fix(chart): improve error handling and color variety
- Add quotaExceeded flag to response for better error UX - Show dedicated quota exceeded state with upgrade button - Improve AI prompt to better detect data patterns - Add chart type-specific colors (blue, indigo, emerald, violet, etc.) - Replace generic primary/10 colors with varied accent colors Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
@@ -1027,6 +1027,38 @@ You MUST use the task_extract tool. Do NOT respond with text, call the tool dire
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},
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}
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function extractJsonFromText(text: string): any {
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if (!text) return null
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// Try direct parsing first
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try {
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const parsed = JSON.parse(text.trim())
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if (parsed && typeof parsed === 'object') return parsed
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} catch (e) {}
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// Try extracting markdown code block
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const jsonBlockRegex = /```json\s*([\s\S]*?)\s*```/i
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const match = text.match(jsonBlockRegex)
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if (match && match[1]) {
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try {
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const parsed = JSON.parse(match[1].trim())
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if (parsed && typeof parsed === 'object') return parsed
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} catch (e) {}
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}
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// Try extracting any { ... } or [ ... ] block
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const braceRegex = /(\{[\s\S]*\}|\[[\s\S]*\])/
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const braceMatch = text.match(braceRegex)
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if (braceMatch && braceMatch[1]) {
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try {
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const parsed = JSON.parse(braceMatch[1].trim())
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if (parsed && typeof parsed === 'object') return parsed
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} catch (e) {}
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}
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return null
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}
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// --- Tool-Use Agent ---
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async function executeToolUseAgent(
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@@ -1354,6 +1386,15 @@ async function executeToolUseAgent(
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const duration = Date.now() - startTime
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// Check if AI already created a note via note_create tool
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// Or if excalidraw/slide generator created a canvas
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let existingNoteId: string | null = null
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let canvasId: string | null = null
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const scrapedUrls: string[] = []
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let specificToolCalled = false
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let fallbackSuccess = false
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let parsedFallbackJson: any = null
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// Détecte si le modèle ne supporte pas le function calling
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// (il retourne le JSON de l'outil comme texte brut au lieu de l'exécuter)
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const totalToolCallsCheck = result.steps.reduce((acc, s) => acc + s.toolCalls.length, 0)
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@@ -1371,16 +1412,96 @@ async function executeToolUseAgent(
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}
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if (agentType === 'slide-generator' || agentType === 'excalidraw-generator') {
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const toolName = agentType === 'slide-generator' ? 'generate_slides' : 'generate_excalidraw'
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await prisma.agentAction.update({
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where: { id: actionId },
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data: {
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status: 'failure',
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log: lang === 'fr'
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? `L'IA n'a pas appelé l'outil ${toolName}. Le modèle a répondu avec du texte au lieu de générer le fichier. Modèle: "${sysConfig.AI_MODEL_CHAT}". Essayez un modèle compatible avec le function calling.`
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: `The AI did not call the ${toolName} tool. The model responded with text instead of generating the file. Model: "${sysConfig.AI_MODEL_CHAT}". Try a model that supports function calling.`,
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parsedFallbackJson = extractJsonFromText(result.text)
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if (parsedFallbackJson) {
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try {
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if (agentType === 'slide-generator') {
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let slides: any[] = []
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let title = agent.name || "Présentation"
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let theme = agent.slideTheme || "architectural-saas"
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if (Array.isArray(parsedFallbackJson)) {
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slides = parsedFallbackJson
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} else if (parsedFallbackJson && typeof parsedFallbackJson === 'object') {
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if (Array.isArray(parsedFallbackJson.slides)) {
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slides = parsedFallbackJson.slides
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} else if (parsedFallbackJson.slides && typeof parsedFallbackJson.slides === 'object') {
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// nested structure support
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} else {
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if (parsedFallbackJson.type) {
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slides = [parsedFallbackJson]
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} else {
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const arrays = Object.values(parsedFallbackJson).filter(val => Array.isArray(val))
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if (arrays.length > 0) {
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slides = arrays[0] as any[]
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}
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}
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}
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if (typeof parsedFallbackJson.title === 'string') title = parsedFallbackJson.title
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if (typeof parsedFallbackJson.theme === 'string') theme = parsedFallbackJson.theme
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}
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const registered = toolRegistry.get('generate_slides')
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if (registered) {
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console.log('[AgentExecutor] Running manual fallback execution for generate_slides')
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const slideTool = registered.buildTool(ctx)
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const executionResult = await slideTool.execute({ title, theme, slides })
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if (executionResult && executionResult.success && executionResult.canvasId) {
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canvasId = executionResult.canvasId
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specificToolCalled = true
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fallbackSuccess = true
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}
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}
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} else {
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let diagramStr = ""
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let title = agent.name || "Diagramme"
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if (parsedFallbackJson && typeof parsedFallbackJson === 'object') {
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if (typeof parsedFallbackJson.diagram === 'string') {
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diagramStr = parsedFallbackJson.diagram
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if (typeof parsedFallbackJson.title === 'string') title = parsedFallbackJson.title
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} else if (parsedFallbackJson.diagram && typeof parsedFallbackJson.diagram === 'object') {
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diagramStr = JSON.stringify(parsedFallbackJson.diagram)
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if (typeof parsedFallbackJson.title === 'string') title = parsedFallbackJson.title
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} else {
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diagramStr = JSON.stringify(parsedFallbackJson)
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if (typeof parsedFallbackJson.title === 'string') title = parsedFallbackJson.title
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}
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} else if (typeof parsedFallbackJson === 'string') {
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diagramStr = parsedFallbackJson
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}
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if (diagramStr) {
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const registered = toolRegistry.get('generate_excalidraw')
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if (registered) {
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console.log('[AgentExecutor] Running manual fallback execution for generate_excalidraw')
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const excalidrawTool = registered.buildTool(ctx)
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const executionResult = await excalidrawTool.execute({ title, diagram: diagramStr })
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if (executionResult && executionResult.success && executionResult.canvasId) {
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canvasId = executionResult.canvasId
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specificToolCalled = true
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fallbackSuccess = true
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}
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}
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}
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}
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} catch (err) {
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console.error('[AgentExecutor] Fallback execution failed:', err)
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}
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})
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return { success: false, actionId, error: `AI did not call ${toolName} tool` }
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}
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if (!fallbackSuccess) {
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await prisma.agentAction.update({
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where: { id: actionId },
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data: {
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status: 'failure',
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log: lang === 'fr'
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? `L'IA n'a pas appelé l'outil ${toolName}. Le modèle a répondu avec du texte au lieu de générer le fichier. Modèle: "${sysConfig.AI_MODEL_CHAT}". Essayez un modèle compatible avec le function calling.`
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: `The AI did not call the ${toolName} tool. The model responded with text instead of generating the file. Model: "${sysConfig.AI_MODEL_CHAT}". Try a model that supports function calling.`,
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}
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})
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return { success: false, actionId, error: `AI did not call ${toolName} tool` }
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}
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}
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}
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@@ -1395,12 +1516,27 @@ async function executeToolUseAgent(
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})),
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}))
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// Check if AI already created a note via note_create tool
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// Or if excalidraw/slide generator created a canvas
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let existingNoteId: string | null = null
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let canvasId: string | null = null
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const scrapedUrls: string[] = []
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let specificToolCalled = false
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if (fallbackSuccess) {
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toolLog.push({
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step: toolLog.length + 1,
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text: "Manual JSON parsing & fallback execution succeeded.",
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toolCalls: [{
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id: "fallback",
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type: "function",
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function: {
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name: agentType === 'slide-generator' ? 'generate_slides' : 'generate_excalidraw',
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arguments: JSON.stringify(parsedFallbackJson),
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}
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}] as any,
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toolResults: [{
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toolCallId: "fallback",
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toolName: agentType === 'slide-generator' ? 'generate_slides' : 'generate_excalidraw',
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type: "tool-result",
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result: { success: true, canvasId }
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}] as any
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})
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}
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const requiredTool = isFileGenerator
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? (agentType === 'slide-generator' ? ['generate_slides'] : ['generate_excalidraw'])
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: null
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@@ -17,6 +17,7 @@ export interface SuggestChartsResponse {
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detectedData: string
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hasData: boolean
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error?: string
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quotaExceeded?: boolean
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}
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export interface SuggestChartsRequest {
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@@ -42,12 +43,16 @@ export async function suggestCharts(request: SuggestChartsRequest): Promise<Sugg
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if (!response.ok) {
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const errorData = await response.json().catch(() => ({ error: 'Unknown error' }))
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const isQuotaError = response.status === 402 || errorData.error === 'QUOTA_EXCEEDED'
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return {
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suggestions: [],
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analyzedText: '',
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detectedData: '',
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hasData: false,
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error: errorData.error || `HTTP ${response.status}`,
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error: isQuotaError
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? 'AI quota exceeded. Please upgrade your plan to continue using AI features.'
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: (errorData.error || `HTTP ${response.status}`),
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quotaExceeded: isQuotaError,
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}
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}
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