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重构主控编排与运行时预热链路，统一工作区提示词/专家调度协议并补齐 wiki 记忆注入与写回闭环。
同时收敛启动与运维脚本默认行为（含 wiki worker）、更新 Admin 可观测性与相关测试，降低首轮时延并提高运行稳定性。 Made-with: Cursor
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openclaw/qa/scenarios/media/image-generation-roundtrip.md
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openclaw/qa/scenarios/media/image-generation-roundtrip.md
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# Image generation roundtrip
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```yaml qa-scenario
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id: image-generation-roundtrip
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title: Image generation roundtrip
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surface: image-generation
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coverage:
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primary:
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- media.image-generation
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secondary:
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- channels.qa-channel
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objective: Verify a generated image is saved as media, reattached on the next turn, and described correctly through the vision path.
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successCriteria:
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- image_generate produces a saved MEDIA artifact.
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- The generated artifact is reattached on a follow-up turn.
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- The follow-up vision answer describes the generated scene rather than a generic attachment placeholder.
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docsRefs:
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- docs/tools/image-generation.md
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- docs/help/testing.md
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codeRefs:
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- src/agents/tools/image-generate-tool.ts
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- src/gateway/chat-attachments.ts
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- extensions/qa-lab/src/mock-openai-server.ts
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execution:
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kind: flow
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summary: Verify a generated image is saved as media, reattached on the next turn, and described correctly through the vision path.
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config:
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generatePrompt: "Image generation check: generate a QA lighthouse image and summarize it in one short sentence."
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generatePromptSnippet: "Image generation check"
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inspectPrompt: "Roundtrip image inspection check: describe the generated lighthouse attachment in one short sentence."
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expectedNeedle: "lighthouse"
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```
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```yaml qa-flow
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steps:
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- name: reattaches the generated media artifact on the follow-up turn
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actions:
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- call: ensureImageGenerationConfigured
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args:
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- ref: env
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- call: createSession
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args:
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- ref: env
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- Image roundtrip
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- agent:qa:image-roundtrip
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- call: reset
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- set: generatedStartedAtMs
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value:
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expr: Date.now()
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- call: runAgentPrompt
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args:
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- ref: env
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- sessionKey: agent:qa:image-roundtrip
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message:
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expr: config.generatePrompt
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timeoutMs:
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expr: liveTurnTimeoutMs(env, 45000)
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- call: resolveGeneratedImagePath
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saveAs: mediaPath
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args:
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- env:
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ref: env
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promptSnippet:
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expr: config.generatePromptSnippet
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startedAtMs:
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ref: generatedStartedAtMs
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timeoutMs:
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expr: liveTurnTimeoutMs(env, 45000)
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- call: fs.readFile
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saveAs: imageBuffer
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args:
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- ref: mediaPath
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- call: runAgentPrompt
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args:
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- ref: env
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- sessionKey: agent:qa:image-roundtrip
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message:
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expr: config.inspectPrompt
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attachments:
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- mimeType: image/png
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fileName:
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expr: path.basename(mediaPath)
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content:
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expr: imageBuffer.toString('base64')
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timeoutMs:
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expr: liveTurnTimeoutMs(env, 45000)
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- call: waitForCondition
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saveAs: outbound
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args:
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- lambda:
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expr: "state.getSnapshot().messages.filter((candidate) => candidate.direction === 'outbound' && candidate.conversation.id === 'qa-operator' && normalizeLowercaseStringOrEmpty(candidate.text).includes(normalizeLowercaseStringOrEmpty(config.expectedNeedle))).at(-1)"
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- expr: liveTurnTimeoutMs(env, 45000)
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- assert:
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expr: "!env.mock || Boolean((await fetchJson(`${env.mock.baseUrl}/debug/requests`)).find((request) => request.plannedToolName === 'image_generate' && String(request.prompt ?? '').includes(config.generatePromptSnippet)))"
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message: expected image_generate call before roundtrip inspection
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- assert:
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expr: "!env.mock || (((await fetchJson(`${env.mock.baseUrl}/debug/requests`)).find((request) => String(request.prompt ?? '').includes(config.inspectPrompt))?.imageInputCount ?? 0) >= 1)"
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message: expected generated artifact to be reattached on follow-up turn
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detailsExpr: "`MEDIA:${mediaPath}\\n${outbound.text}`"
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```
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# Image understanding from attachment
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```yaml qa-scenario
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id: image-understanding-attachment
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title: Image understanding from attachment
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surface: image-understanding
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coverage:
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primary:
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- media.image-understanding
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secondary:
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- channels.qa-channel
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objective: Verify an attached image reaches the agent model and the agent can describe what it sees.
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successCriteria:
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- Agent receives at least one image attachment.
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- Final answer describes the visible image content in one short sentence.
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- The description mentions the expected red and blue regions.
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docsRefs:
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- docs/help/testing.md
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- docs/tools/index.md
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codeRefs:
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- src/gateway/server-methods/agent.ts
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- extensions/qa-lab/src/suite.ts
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- extensions/qa-lab/src/mock-openai-server.ts
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execution:
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kind: flow
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summary: Verify an attached image reaches the agent model and the agent can describe what it sees.
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config:
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prompt: "Image understanding check: describe the top and bottom colors in the attached image in one short sentence."
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requiredColorGroups:
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- [red, scarlet, crimson]
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- [blue, azure, teal, cyan, aqua]
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```
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```yaml qa-flow
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steps:
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- name: describes an attached image in one short sentence
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actions:
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- call: reset
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- set: outboundStartIndex
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value:
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expr: "state.getSnapshot().messages.filter((message) => message.direction === 'outbound').length"
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- call: runAgentPrompt
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args:
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- ref: env
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- sessionKey: agent:qa:image-understanding
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message:
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expr: config.prompt
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attachments:
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- mimeType: image/png
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fileName: red-top-blue-bottom.png
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content:
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expr: imageUnderstandingValidPngBase64
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timeoutMs:
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expr: liveTurnTimeoutMs(env, 45000)
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- call: waitForOutboundMessage
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saveAs: outbound
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args:
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- ref: state
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- lambda:
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params: [candidate]
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expr: "candidate.conversation.id === 'qa-operator' && config.requiredColorGroups.every((group) => group.some((color) => normalizeLowercaseStringOrEmpty(candidate.text).includes(color)))"
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- expr: liveTurnTimeoutMs(env, 45000)
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- sinceIndex:
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ref: outboundStartIndex
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- set: missingColorGroup
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value:
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expr: "config.requiredColorGroups.find((group) => !group.some((candidate) => normalizeLowercaseStringOrEmpty(outbound.text).includes(candidate)))"
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- assert:
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expr: "!missingColorGroup"
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message:
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expr: "`missing expected colors in image description: ${outbound.text}`"
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# Image-processing assertion: verify the mock actually received an
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# image on the scenario-unique prompt. This is as strong as a
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# tool-call assertion for this scenario — unlike the
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# `source-docs-discovery-report` / `subagent-handoff` /
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# `config-restart-capability-flip` scenarios that rely on a real
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# tool call to satisfy the parity criterion, image understanding
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# is handled inside the provider's vision capability and does NOT
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# emit a tool call the mock can record as `plannedToolName`. The
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# `imageInputCount` field IS the tool-call evidence for vision
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# scenarios: it proves the attachment reached the provider, which
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# is the only thing an external harness can verify in mock mode.
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# Match on the scenario-unique prompt substring so the assertion
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# can't be accidentally satisfied by some other scenario's image
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# request that happens to share a debug log with this one.
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- set: imageRequest
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value:
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expr: "env.mock ? [...(await fetchJson(`${env.mock.baseUrl}/debug/requests`))].find((request) => String(request.prompt ?? '').includes('Image understanding check')) : null"
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- assert:
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expr: "!env.mock || (imageRequest && (imageRequest.imageInputCount ?? 0) >= 1)"
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message:
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expr: "`expected at least one input image on the Image understanding check request, got imageInputCount=${String(imageRequest?.imageInputCount ?? 0)}`"
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detailsExpr: outbound.text
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```
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86
openclaw/qa/scenarios/media/native-image-generation.md
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openclaw/qa/scenarios/media/native-image-generation.md
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# Native image generation
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```yaml qa-scenario
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id: native-image-generation
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title: Native image generation
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surface: image-generation
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coverage:
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primary:
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- media.image-generation
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secondary:
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- tools.native-image-generation
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objective: Verify image_generate appears when configured and returns a real saved media artifact.
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successCriteria:
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- image_generate appears in the effective tool inventory.
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- Agent triggers native image_generate.
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- Tool output returns a saved MEDIA path and the file exists.
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docsRefs:
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- docs/tools/image-generation.md
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- docs/providers/openai.md
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codeRefs:
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- src/agents/tools/image-generate-tool.ts
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- extensions/qa-lab/src/mock-openai-server.ts
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execution:
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kind: flow
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summary: Verify image_generate appears when configured and returns a real saved media artifact.
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config:
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prompt: "Image generation check: generate a QA lighthouse image and summarize it in one short sentence."
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promptSnippet: "Image generation check"
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generatedNeedle: "QA lighthouse"
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```
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```yaml qa-flow
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steps:
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- name: enables image_generate and saves a real media artifact
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actions:
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- call: ensureImageGenerationConfigured
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args:
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- ref: env
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- call: createSession
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saveAs: sessionKey
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args:
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- ref: env
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- Image generation
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- call: readEffectiveTools
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saveAs: tools
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args:
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- ref: env
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- ref: sessionKey
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- assert:
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expr: "tools.has('image_generate')"
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message: image_generate not present after imageGenerationModel patch
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- call: reset
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- call: runAgentPrompt
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args:
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- ref: env
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- sessionKey: agent:qa:image-generate
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message:
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expr: config.prompt
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timeoutMs:
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expr: liveTurnTimeoutMs(env, 45000)
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- call: waitForOutboundMessage
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saveAs: outbound
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args:
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- ref: state
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- lambda:
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params: [candidate]
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expr: "candidate.conversation.id === 'qa-operator'"
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- expr: liveTurnTimeoutMs(env, 45000)
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- assert:
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expr: "!env.mock || ((await fetchJson(`${env.mock.baseUrl}/debug/requests`)).find((request) => String(request.allInputText ?? '').includes(config.promptSnippet))?.plannedToolName === 'image_generate')"
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message:
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expr: "`expected image_generate, got ${String((await fetchJson(`${env.mock.baseUrl}/debug/requests`)).find((request) => String(request.allInputText ?? '').includes(config.promptSnippet))?.plannedToolName ?? '')}`"
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- call: waitForCondition
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saveAs: generated
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args:
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- lambda:
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async: true
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expr: "!env.mock ? true : (await fetchJson(`${env.mock.baseUrl}/debug/image-generations`)).find((request) => request.model === 'gpt-image-1' && String(request.prompt ?? '').includes(config.generatedNeedle))"
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- 15000
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- 250
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- assert:
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expr: "!env.mock || Boolean(generated)"
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message:
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expr: "`image provider was never invoked`"
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detailsExpr: "env.mock ? `${outbound.text}\\nIMAGE_PROMPT:${generated.prompt ?? ''}` : outbound.text"
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```
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