experiment(confidence-engine): complete openai reconstruction apparatus

This commit is contained in:
2026-09-06 10:06:06 +01:00
parent a45dd903cf
commit 215c783d11
5 changed files with 281 additions and 7 deletions
+11
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@@ -134,6 +134,17 @@
- Its import-only proof succeeded with `startCaseResolved: true`: the real `startCase()` dependency chain resolves and no provider call occurs. Production runtime and the Ollama/Qwen default remain unchanged.
- Next boundary: exactly one live GPT-5.6 Terra reconstruction through this canonical helper.
## OpenAI CLI experiment selection
- The canonical helper now exposes experiment-only OpenAI selection through `START_CASE_EXPERIMENT_PROVIDER=openai`, reusing the existing OpenAI provider constructor and provider-injection seam. Its default behavior is unchanged.
- Import-only mode remains inert, production provider selection remains Ollama/Qwen, and no live calls occurred. Next boundary: exactly one live OpenAI call using the fixed manufacturing scenario.
## OpenAI strict reconstruction transport apparatus
- The first real OpenAI request reached Responses API but failed before inference with `invalid_json_schema`; the first reported incompatibility was optional `unexplainedTransitions[].entity` absent from `required`.
- OpenAI strict transport projection now derives structure from canonical Zod-generated JSON Schema and canonical input optionality from the Zod contract, including `.optional().default(...)`. Canonically omittable fields are required-but-nullable for transport; null placeholders are omitted only for those fields before canonical Zod validation, while genuinely required fields remain non-nullable.
- `reconstructionV2Schema` and Ollama behavior remain unchanged. `START_CASE_EXPERIMENT_PROVIDER=openai` is experiment-only selection; default behavior remains Ollama/Qwen. Deterministic closeout passed with zero live calls; next boundary is exactly one live GPT-5.6 Terra reconstruction.
## Current product architecture
Three distinct routes, not a single page:
+118 -2
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@@ -71,6 +71,122 @@ function recoverJson(raw) {
let _chatSupported = null;
const reconstructionJsonSchema = z.toJSONSchema(reconstructionV2Schema);
const openAIReconstructionJsonSchema = createOpenAIStrictSchema(
reconstructionJsonSchema,
reconstructionV2Schema,
);
/** @internal OpenAI Structured Outputs requires every object property. */
export function createOpenAIStrictSchema(schema, zodSchema = reconstructionV2Schema) {
const projected = structuredClone(schema);
projectOpenAIStrictSchema(projected, zodSchema, projected);
return projected;
}
/** @internal Remove OpenAI null placeholders for canonically optional fields only. */
export function normaliseOpenAITransportResponse(
value,
zodSchema = reconstructionV2Schema,
schema = reconstructionJsonSchema,
) {
return normaliseTransportValue(value, schema, zodSchema, schema);
}
function resolveSchema(schema, rootSchema) {
if (!schema?.$ref) return schema;
const path = schema.$ref.replace(/^#\//, "").split("/");
return path.reduce((value, key) => value?.[key], rootSchema) ?? schema;
}
function zodDef(schema) {
return schema?._zod?.def ?? schema?._def;
}
function unwrapZodSchema(schema) {
const def = zodDef(schema);
if (["optional", "nullable", "default"].includes(def?.type)) {
return unwrapZodSchema(def.innerType);
}
return schema;
}
function zodObjectShape(schema) {
const def = zodDef(unwrapZodSchema(schema));
return def?.type === "object" ? def.shape : null;
}
function zodArrayItem(schema) {
const def = zodDef(unwrapZodSchema(schema));
return def?.type === "array" ? def.element : null;
}
function zodAcceptsNull(schema) {
return schema?.isNullable?.() === true;
}
function projectOpenAIStrictSchema(schema, zodSchema, rootSchema) {
const resolved = resolveSchema(schema, rootSchema);
const shape = zodObjectShape(zodSchema);
if (resolved?.properties && shape) {
for (const [key, property] of Object.entries(resolved.properties)) {
const propertyZodSchema = shape[key];
if (propertyZodSchema?.isOptional?.() && !schemaAllowsNull(property, rootSchema)) {
resolved.properties[key] = { anyOf: [property, { type: "null" }] };
}
}
resolved.required = Object.keys(resolved.properties);
}
if (resolved?.items) {
projectOpenAIStrictSchema(resolved.items, zodArrayItem(zodSchema), rootSchema);
}
if (resolved?.properties && shape) {
for (const [key, property] of Object.entries(resolved.properties)) {
projectOpenAIStrictSchema(property, shape[key], rootSchema);
}
}
}
function schemaAllowsNull(schema, rootSchema) {
const resolved = resolveSchema(schema, rootSchema);
return (
resolved?.type === "null" ||
(Array.isArray(resolved?.type) && resolved.type.includes("null")) ||
[...(resolved?.anyOf ?? []), ...(resolved?.oneOf ?? [])].some((branch) =>
schemaAllowsNull(branch, rootSchema),
)
);
}
function normaliseTransportValue(value, schema, zodSchema, rootSchema) {
const resolved = resolveSchema(schema, rootSchema);
if (Array.isArray(value) && resolved?.items) {
return value.map((item) =>
normaliseTransportValue(item, resolved.items, zodArrayItem(zodSchema), rootSchema),
);
}
if (!value || typeof value !== "object" || !resolved?.properties) return value;
const shape = zodObjectShape(zodSchema);
const normalised = {};
for (const [key, item] of Object.entries(value)) {
const propertySchema = resolved.properties[key];
const propertyZodSchema = shape?.[key];
if (!propertySchema || !propertyZodSchema) {
normalised[key] = item;
} else if (item === null && propertyZodSchema.isOptional?.() && !zodAcceptsNull(propertyZodSchema)) {
continue;
} else {
normalised[key] = normaliseTransportValue(
item,
propertySchema,
propertyZodSchema,
rootSchema,
);
}
}
return normalised;
}
/** @internal Test-only seam for isolated provider capability scenarios. */
export function __resetChatSupportForTests() {
@@ -326,7 +442,7 @@ class OpenAIReconstructionProvider {
type: "json_schema",
name: "reconstruction",
strict: true,
schema: reconstructionJsonSchema,
schema: openAIReconstructionJsonSchema,
},
},
}),
@@ -350,7 +466,7 @@ class OpenAIReconstructionProvider {
}
return {
response: recoverJson(outputText),
response: normaliseOpenAITransportResponse(recoverJson(outputText)),
providerApiPath: "/v1/responses",
};
}
+20 -4
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@@ -62,8 +62,26 @@ async function runStartCaseExperiment(scenarioInput, experimentInstruction, opti
}
let startCase = options.startCase;
let reconstructionProvider = options.reconstructionProvider;
let reconstructionModelName = options.reconstructionModelName;
const isMock = process.env.START_CASE_EXPERIMENT_HELPER_MOCK === "1";
if (process.env.START_CASE_EXPERIMENT_PROVIDER === "openai") {
if (!process.env.OPENAI_API_KEY) {
throw new Error(
"START_CASE_EXPERIMENT_PROVIDER=openai requires OPENAI_API_KEY",
);
}
const { createOpenAIReconstructionProvider } = await import(
PROJECT_ROOT + "/lib/llm/provider.js"
);
reconstructionProvider = createOpenAIReconstructionProvider({
apiKey: process.env.OPENAI_API_KEY,
fetchImpl: fetch,
});
reconstructionModelName = "gpt-5.6-terra";
}
if (!startCase && isMock) {
// Deterministic mode: skip environment checks and use inline test double.
startCase = async (body) => {
@@ -100,8 +118,8 @@ async function runStartCaseExperiment(scenarioInput, experimentInstruction, opti
const endToEndStartedAt = Date.now();
try {
result = await startCase(scenarioInput, {
reconstructionProvider: options.reconstructionProvider,
reconstructionModelName: options.reconstructionModelName,
reconstructionProvider,
reconstructionModelName,
});
} finally {
// Clean up experiment env var after execution regardless of outcome
@@ -191,5 +209,3 @@ if (require.main === module) {
}
module.exports = { runStartCaseExperiment };
module.exports = { runStartCaseExperiment };
+75
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@@ -1,9 +1,13 @@
import { describe, expect, it, vi } from "vitest";
import {
__resetChatSupportForTests,
createOpenAIStrictSchema,
createOpenAIReconstructionProvider,
getProvider,
normaliseOpenAITransportResponse,
} from "@/lib/llm/provider.js";
import { reconstructionV2Schema } from "@/lib/reconstruction/schema.js";
import { z } from "zod";
describe("OllamaLlmProvider chat capability detection", () => {
it("uses the configured model for the chat probe and keeps the chat path", async () => {
@@ -121,6 +125,76 @@ describe("OllamaLlmProvider chat capability detection", () => {
});
describe("OpenAI reconstruction provider experiment seam", () => {
it("projects canonical optional fields as required but nullable", () => {
const nativeSchema = z.toJSONSchema(reconstructionV2Schema);
const projectedSchema = createOpenAIStrictSchema(
nativeSchema,
reconstructionV2Schema,
);
function resolveLocalRef(schema, root = projectedSchema) {
if (!schema.$ref) return schema;
return schema.$ref
.replace(/^#\//, "")
.split("/")
.reduce((value, key) => value?.[key], root);
}
function acceptsNull(schema, root = projectedSchema) {
const resolved = resolveLocalRef(schema, root);
return (
resolved?.type === "null" ||
(Array.isArray(resolved?.type) && resolved.type.includes("null")) ||
[...(resolved?.anyOf ?? []), ...(resolved?.oneOf ?? [])].some((branch) =>
acceptsNull(branch, root),
)
);
}
function assertAllPropertiesRequired(schema, root = projectedSchema) {
const resolved = resolveLocalRef(schema, root);
if (resolved?.properties) {
expect(resolved.required).toEqual(Object.keys(resolved.properties));
Object.values(resolved.properties).forEach((property) => assertAllPropertiesRequired(property, root));
}
(resolved?.anyOf ?? []).forEach((branch) => assertAllPropertiesRequired(branch, root));
(resolved?.oneOf ?? []).forEach((branch) => assertAllPropertiesRequired(branch, root));
if (resolved?.items) assertAllPropertiesRequired(resolved.items, root);
}
assertAllPropertiesRequired(projectedSchema);
const transition = projectedSchema.properties.reconstruction.properties.unexplainedTransitions.items;
expect(transition.required).toContain("entity");
expect(acceptsNull(transition.properties.entity)).toBe(true);
const inputClassification = resolveLocalRef(
projectedSchema.properties.inputClassification,
);
expect(inputClassification.required).toContain("secondaryTypes");
expect(acceptsNull(inputClassification.properties.secondaryTypes)).toBe(true);
expect(acceptsNull(transition.properties.id)).toBe(false);
});
it("removes only optional transport null placeholders", () => {
const schema = z.object({
optionalText: z.string().optional(),
nullableText: z.string().nullable(),
requiredText: z.string(),
children: z.array(z.object({ optionalChild: z.string().optional() })),
});
const nativeSchema = z.toJSONSchema(schema);
expect(normaliseOpenAITransportResponse({
optionalText: null,
nullableText: null,
requiredText: null,
children: [{ optionalChild: null }],
}, schema, nativeSchema)).toEqual({
nullableText: null,
requiredText: null,
children: [{}],
});
});
it("uses the Responses API with the canonical strict reconstruction schema", async () => {
const fetchSpy = vi.fn().mockResolvedValue({
ok: true,
@@ -158,6 +232,7 @@ describe("OpenAI reconstruction provider experiment seam", () => {
expect(schemaText).toContain("secondaryTypes");
expect(schemaText).toContain("confidence");
expect(schemaText).toContain("importance");
expect(request.text.format.schema).not.toEqual(z.toJSONSchema(reconstructionV2Schema));
expect(result).toEqual({
response: { reconstruction: "result" },
providerApiPath: "/v1/responses",
@@ -9,7 +9,7 @@
* with a deterministic inline double (zero live model calls).
*/
import { describe, expect, it, beforeAll, afterAll } from "vitest";
import { describe, expect, it, beforeAll, afterAll, vi } from "vitest";
import { execFile } from "child_process";
import { writeFile, unlink } from "fs/promises";
import { join, dirname } from "path";
@@ -159,6 +159,62 @@ describe("start-case-experiment-helper.cjs apparatus", () => {
// ── D — Success output ──────────────────────────────────────────
describe("D — success output", () => {
it("selects the existing OpenAI provider through the helper injection seam", async () => {
const { runStartCaseExperiment } = require(helperPath);
const previousProvider = process.env.START_CASE_EXPERIMENT_PROVIDER;
const previousKey = process.env.OPENAI_API_KEY;
process.env.START_CASE_EXPERIMENT_PROVIDER = "openai";
process.env.OPENAI_API_KEY = "test-key";
try {
const result = await runStartCaseExperiment(
{ scenario: "OpenAI provider selection scenario" },
null,
{
startCase: async (_input, dependencies) => {
expect(typeof dependencies.reconstructionProvider?.generateReconstruction).toBe("function");
expect(dependencies.reconstructionModelName).toBe("gpt-5.6-terra");
return {
success: true,
situationGraph: { nodes: [], edges: [] },
assessment: null,
selectedQuestion: null,
summary: "test",
};
},
},
);
expect(result.success).toBe(true);
} finally {
if (previousProvider === undefined) delete process.env.START_CASE_EXPERIMENT_PROVIDER;
else process.env.START_CASE_EXPERIMENT_PROVIDER = previousProvider;
if (previousKey === undefined) delete process.env.OPENAI_API_KEY;
else process.env.OPENAI_API_KEY = previousKey;
}
});
it("fails before startCase when OpenAI is selected without a key", async () => {
const { runStartCaseExperiment } = require(helperPath);
const previousProvider = process.env.START_CASE_EXPERIMENT_PROVIDER;
const previousKey = process.env.OPENAI_API_KEY;
process.env.START_CASE_EXPERIMENT_PROVIDER = "openai";
delete process.env.OPENAI_API_KEY;
const startCase = vi.fn();
try {
await expect(
runStartCaseExperiment({ scenario: "Missing key scenario" }, null, { startCase }),
).rejects.toThrow("START_CASE_EXPERIMENT_PROVIDER=openai requires OPENAI_API_KEY");
expect(startCase).not.toHaveBeenCalled();
} finally {
if (previousProvider === undefined) delete process.env.START_CASE_EXPERIMENT_PROVIDER;
else process.env.START_CASE_EXPERIMENT_PROVIDER = previousProvider;
if (previousKey === undefined) delete process.env.OPENAI_API_KEY;
else process.env.OPENAI_API_KEY = previousKey;
}
});
it("forwards an explicit reconstruction provider through the startCase path", async () => {
const { runStartCaseExperiment } = require(helperPath);
const reconstructionProvider = { generateReconstruction() {} };