{"version":3,"file":"ollama.cjs","names":["flattenHeaders","getContext","getTestId","matchFixtureDiagnostic","recordMatchOptions","applyChaos","resolveStrictMode","strictNoMatchMessage","strictNoMatchLogLine","strictOverrideField","proxyAndRecord","resolveResponse","isErrorResponse","serializeErrorResponse","isContentWithToolCallsResponse","resolveReasoningForModel","createInterruptionSignal","writeNDJSONStream","isTextResponse","isToolCallResponse","isEmbeddingResponse","generateDeterministicEmbedding"],"sources":["../src/ollama.ts"],"sourcesContent":["/**\n * Ollama API endpoint support.\n *\n * Translates incoming /api/chat, /api/generate, and /api/embeddings requests\n * into the ChatCompletionRequest format used by the fixture router, and converts\n * fixture responses back into Ollama's NDJSON streaming or non-streaming format.\n *\n * Key differences from OpenAI:\n * - Ollama defaults to stream: true (opposite of OpenAI)\n * - Streaming uses NDJSON, not SSE\n * - Tool call arguments are objects, not JSON strings\n * - Tool calls have no id field\n * - Embeddings return a single `embedding` array, not an array of objects\n */\n\nimport type * as http from \"node:http\";\nimport type {\n ChatCompletionRequest,\n ChatMessage,\n Fixture,\n HandlerDefaults,\n ToolCall,\n ToolDefinition,\n} from \"./types.js\";\nimport {\n isTextResponse,\n isToolCallResponse,\n isContentWithToolCallsResponse,\n isErrorResponse,\n isEmbeddingResponse,\n serializeErrorResponse,\n generateDeterministicEmbedding,\n flattenHeaders,\n getTestId,\n resolveResponse,\n resolveStrictMode,\n resolveReasoningForModel,\n strictOverrideField,\n getContext,\n strictNoMatchMessage,\n strictNoMatchLogLine,\n} from \"./helpers.js\";\nimport { matchFixtureDiagnostic, recordMatchOptions } from \"./router.js\";\nimport { writeErrorResponse } from \"./sse-writer.js\";\nimport { writeNDJSONStream } from \"./ndjson-writer.js\";\nimport { createInterruptionSignal } from \"./interruption.js\";\nimport type { Journal } from \"./journal.js\";\nimport type { Logger } from \"./logger.js\";\nimport { applyChaos } from \"./chaos.js\";\nimport { proxyAndRecord } from \"./recorder.js\";\n\n// ─── Ollama request types ────────────────────────────────────────────────────\n\ninterface OllamaMessage {\n role: \"system\" | \"user\" | \"assistant\" | \"tool\";\n content: string;\n tool_calls?: Array<{ function: { name: string; arguments: unknown } }>;\n images?: string[];\n}\n\ninterface OllamaToolDef {\n type: string;\n function: {\n name: string;\n description?: string;\n parameters?: object;\n };\n}\n\ninterface OllamaRequest {\n model: string;\n messages: OllamaMessage[];\n stream?: boolean; // default true!\n options?: { temperature?: number; num_predict?: number };\n tools?: OllamaToolDef[];\n}\n\ninterface OllamaGenerateRequest {\n model: string;\n prompt: string;\n stream?: boolean; // default true!\n options?: { temperature?: number; num_predict?: number };\n system?: string;\n images?: string[];\n}\n\n// ─── Duration fields (zeroed, required on final/non-streaming responses) ────\n\nconst DURATION_FIELDS = {\n done_reason: \"stop\" as const,\n total_duration: 0,\n load_duration: 0,\n prompt_eval_count: 0,\n prompt_eval_duration: 0,\n eval_count: 0,\n eval_duration: 0,\n};\n\n// ─── Input conversion: Ollama → ChatCompletionRequest ────────────────────────\n\nexport function ollamaToCompletionRequest(req: OllamaRequest): ChatCompletionRequest {\n const messages: ChatMessage[] = [];\n\n for (const msg of req.messages) {\n const chatMsg: ChatMessage = {\n role: msg.role as ChatMessage[\"role\"],\n content: msg.content,\n };\n\n // Map inbound tool_calls on assistant messages to the internal format\n if (msg.tool_calls && msg.tool_calls.length > 0) {\n chatMsg.tool_calls = msg.tool_calls.map((tc, i) => ({\n id: `call_${i}`,\n type: \"function\" as const,\n function: {\n name: tc.function.name,\n arguments:\n typeof tc.function.arguments === \"string\"\n ? tc.function.arguments\n : JSON.stringify(tc.function.arguments),\n },\n }));\n }\n\n messages.push(chatMsg);\n }\n\n // Convert tools\n let tools: ToolDefinition[] | undefined;\n if (req.tools && req.tools.length > 0) {\n tools = req.tools.map((t) => ({\n type: \"function\" as const,\n function: {\n name: t.function.name,\n description: t.function.description,\n parameters: t.function.parameters,\n },\n }));\n }\n\n return {\n model: req.model,\n messages,\n stream: req.stream ?? true,\n temperature: req.options?.temperature,\n max_tokens: req.options?.num_predict,\n tools,\n };\n}\n\nfunction ollamaGenerateToCompletionRequest(req: OllamaGenerateRequest): ChatCompletionRequest {\n const messages: ChatMessage[] = [];\n\n // Prepend system message if present\n if (req.system) {\n messages.push({ role: \"system\", content: req.system });\n }\n\n messages.push({ role: \"user\", content: req.prompt });\n\n return {\n model: req.model,\n messages,\n stream: req.stream ?? true,\n temperature: req.options?.temperature,\n max_tokens: req.options?.num_predict,\n };\n}\n\n// ─── Response builders: /api/chat ────────────────────────────────────────────\n\nfunction buildOllamaChatTextChunks(\n content: string,\n model: string,\n chunkSize: number,\n reasoning?: string,\n): object[] {\n const chunks: object[] = [];\n const createdAt = new Date().toISOString();\n\n // Reasoning chunks (before content)\n if (reasoning) {\n for (let i = 0; i < reasoning.length; i += chunkSize) {\n const slice = reasoning.slice(i, i + chunkSize);\n chunks.push({\n model,\n created_at: createdAt,\n message: { role: \"assistant\", content: \"\", reasoning_content: slice },\n done: false,\n });\n }\n }\n\n for (let i = 0; i < content.length; i += chunkSize) {\n const slice = content.slice(i, i + chunkSize);\n chunks.push({\n model,\n created_at: createdAt,\n message: { role: \"assistant\", content: slice },\n done: false,\n });\n }\n\n // Final chunk with done: true and all duration fields\n chunks.push({\n model,\n created_at: createdAt,\n message: { role: \"assistant\", content: \"\" },\n done: true,\n ...DURATION_FIELDS,\n });\n\n return chunks;\n}\n\nfunction buildOllamaChatTextResponse(content: string, model: string, reasoning?: string): object {\n return {\n model,\n created_at: new Date().toISOString(),\n message: {\n role: \"assistant\",\n content,\n ...(reasoning ? { reasoning_content: reasoning } : {}),\n },\n done: true,\n ...DURATION_FIELDS,\n };\n}\n\nfunction buildOllamaChatToolCallChunks(\n toolCalls: ToolCall[],\n model: string,\n chunkSize: number,\n logger: Logger,\n reasoning?: string,\n): object[] {\n const ollamaToolCalls = toolCalls.map((tc) => {\n let argsObj: unknown;\n try {\n argsObj = JSON.parse(tc.arguments || \"{}\");\n } catch {\n logger.warn(\n `Malformed JSON in fixture tool call arguments for \"${tc.name}\": ${tc.arguments}`,\n );\n argsObj = {};\n }\n return {\n function: {\n name: tc.name,\n arguments: argsObj,\n },\n };\n });\n\n // Tool calls are sent in a single chunk (no streaming of individual args)\n const chunks: object[] = [];\n const createdAt = new Date().toISOString();\n\n // Reasoning chunks (before tool calls)\n if (reasoning) {\n for (let i = 0; i < reasoning.length; i += chunkSize) {\n const slice = reasoning.slice(i, i + chunkSize);\n chunks.push({\n model,\n created_at: createdAt,\n message: { role: \"assistant\", content: \"\", reasoning_content: slice },\n done: false,\n });\n }\n }\n\n chunks.push({\n model,\n created_at: createdAt,\n message: {\n role: \"assistant\",\n content: \"\",\n tool_calls: ollamaToolCalls,\n },\n done: false,\n });\n\n // Final chunk\n chunks.push({\n model,\n created_at: createdAt,\n message: { role: \"assistant\", content: \"\" },\n done: true,\n ...DURATION_FIELDS,\n });\n\n return chunks;\n}\n\nfunction buildOllamaChatToolCallResponse(\n toolCalls: ToolCall[],\n model: string,\n logger: Logger,\n reasoning?: string,\n): object {\n const ollamaToolCalls = toolCalls.map((tc) => {\n let argsObj: unknown;\n try {\n argsObj = JSON.parse(tc.arguments || \"{}\");\n } catch {\n logger.warn(\n `Malformed JSON in fixture tool call arguments for \"${tc.name}\": ${tc.arguments}`,\n );\n argsObj = {};\n }\n return {\n function: {\n name: tc.name,\n arguments: argsObj,\n },\n };\n });\n\n return {\n model,\n created_at: new Date().toISOString(),\n message: {\n role: \"assistant\",\n content: \"\",\n ...(reasoning ? { reasoning_content: reasoning } : {}),\n tool_calls: ollamaToolCalls,\n },\n done: true,\n ...DURATION_FIELDS,\n };\n}\n\n// ─── Response builders: /api/chat — content + tool calls ────────────────────\n\nfunction buildOllamaChatContentWithToolCallsChunks(\n content: string,\n toolCalls: ToolCall[],\n model: string,\n chunkSize: number,\n logger: Logger,\n reasoning?: string,\n): object[] {\n const chunks: object[] = [];\n const createdAt = new Date().toISOString();\n\n // Reasoning chunks (before content)\n if (reasoning) {\n for (let i = 0; i < reasoning.length; i += chunkSize) {\n const slice = reasoning.slice(i, i + chunkSize);\n chunks.push({\n model,\n created_at: createdAt,\n message: { role: \"assistant\", content: \"\", reasoning_content: slice },\n done: false,\n });\n }\n }\n\n // Content chunks first\n for (let i = 0; i < content.length; i += chunkSize) {\n const slice = content.slice(i, i + chunkSize);\n chunks.push({\n model,\n created_at: createdAt,\n message: { role: \"assistant\", content: slice },\n done: false,\n });\n }\n\n // Tool calls in a single chunk (same as tool-call-only path)\n const ollamaToolCalls = toolCalls.map((tc) => {\n let argsObj: unknown;\n try {\n argsObj = JSON.parse(tc.arguments || \"{}\");\n } catch {\n logger.warn(\n `Malformed JSON in fixture tool call arguments for \"${tc.name}\": ${tc.arguments}`,\n );\n argsObj = {};\n }\n return {\n function: {\n name: tc.name,\n arguments: argsObj,\n },\n };\n });\n\n chunks.push({\n model,\n created_at: createdAt,\n message: {\n role: \"assistant\",\n content: \"\",\n tool_calls: ollamaToolCalls,\n },\n done: false,\n });\n\n // Final chunk\n chunks.push({\n model,\n created_at: createdAt,\n message: { role: \"assistant\", content: \"\" },\n done: true,\n ...DURATION_FIELDS,\n });\n\n return chunks;\n}\n\nfunction buildOllamaChatContentWithToolCallsResponse(\n content: string,\n toolCalls: ToolCall[],\n model: string,\n logger: Logger,\n reasoning?: string,\n): object {\n const ollamaToolCalls = toolCalls.map((tc) => {\n let argsObj: unknown;\n try {\n argsObj = JSON.parse(tc.arguments || \"{}\");\n } catch {\n logger.warn(\n `Malformed JSON in fixture tool call arguments for \"${tc.name}\": ${tc.arguments}`,\n );\n argsObj = {};\n }\n return {\n function: {\n name: tc.name,\n arguments: argsObj,\n },\n };\n });\n\n return {\n model,\n created_at: new Date().toISOString(),\n message: {\n role: \"assistant\",\n content,\n ...(reasoning ? { reasoning_content: reasoning } : {}),\n tool_calls: ollamaToolCalls,\n },\n done: true,\n ...DURATION_FIELDS,\n };\n}\n\n// ─── Response builders: /api/generate ────────────────────────────────────────\n\nfunction buildOllamaGenerateTextChunks(\n content: string,\n model: string,\n chunkSize: number,\n reasoning?: string,\n): object[] {\n const chunks: object[] = [];\n const createdAt = new Date().toISOString();\n\n // Reasoning chunks (before content)\n if (reasoning) {\n for (let i = 0; i < reasoning.length; i += chunkSize) {\n const slice = reasoning.slice(i, i + chunkSize);\n chunks.push({\n model,\n created_at: createdAt,\n response: \"\",\n reasoning_content: slice,\n done: false,\n });\n }\n }\n\n for (let i = 0; i < content.length; i += chunkSize) {\n const slice = content.slice(i, i + chunkSize);\n chunks.push({\n model,\n created_at: createdAt,\n response: slice,\n done: false,\n });\n }\n\n // Final chunk\n chunks.push({\n model,\n created_at: createdAt,\n response: \"\",\n done: true,\n ...DURATION_FIELDS,\n context: [],\n });\n\n return chunks;\n}\n\nfunction buildOllamaGenerateTextResponse(\n content: string,\n model: string,\n reasoning?: string,\n): object {\n return {\n model,\n created_at: new Date().toISOString(),\n response: content,\n ...(reasoning ? { reasoning_content: reasoning } : {}),\n done: true,\n ...DURATION_FIELDS,\n context: [],\n };\n}\n\n// ─── Request handler: /api/chat ──────────────────────────────────────────────\n\nexport async function handleOllama(\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 const { logger } = defaults;\n setCorsHeaders(res);\n\n const urlPath = req.url ?? \"/api/chat\";\n\n let ollamaReq: OllamaRequest;\n try {\n ollamaReq = JSON.parse(raw) as OllamaRequest;\n } catch (parseErr) {\n const detail = parseErr instanceof Error ? parseErr.message : \"unknown\";\n journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\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 body: ${detail}`,\n type: \"invalid_request_error\",\n },\n }),\n );\n return;\n }\n\n if (!ollamaReq.messages || !Array.isArray(ollamaReq.messages)) {\n journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\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: \"Invalid request: messages array is required\",\n type: \"invalid_request_error\",\n },\n }),\n );\n return;\n }\n\n // Convert to ChatCompletionRequest for fixture matching\n const completionReq = ollamaToCompletionRequest(ollamaReq);\n completionReq._endpointType = \"chat\";\n completionReq._context = getContext(req);\n\n const testId = getTestId(req);\n const { fixture, skippedBySequenceOrTurn } = matchFixtureDiagnostic(\n fixtures,\n completionReq,\n journal.getFixtureMatchCountsForTest(testId),\n defaults.requestTransform,\n // Record mode proxies on a miss to capture a fresh turn (see record gate\n // below), so keep turnIndex strict to prevent an earlier-turn fixture from\n // shadowing a longer request and skipping the new turn's recording.\n recordMatchOptions(!!defaults.record, defaults.logger),\n );\n\n if (fixture) {\n journal.incrementFixtureMatchCount(fixture, fixtures, testId);\n logger.debug(`Fixture matched: ${JSON.stringify(fixture.match).slice(0, 120)}`);\n } else {\n 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 {\n method: req.method ?? \"POST\",\n path: urlPath,\n headers: flattenHeaders(req.headers),\n body: completionReq,\n },\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 strictStatus = 503;\n const strictMessage = strictNoMatchMessage(skippedBySequenceOrTurn);\n logger.error(strictNoMatchLogLine(req.method ?? \"POST\", urlPath, skippedBySequenceOrTurn));\n journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\n headers: flattenHeaders(req.headers),\n body: completionReq,\n response: {\n status: strictStatus,\n fixture: null,\n ...strictOverrideField(defaults.strict, req.headers),\n },\n });\n writeErrorResponse(\n res,\n strictStatus,\n JSON.stringify({\n error: {\n message: strictMessage,\n type: \"invalid_request_error\",\n },\n }),\n );\n return;\n }\n if (defaults.record) {\n const outcome = await proxyAndRecord(\n req,\n res,\n completionReq,\n \"ollama\",\n urlPath,\n fixtures,\n defaults,\n raw,\n );\n if (outcome === \"handled_by_hook\") return;\n if (outcome !== \"not_configured\") {\n journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\n headers: flattenHeaders(req.headers),\n body: completionReq,\n response: { status: res.statusCode ?? 200, fixture: null, source: \"proxy\" },\n });\n return;\n }\n }\n journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\n headers: flattenHeaders(req.headers),\n body: completionReq,\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 },\n }),\n );\n return;\n }\n\n const response = await resolveResponse(fixture, completionReq);\n const latency = fixture.latency ?? defaults.latency;\n const chunkSize = Math.max(1, fixture.chunkSize ?? defaults.chunkSize);\n\n // Ollama defaults to streaming when stream is absent or true\n const streaming = ollamaReq.stream !== false;\n\n // Error response\n if (isErrorResponse(response)) {\n const status = response.status ?? 500;\n journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\n headers: flattenHeaders(req.headers),\n body: completionReq,\n response: { status, fixture },\n });\n writeErrorResponse(res, status, serializeErrorResponse(response), {\n retryAfter: response.retryAfter,\n });\n return;\n }\n\n // Content + tool calls response (must be checked before text/tool-only branches)\n if (isContentWithToolCallsResponse(response)) {\n if (response.webSearches?.length) {\n logger.warn(\"webSearches in fixture response are not supported for Ollama API -- ignoring\");\n }\n const journalEntry = journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\n headers: flattenHeaders(req.headers),\n body: completionReq,\n response: { status: 200, fixture },\n });\n // Gate reasoning emission on the requested model's capability (aimock#254).\n const effectiveStrict = resolveStrictMode(defaults.strict, req.headers);\n const effReasoning = resolveReasoningForModel(\n response.reasoning,\n completionReq.model,\n effectiveStrict,\n logger,\n );\n if (!streaming) {\n const body = buildOllamaChatContentWithToolCallsResponse(\n response.content,\n response.toolCalls,\n completionReq.model,\n logger,\n effReasoning,\n );\n res.writeHead(200, { \"Content-Type\": \"application/json\" });\n res.end(JSON.stringify(body));\n } else {\n const chunks = buildOllamaChatContentWithToolCallsChunks(\n response.content,\n response.toolCalls,\n completionReq.model,\n chunkSize,\n logger,\n effReasoning,\n );\n const interruption = createInterruptionSignal(fixture);\n const completed = await writeNDJSONStream(res, chunks, {\n latency,\n streamingProfile: fixture.streamingProfile,\n recordedTimings: fixture.recordedTimings,\n replaySpeed: fixture.replaySpeed ?? defaults.replaySpeed,\n signal: interruption?.signal,\n onChunkSent: interruption?.tick,\n });\n if (!completed) {\n if (!res.writableEnded) res.destroy();\n journalEntry.response.interrupted = true;\n journalEntry.response.interruptReason = interruption?.reason();\n }\n interruption?.cleanup();\n }\n return;\n }\n\n // Text response\n if (isTextResponse(response)) {\n if (response.webSearches?.length) {\n logger.warn(\"webSearches in fixture response are not supported for Ollama API -- ignoring\");\n }\n const journalEntry = journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\n headers: flattenHeaders(req.headers),\n body: completionReq,\n response: { status: 200, fixture },\n });\n // Gate reasoning emission on the requested model's capability (aimock#254).\n const effectiveStrict = resolveStrictMode(defaults.strict, req.headers);\n const effReasoning = resolveReasoningForModel(\n response.reasoning,\n completionReq.model,\n effectiveStrict,\n logger,\n );\n if (!streaming) {\n const body = buildOllamaChatTextResponse(response.content, completionReq.model, effReasoning);\n res.writeHead(200, { \"Content-Type\": \"application/json\" });\n res.end(JSON.stringify(body));\n } else {\n const chunks = buildOllamaChatTextChunks(\n response.content,\n completionReq.model,\n chunkSize,\n effReasoning,\n );\n const interruption = createInterruptionSignal(fixture);\n const completed = await writeNDJSONStream(res, chunks, {\n latency,\n streamingProfile: fixture.streamingProfile,\n recordedTimings: fixture.recordedTimings,\n replaySpeed: fixture.replaySpeed ?? defaults.replaySpeed,\n signal: interruption?.signal,\n onChunkSent: interruption?.tick,\n });\n if (!completed) {\n if (!res.writableEnded) res.destroy();\n journalEntry.response.interrupted = true;\n journalEntry.response.interruptReason = interruption?.reason();\n }\n interruption?.cleanup();\n }\n return;\n }\n\n // Tool call response\n if (isToolCallResponse(response)) {\n if (response.webSearches?.length) {\n logger.warn(\"webSearches in fixture response are not supported for Ollama API — ignoring\");\n }\n const journalEntry = journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\n headers: flattenHeaders(req.headers),\n body: completionReq,\n response: { status: 200, fixture },\n });\n // Gate reasoning emission on the requested model's capability (aimock#254).\n const effectiveStrict = resolveStrictMode(defaults.strict, req.headers);\n const effReasoning = resolveReasoningForModel(\n response.reasoning,\n completionReq.model,\n effectiveStrict,\n logger,\n );\n if (!streaming) {\n const body = buildOllamaChatToolCallResponse(\n response.toolCalls,\n completionReq.model,\n logger,\n effReasoning,\n );\n res.writeHead(200, { \"Content-Type\": \"application/json\" });\n res.end(JSON.stringify(body));\n } else {\n const chunks = buildOllamaChatToolCallChunks(\n response.toolCalls,\n completionReq.model,\n chunkSize,\n logger,\n effReasoning,\n );\n const interruption = createInterruptionSignal(fixture);\n const completed = await writeNDJSONStream(res, chunks, {\n latency,\n streamingProfile: fixture.streamingProfile,\n recordedTimings: fixture.recordedTimings,\n replaySpeed: fixture.replaySpeed ?? defaults.replaySpeed,\n signal: interruption?.signal,\n onChunkSent: interruption?.tick,\n });\n if (!completed) {\n if (!res.writableEnded) res.destroy();\n journalEntry.response.interrupted = true;\n journalEntry.response.interruptReason = interruption?.reason();\n }\n interruption?.cleanup();\n }\n return;\n }\n\n // Unknown response type\n journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\n headers: flattenHeaders(req.headers),\n body: completionReq,\n response: { status: 500, fixture },\n });\n writeErrorResponse(\n res,\n 500,\n JSON.stringify({\n error: {\n message: \"Fixture response did not match any known type\",\n type: \"server_error\",\n },\n }),\n );\n}\n\n// ─── Request handler: /api/generate ──────────────────────────────────────────\n\nexport async function handleOllamaGenerate(\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\n const urlPath = req.url ?? \"/api/generate\";\n\n let generateReq: OllamaGenerateRequest;\n try {\n generateReq = JSON.parse(raw) as OllamaGenerateRequest;\n } catch (parseErr) {\n const detail = parseErr instanceof Error ? parseErr.message : \"unknown\";\n journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\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 body: ${detail}`,\n type: \"invalid_request_error\",\n },\n }),\n );\n return;\n }\n\n if (!generateReq.prompt || typeof generateReq.prompt !== \"string\") {\n journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\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: \"Invalid request: prompt field is required\",\n type: \"invalid_request_error\",\n },\n }),\n );\n return;\n }\n\n // Convert to ChatCompletionRequest for fixture matching\n const completionReq = ollamaGenerateToCompletionRequest(generateReq);\n completionReq._endpointType = \"chat\";\n completionReq._context = getContext(req);\n\n const testId = getTestId(req);\n const { fixture, skippedBySequenceOrTurn } = matchFixtureDiagnostic(\n fixtures,\n completionReq,\n journal.getFixtureMatchCountsForTest(testId),\n defaults.requestTransform,\n // Record mode proxies on a miss to capture a fresh turn (see record gate\n // below), so keep turnIndex strict to prevent an earlier-turn fixture from\n // shadowing a longer request and skipping the new turn's recording.\n recordMatchOptions(!!defaults.record, defaults.logger),\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 {\n method: req.method ?? \"POST\",\n path: urlPath,\n headers: flattenHeaders(req.headers),\n body: completionReq,\n },\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 strictStatus = 503;\n const strictMessage = strictNoMatchMessage(skippedBySequenceOrTurn);\n defaults.logger.error(\n strictNoMatchLogLine(req.method ?? \"POST\", urlPath, skippedBySequenceOrTurn),\n );\n journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\n headers: flattenHeaders(req.headers),\n body: completionReq,\n response: {\n status: strictStatus,\n fixture: null,\n ...strictOverrideField(defaults.strict, req.headers),\n },\n });\n writeErrorResponse(\n res,\n strictStatus,\n JSON.stringify({\n error: {\n message: strictMessage,\n type: \"invalid_request_error\",\n },\n }),\n );\n return;\n }\n if (defaults.record) {\n const outcome = await proxyAndRecord(\n req,\n res,\n completionReq,\n \"ollama\",\n urlPath,\n fixtures,\n defaults,\n raw,\n );\n if (outcome === \"handled_by_hook\") return;\n if (outcome !== \"not_configured\") {\n journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\n headers: flattenHeaders(req.headers),\n body: completionReq,\n response: { status: res.statusCode ?? 200, fixture: null, source: \"proxy\" },\n });\n return;\n }\n }\n journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\n headers: flattenHeaders(req.headers),\n body: completionReq,\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 },\n }),\n );\n return;\n }\n\n const response = await resolveResponse(fixture, completionReq);\n const latency = fixture.latency ?? defaults.latency;\n const chunkSize = Math.max(1, fixture.chunkSize ?? defaults.chunkSize);\n\n // Ollama defaults to streaming when stream is absent or true\n const streaming = generateReq.stream !== false;\n\n // Error response\n if (isErrorResponse(response)) {\n const status = response.status ?? 500;\n journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\n headers: flattenHeaders(req.headers),\n body: completionReq,\n response: { status, fixture },\n });\n writeErrorResponse(res, status, serializeErrorResponse(response), {\n retryAfter: response.retryAfter,\n });\n return;\n }\n\n // Text response (only type supported for /api/generate)\n if (isTextResponse(response)) {\n const journalEntry = journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\n headers: flattenHeaders(req.headers),\n body: completionReq,\n response: { status: 200, fixture },\n });\n // Gate reasoning emission on the requested model's capability (aimock#254).\n const effectiveStrict = resolveStrictMode(defaults.strict, req.headers);\n const effReasoning = resolveReasoningForModel(\n response.reasoning,\n completionReq.model,\n effectiveStrict,\n defaults.logger,\n );\n if (!streaming) {\n const body = buildOllamaGenerateTextResponse(\n response.content,\n completionReq.model,\n effReasoning,\n );\n res.writeHead(200, { \"Content-Type\": \"application/json\" });\n res.end(JSON.stringify(body));\n } else {\n const chunks = buildOllamaGenerateTextChunks(\n response.content,\n completionReq.model,\n chunkSize,\n effReasoning,\n );\n const interruption = createInterruptionSignal(fixture);\n const completed = await writeNDJSONStream(res, chunks, {\n latency,\n streamingProfile: fixture.streamingProfile,\n recordedTimings: fixture.recordedTimings,\n replaySpeed: fixture.replaySpeed ?? defaults.replaySpeed,\n signal: interruption?.signal,\n onChunkSent: interruption?.tick,\n });\n if (!completed) {\n if (!res.writableEnded) res.destroy();\n journalEntry.response.interrupted = true;\n journalEntry.response.interruptReason = interruption?.reason();\n }\n interruption?.cleanup();\n }\n return;\n }\n\n // Tool call fixtures matched but not supported on /api/generate\n if (isToolCallResponse(response) || isContentWithToolCallsResponse(response)) {\n journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\n headers: flattenHeaders(req.headers),\n body: completionReq,\n response: { status: 400, fixture },\n });\n writeErrorResponse(\n res,\n 400,\n JSON.stringify({\n error: {\n message: \"Tool call fixtures are not supported on /api/generate — use /api/chat instead\",\n type: \"invalid_request_error\",\n },\n }),\n );\n return;\n }\n\n // Unknown response type\n journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\n headers: flattenHeaders(req.headers),\n body: completionReq,\n response: { status: 500, fixture },\n });\n writeErrorResponse(\n res,\n 500,\n JSON.stringify({\n error: {\n message: \"Fixture response did not match any known type\",\n type: \"server_error\",\n },\n }),\n );\n}\n\n// ─── Ollama embeddings request type ─────────────────────────────────────────\n\ninterface OllamaEmbeddingsRequest {\n model: string;\n prompt?: string;\n input?: string | string[];\n}\n\n// ─── Request handler: /api/embeddings ───────────────────────────────────────\n\nexport async function handleOllamaEmbeddings(\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 const { logger } = defaults;\n setCorsHeaders(res);\n\n const urlPath = req.url ?? \"/api/embeddings\";\n\n let embReq: OllamaEmbeddingsRequest;\n try {\n embReq = JSON.parse(raw) as OllamaEmbeddingsRequest;\n } catch (parseErr) {\n const detail = parseErr instanceof Error ? parseErr.message : \"unknown\";\n journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\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 body: ${detail}`,\n type: \"invalid_request_error\",\n },\n }),\n );\n return;\n }\n\n // Ollama accepts either \"prompt\" or \"input\" for the text to embed\n const inputText =\n embReq.prompt ??\n (typeof embReq.input === \"string\" ? embReq.input : undefined) ??\n (Array.isArray(embReq.input) ? embReq.input.join(\" \") : undefined);\n\n if (!embReq.model) {\n journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\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: 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capture a fresh turn (see record gate\n // below), so keep turnIndex strict to prevent an earlier-turn fixture from\n // shadowing a longer request and skipping the new turn's recording.\n recordMatchOptions(!!defaults.record, defaults.logger),\n );\n\n if (fixture) {\n journal.incrementFixtureMatchCount(fixture, fixtures, testId);\n logger.debug(`Fixture matched: ${JSON.stringify(fixture.match).slice(0, 120)}`);\n } else {\n 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 {\n method: req.method ?? \"POST\",\n path: urlPath,\n headers: flattenHeaders(req.headers),\n body: syntheticReq,\n },\n fixture ? \"fixture\" : \"proxy\",\n defaults.registry,\n defaults.logger,\n )\n )\n return;\n\n if (fixture) {\n const response = await resolveResponse(fixture, syntheticReq);\n\n // Error response\n if (isErrorResponse(response)) {\n const status = response.status ?? 500;\n journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\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 // Embedding response — use the fixture's embedding\n if (isEmbeddingResponse(response)) {\n journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\n headers: flattenHeaders(req.headers),\n body: syntheticReq,\n response: { status: 200, fixture },\n });\n const body = {\n model: embReq.model,\n embedding: [...response.embedding],\n };\n res.writeHead(200, { \"Content-Type\": \"application/json\" });\n res.end(JSON.stringify(body));\n return;\n }\n\n // Fixture matched but response type is not compatible with embeddings\n journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\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: {\n message:\n \"Fixture response did not match any known embedding type (must have embedding or error)\",\n type: \"server_error\",\n },\n }),\n );\n return;\n }\n\n // No fixture match — check strict mode first, then try proxy\n const effectiveStrict = resolveStrictMode(defaults.strict, req.headers);\n if (effectiveStrict) {\n const strictMessage = strictNoMatchMessage(skippedBySequenceOrTurn);\n logger.error(strictNoMatchLogLine(req.method ?? \"POST\", urlPath, skippedBySequenceOrTurn));\n journal.add({\n method: req.method ?? \"POST\",\n path: urlPath,\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 },\n }),\n );\n return;\n }\n\n if (defaults.record) {\n const outcome 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