File size: 4,116 Bytes
6dc0fd7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 | import { createStudioRender } from '../../../domain/factories'
import type { StudioToolDefinition, StudioToolResult } from '../../../domain/types'
import type { StudioRuntimeBackedToolContext } from '../../../runtime/tools/tool-runtime-context'
import { throwIfStudioRunCancelled } from '../../../runtime/execution/run-cancellation'
import type { StudioRenderDriver } from '../../../render/studio-render-driver'
import { plotRenderToolParameters } from '../../../tools/tool-parameters'
import { publishStudioRenderUpdated } from '../../../render/render-events'
import {
executeStudioRenderLifecycle,
studioRenderFailureMessage,
studioRenderFailureStatus
} from '../../../render/render-lifecycle'
interface PlotRenderToolInput {
concept: string
code: string
}
export function createPlotStudioRenderTool(
driver: StudioRenderDriver
): StudioToolDefinition<PlotRenderToolInput> {
return {
name: 'render',
parameters: plotRenderToolParameters,
description: 'Execute the matplotlib source and persist the plot images.',
allowedAgents: ['builder'],
allowedStudioKinds: ['matplotlib'],
execute: async (input, context) =>
executePlotRenderTool(input, context as StudioRuntimeBackedToolContext, driver)
}
}
async function executePlotRenderTool(
input: PlotRenderToolInput,
context: StudioRuntimeBackedToolContext,
driver: StudioRenderDriver
): Promise<StudioToolResult> {
if (!input.concept?.trim() || !input.code?.trim()) {
throw new Error('Render tool requires non-empty "concept" and "code"')
}
const title = `Plot render: ${input.concept.slice(0, 80)}`
return executeStudioRenderLifecycle({
context,
createRender: () => {
const render = createStudioRender({
ownerId: context.session.ownerId,
sessionId: context.session.id,
runId: context.run.id,
// The Run is the authoritative scope source; a Legacy Run leaves the key absent.
sceneId: context.run.sceneId,
kind: 'matplotlib',
title,
concept: input.concept,
outputMode: 'image',
quality: 'medium',
status: 'running',
metadata: {
studioKind: 'matplotlib',
outputMode: 'image'
},
})
render.metadata = { ...(render.metadata ?? {}), renderId: render.id }
return render
},
execute: async (render, renderStore) => {
context.setToolMetadata?.({
title,
metadata: {
renderId: render.id,
studioKind: 'matplotlib'
}
})
const result = await driver.execute({
render,
workspaceDirectory: context.session.directory,
code: input.code,
signal: context.abortSignal,
})
throwIfStudioRunCancelled(context.abortSignal)
const attachments = result.attachments ?? []
const completed = await renderStore.update(context.session.ownerId, render.id, {
status: 'completed',
attachments,
metadata: {
...(render.metadata ?? {}),
...(result.metadata ?? {}),
},
})
if (!completed) {
throw new Error('Render record disappeared before completion')
}
publishStudioRenderUpdated(context.eventBus, completed)
return {
title,
output: `version: ${render.metadata?.label}\noutput_directory: ${render.metadata?.workspaceOutputDirectory}\nplot_render_id: ${render.id}`,
attachments,
metadata: {
renderId: render.id,
phase: 'render',
diagnosticCount: 0,
imageCount: result.metadata?.imageCount,
scriptPath: completed.metadata?.scriptPath,
imagePaths: completed.metadata?.imagePaths,
},
}
},
markFailed: async (render, renderStore, error) => {
const failedRender = await renderStore.update(context.session.ownerId, render.id, {
status: studioRenderFailureStatus(error),
error: studioRenderFailureMessage(error),
})
if (failedRender) {
publishStudioRenderUpdated(context.eventBus, failedRender)
}
}
})
}
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