{"version":3,"file":"images.cjs","names":["flattenHeaders","getContext","getTestId","matchFixtureDiagnostic","applyChaos","resolveStrictMode","strictNoMatchMessage","strictNoMatchLogLine","strictOverrideField","proxyAndRecord","resolveResponse","isErrorResponse","serializeErrorResponse","isImageResponse","extractBoundary","extractFormField"],"sources":["../src/images.ts"],"sourcesContent":["import type * as http from \"node:http\";\nimport type { ChatCompletionRequest, Fixture, HandlerDefaults } from \"./types.js\";\nimport {\n isImageResponse,\n isErrorResponse,\n serializeErrorResponse,\n flattenHeaders,\n getContext,\n getTestId,\n resolveResponse,\n resolveStrictMode,\n strictOverrideField,\n strictNoMatchMessage,\n strictNoMatchLogLine,\n} from \"./helpers.js\";\nimport { matchFixtureDiagnostic } from \"./router.js\";\nimport { writeErrorResponse } from \"./sse-writer.js\";\nimport type { Journal } from \"./journal.js\";\nimport { applyChaos } from \"./chaos.js\";\nimport { proxyAndRecord } from \"./recorder.js\";\nimport { extractBoundary, extractFormField } from \"./transcription.js\";\n\ninterface OpenAIImageRequest {\n model?: string;\n prompt: string;\n n?: number;\n size?: string;\n response_format?: \"url\" | \"b64_json\";\n [key: string]: unknown;\n}\n\ninterface GeminiPredictRequest {\n instances: Array<{ prompt: string }>;\n parameters?: { sampleCount?: number };\n [key: string]: unknown;\n}\n\nfunction buildSyntheticRequest(\n model: string,\n prompt: string,\n context?: string,\n): ChatCompletionRequest {\n return {\n model,\n messages: [{ role: \"user\", content: prompt }],\n _endpointType: \"image\",\n ...(context !== undefined && { _context: context }),\n };\n}\n\nexport async function handleImages(\n req: http.IncomingMessage,\n res: http.ServerResponse,\n raw: string,\n fixtures: Fixture[],\n journal: Journal,\n defaults: HandlerDefaults,\n setCorsHeaders: (res: http.ServerResponse) => void,\n format: \"openai\" | \"gemini\" = \"openai\",\n geminiModel?: string,\n): Promise {\n setCorsHeaders(res);\n const path = req.url ?? \"/v1/images/generations\";\n const method = req.method ?? \"POST\";\n\n let model: string;\n let prompt: string;\n\n try {\n const body = JSON.parse(raw);\n if (format === \"gemini\") {\n const geminiReq = body as GeminiPredictRequest;\n prompt = geminiReq.instances?.[0]?.prompt ?? \"\";\n model = geminiModel ?? \"imagen\";\n } else {\n const openaiReq = body as OpenAIImageRequest;\n prompt = openaiReq.prompt ?? \"\";\n model = openaiReq.model ?? \"dall-e-3\";\n }\n } catch (parseErr) {\n const detail = parseErr instanceof Error ? parseErr.message : \"unknown\";\n journal.add({\n method,\n path,\n headers: flattenHeaders(req.headers),\n body: null,\n response: { status: 400, fixture: null },\n });\n writeErrorResponse(\n res,\n 400,\n JSON.stringify({\n error: {\n message: `Malformed JSON: ${detail}`,\n type: \"invalid_request_error\",\n code: \"invalid_json\",\n },\n }),\n );\n return;\n }\n\n if (!prompt) {\n journal.add({\n method,\n path,\n headers: flattenHeaders(req.headers),\n body: null,\n response: { status: 400, fixture: null },\n });\n writeErrorResponse(\n res,\n 400,\n JSON.stringify({\n error: { message: \"Missing required parameter: 'prompt'\", type: \"invalid_request_error\" },\n }),\n );\n return;\n }\n\n const syntheticReq = buildSyntheticRequest(model, prompt, getContext(req));\n const testId = getTestId(req);\n const { fixture, skippedBySequenceOrTurn } = matchFixtureDiagnostic(\n fixtures,\n syntheticReq,\n journal.getFixtureMatchCountsForTest(testId),\n defaults.requestTransform,\n );\n\n if (fixture) {\n journal.incrementFixtureMatchCount(fixture, fixtures, testId);\n defaults.logger.debug(`Fixture matched: ${JSON.stringify(fixture.match).slice(0, 120)}`);\n } else {\n defaults.logger.debug(`No fixture matched for request`);\n }\n\n if (\n applyChaos(\n res,\n fixture,\n defaults.chaos,\n req.headers,\n journal,\n { method, path, headers: flattenHeaders(req.headers), body: syntheticReq },\n fixture ? \"fixture\" : \"proxy\",\n defaults.registry,\n defaults.logger,\n )\n )\n return;\n\n if (!fixture) {\n const effectiveStrict = resolveStrictMode(defaults.strict, req.headers);\n if (effectiveStrict) {\n const strictMessage = strictNoMatchMessage(skippedBySequenceOrTurn);\n defaults.logger.error(strictNoMatchLogLine(method, path, skippedBySequenceOrTurn));\n journal.add({\n method,\n path,\n headers: flattenHeaders(req.headers),\n body: syntheticReq,\n response: {\n status: 503,\n fixture: null,\n ...strictOverrideField(defaults.strict, req.headers),\n },\n });\n writeErrorResponse(\n res,\n 503,\n JSON.stringify({\n error: {\n message: strictMessage,\n type: \"invalid_request_error\",\n code: \"no_fixture_match\",\n },\n }),\n );\n return;\n }\n if (defaults.record) {\n const outcome = await proxyAndRecord(\n req,\n res,\n syntheticReq,\n format === \"gemini\" ? \"gemini\" : \"openai\",\n req.url ?? \"/v1/images/generations\",\n fixtures,\n defaults,\n raw,\n );\n if (outcome === \"handled_by_hook\") return;\n if (outcome !== \"not_configured\") {\n journal.add({\n method,\n path,\n headers: flattenHeaders(req.headers),\n body: syntheticReq,\n response: { status: res.statusCode ?? 200, fixture: null, source: \"proxy\" },\n });\n return;\n }\n }\n\n journal.add({\n method,\n path,\n headers: flattenHeaders(req.headers),\n body: syntheticReq,\n response: {\n status: 404,\n fixture: null,\n ...strictOverrideField(defaults.strict, req.headers),\n },\n });\n writeErrorResponse(\n res,\n 404,\n JSON.stringify({\n error: {\n message: \"No fixture matched\",\n type: \"invalid_request_error\",\n code: \"no_fixture_match\",\n },\n }),\n );\n return;\n }\n\n const response = await resolveResponse(fixture, syntheticReq);\n\n if (isErrorResponse(response)) {\n const status = response.status ?? 500;\n journal.add({\n method,\n path,\n headers: flattenHeaders(req.headers),\n body: syntheticReq,\n response: { status, fixture },\n });\n writeErrorResponse(res, status, serializeErrorResponse(response), {\n retryAfter: response.retryAfter,\n });\n return;\n }\n\n if (!isImageResponse(response)) {\n journal.add({\n method,\n path,\n headers: flattenHeaders(req.headers),\n body: syntheticReq,\n response: { status: 500, fixture },\n });\n writeErrorResponse(\n res,\n 500,\n JSON.stringify({\n error: { message: \"Fixture response is not an image type\", type: \"server_error\" },\n }),\n );\n return;\n }\n\n journal.add({\n method,\n path,\n headers: flattenHeaders(req.headers),\n body: syntheticReq,\n response: { status: 200, fixture },\n });\n\n // Normalize to array of image items\n const items = response.images ?? (response.image ? [response.image] : []);\n\n if (format === \"gemini\") {\n const predictions = items.map((item) => ({\n bytesBase64Encoded: item.b64Json ?? \"\",\n mimeType: \"image/png\" as const,\n }));\n res.writeHead(200, { \"Content-Type\": \"application/json\" });\n res.end(JSON.stringify({ predictions }));\n } else {\n serializeOpenAIImageResponse(res, items);\n }\n}\n\n/**\n * Write the standard OpenAI image response envelope (`{ created, data }`).\n * Shared by generations, edit, and variations endpoints.\n */\nfunction serializeOpenAIImageResponse(\n res: http.ServerResponse,\n items: Array<{ url?: string; b64Json?: string; revisedPrompt?: string }>,\n): void {\n const data = items.map((item) => {\n const entry: Record = {};\n if (item.url) entry.url = item.url;\n if (item.b64Json) entry.b64_json = item.b64Json;\n if (item.revisedPrompt) entry.revised_prompt = item.revisedPrompt;\n return entry;\n });\n res.writeHead(200, { \"Content-Type\": \"application/json\" });\n res.end(JSON.stringify({ created: Math.floor(Date.now() / 1000), data }));\n}\n\n/**\n * Handle POST /v1/images/edits — OpenAI Image Edit API.\n *\n * Request uses multipart/form-data. We extract text fields (`prompt`, `model`,\n * `n`, `size`, `response_format`) and ignore binary fields (`image`, `mask`)\n * since aimock doesn't process actual image data.\n *\n * The response envelope is identical to /v1/images/generations.\n */\nexport async function handleImageEdit(\n req: http.IncomingMessage,\n res: http.ServerResponse,\n raw: string,\n fixtures: Fixture[],\n journal: Journal,\n defaults: HandlerDefaults,\n setCorsHeaders: (res: http.ServerResponse) => void,\n): Promise {\n setCorsHeaders(res);\n const path = req.url ?? \"/v1/images/edits\";\n const method = req.method ?? \"POST\";\n\n const contentType = Array.isArray(req.headers[\"content-type\"])\n ? req.headers[\"content-type\"][0]\n : req.headers[\"content-type\"];\n const boundary = extractBoundary(contentType);\n\n const prompt = extractFormField(raw, \"prompt\", boundary) ?? \"\";\n const model = extractFormField(raw, \"model\", boundary) ?? \"dall-e-2\";\n\n if (!prompt) {\n journal.add({\n method,\n path,\n headers: flattenHeaders(req.headers),\n body: null,\n response: { status: 400, fixture: null },\n });\n writeErrorResponse(\n res,\n 400,\n JSON.stringify({\n error: { message: \"Missing required parameter: 'prompt'\", type: \"invalid_request_error\" },\n }),\n );\n return;\n }\n\n const syntheticReq = buildSyntheticRequest(model, prompt, getContext(req));\n const testId = getTestId(req);\n const { fixture, skippedBySequenceOrTurn } = matchFixtureDiagnostic(\n fixtures,\n syntheticReq,\n journal.getFixtureMatchCountsForTest(testId),\n defaults.requestTransform,\n );\n\n if (fixture) {\n journal.incrementFixtureMatchCount(fixture, fixtures, testId);\n defaults.logger.debug(`Fixture matched: ${JSON.stringify(fixture.match).slice(0, 120)}`);\n } else {\n defaults.logger.debug(`No fixture matched for request`);\n }\n\n if (\n applyChaos(\n res,\n fixture,\n defaults.chaos,\n req.headers,\n journal,\n { method, path, headers: flattenHeaders(req.headers), body: syntheticReq },\n fixture ? \"fixture\" : \"proxy\",\n defaults.registry,\n defaults.logger,\n )\n )\n return;\n\n if (!fixture) {\n const effectiveStrict = resolveStrictMode(defaults.strict, req.headers);\n if (effectiveStrict) {\n const strictMessage = strictNoMatchMessage(skippedBySequenceOrTurn);\n defaults.logger.error(strictNoMatchLogLine(method, path, skippedBySequenceOrTurn));\n journal.add({\n method,\n path,\n headers: flattenHeaders(req.headers),\n body: syntheticReq,\n response: {\n status: 503,\n fixture: null,\n ...strictOverrideField(defaults.strict, req.headers),\n },\n });\n writeErrorResponse(\n res,\n 503,\n JSON.stringify({\n error: {\n message: strictMessage,\n type: \"invalid_request_error\",\n code: \"no_fixture_match\",\n },\n }),\n );\n return;\n }\n if (defaults.record) {\n const outcome = await proxyAndRecord(\n req,\n res,\n syntheticReq,\n \"openai\",\n req.url ?? \"/v1/images/edits\",\n fixtures,\n defaults,\n raw,\n );\n if (outcome === \"handled_by_hook\") return;\n if (outcome !== \"not_configured\") {\n journal.add({\n method,\n path,\n headers: flattenHeaders(req.headers),\n body: syntheticReq,\n response: { status: res.statusCode ?? 200, fixture: null, source: \"proxy\" },\n });\n return;\n }\n }\n\n journal.add({\n method,\n path,\n headers: flattenHeaders(req.headers),\n body: syntheticReq,\n response: {\n status: 404,\n fixture: null,\n ...strictOverrideField(defaults.strict, req.headers),\n },\n });\n writeErrorResponse(\n res,\n 404,\n JSON.stringify({\n error: {\n message: \"No fixture matched\",\n type: \"invalid_request_error\",\n code: \"no_fixture_match\",\n },\n }),\n );\n return;\n }\n\n const response = await resolveResponse(fixture, syntheticReq);\n\n if (isErrorResponse(response)) {\n const status = response.status ?? 500;\n journal.add({\n method,\n path,\n headers: flattenHeaders(req.headers),\n body: syntheticReq,\n response: { status, fixture },\n });\n writeErrorResponse(res, status, serializeErrorResponse(response), {\n retryAfter: response.retryAfter,\n });\n return;\n }\n\n if (!isImageResponse(response)) {\n journal.add({\n method,\n path,\n headers: flattenHeaders(req.headers),\n body: syntheticReq,\n response: { status: 500, fixture },\n });\n writeErrorResponse(\n res,\n 500,\n JSON.stringify({\n error: { message: \"Fixture response is not an image type\", type: \"server_error\" },\n }),\n );\n return;\n }\n\n journal.add({\n method,\n path,\n headers: flattenHeaders(req.headers),\n body: syntheticReq,\n response: { status: 200, fixture },\n });\n\n const items = response.images ?? (response.image ? [response.image] : []);\n serializeOpenAIImageResponse(res, items);\n}\n\n/**\n * Handle POST /v1/images/variations — OpenAI Image Variations API.\n *\n * Request uses multipart/form-data. We extract text fields (`model`, `n`,\n * `size`, `response_format`) and ignore the binary `image` field.\n * Unlike edit, no `prompt` field is required.\n *\n * The response envelope is identical to /v1/images/generations.\n */\nexport async function handleImageVariations(\n req: http.IncomingMessage,\n res: http.ServerResponse,\n raw: string,\n fixtures: Fixture[],\n journal: Journal,\n defaults: HandlerDefaults,\n setCorsHeaders: (res: http.ServerResponse) => void,\n): Promise {\n setCorsHeaders(res);\n const path = req.url ?? \"/v1/images/variations\";\n const method = req.method ?? \"POST\";\n\n const contentType = Array.isArray(req.headers[\"content-type\"])\n ? req.headers[\"content-type\"][0]\n : req.headers[\"content-type\"];\n const boundary = extractBoundary(contentType);\n\n const model = extractFormField(raw, \"model\", boundary) ?? \"dall-e-2\";\n\n // Variations don't have a prompt — use a synthetic placeholder for fixture matching\n const syntheticReq = buildSyntheticRequest(model, \"[variation]\", getContext(req));\n const testId = getTestId(req);\n const { fixture, skippedBySequenceOrTurn } = matchFixtureDiagnostic(\n fixtures,\n syntheticReq,\n journal.getFixtureMatchCountsForTest(testId),\n defaults.requestTransform,\n );\n\n if (fixture) {\n journal.incrementFixtureMatchCount(fixture, fixtures, testId);\n defaults.logger.debug(`Fixture matched: ${JSON.stringify(fixture.match).slice(0, 120)}`);\n } else {\n defaults.logger.debug(`No fixture matched for request`);\n }\n\n if (\n applyChaos(\n res,\n fixture,\n defaults.chaos,\n req.headers,\n journal,\n { method, path, headers: flattenHeaders(req.headers), body: syntheticReq },\n fixture ? \"fixture\" : \"proxy\",\n defaults.registry,\n defaults.logger,\n )\n )\n return;\n\n if (!fixture) {\n const effectiveStrict = resolveStrictMode(defaults.strict, req.headers);\n if (effectiveStrict) {\n const strictMessage = strictNoMatchMessage(skippedBySequenceOrTurn);\n defaults.logger.error(strictNoMatchLogLine(method, path, skippedBySequenceOrTurn));\n journal.add({\n method,\n path,\n headers: flattenHeaders(req.headers),\n body: syntheticReq,\n response: {\n status: 503,\n fixture: null,\n ...strictOverrideField(defaults.strict, req.headers),\n },\n });\n writeErrorResponse(\n res,\n 503,\n JSON.stringify({\n error: {\n message: strictMessage,\n type: \"invalid_request_error\",\n code: \"no_fixture_match\",\n },\n }),\n );\n return;\n }\n if (defaults.record) {\n const outcome = await proxyAndRecord(\n req,\n res,\n syntheticReq,\n \"openai\",\n req.url ?? \"/v1/images/variations\",\n fixtures,\n defaults,\n raw,\n );\n if (outcome === \"handled_by_hook\") return;\n if (outcome !== \"not_configured\") {\n journal.add({\n method,\n path,\n headers: flattenHeaders(req.headers),\n body: syntheticReq,\n response: { status: res.statusCode ?? 200, fixture: null, source: \"proxy\" },\n });\n return;\n }\n }\n\n journal.add({\n method,\n path,\n headers: flattenHeaders(req.headers),\n body: syntheticReq,\n response: {\n status: 404,\n fixture: null,\n ...strictOverrideField(defaults.strict, req.headers),\n },\n });\n writeErrorResponse(\n res,\n 404,\n JSON.stringify({\n error: {\n message: \"No fixture matched\",\n type: \"invalid_request_error\",\n code: \"no_fixture_match\",\n },\n }),\n );\n return;\n }\n\n const response = await resolveResponse(fixture, syntheticReq);\n\n if (isErrorResponse(response)) {\n const status = response.status ?? 500;\n journal.add({\n method,\n path,\n headers: flattenHeaders(req.headers),\n body: syntheticReq,\n response: { status, fixture },\n });\n writeErrorResponse(res, status, serializeErrorResponse(response), {\n retryAfter: response.retryAfter,\n });\n return;\n }\n\n if (!isImageResponse(response)) {\n journal.add({\n method,\n path,\n headers: flattenHeaders(req.headers),\n body: syntheticReq,\n response: { status: 500, fixture },\n });\n writeErrorResponse(\n res,\n 500,\n JSON.stringify({\n error: { message: \"Fixture response is not an image type\", type: \"server_error\" },\n }),\n );\n return;\n }\n\n journal.add({\n method,\n path,\n headers: flattenHeaders(req.headers),\n body: syntheticReq,\n response: { status: 200, fixture },\n });\n\n const items = response.images ?? (response.image ? [response.image] : []);\n serializeOpenAIImageResponse(res, 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