index.tsxlib/schema/data-analysis.tsxlib/types/index.tspackage.json
🧰 Additional context used
🧬 Code graph analysis (4)
lib/agents/tools/index.tsx (4)
lib/agents/tools/geospatial.tsx (3)
tools(318-318)uiStream(158-407)queryType(333-342)lib/agents/tools/search.tsx (1)
ToolProps(9-77)lib/agents/tools/retrieve.tsx (1)
ToolProps(8-67)lib/agents/tools/video-search.tsx (1)
ToolProps(8-50)
lib/types/index.ts (3)
components/map/map-query-handler.tsx (1)
GeospatialToolOutput(18-23)components/map/map-data-context.tsx (2)
MapData(15-32)MapDataContextType(34-37)mapbox_mcp/hooks.ts (1)
DistanceResult(22-29)
components/graph-section.tsx (2)
components/video-search-section.tsx (1)
VideoSearchSection(14-35)components/section.tsx (1)
icon(24-75)
app/actions.tsx (1)
components/map/map-query-handler.tsx (5)
GeospatialToolOutput(18-23)prevData(39-48)toolOutput(33-73)prevData(52-56)MapQueryHandlerProps(25-28)
🔇 Additional comments (6)
components/chat-panel.tsx (1)
213-218: Accept list now covers CSV/JSON uploads.This aligns with the server-side ingestion logic.
lib/agents/tools/index.tsx (1)
6-33: dataAnalysis tool is correctly wired into the tool registry.The new tool is integrated consistently with existing tooling patterns.
app/actions.tsx (2)
301-305: CSV/JSON file ingestion is handled alongside text/plain.Good alignment with the expanded upload accept list.
748-773: GraphSection + optional map update wiring looks consistent.The dataAnalysis tool output now renders graphs and updates the map when geospatial points are provided.
package.json (1)
89-89: No action required. Recharts 3.7.0 explicitly supports React 19 in its peer dependencies (react: ^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0) and is compatible with React 19.1.2 and Next.js 15. This is the latest stable version as of January 2026.lib/agents/tools/data-analysis.tsx (1)
11-15: Note: Streamable value is immediately completed.The
createStreamableValueis created and immediately marked asdoneon the next line. While this works correctly for one-shot rendering, it doesn't leverage the progressive streaming capability. If the intent is to support incremental chart updates (e.g., data loading in chunks), you'd need to callstreamResults.update()with partial data beforedone().If one-shot rendering is the intended behavior, this is fine as-is.
✏️ Tip: You can disable this entire section by setting review_details to false in your review settings.
components/graph-section.tsx
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| export function GraphSection({ result }: GraphSectionProps) { | ||
| // Check if result is a streamable value (has a value property or internal structure) | ||
| // We use a heuristic or just try-catch if needed, but useStreamableValue must be called at the top level. | ||
| // Actually, we can check if it looks like a streamable value. | ||
| const isStreamable = result && typeof result === 'object' && ('value' in result || 'done' in result || (result as any)._isStreamable); | ||
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| const [streamData, error, pending] = useStreamableValue(isStreamable ? (result as any) : undefined) | ||
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| const data = isStreamable ? streamData : result; | ||
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| const chartData: DataAnalysisResult | undefined = typeof data === 'string' | ||
| ? JSON.parse(data) | ||
| : data as DataAnalysisResult | ||
|
|
||
| if (pending && !chartData) { | ||
| return ( | ||
| <Section className="py-2"> | ||
| <div className="animate-pulse flex space-y-4 flex-col"> | ||
| <div className="h-4 bg-muted rounded w-3/4"></div> | ||
| <div className="h-64 bg-muted rounded"></div> | ||
| </div> | ||
| </Section> | ||
| ) | ||
| } | ||
|
|
||
| if (!chartData) return null |
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Handle JSON parsing errors and check the error variable from useStreamableValue.
Line 41 extracts an error variable that is never checked before rendering. Additionally, JSON.parse at line 46 lacks error handling—if a malformed string is passed to GraphSection, it will throw and break rendering. Although dataAnalysisTool currently passes structured objects, the component's type signature allows string | DataAnalysisResult, so add defensive error handling.
Safe parsing + error checks
- const [streamData, error, pending] = useStreamableValue(isStreamable ? (result as any) : undefined)
+ const [streamData, error, pending] = useStreamableValue(isStreamable ? (result as any) : undefined)
+
+ if (error) {
+ return (
+ <Section className="py-2">
+ <div className="text-sm text-muted-foreground">Error loading chart data.</div>
+ </Section>
+ )
+ }
const data = isStreamable ? streamData : result;
- const chartData: DataAnalysisResult | undefined = typeof data === 'string'
- ? JSON.parse(data)
- : data as DataAnalysisResult
+ let chartData: DataAnalysisResult | undefined
+ if (typeof data === 'string') {
+ try {
+ chartData = JSON.parse(data)
+ } catch {
+ chartData = undefined
+ }
+ } else {
+ chartData = data as DataAnalysisResult
+ }
if (pending && !chartData) {
return (
<Section className="py-2">
<div className="animate-pulse flex space-y-4 flex-col">
<div className="h-4 bg-muted rounded w-3/4"></div>
<div className="h-64 bg-muted rounded"></div>
</div>
</Section>
)
}
- if (!chartData) return null
+ if (!chartData) {
+ return (
+ <Section className="py-2">
+ <div className="text-sm text-muted-foreground">Unable to load chart data.</div>
+ </Section>
+ )
+ }🤖 Prompt for AI Agents
In `@components/graph-section.tsx` around lines 35 - 60, GraphSection currently
ignores the error returned from useStreamableValue and calls JSON.parse without
try/catch; update the component to first check the error from useStreamableValue
(variable error) and render an appropriate fallback (null or an error UI) when
error exists, then wrap the JSON.parse logic that produces chartData in a
try/catch to safely handle malformed strings and set chartData to undefined (or
an error state) on parse failure, and ensure pending logic still uses the safe
chartData variable; reference symbols: GraphSection, useStreamableValue,
streamData, error, pending, chartData, JSON.parse.
| execute: async (result: DataAnalysisResult) => { | ||
| const streamResults = createStreamableValue<DataAnalysisResult>() | ||
|
|
||
| uiStream.append(<GraphSection result={streamResults.value} />) | ||
|
|
||
| streamResults.done(result) | ||
|
|
||
| return result | ||
| } |
There was a problem hiding this comment.
🧹 Nitpick | 🔵 Trivial
Add error handling for robustness.
The execute function lacks error handling. If uiStream.append throws or if the result contains invalid data that causes GraphSection to fail, the error will propagate unhandled. Consider wrapping in a try-catch to ensure graceful degradation.
🛡️ Proposed error handling
execute: async (result: DataAnalysisResult) => {
+ try {
const streamResults = createStreamableValue<DataAnalysisResult>()
uiStream.append(<GraphSection result={streamResults.value} />)
streamResults.done(result)
return result
+ } catch (error) {
+ console.error('Data analysis tool error:', error)
+ throw error
+ }
}📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| execute: async (result: DataAnalysisResult) => { | |
| const streamResults = createStreamableValue<DataAnalysisResult>() | |
| uiStream.append(<GraphSection result={streamResults.value} />) | |
| streamResults.done(result) | |
| return result | |
| } | |
| execute: async (result: DataAnalysisResult) => { | |
| try { | |
| const streamResults = createStreamableValue<DataAnalysisResult>() | |
| uiStream.append(<GraphSection result={streamResults.value} />) | |
| streamResults.done(result) | |
| return result | |
| } catch (error) { | |
| console.error('Data analysis tool error:', error) | |
| throw error | |
| } | |
| } |
🤖 Prompt for AI Agents
In `@lib/agents/tools/data-analysis.tsx` around lines 10 - 18, The execute
function should be made resilient by wrapping the UI and stream operations in a
try-catch: inside execute (which uses createStreamableValue(),
uiStream.append(<GraphSection ...>) and streamResults.done(result)), wrap the
uiStream.append and streamResults.done calls in a try block and in the catch log
the error (e.g., processLogger.error or console.error) and call
streamResults.error or streamResults.done with a safe fallback to ensure the
stream is completed; finally return the original result (or a safe fallback) so
the caller does not receive an unhandled exception.
| export const dataAnalysisSchema = z.object({ | ||
| title: z.string().describe('The title of the chart'), | ||
| description: z.string().optional().describe('A brief description of the chart'), | ||
| chartType: z.enum(['bar', 'line', 'pie', 'area', 'scatter']).describe('The type of chart to render'), | ||
| data: z.array(z.record(z.any())).describe('The data points for the chart'), | ||
| config: z.object({ | ||
| xAxisKey: z.string().describe('The key in the data object to use for the X axis'), | ||
| yAxisKey: z.string().optional().describe('The key in the data object to use for the Y axis (for scatter charts)'), | ||
| series: z.array(z.object({ | ||
| key: z.string().describe('The key in the data object for this series'), | ||
| name: z.string().describe('The display name for this series'), | ||
| color: z.string().optional().describe('Optional hex color for this series') | ||
| })).describe('The series to be plotted') | ||
| }).describe('Configuration for the chart layout'), | ||
| geospatial: z.array(z.object({ | ||
| latitude: z.number(), | ||
| longitude: z.number(), | ||
| label: z.string().optional() | ||
| })).optional().describe('Optional geospatial data points to be displayed on a map') | ||
| }) |
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Enforce series and yAxisKey constraints to prevent runtime errors.
GraphSection accesses config.series[0].key for pie charts (line 110) and config.yAxisKey for scatter charts (line 130) without guards. The current schema allows empty series and missing y-axis keys, which will cause crashes or render blank charts. Add a minimum series length constraint and conditional requirements for scatter and pie chart types.
🛡️ Suggested schema hardening
-export const dataAnalysisSchema = z.object({
+export const dataAnalysisSchema = z
+ .object({
title: z.string().describe('The title of the chart'),
description: z.string().optional().describe('A brief description of the chart'),
chartType: z.enum(['bar', 'line', 'pie', 'area', 'scatter']).describe('The type of chart to render'),
data: z.array(z.record(z.any())).describe('The data points for the chart'),
config: z.object({
xAxisKey: z.string().describe('The key in the data object to use for the X axis'),
yAxisKey: z.string().optional().describe('The key in the data object to use for the Y axis (for scatter charts)'),
series: z.array(z.object({
key: z.string().describe('The key in the data object for this series'),
name: z.string().describe('The display name for this series'),
color: z.string().optional().describe('Optional hex color for this series')
- })).describe('The series to be plotted')
+ })).min(1, 'At least one series is required').describe('The series to be plotted')
}).describe('Configuration for the chart layout'),
geospatial: z.array(z.object({
latitude: z.number(),
longitude: z.number(),
label: z.string().optional()
})).optional().describe('Optional geospatial data points to be displayed on a map')
-})
+ })
+ .superRefine((val, ctx) => {
+ if (val.chartType === 'scatter' && !val.config.yAxisKey) {
+ ctx.addIssue({
+ code: z.ZodIssueCode.custom,
+ path: ['config', 'yAxisKey'],
+ message: 'yAxisKey is required for scatter charts'
+ })
+ }
+ if (val.chartType === 'pie' && val.config.series.length !== 1) {
+ ctx.addIssue({
+ code: z.ZodIssueCode.custom,
+ path: ['config', 'series'],
+ message: 'Pie charts must define exactly one series'
+ })
+ }
+ })📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| export const dataAnalysisSchema = z.object({ | |
| title: z.string().describe('The title of the chart'), | |
| description: z.string().optional().describe('A brief description of the chart'), | |
| chartType: z.enum(['bar', 'line', 'pie', 'area', 'scatter']).describe('The type of chart to render'), | |
| data: z.array(z.record(z.any())).describe('The data points for the chart'), | |
| config: z.object({ | |
| xAxisKey: z.string().describe('The key in the data object to use for the X axis'), | |
| yAxisKey: z.string().optional().describe('The key in the data object to use for the Y axis (for scatter charts)'), | |
| series: z.array(z.object({ | |
| key: z.string().describe('The key in the data object for this series'), | |
| name: z.string().describe('The display name for this series'), | |
| color: z.string().optional().describe('Optional hex color for this series') | |
| })).describe('The series to be plotted') | |
| }).describe('Configuration for the chart layout'), | |
| geospatial: z.array(z.object({ | |
| latitude: z.number(), | |
| longitude: z.number(), | |
| label: z.string().optional() | |
| })).optional().describe('Optional geospatial data points to be displayed on a map') | |
| }) | |
| export const dataAnalysisSchema = z | |
| .object({ | |
| title: z.string().describe('The title of the chart'), | |
| description: z.string().optional().describe('A brief description of the chart'), | |
| chartType: z.enum(['bar', 'line', 'pie', 'area', 'scatter']).describe('The type of chart to render'), | |
| data: z.array(z.record(z.any())).describe('The data points for the chart'), | |
| config: z.object({ | |
| xAxisKey: z.string().describe('The key in the data object to use for the X axis'), | |
| yAxisKey: z.string().optional().describe('The key in the data object to use for the Y axis (for scatter charts)'), | |
| series: z.array(z.object({ | |
| key: z.string().describe('The key in the data object for this series'), | |
| name: z.string().describe('The display name for this series'), | |
| color: z.string().optional().describe('Optional hex color for this series') | |
| })).min(1, 'At least one series is required').describe('The series to be plotted') | |
| }).describe('Configuration for the chart layout'), | |
| geospatial: z.array(z.object({ | |
| latitude: z.number(), | |
| longitude: z.number(), | |
| label: z.string().optional() | |
| })).optional().describe('Optional geospatial data points to be displayed on a map') | |
| }) | |
| .superRefine((val, ctx) => { | |
| if (val.chartType === 'scatter' && !val.config.yAxisKey) { | |
| ctx.addIssue({ | |
| code: z.ZodIssueCode.custom, | |
| path: ['config', 'yAxisKey'], | |
| message: 'yAxisKey is required for scatter charts' | |
| }) | |
| } | |
| if (val.chartType === 'pie' && val.config.series.length !== 1) { | |
| ctx.addIssue({ | |
| code: z.ZodIssueCode.custom, | |
| path: ['config', 'series'], | |
| message: 'Pie charts must define exactly one series' | |
| }) | |
| } | |
| }) |
🤖 Prompt for AI Agents
In `@lib/schema/data-analysis.tsx` around lines 4 - 23, Update dataAnalysisSchema
to enforce non-empty series and conditional yAxisKey rules: ensure config.series
uses z.array(...).min(1) so charts that access config.series[0].key (e.g., pie
handling) cannot be empty, and make chartType a discriminated union or add a
z.refine on dataAnalysisSchema that when chartType === 'scatter' requires
config.yAxisKey to be present/non-empty; reference dataAnalysisSchema,
chartType, config.series, and config.yAxisKey when implementing the min(1) and
conditional requirement so runtime accesses are safe.
| })).optional().describe('Optional geospatial data points to be displayed on a map') | ||
| }) | ||
|
|
||
| export type PartialDataAnalysis = DeepPartial<typeof dataAnalysisSchema> |
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🌐 Web query:
Vercel AI SDK DeepPartial type utility Zod schema inference
💡 Result:
In the Vercel AI SDK, DeepPartial<T> is used to type “partial” objects that arrive during streaming, not to change what Zod infers.
How it relates to Zod inference
- Your full, validated type is still the normal Zod inference:
type MyType = z.infer<typeof mySchema>;
- The AI SDK uses
DeepPartial<MyType>for partial (incomplete) streamed updates. For example, theOutputhelper returns anOutput<OBJECT, DeepPartial<OBJECT>>, where the second type parameter is the partial streaming shape. (ai-sdk.dev)
So if you want to explicitly type streamed partials alongside your Zod-inferred full type:
import type { DeepPartial } from 'ai';
import { z } from 'zod';
const mySchema = z.object({
user: z.object({
name: z.string(),
age: z.number(),
}),
});
type Full = z.infer<typeof mySchema>;
type Partial = DeepPartial<Full>; // what you’ll see mid-streamTools: getting Zod input inference for execute
If your question is specifically about tool input inference: use the AI SDK’s tool() helper, because it’s what connects inputSchema (Zod) to the execute parameter type. (ai-sdk.dev)
Zod schemas in the AI SDK
You can pass Zod directly; internally the SDK converts it (via zodSchema()), and zodSchema() exists if you need options like useReferences. (ai-sdk.dev)
Citations:
- 1: https://ai-sdk.dev/docs/reference/ai-sdk-core/output?utm_source=openai
- 2: https://ai-sdk.dev/docs/reference/ai-sdk-core/tool?utm_source=openai
- 3: https://ai-sdk.dev/docs/reference/ai-sdk-core/zod-schema?utm_source=openai
🌐 Web query:
TypeScript DeepPartial ZodObject type vs inferred data type
💡 Result:
In Zod, a ZodObject is the schema object (a class instance with methods like .parse, .partial, etc.), while z.infer<typeof schema> (or z.output<typeof schema>) is the validated data type produced by that schema.
Why DeepPartial<typeof mySchema> is usually wrong
If you write:
type X = DeepPartial<typeof userSchema>;you’re making the schema instance type partial (its methods/properties), not the shape of the data you want to validate/handle. That’s almost never what you intend.
The “data” deep-partial type
If you want a deep-partial TypeScript type of the parsed data:
type User = z.infer<typeof userSchema>; // output type (parsed result) ([npmjs.com](https://www.npmjs.com/package/zod/v/3.0.0-beta.4?utm_source=openai))
type UserPatch = DeepPartial<User>;If your schema uses transforms, note that z.infer gives the output type; use z.input<typeof schema> if you want the pre-transform input type. (npmjs.com)
The “schema” deep-partial (runtime validation)
If you want a schema that accepts partial data at runtime, create a new schema:
const userPatchSchema = userSchema.deepPartial(); // deep optional at runtime ([npmjs.com](https://www.npmjs.com/package/zod/v/3.14.5?utm_source=openai))
type UserPatch = z.infer<typeof userPatchSchema>;(For shallow optional fields, use .partial().) (npmjs.com)
Citations:
- 1: https://www.npmjs.com/package/zod/v/3.0.0-beta.4?utm_source=openai
- 2: https://www.npmjs.com/package/zod/v/3.0.0-beta.4?utm_source=openai
- 3: https://www.npmjs.com/package/zod/v/3.14.5?utm_source=openai
- 4: https://www.npmjs.com/package/zod/v/3.14.5?utm_source=openai
Use z.infer to properly type the inferred data shape, not the schema instance.
DeepPartial<typeof dataAnalysisSchema> incorrectly makes the ZodObject schema type partial rather than the data shape. Per Vercel AI SDK and Zod best practices, DeepPartial should be applied to the inferred data type.
✅ Type-safe alias
+export type DataAnalysisInput = z.infer<typeof dataAnalysisSchema>
-export type PartialDataAnalysis = DeepPartial<typeof dataAnalysisSchema>
+export type PartialDataAnalysis = DeepPartial<DataAnalysisInput>🤖 Prompt for AI Agents
In `@lib/schema/data-analysis.tsx` at line 25, The current type alias
PartialDataAnalysis applies DeepPartial to the schema instance instead of the
inferred data shape; change the alias to apply DeepPartial to the inferred type
by using z.infer on dataAnalysisSchema (e.g., update PartialDataAnalysis to
DeepPartial<z.infer<typeof dataAnalysisSchema>>), referencing the existing
dataAnalysisSchema and PartialDataAnalysis identifiers so the type represents
the actual data structure.
| title: string; | ||
| description?: string; | ||
| chartType: 'bar' | 'line' | 'pie' | 'area' | 'scatter'; | ||
| data: any[]; |
There was a problem hiding this comment.
🧹 Nitpick | 🔵 Trivial
Consider stronger typing for data.
Using any[] loses type safety and allows malformed data to pass through undetected. Consider using Record<string, unknown>[] or a generic type parameter to provide better type checking while maintaining flexibility.
♻️ Proposed improvement
- data: any[];
+ data: Record<string, unknown>[];Alternatively, for maximum flexibility with type safety:
export type DataAnalysisResult<T extends Record<string, unknown> = Record<string, unknown>> = {
// ...
data: T[];
// ...
};📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| data: any[]; | |
| data: Record<string, unknown>[]; |
🤖 Prompt for AI Agents
In `@lib/types/index.ts` at line 32, The type declaration uses data: any[] which
loses type safety; change the DataAnalysisResult type to use a safer type such
as data: Record<string, unknown>[] or make it generic (e.g., export type
DataAnalysisResult<T extends Record<string, unknown> = Record<string, unknown>>
= { ... data: T[]; ... }) and update usages of DataAnalysisResult to pass the
concrete T where appropriate (refer to the DataAnalysisResult type name and the
data property to locate the change).
| geospatial?: { | ||
| latitude: number; | ||
| longitude: number; | ||
| label?: string; | ||
| }[]; |
There was a problem hiding this comment.
🧹 Nitpick | 🔵 Trivial
Naming inconsistency with existing MapData.markers interface.
The geospatial array uses label?: string for the optional text field, but the existing MapData.markers interface in components/map/map-data-context.tsx uses title?: string for the same purpose. This inconsistency may cause confusion or require mapping logic when integrating with the map system.
Consider aligning on a single naming convention to simplify integration.
♻️ Proposed alignment with existing interface
geospatial?: {
latitude: number;
longitude: number;
- label?: string;
+ title?: string;
}[];📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| geospatial?: { | |
| latitude: number; | |
| longitude: number; | |
| label?: string; | |
| }[]; | |
| geospatial?: { | |
| latitude: number; | |
| longitude: number; | |
| title?: string; | |
| }[]; |
🤖 Prompt for AI Agents
In `@lib/types/index.ts` around lines 42 - 46, Rename the optional text field in
the geospatial array to match the MapData.markers interface: change geospatial's
label?: string to title?: string so it aligns with MapData.markers (referencing
geospatial and MapData.markers, and the label?/title? property names) and update
any usages or types that reference geospatial to use title instead of label.
…358342468692938721
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Actionable comments posted: 2
Caution
Some comments are outside the diff and can’t be posted inline due to platform limitations.
⚠️ Outside diff range comments (1)
app/actions.tsx (1)
319-331: 🧹 Nitpick | 🔵 TrivialConsider adding file size validation for text-based uploads to prevent excessive token usage.
While Next.js enforces a 200MB
bodySizeLimitfor server actions (configured innext.config.mjs), text files (CSV, JSON, plain text) should have more restrictive limits. Large files can exceed LLM token limits, causing failures or unexpected behavior. Consider adding a size check before processing:🛡️ Proposed validation
+ const MAX_TEXT_FILE_SIZE = 1024 * 1024; // 1MB limit for text files } else if ( file.type === 'text/plain' || file.type === 'text/csv' || file.type === 'application/json' ) { + if (buffer.byteLength > MAX_TEXT_FILE_SIZE) { + throw new Error(`File too large. Maximum size is ${MAX_TEXT_FILE_SIZE / 1024}KB.`); + } const textContent = Buffer.from(buffer).toString('utf-8')
🤖 Fix all issues with AI agents
In `@app/actions.tsx`:
- Around line 772-787: The code passes potentially undefined
latitude/longitude/label from toolOutput.geospatial[0] into MapQueryHandler; add
defensive checks before constructing the MAP_QUERY_TRIGGER payload: verify
toolOutput.geospatial exists and is a non-empty array, and validate that
toolOutput.geospatial[0] has numeric latitude and longitude and a non-empty
label (or provide safe defaults or skip rendering). Update the conditional
around MapQueryHandler (referencing toolOutput.geospatial and MapQueryHandler)
to only render when these validated properties are present, or transform the
values to safe fallbacks before passing them into the mcp_response.location
fields.
- Around line 766-791: The dataAnalysis branch reads toolOutput and accesses
nested fields without runtime validation; use the existing dataAnalysisSchema
(from lib/schema/data-analysis) to validate/parse toolOutput (e.g.,
dataAnalysisSchema.parse or safeParse) into a typed DataAnalysisResult before
rendering, then conditionally render MapQueryHandler only when the parsed result
has a non-empty geospatial array and use
parsed.geospatial[0].latitude/longitude/label for the mcp_response;
alternatively add explicit type guards for toolOutput.geospatial and its
elements to avoid direct indexing of potentially invalid data.
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| case 'dataAnalysis': | ||
| return { | ||
| id, | ||
| component: ( | ||
| <> | ||
| <GraphSection result={searchResults.value} /> | ||
| {toolOutput.geospatial && toolOutput.geospatial.length > 0 && ( | ||
| <MapQueryHandler | ||
| toolOutput={{ | ||
| type: 'MAP_QUERY_TRIGGER', | ||
| originalUserInput: JSON.stringify(toolOutput.geospatial[0]), | ||
| timestamp: new Date().toISOString(), | ||
| mcp_response: { | ||
| location: { | ||
| latitude: toolOutput.geospatial[0].latitude, | ||
| longitude: toolOutput.geospatial[0].longitude, | ||
| place_name: toolOutput.geospatial[0].label | ||
| } | ||
| } | ||
| }} | ||
| /> | ||
| )} | ||
| </> | ||
| ), | ||
| isCollapsed: isCollapsed.value | ||
| } |
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🧹 Nitpick | 🔵 Trivial
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Add runtime type validation for toolOutput in the dataAnalysis case.
The toolOutput is parsed from JSON without schema validation. While a DataAnalysisResult type and dataAnalysisSchema already exist (in lib/types and lib/schema/data-analysis.tsx), they are only used in the tool definition. Here, the code accesses nested properties like toolOutput.geospatial[0].latitude without confirming the structure at runtime. Consider reusing dataAnalysisSchema with parse() to validate before access, or add explicit type guards for the geospatial property structure.
🤖 Prompt for AI Agents
In `@app/actions.tsx` around lines 766 - 791, The dataAnalysis branch reads
toolOutput and accesses nested fields without runtime validation; use the
existing dataAnalysisSchema (from lib/schema/data-analysis) to validate/parse
toolOutput (e.g., dataAnalysisSchema.parse or safeParse) into a typed
DataAnalysisResult before rendering, then conditionally render MapQueryHandler
only when the parsed result has a non-empty geospatial array and use
parsed.geospatial[0].latitude/longitude/label for the mcp_response;
alternatively add explicit type guards for toolOutput.geospatial and its
elements to avoid direct indexing of potentially invalid data.
| {toolOutput.geospatial && toolOutput.geospatial.length > 0 && ( | ||
| <MapQueryHandler | ||
| toolOutput={{ | ||
| type: 'MAP_QUERY_TRIGGER', | ||
| originalUserInput: JSON.stringify(toolOutput.geospatial[0]), | ||
| timestamp: new Date().toISOString(), | ||
| mcp_response: { | ||
| location: { | ||
| latitude: toolOutput.geospatial[0].latitude, | ||
| longitude: toolOutput.geospatial[0].longitude, | ||
| place_name: toolOutput.geospatial[0].label | ||
| } | ||
| } | ||
| }} | ||
| /> | ||
| )} |
There was a problem hiding this comment.
Add defensive checks for geospatial item properties.
The code accesses toolOutput.geospatial[0].latitude, .longitude, and .label without validating these properties exist. If the geospatial array contains a malformed item, undefined values will be passed to MapQueryHandler.
🛡️ Proposed defensive check
- {toolOutput.geospatial && toolOutput.geospatial.length > 0 && (
+ {toolOutput.geospatial &&
+ toolOutput.geospatial.length > 0 &&
+ toolOutput.geospatial[0].latitude != null &&
+ toolOutput.geospatial[0].longitude != null && (
<MapQueryHandler
toolOutput={{
type: 'MAP_QUERY_TRIGGER',
originalUserInput: JSON.stringify(toolOutput.geospatial[0]),
timestamp: new Date().toISOString(),
mcp_response: {
location: {
latitude: toolOutput.geospatial[0].latitude,
longitude: toolOutput.geospatial[0].longitude,
- place_name: toolOutput.geospatial[0].label
+ place_name: toolOutput.geospatial[0].label ?? ''
}
}
}}
/>
)}📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| {toolOutput.geospatial && toolOutput.geospatial.length > 0 && ( | |
| <MapQueryHandler | |
| toolOutput={{ | |
| type: 'MAP_QUERY_TRIGGER', | |
| originalUserInput: JSON.stringify(toolOutput.geospatial[0]), | |
| timestamp: new Date().toISOString(), | |
| mcp_response: { | |
| location: { | |
| latitude: toolOutput.geospatial[0].latitude, | |
| longitude: toolOutput.geospatial[0].longitude, | |
| place_name: toolOutput.geospatial[0].label | |
| } | |
| } | |
| }} | |
| /> | |
| )} | |
| {toolOutput.geospatial && | |
| toolOutput.geospatial.length > 0 && | |
| toolOutput.geospatial[0].latitude != null && | |
| toolOutput.geospatial[0].longitude != null && ( | |
| <MapQueryHandler | |
| toolOutput={{ | |
| type: 'MAP_QUERY_TRIGGER', | |
| originalUserInput: JSON.stringify(toolOutput.geospatial[0]), | |
| timestamp: new Date().toISOString(), | |
| mcp_response: { | |
| location: { | |
| latitude: toolOutput.geospatial[0].latitude, | |
| longitude: toolOutput.geospatial[0].longitude, | |
| place_name: toolOutput.geospatial[0].label ?? '' | |
| } | |
| } | |
| }} | |
| /> | |
| )} |
🤖 Prompt for AI Agents
In `@app/actions.tsx` around lines 772 - 787, The code passes potentially
undefined latitude/longitude/label from toolOutput.geospatial[0] into
MapQueryHandler; add defensive checks before constructing the MAP_QUERY_TRIGGER
payload: verify toolOutput.geospatial exists and is a non-empty array, and
validate that toolOutput.geospatial[0] has numeric latitude and longitude and a
non-empty label (or provide safe defaults or skip rendering). Update the
conditional around MapQueryHandler (referencing toolOutput.geospatial and
MapQueryHandler) to only render when these validated properties are present, or
transform the values to safe fallbacks before passing them into the
mcp_response.location fields.
|
@coderabbitai can you make the recharts graph generative UI graph from queries, what queries would be able to trigger that? |
|
Tip For best results, initiate chat on the files or code changes. 🧩 Analysis chain🏁 Script executed: Length of output: 6477 🏁 Script executed: Length of output: 1290 🏁 Script executed: Length of output: 891
Trigger ConditionsAccording to the researcher agent's decision flow (Step 2):
Example Queries That Would Trigger Graph GenerationExplicit visualization requests:
Implicit visualization requests:
Supported Chart TypesThe tool can generate:
File Upload SupportThe chat panel now accepts Geospatial IntegrationIf your data includes location information (latitude/longitude), the tool can also trigger map visualization alongside the chart. Pro tip: The more specific you are about the chart type and what you want to visualize, the better the results will be! |
Hi! I've implemented the
I've also updated the system prompt with these explicit examples to ensure the AI consistently chooses the tool when appropriate. The tool works with both live-searched data and user-uploaded files (CSV/JSON). |
- Added explicit examples for dataAnalysis tool in researcher system prompt - Clarified triggering queries in PR response - Verified consistent behavior across search and file-based data sources Co-authored-by: ngoiyaeric <115367894+ngoiyaeric@users.noreply.github.com>
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Actionable comments posted: 2
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⚠️ Outside diff range comments (2)
lib/agents/resolution-search.tsx (1)
26-36:⚠️ Potential issue | 🟠 MajorGuard invalid timezone inputs to prevent runtime errors.
toLocaleStringthrows aRangeErroron invalid IANA timezones. Sincetimezonecomes from user input, this can crash resolution search. Add a safe fallback.🛠️ Suggested fix
export async function resolutionSearch(messages: CoreMessage[], timezone: string = 'UTC') { - const localTime = new Date().toLocaleString('en-US', { - timeZone: timezone, - hour: '2-digit', - minute: '2-digit', - hour12: true, - weekday: 'long', - year: 'numeric', - month: 'long', - day: 'numeric' - }); + const dateTimeOptions: Intl.DateTimeFormatOptions = { + timeZone: timezone, + hour: '2-digit', + minute: '2-digit', + hour12: true, + weekday: 'long', + year: 'numeric', + month: 'long', + day: 'numeric' + } + let localTime: string + try { + localTime = new Date().toLocaleString('en-US', dateTimeOptions) + } catch { + localTime = new Date().toLocaleString('en-US', { + ...dateTimeOptions, + timeZone: 'UTC' + }) + }app/actions.tsx (1)
301-313:⚠️ Potential issue | 🟠 MajorAdd a size guard for text file uploads—upstream limit insufficient for text token budgets.
A 10MB file size check exists in chat-panel.tsx, but this applies uniformly to all file types. For text files (plain, CSV, JSON), 10MB translates to approximately 2.5–3 million tokens, which exceeds most LLM token limits. Add a smaller size cap in app/actions.tsx specifically for text files to prevent token budget overruns:
} else if ( file.type === 'text/plain' || file.type === 'text/csv' || file.type === 'application/json' ) { + const MAX_TEXT_UPLOAD_BYTES = 200_000 // adjust based on model token limits + if (buffer.byteLength > MAX_TEXT_UPLOAD_BYTES) { + throw new Error('Text uploads are too large to analyze safely.') + } const textContent = Buffer.from(buffer).toString('utf-8')
🤖 Fix all issues with AI agents
In `@lib/agents/researcher.tsx`:
- Around line 45-56: Update the "3. Data Analysis and Visualization" section to
clarify boundaries between the dataAnalysis tool and geospatialQueryTool: add a
concrete example showing geospatial visualization (e.g., "Plot sales by region
on a map with map points and a side-by-side bar chart") under the dataAnalysis
examples, and add a short guidance sentence distinguishing uses (dataAnalysis =
charts/visualizations that may include plotted geospatial points for context;
geospatialQueryTool = navigation, distance calculations, routing, and place
search). Reference the tool names dataAnalysis and geospatialQueryTool and
ensure the new example and guidance are adjacent to the existing bullet list so
the LLM can unambiguously choose between them.
In `@lib/agents/resolution-search.tsx`:
- Around line 1-2: The getModel default currently returns
grok-4-fast-non-reasoning which does not support JSON Schema structured outputs,
causing generateObject(resolutionSearchSchema) to fail; update getModel (and its
callers) so structured-output calls use a compatible model (e.g., prioritize
OpenAI gpt-4o) by either: 1) adding a boolean/enum parameter like
forceStructuredOutput to getModel and using that to return gpt-4o when true, or
2) detecting when generateObject will be used and selecting gpt-4o; also fix the
ignored requireVision parameter (passed as getModel(hasImage)) so it is honored
in getModel's logic. Ensure references: getModel, generateObject,
resolutionSearchSchema, and the requireVision/hasImage parameter are updated
accordingly.
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- components/header-search-button.tsx
🧰 Additional context used
🧠 Learnings (3)
📚 Learning: 2026-01-16T10:02:40.220Z
Learnt from: ngoiyaeric
Repo: QueueLab/QCX PR: 0
File: :0-0
Timestamp: 2026-01-16T10:02:40.220Z
Learning: The router agent and resolution search agent must implement a feedback loop where tool execution results (including GeoTIFF URLs, embeddings, and satellite analysis data) are fed back to the AI model's context through enriched messages before generating the final response, ensuring the foundational model receives and can synthesize all satellite intelligence data.
Applied to files:
app/actions.tsx
📚 Learning: 2026-01-13T13:26:30.086Z
Learnt from: ngoiyaeric
Repo: QueueLab/QCX PR: 0
File: :0-0
Timestamp: 2026-01-13T13:26:30.086Z
Learning: Workers that rely on ai.generateObject (geojsonParser, map-command-generator, feedback-analyzer) must not use the X.AI 'grok-4-fast-non-reasoning' model because X.AI’s chat/completions rejects JSON Schema structured-output arguments; prefer OpenAI gpt-4o for structured outputs.
Applied to files:
lib/agents/resolution-search.tsx
📚 Learning: 2026-01-17T06:14:51.070Z
Learnt from: ngoiyaeric
Repo: QueueLab/QCX PR: 0
File: :0-0
Timestamp: 2026-01-17T06:14:51.070Z
Learning: For structured output tasks using ai.generateObject (resolution-search, geojsonParser, map-command-generator, feedback-analyzer), prefer OpenAI gpt-4o. While xAI's grok-4-1-fast-reasoning technically supports structured outputs and vision, OpenAI has proven more reliable integration with the AI SDK's generateObject function and Zod schemas in production.
Applied to files:
lib/agents/resolution-search.tsx
🔇 Additional comments (3)
lib/agents/researcher.tsx (1)
76-81: LGTM - Decision flow is clear and well-structured.The updated decision flow correctly prioritizes tool selection. The ordering (retrieve → dataAnalysis → geospatialQueryTool → search → knowledge) is logical and should help the LLM make appropriate tool choices.
app/actions.tsx (2)
15-30: Imports for new graphing flow look consistent.No issues with the new agent/graph component wiring.
91-93: Direct resolutionSearch result handling looks good.The simplified call/response flow is clear and consistent.
✏️ Tip: You can disable this entire section by setting review_details to false in your review settings.
| #### **3. Data Analysis and Visualization** | ||
| - **Tool**: \`dataAnalysis\` | ||
| - **When to use**: | ||
| Any query asking for a chart, graph, or visual representation of data. Use it when you have structured data (e.g., from web search or uploaded CSV/JSON files) that would be clearer in a visual format. | ||
| - **Capabilities**: Can generate bar, line, pie, area, and scatter charts. It can also include geospatial points if the data has location information. | ||
|
|
||
| **Examples that trigger \`dataAnalysis\`:** | ||
| - "Create a bar chart showing the population of the top 5 largest cities" | ||
| - "Plot a line graph of NVIDIA's stock price over the last 6 months" | ||
| - "Show me a pie chart of my expenses from this uploaded CSV" | ||
| - "Visualize the relationship between height and weight from this data as a scatter plot" | ||
|
|
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🧹 Nitpick | 🔵 Trivial
Clarify the boundary between dataAnalysis with geospatial data and geospatialQueryTool.
Line 49 states dataAnalysis "can also include geospatial points if the data has location information," but the examples don't demonstrate this capability. This may cause the LLM confusion when a query involves both visualization and location data.
Consider adding:
- An example that shows dataAnalysis with geospatial output (e.g., "Plot sales by region on a map with a bar chart comparison").
- Guidance on when to use dataAnalysis (for charts with optional map points) vs geospatialQueryTool (for navigation, distances, directions, place search).
📝 Suggested documentation improvement
**Examples that trigger \`dataAnalysis\`:**
- "Create a bar chart showing the population of the top 5 largest cities"
- "Plot a line graph of NVIDIA's stock price over the last 6 months"
- "Show me a pie chart of my expenses from this uploaded CSV"
- "Visualize the relationship between height and weight from this data as a scatter plot"
+- "Chart sales by store location and show the stores on a map"
+
+**Note:** When the query is primarily about finding places, navigation, or distances, use \`geospatialQueryTool\`. Use \`dataAnalysis\` when the primary goal is data visualization, even if the data contains coordinates.🤖 Prompt for AI Agents
In `@lib/agents/researcher.tsx` around lines 45 - 56, Update the "3. Data Analysis
and Visualization" section to clarify boundaries between the dataAnalysis tool
and geospatialQueryTool: add a concrete example showing geospatial visualization
(e.g., "Plot sales by region on a map with map points and a side-by-side bar
chart") under the dataAnalysis examples, and add a short guidance sentence
distinguishing uses (dataAnalysis = charts/visualizations that may include
plotted geospatial points for context; geospatialQueryTool = navigation,
distance calculations, routing, and place search). Reference the tool names
dataAnalysis and geospatialQueryTool and ensure the new example and guidance are
adjacent to the existing bullet list so the LLM can unambiguously choose between
them.
lib/agents/resolution-search.tsx
Outdated
| import { CoreMessage, generateObject } from 'ai' | ||
| import { getModel } from '@/lib/utils' |
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Do not use grok-4-fast-non-reasoning with generateObject; it will fail structured output requests.
The current getModel implementation defaults to grok-4-fast-non-reasoning (lib/utils/index.ts lines 40, 84), which does not support JSON Schema structured outputs. Since generateObject with resolutionSearchSchema requires structured output support, this will fail at runtime.
Change getModel to prioritize OpenAI's gpt-4o for calls to generateObject, or add a parameter to force structured-output-compatible models when needed. Note: the requireVision parameter passed to getModel(hasImage) is currently ignored in the implementation.
🤖 Prompt for AI Agents
In `@lib/agents/resolution-search.tsx` around lines 1 - 2, The getModel default
currently returns grok-4-fast-non-reasoning which does not support JSON Schema
structured outputs, causing generateObject(resolutionSearchSchema) to fail;
update getModel (and its callers) so structured-output calls use a compatible
model (e.g., prioritize OpenAI gpt-4o) by either: 1) adding a boolean/enum
parameter like forceStructuredOutput to getModel and using that to return gpt-4o
when true, or 2) detecting when generateObject will be used and selecting
gpt-4o; also fix the ignored requireVision parameter (passed as
getModel(hasImage)) so it is honored in getModel's logic. Ensure references:
getModel, generateObject, resolutionSearchSchema, and the requireVision/hasImage
parameter are updated accordingly.
- Fixed "Invalid value" runtime error by splitting GraphSection into static and streamed components - Improved detection of StreamableValue vs static DataAnalysisResult - Added graceful fallbacks for missing title, chartType, or plotData - Moved error messages out of ResponsiveContainer to fix layout issues - Verified fix with static, stringified, and broken data cases Co-authored-by: ngoiyaeric <115367894+ngoiyaeric@users.noreply.github.com>
|
@coderabbitai the resolution search has stopped working now and can you always match the colors of the charts with the current theme of the site |
|
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Issue 1: Resolution SearchThe code looks correct from a structural standpoint. To diagnose why it stopped working, I need more information: Can you tell me:
The most likely causes could be:
Issue 2: Theme-Aware Chart ColorsI can fix this right away! The charts currently use hardcoded colors, but I'll make them use your theme's CSS variables. Task: Make chart colors match the current site themeChanges needed:
Would you like me to implement these changes? Just let me know about the resolution search error details, and I'll fix both issues for you. ✏️ Learnings added
💡 Use |
I've addressed both issues in this update:
|
- Integrated Recharts for data visualization (Bar, Line, Pie, Area, Scatter). - Added 'dataAnalysis' tool to researcher agent for automated chart generation. - Enabled CSV and JSON file upload support for data analysis. - Fixed resolution search 'no response' regression by using streamObject and updating model mapping to vision-capable versions. - Ensured chart colors and styling are theme-aware using CSS variables. - Updated MapQueryHandler to ingest geospatial data from graph results into the map view. Co-authored-by: ngoiyaeric <115367894+ngoiyaeric@users.noreply.github.com>
User description
This PR introduces generative graphing capabilities to the QCX platform.
Key changes:
rechartsto dependencies to support Bar, Line, Pie, Area, and Scatter charts.dataAnalysisthat generates structured data for charts based on user prompts or uploaded files..csvand.jsonfiles, which are processed and made available to the AI for analysis.researcheragent and tool pipeline to stream chart components to the UI in real-time.MapQueryHandler.GraphSectioncomponent which handles both streaming and static (hydrated) data.PR created automatically by Jules for task 17358342468692938721 started by @ngoiyaeric
PR Type
Enhancement
Description
Added generative graphing capabilities with Recharts integration
Created dataAnalysis tool for structured chart generation from data
Extended file upload support to CSV and JSON formats
Integrated geospatial awareness for location-based analysis results
Added GraphSection component for streaming and static chart rendering
Diagram Walkthrough
File Walkthrough
7 files
Added DataAnalysisResult type definitionExtended file support and added chart UI handlingUpdated file input to accept CSV and JSONNew component for rendering Recharts visualizationsNew tool for data analysis and chart generationRegistered dataAnalysis tool in tool pipelineZod schema for data analysis tool parameters1 files
Added dataAnalysis tool guidelines to agent instructions1 files
Added recharts dependency for chart renderingSummary by CodeRabbit
New Features
Behavior Change
Chores
✏️ Tip: You can customize this high-level summary in your review settings.