mirror of
https://github.com/morluto/rea.git
synced 2026-11-15 11:13:21 +00:00
morluto
b138f52e12
* refactor: prune internal seams and preserve configuration ownership * fix(setup): keep YAML aliases and inherited registration settings on refresh - Reuse an unchanged YAML collection only while every alias in it still resolves after the edit; otherwise rebuild it so the alias becomes its value. A sibling anchor replaced or moved in the same refresh no longer leaves an unresolved alias in Hermes or Goose output. - Keep a connection selector whose existing value already chooses stdio (for example an inherited Hermes transport: stdio) instead of superseding it; remote selectors are still replaced. Explicit stdio selectors are therefore no longer rewritten (Kimi expectation updated). - When the whole Hermes registration is inherited through a merge, override it with that merge and write only the changed fields. * fix(setup): edit registration fields whose YAML key is an alias A key written as an alias to a string scalar (for example *field with field: &field env) was treated as a source-only key, so any change to its value was refused in Hermes and Goose. Resolve such keys to their string, keep the aliased spelling while its anchor survives the edit, and write the plain key when the same edit rebuilds the anchor. * test(process): bound cleanup-boundary waits and always release gates Both cancellation tests awaited a bare started promise and released their gates only on success, so a missed boundary waited for the outer deadline and could leave cleanup parked. Use awaitAcknowledgement and release and join the cleanup in finally. * fix(setup): repair only aliases an edit leaves unresolved Replace the pre-edit alias survival guess, which expanded aliases to sibling anchors that survive unchanged, with an exact repair: record what each alias in the replaced value resolves to, write the edit, then replace only aliases left without a preceding anchor by that value. - Keep an aliased key's source position, so its anchor stays ahead of later aliases. - Treat an aliased key as its string only when no other key in the map resolves to the same string; an ambiguous one stays guarded. - Override an inherited Hermes registration only when the requested entry keeps every inherited field, so an explicit replacement can drop remote selectors. * fix(setup): repair aliases whose binding an edit changes, keeping comments An alias whose own anchor was removed could resolve to an earlier anchor with the same name and silently change value. Record the node each alias resolved to and repair any alias that no longer resolves to that node. Carry the alias's comments and spacing onto the repaired value. * test(setup): split the Hermes anchor and merge refresh cases * fix(setup): refuse removing an overridden key its merge would restore The merge-retention check skipped keys the mapping also overrides, so dropping such a key (for example a remote url during an explicit stdio replacement) let the retained merge restore it. Check removal before skipping overridden keys, so the edit is refused with the existing message instead of producing a registration that cannot be applied.
1319 lines
44 KiB
TypeScript
1319 lines
44 KiB
TypeScript
import { createHash } from "node:crypto";
|
|
import { readFile, writeFile, unlink } from "node:fs/promises";
|
|
import { join } from "node:path";
|
|
import { afterAll, expect, it } from "vitest";
|
|
import { INSPECT_MODEL_ARTIFACT_CONTRACT } from "../../src/contracts/model/modelToolContracts.js";
|
|
import {
|
|
modelArtifactSchema,
|
|
type ModelArtifact,
|
|
} from "../../src/domain/model/modelArtifact.js";
|
|
import {
|
|
modelArtifactSummaryViewResultSchema,
|
|
analysisViewResultSchema,
|
|
} from "../../src/domain/analysisView/analysisViewResult.js";
|
|
import { createEvidence, parseEvidence } from "../../src/domain/evidence.js";
|
|
import { readEvidenceBundle } from "../../src/application/EvidenceBundleFiles.js";
|
|
import { connectLocalToolsMcp } from "../fixtures/localToolsMcp.js";
|
|
import { parseMcpToolError } from "../fixtures/mcpToolError.js";
|
|
import {
|
|
ggufFixture,
|
|
ggufKLayouts,
|
|
ggufShiftedTypeLayouts,
|
|
safetensorsFixture,
|
|
} from "../fixtures/model/model.js";
|
|
import { createTestTempDirectory } from "../fixtures/temporaryDirectory.js";
|
|
import { cliTest, createSharedMcpSession } from "../support/cli/cliFixture.js";
|
|
|
|
// Model queries are target-free; share immutable registration and schema setup.
|
|
// Portable export keeps its separate post-CLI connection below.
|
|
const modelMcp = createSharedMcpSession(async (registerCleanup) => {
|
|
const { call } = await connectLocalToolsMcp({}, registerCleanup);
|
|
return call;
|
|
});
|
|
afterAll(() => modelMcp.close());
|
|
|
|
cliTest(
|
|
"preserves lowercase hyphenated GGUF architecture metadata from the published writer",
|
|
async ({ cli }) => {
|
|
const root = await createTestTempDirectory(
|
|
"rea-model-hyphen-architecture-",
|
|
);
|
|
const base = ggufFixture();
|
|
for (const architecture of ["gpt-oss", "wavtokenizer-dec"] as const) {
|
|
const path = join(root, `${architecture}.gguf`);
|
|
const bytes = ggufFixture({
|
|
tensors: [],
|
|
metadata: [
|
|
{
|
|
key: "general.architecture",
|
|
type: 8,
|
|
value: base.text(architecture),
|
|
},
|
|
{
|
|
key: `${architecture}.context_length`,
|
|
type: 4,
|
|
value: base.u32(4096),
|
|
},
|
|
],
|
|
}).bytes;
|
|
await writeFile(path, bytes);
|
|
const response = await cli.run({
|
|
arguments: [
|
|
"inspect-model-artifact",
|
|
path,
|
|
"--detail",
|
|
"complete",
|
|
"--json",
|
|
],
|
|
});
|
|
expect(response.exitCode, response.stderr).toBe(0);
|
|
const report = modelArtifactSchema.parse(
|
|
INSPECT_MODEL_ARTIFACT_CONTRACT.outputSchema.parse(response.json)
|
|
.normalized_result,
|
|
);
|
|
expect(report.metadata.map(({ key, value }) => ({ key, value }))).toEqual(
|
|
[
|
|
{ key: "general.architecture", value: architecture },
|
|
{ key: `${architecture}.context_length`, value: 4096 },
|
|
],
|
|
);
|
|
expect(report.artifact.sha256).toBeNull();
|
|
}
|
|
},
|
|
);
|
|
|
|
cliTest(
|
|
"preserves unresolved Q8_1 layout through CLI, MCP summaries and retained tensor/type pages",
|
|
async ({ cli }) => {
|
|
const root = await createTestTempDirectory("rea-model-q8-layout-");
|
|
const call = await modelMcp.session.call();
|
|
for (const blockBytes of [36, 40]) {
|
|
const path = join(root, `blocks-${String(blockBytes)}.gguf`);
|
|
const base = ggufFixture();
|
|
// Released layouts share GGUF v3/type 9/quantization version 2.
|
|
// Trailing alignment space is not a storage-layout declaration.
|
|
const fixture = ggufFixture({
|
|
metadata: [
|
|
{ key: "general.quantization_version", type: 4, value: base.u32(2) },
|
|
],
|
|
tensors: [
|
|
{ name: "control", type: 0, shape: [4n], offset: 0n, bytes: 16 },
|
|
{
|
|
name: "weight",
|
|
type: 9,
|
|
shape: [320n],
|
|
offset: 32n,
|
|
bytes: 10 * blockBytes,
|
|
},
|
|
],
|
|
});
|
|
const bytes = Buffer.concat([fixture.bytes, Buffer.alloc(16)]);
|
|
await writeFile(path, bytes);
|
|
const cliResult = await cli.run({
|
|
arguments: [
|
|
"inspect-model-artifact",
|
|
path,
|
|
"--detail",
|
|
"complete",
|
|
"--hash",
|
|
"full",
|
|
"--json",
|
|
],
|
|
});
|
|
expect(cliResult.exitCode, cliResult.stderr).toBe(0);
|
|
const report = modelArtifactSchema.parse(
|
|
parseEvidence(cliResult.json).normalized_result,
|
|
);
|
|
const sha256 = createHash("sha256").update(bytes).digest("hex");
|
|
expect(report.artifact).toMatchObject({ path, sha256 });
|
|
expect(report.tensors[0]).toMatchObject({
|
|
byte_length: 16,
|
|
storage_validation: "consistent",
|
|
});
|
|
const weight = {
|
|
index: 1,
|
|
name: "weight",
|
|
type: "Q8_1",
|
|
type_id: 9,
|
|
shape: ["320"],
|
|
file_offset: fixture.dataOffset + 32,
|
|
byte_length: null,
|
|
byte_length_state: "unknown",
|
|
storage_validation: "unknown",
|
|
};
|
|
expect(report.tensors[1]).toMatchObject(weight);
|
|
expect(report.totals).toMatchObject({
|
|
parameter_count: "324",
|
|
tensor_bytes: null,
|
|
by_type: [
|
|
{ type: "F32", bytes: 16 },
|
|
{ type: "Q8_1", bytes: null },
|
|
],
|
|
});
|
|
const coverage = { storage_sizes: "partial", tensor_ranges: "partial" };
|
|
expect(report.coverage).toMatchObject(coverage);
|
|
const limitation = expect.stringContaining(
|
|
"Q8_1 has released 40-byte and 36-byte layouts",
|
|
);
|
|
expect(report.limitations).toContainEqual(limitation);
|
|
|
|
const response = await call("inspect_model_artifact", {
|
|
path,
|
|
hash: "full",
|
|
});
|
|
expect(response.isError, JSON.stringify(response)).not.toBe(true);
|
|
const summary = modelArtifactSummaryViewResultSchema.parse(
|
|
parseEvidence(response.structuredContent).normalized_result,
|
|
);
|
|
expect(summary.summary).toMatchObject({
|
|
artifact: { path, sha256 },
|
|
totals: { parameter_count: "324", tensor_bytes: null },
|
|
coverage,
|
|
});
|
|
expect(summary.summary.limitations).toContainEqual(limitation);
|
|
expect(Buffer.compare(await readFile(path), bytes)).toBe(0);
|
|
await unlink(path);
|
|
|
|
const source = {
|
|
kind: "retained-evidence",
|
|
evidence_id: summary.parent_evidence_id,
|
|
};
|
|
const tensorResponse = await call("inspect_analysis_view", {
|
|
source,
|
|
view: {
|
|
kind: "model-artifact",
|
|
collection: "tensors",
|
|
types: ["Q8_1"],
|
|
storage_validation: ["unknown"],
|
|
fields: Object.keys(weight).filter((field) => field !== "index"),
|
|
},
|
|
});
|
|
expect(tensorResponse.isError, JSON.stringify(tensorResponse)).not.toBe(
|
|
true,
|
|
);
|
|
const tensorView = analysisViewResultSchema.parse(
|
|
parseEvidence(tensorResponse.structuredContent).normalized_result,
|
|
);
|
|
if (tensorView.kind !== "model-artifact")
|
|
throw new Error("Incorrect tensor view");
|
|
expect(tensorView.items).toEqual([weight]);
|
|
expect(tensorView.source).toMatchObject({ path, sha256 });
|
|
expect(tensorView.source_coverage).toMatchObject(coverage);
|
|
expect(tensorView.limitations).toContainEqual(limitation);
|
|
|
|
const typeResponse = await call("inspect_analysis_view", {
|
|
source,
|
|
view: {
|
|
kind: "model-artifact",
|
|
collection: "types",
|
|
types: ["Q8_1"],
|
|
fields: ["type", "parameter_count", "bytes"],
|
|
},
|
|
});
|
|
expect(typeResponse.isError, JSON.stringify(typeResponse)).not.toBe(true);
|
|
const typeView = analysisViewResultSchema.parse(
|
|
parseEvidence(typeResponse.structuredContent).normalized_result,
|
|
);
|
|
if (typeView.kind !== "model-artifact")
|
|
throw new Error("Incorrect type view");
|
|
expect(typeView.items).toEqual([
|
|
{ index: 1, type: "Q8_1", parameter_count: "320", bytes: null },
|
|
]);
|
|
expect(typeView.source_coverage).toMatchObject(coverage);
|
|
}
|
|
},
|
|
);
|
|
|
|
const assertRetainedLayoutViews = async (
|
|
call: Awaited<ReturnType<typeof connectLocalToolsMcp>>["call"],
|
|
parentEvidenceId: string,
|
|
report: ModelArtifact,
|
|
sha256: string,
|
|
): Promise<void> => {
|
|
const { path } = report.artifact;
|
|
const { header, tensor_ranges, storage_sizes } = report.coverage;
|
|
const coverage = { header, tensor_ranges, storage_sizes };
|
|
const source = {
|
|
kind: "retained-evidence",
|
|
evidence_id: parentEvidenceId,
|
|
};
|
|
const types = ["Q2_K", "AMBIGUOUS_16", "AMBIGUOUS_24", "AMBIGUOUS_25"];
|
|
const tensorResponse = await call("inspect_analysis_view", {
|
|
source,
|
|
view: {
|
|
kind: "model-artifact",
|
|
collection: "tensors",
|
|
types,
|
|
storage_validation: ["unknown"],
|
|
fields: [
|
|
"type",
|
|
"type_id",
|
|
"shape",
|
|
"file_offset",
|
|
"byte_length",
|
|
"storage_validation",
|
|
],
|
|
},
|
|
});
|
|
expect(tensorResponse.isError, JSON.stringify(tensorResponse)).not.toBe(true);
|
|
const tensorView = analysisViewResultSchema.parse(
|
|
parseEvidence(tensorResponse.structuredContent).normalized_result,
|
|
);
|
|
if (tensorView.kind !== "model-artifact")
|
|
throw new Error("Incorrect tensor view");
|
|
expect(tensorView.items).toEqual(
|
|
report.tensors
|
|
.filter((tensor) => types.includes(tensor.type))
|
|
.map(
|
|
({
|
|
index,
|
|
type,
|
|
type_id,
|
|
shape,
|
|
file_offset,
|
|
byte_length,
|
|
storage_validation,
|
|
}) => ({
|
|
index,
|
|
type,
|
|
type_id,
|
|
shape,
|
|
file_offset,
|
|
byte_length,
|
|
storage_validation,
|
|
}),
|
|
),
|
|
);
|
|
expect(tensorView.source).toMatchObject({ path, sha256 });
|
|
expect(tensorView.source_coverage).toMatchObject(coverage);
|
|
const typeResponse = await call("inspect_analysis_view", {
|
|
source,
|
|
view: {
|
|
kind: "model-artifact",
|
|
collection: "types",
|
|
types,
|
|
fields: ["type", "bytes"],
|
|
},
|
|
});
|
|
expect(typeResponse.isError, JSON.stringify(typeResponse)).not.toBe(true);
|
|
const typeView = analysisViewResultSchema.parse(
|
|
parseEvidence(typeResponse.structuredContent).normalized_result,
|
|
);
|
|
if (typeView.kind !== "model-artifact")
|
|
throw new Error("Incorrect type view");
|
|
expect(typeView.items).toEqual(
|
|
report.totals.by_type.flatMap((row, index) =>
|
|
types.includes(row.type) ? [{ index, type: row.type, bytes: null }] : [],
|
|
),
|
|
);
|
|
expect(typeView.source_coverage).toMatchObject(coverage);
|
|
};
|
|
|
|
cliTest(
|
|
"preserves released K and shifted integer/IQ uncertainty through CLI and retained MCP views",
|
|
async ({ cli }) => {
|
|
const root = await createTestTempDirectory("rea-model-historical-layouts-");
|
|
const call = await modelMcp.session.call();
|
|
for (const layout of ["legacy", "modern"] as const) {
|
|
const path = join(root, `${layout}.gguf`);
|
|
const base = ggufFixture();
|
|
// Authored bodies follow released source sizes; historical producers are
|
|
// not executed. Both files carry the same version and global file type.
|
|
const declarations = [
|
|
{ name: "control", type: 0, shape: [4n], bytes: 16, label: "F32" },
|
|
{
|
|
name: "stable-integer",
|
|
type: 26,
|
|
shape: [3n],
|
|
bytes: 12,
|
|
label: "I32",
|
|
},
|
|
...ggufKLayouts.flatMap(({ id, name, bytes64, bytes256 }) =>
|
|
(layout === "legacy" ? [64, 256] : [256]).map((elements) => ({
|
|
name: `${name}-${String(elements)}`,
|
|
type: id,
|
|
shape: [BigInt(elements)],
|
|
bytes: layout === "legacy" ? (elements / 64) * bytes64 : bytes256,
|
|
label: name,
|
|
})),
|
|
),
|
|
...ggufShiftedTypeLayouts.map(
|
|
({ id, integerBytes, modernBytes256 }) => ({
|
|
name: `shifted-${String(id)}`,
|
|
type: id,
|
|
shape: [256n],
|
|
bytes: layout === "legacy" ? 256 * integerBytes : modernBytes256,
|
|
label: `AMBIGUOUS_${String(id)}`,
|
|
}),
|
|
),
|
|
];
|
|
let nextOffset = 0n;
|
|
const tensors = declarations.map((declaration) => {
|
|
const tensor = { ...declaration, offset: nextOffset };
|
|
nextOffset += BigInt(Math.ceil(declaration.bytes / 32) * 32);
|
|
return tensor;
|
|
});
|
|
const fixture = ggufFixture({
|
|
metadata: [
|
|
{ key: "general.quantization_version", type: 4, value: base.u32(2) },
|
|
{ key: "general.file_type", type: 4, value: base.u32(15) },
|
|
],
|
|
tensors,
|
|
});
|
|
await writeFile(path, fixture.bytes);
|
|
const response = await cli.run({
|
|
arguments: [
|
|
"inspect-model-artifact",
|
|
path,
|
|
"--detail",
|
|
"complete",
|
|
"--json",
|
|
],
|
|
});
|
|
expect(response.exitCode, response.stderr).toBe(0);
|
|
const report = modelArtifactSchema.parse(
|
|
parseEvidence(response.json).normalized_result,
|
|
);
|
|
expect(report.tensors.slice(0, 2)).toMatchObject([
|
|
{ type: "F32", byte_length: 16, storage_validation: "consistent" },
|
|
{
|
|
type: "I32",
|
|
type_id: 26,
|
|
byte_length: 12,
|
|
storage_validation: "consistent",
|
|
},
|
|
]);
|
|
const unresolved = tensors.slice(2).map((tensor, index) => ({
|
|
index: index + 2,
|
|
type: tensor.label,
|
|
type_id: tensor.type,
|
|
shape: tensor.shape.map(String),
|
|
file_offset: fixture.dataOffset + Number(tensor.offset),
|
|
byte_length: null,
|
|
storage_validation: "unknown",
|
|
}));
|
|
expect(report.tensors.slice(2)).toMatchObject(unresolved);
|
|
const coverage = {
|
|
header: "complete",
|
|
tensor_ranges: "partial",
|
|
storage_sizes: "partial",
|
|
};
|
|
expect(report.coverage).toMatchObject(coverage);
|
|
expect(report.totals.tensor_bytes).toBeNull();
|
|
for (const { id, modernName } of ggufShiftedTypeLayouts) {
|
|
expect(report.limitations).toContainEqual(
|
|
expect.stringMatching(
|
|
new RegExp(`type ID ${String(id)} has released .*${modernName}`),
|
|
),
|
|
);
|
|
}
|
|
|
|
const mcpResponse = await call("inspect_model_artifact", {
|
|
path,
|
|
hash: "full",
|
|
});
|
|
expect(mcpResponse.isError, JSON.stringify(mcpResponse)).not.toBe(true);
|
|
const summary = modelArtifactSummaryViewResultSchema.parse(
|
|
parseEvidence(mcpResponse.structuredContent).normalized_result,
|
|
);
|
|
const sha256 = createHash("sha256").update(fixture.bytes).digest("hex");
|
|
expect(summary.summary).toMatchObject({
|
|
artifact: { path, sha256 },
|
|
totals: { tensor_bytes: null },
|
|
coverage,
|
|
});
|
|
for (const limitation of report.limitations.filter(
|
|
(reason) =>
|
|
reason.includes("have released") || reason.includes("has released"),
|
|
))
|
|
expect(summary.summary.limitations).toContain(limitation);
|
|
expect(Buffer.compare(await readFile(path), fixture.bytes)).toBe(0);
|
|
await unlink(path);
|
|
await assertRetainedLayoutViews(
|
|
call,
|
|
summary.parent_evidence_id,
|
|
report,
|
|
sha256,
|
|
);
|
|
}
|
|
},
|
|
);
|
|
|
|
cliTest(
|
|
"preserves exact large safetensors dimensions while rejecting impossible file offsets",
|
|
async ({ cli }) => {
|
|
const root = await createTestTempDirectory("rea-model-shape-precision-");
|
|
const path = join(root, "empty.safetensors");
|
|
const fixture = safetensorsFixture(
|
|
'{"a":{"dtype":"F32","shape":[0,9007199254740992],"data_offsets":[0,0]},"b":{"dtype":"F32","shape":[18446744073709551615,0],"data_offsets":[0,0]}}',
|
|
Buffer.alloc(0),
|
|
);
|
|
await writeFile(path, fixture.bytes);
|
|
const result = await cli.run({
|
|
arguments: [
|
|
"inspect-model-artifact",
|
|
path,
|
|
"--detail",
|
|
"complete",
|
|
"--hash",
|
|
"full",
|
|
"--json",
|
|
],
|
|
});
|
|
expect(result.exitCode, result.stderr).toBe(0);
|
|
const report = modelArtifactSchema.parse(
|
|
INSPECT_MODEL_ARTIFACT_CONTRACT.outputSchema.parse(result.json)
|
|
.normalized_result,
|
|
);
|
|
expect(
|
|
report.tensors.map(
|
|
({ shape, parameter_count, byte_length, storage_validation }) => ({
|
|
shape,
|
|
parameter_count,
|
|
byte_length,
|
|
storage_validation,
|
|
}),
|
|
),
|
|
).toEqual([
|
|
{
|
|
shape: ["0", "9007199254740992"],
|
|
parameter_count: "0",
|
|
byte_length: 0,
|
|
storage_validation: "consistent",
|
|
},
|
|
{
|
|
shape: ["18446744073709551615", "0"],
|
|
parameter_count: "0",
|
|
byte_length: 0,
|
|
storage_validation: "consistent",
|
|
},
|
|
]);
|
|
expect(report.totals).toMatchObject({
|
|
parameter_count: "0",
|
|
tensor_bytes: 0,
|
|
});
|
|
expect(report.artifact.sha256).toBe(
|
|
createHash("sha256").update(fixture.bytes).digest("hex"),
|
|
);
|
|
const call = await modelMcp.session.call();
|
|
const response = await call("inspect_model_artifact", {
|
|
path,
|
|
detail: "complete",
|
|
hash: "full",
|
|
});
|
|
expect(response.isError, JSON.stringify(response)).not.toBe(true);
|
|
expect(parseEvidence(response.structuredContent).normalized_result).toEqual(
|
|
report,
|
|
);
|
|
|
|
await writeFile(
|
|
path,
|
|
safetensorsFixture(
|
|
'{"x":{"dtype":"F32","shape":[0],"data_offsets":[9007199254740992,9007199254740992]}}',
|
|
Buffer.alloc(0),
|
|
).bytes,
|
|
);
|
|
const offsetFailure = parseMcpToolError(
|
|
await call("inspect_model_artifact", { path }),
|
|
);
|
|
// The raw extent is outside this empty file, and that check runs before
|
|
// the offset is converted to a host number.
|
|
expect(offsetFailure.error).toMatchObject({
|
|
code: "target_unavailable",
|
|
category: "unsupported_target",
|
|
details: {
|
|
constraint: "file_format_rejected",
|
|
path,
|
|
reason: "Declared extent is outside the file",
|
|
},
|
|
});
|
|
},
|
|
);
|
|
|
|
it.each(["named", "default", "inventory-only", "absent"] as const)(
|
|
"reports actual chat-template presence in summaries and page context (%s)",
|
|
async (kind) => {
|
|
const root = await createTestTempDirectory("rea-model-templates-");
|
|
const path = join(root, "model.gguf");
|
|
const { text, u32, u64 } = ggufFixture();
|
|
const names = {
|
|
key: "tokenizer.chat_templates",
|
|
type: 9,
|
|
value: Buffer.concat([u32(8), u64(1n), text("tool_use")]),
|
|
};
|
|
const template = {
|
|
key:
|
|
kind === "default"
|
|
? "tokenizer.chat_template"
|
|
: "tokenizer.chat_template.tool_use",
|
|
type: 8,
|
|
value: text("{{ messages }}"),
|
|
};
|
|
const metadata =
|
|
kind === "named"
|
|
? [names, template]
|
|
: kind === "default"
|
|
? [template]
|
|
: kind === "inventory-only"
|
|
? [names]
|
|
: [];
|
|
await writeFile(path, ggufFixture({ metadata }).bytes);
|
|
const call = await modelMcp.session.call();
|
|
const response = await call("inspect_model_artifact", { path });
|
|
expect(response.isError, JSON.stringify(response)).not.toBe(true);
|
|
const summary = modelArtifactSummaryViewResultSchema.parse(
|
|
parseEvidence(response.structuredContent).normalized_result,
|
|
);
|
|
const present = kind === "named" || kind === "default";
|
|
expect(summary.summary.chat_template_present).toBe(present);
|
|
const pageResponse = await call("inspect_analysis_view", {
|
|
source: {
|
|
kind: "retained-evidence",
|
|
evidence_id: summary.parent_evidence_id,
|
|
},
|
|
view: {
|
|
kind: "model-artifact",
|
|
collection: "metadata",
|
|
fields: ["key", "value"],
|
|
},
|
|
});
|
|
expect(pageResponse.isError, JSON.stringify(pageResponse)).not.toBe(true);
|
|
const page = analysisViewResultSchema.parse(
|
|
parseEvidence(pageResponse.structuredContent).normalized_result,
|
|
);
|
|
if (page.kind !== "model-artifact") throw new Error("Incorrect model view");
|
|
expect(page.model.chat_template_present).toBe(present);
|
|
expect(
|
|
page.items.map((row) => ("key" in row ? row.key : undefined)),
|
|
).toEqual(metadata.map((row) => row.key));
|
|
},
|
|
);
|
|
|
|
it("keeps generated headline keys and imported compound metadata out of compact summaries", async () => {
|
|
const root = await createTestTempDirectory("rea-model-headlines-");
|
|
const path = join(root, "model");
|
|
const architecture = "a".repeat(12000);
|
|
const { text, u32 } = ggufFixture();
|
|
await writeFile(
|
|
path,
|
|
ggufFixture({
|
|
tensors: [],
|
|
metadata: [
|
|
{ key: "general.architecture", type: 8, value: text(architecture) },
|
|
{ key: `${architecture}.context_length`, type: 4, value: u32(2048) },
|
|
],
|
|
}).bytes,
|
|
);
|
|
const call = await modelMcp.session.call();
|
|
const compact = await call("inspect_model_artifact", { path });
|
|
expect(compact.isError, JSON.stringify(compact)).not.toBe(true);
|
|
const summary = modelArtifactSummaryViewResultSchema.parse(
|
|
parseEvidence(compact.structuredContent).normalized_result,
|
|
);
|
|
expect(summary.summary.headlines).toEqual([]);
|
|
const full = parseEvidence(
|
|
(await call("inspect_model_artifact", { path, detail: "complete" }))
|
|
.structuredContent,
|
|
);
|
|
const report = modelArtifactSchema.parse(full.normalized_result);
|
|
expect(report.metadata.map(({ key, value }) => ({ key, value }))).toEqual([
|
|
{ key: "general.architecture", value: architecture },
|
|
{ key: `${architecture}.context_length`, value: 2048 },
|
|
]);
|
|
report.metadata[0]!.value = { future: architecture };
|
|
const imported = createEvidence(undefined, full.provider, {
|
|
operation: "inspect_model_artifact",
|
|
parameters: full.parameters,
|
|
result: report,
|
|
});
|
|
const page = await call("inspect_analysis_view", {
|
|
source: { kind: "inline", evidence: imported },
|
|
view: { kind: "summary" },
|
|
});
|
|
expect(page.isError, JSON.stringify(page)).not.toBe(true);
|
|
const importedSummary = modelArtifactSummaryViewResultSchema.parse(
|
|
parseEvidence(page.structuredContent).normalized_result,
|
|
);
|
|
expect(importedSummary.summary.headlines).toEqual([]);
|
|
});
|
|
|
|
it("rejects noncanonical imported model indexes and duplicate identities through public MCP", async () => {
|
|
const root = await createTestTempDirectory("rea-model-import-");
|
|
const path = join(root, "model");
|
|
await writeFile(path, ggufFixture().bytes);
|
|
const call = await modelMcp.session.call();
|
|
const response = await call("inspect_model_artifact", {
|
|
path,
|
|
detail: "complete",
|
|
});
|
|
const complete = parseEvidence(response.structuredContent);
|
|
const report = modelArtifactSchema.parse(complete.normalized_result);
|
|
const corruptions: ((value: ModelArtifact) => void)[] = [
|
|
(value) => {
|
|
value.tensors[0]!.index = 7;
|
|
},
|
|
(value) => {
|
|
value.metadata[0]!.index = 7;
|
|
},
|
|
(value) => {
|
|
value.tensors[1]!.name = value.tensors[0]!.name;
|
|
},
|
|
(value) => {
|
|
value.metadata[1]!.key = value.metadata[0]!.key;
|
|
},
|
|
(value) => {
|
|
value.totals.by_type[1]!.type = value.totals.by_type[0]!.type;
|
|
},
|
|
];
|
|
for (const corrupt of corruptions) {
|
|
const result = structuredClone(report);
|
|
corrupt(result);
|
|
const evidence = createEvidence(undefined, complete.provider, {
|
|
operation: "inspect_model_artifact",
|
|
parameters: complete.parameters,
|
|
result,
|
|
});
|
|
const failure = parseMcpToolError(
|
|
await call("inspect_analysis_view", {
|
|
source: { kind: "inline", evidence },
|
|
view: {
|
|
kind: "model-artifact",
|
|
collection: "tensors",
|
|
names: ["weight"],
|
|
},
|
|
}),
|
|
);
|
|
expect(failure.error).toMatchObject({ code: "invalid_request" });
|
|
}
|
|
await assertHistoricalModelPages(call, complete.evidence_id, report);
|
|
});
|
|
|
|
it("bounds compact model warnings and omits unselected long labels while retaining complete Evidence", async () => {
|
|
const root = await createTestTempDirectory("rea-model-long-labels-");
|
|
const path = join(root, "model");
|
|
const name = "tensor".repeat(4000);
|
|
const type = "FUTURE".repeat(4000);
|
|
const key = "metadata".repeat(3000);
|
|
await writeFile(
|
|
path,
|
|
safetensorsFixture(
|
|
JSON.stringify({
|
|
__metadata__: { [key]: "kept" },
|
|
[name]: { dtype: type, shape: [0], data_offsets: [0, 0] },
|
|
}),
|
|
Buffer.alloc(0),
|
|
).bytes,
|
|
);
|
|
const call = await modelMcp.session.call();
|
|
const response = await call("inspect_model_artifact", { path });
|
|
expect(response.isError, JSON.stringify(response)).not.toBe(true);
|
|
expect(JSON.stringify(response).length).toBeLessThan(16_000);
|
|
const summary = modelArtifactSummaryViewResultSchema.parse(
|
|
parseEvidence(response.structuredContent).normalized_result,
|
|
);
|
|
expect(summary.summary.coverage.storage_sizes).toBe("partial");
|
|
expect(summary.summary.limitations.join(" ")).toContain(
|
|
summary.parent_evidence_id,
|
|
);
|
|
const source = {
|
|
kind: "retained-evidence",
|
|
evidence_id: summary.parent_evidence_id,
|
|
};
|
|
for (const collection of ["tensors", "metadata", "types"] as const) {
|
|
const page = await call("inspect_analysis_view", {
|
|
source,
|
|
view: { kind: "model-artifact", collection, fields: [], limit: 1 },
|
|
});
|
|
expect(page.isError, JSON.stringify(page)).not.toBe(true);
|
|
expect(JSON.stringify(page).length).toBeLessThan(16_000);
|
|
const view = analysisViewResultSchema.parse(
|
|
parseEvidence(page.structuredContent).normalized_result,
|
|
);
|
|
if (view.kind !== "model-artifact") throw new Error("Incorrect view");
|
|
expect(view.items).toEqual([{ index: 0 }]);
|
|
expect(view.source_coverage.storage_sizes).toBe("partial");
|
|
expect(view.limitations.join(" ")).toContain(summary.parent_evidence_id);
|
|
}
|
|
const full = await call("inspect_model_artifact", {
|
|
path,
|
|
detail: "complete",
|
|
});
|
|
expect(full.isError, JSON.stringify(full)).not.toBe(true);
|
|
const report = modelArtifactSchema.parse(
|
|
parseEvidence(full.structuredContent).normalized_result,
|
|
);
|
|
expect(report.tensors[0]).toMatchObject({ name, type });
|
|
expect(report.metadata[0]).toMatchObject({ key, value: "kept" });
|
|
expect(report.limitations.join(" ")).toContain(type);
|
|
});
|
|
|
|
const assertHistoricalModelPages = async (
|
|
call: Awaited<ReturnType<typeof connectLocalToolsMcp>>["call"],
|
|
parentEvidenceId: string,
|
|
report: ModelArtifact,
|
|
): Promise<void> => {
|
|
const pages = [];
|
|
for (let offset = 0; offset < report.tensors.length; offset++) {
|
|
const page = await call("inspect_analysis_view", {
|
|
source: {
|
|
kind: "retained-evidence",
|
|
evidence_id: parentEvidenceId,
|
|
},
|
|
view: {
|
|
kind: "model-artifact",
|
|
collection: "tensors",
|
|
offset,
|
|
limit: 1,
|
|
fields: ["name", "type", "shape", "file_offset"],
|
|
},
|
|
});
|
|
expect(page.isError, JSON.stringify(page)).not.toBe(true);
|
|
const selected = analysisViewResultSchema.parse(
|
|
parseEvidence(page.structuredContent).normalized_result,
|
|
);
|
|
if (selected.kind !== "model-artifact") throw new Error("Incorrect view");
|
|
expect(selected.source.header_sha256).toBe(report.artifact.header_sha256);
|
|
expect(selected.source.sha256).toBeNull();
|
|
pages.push(...selected.items);
|
|
}
|
|
expect(pages).toEqual(
|
|
report.tensors.map(({ index, name, type, shape, file_offset }) => ({
|
|
index,
|
|
name,
|
|
type,
|
|
shape,
|
|
file_offset,
|
|
})),
|
|
);
|
|
const selected = await call("inspect_analysis_view", {
|
|
source: {
|
|
kind: "retained-evidence",
|
|
evidence_id: parentEvidenceId,
|
|
},
|
|
view: {
|
|
kind: "model-artifact",
|
|
collection: "tensors",
|
|
names: ["weight", "absent"],
|
|
indices: [0, 1],
|
|
fields: [],
|
|
},
|
|
});
|
|
const selectedView = analysisViewResultSchema.parse(
|
|
parseEvidence(selected.structuredContent).normalized_result,
|
|
);
|
|
if (selectedView.kind !== "model-artifact") throw new Error("Incorrect view");
|
|
expect(selectedView.items).toEqual(
|
|
report.tensors
|
|
.filter((row) => row.name === "weight")
|
|
.map(({ index }) => ({ index })),
|
|
);
|
|
const empty = await call("inspect_analysis_view", {
|
|
source: {
|
|
kind: "retained-evidence",
|
|
evidence_id: parentEvidenceId,
|
|
},
|
|
view: {
|
|
kind: "model-artifact",
|
|
collection: "metadata",
|
|
keys: [],
|
|
offset: 100,
|
|
},
|
|
});
|
|
expect(empty.isError, JSON.stringify(empty)).not.toBe(true);
|
|
const emptyView = analysisViewResultSchema.parse(
|
|
parseEvidence(empty.structuredContent).normalized_result,
|
|
);
|
|
expect(emptyView.coverage).toMatchObject({ total: 0, exhausted: true });
|
|
const unverified = await call("inspect_analysis_view", {
|
|
source: {
|
|
kind: "retained-evidence",
|
|
evidence_id: parentEvidenceId,
|
|
},
|
|
view: {
|
|
kind: "model-artifact",
|
|
collection: "tensors",
|
|
storage_validation: ["unknown"],
|
|
fields: ["name", "storage_validation", "byte_length"],
|
|
},
|
|
});
|
|
expect(unverified.isError, JSON.stringify(unverified)).not.toBe(true);
|
|
const unverifiedView = analysisViewResultSchema.parse(
|
|
parseEvidence(unverified.structuredContent).normalized_result,
|
|
);
|
|
if (unverifiedView.kind !== "model-artifact")
|
|
throw new Error("Incorrect storage selection");
|
|
expect(unverifiedView.items).toEqual(
|
|
report.tensors
|
|
.filter((row) => row.storage_validation === "unknown")
|
|
.map(({ index, name, storage_validation, byte_length }) => ({
|
|
index,
|
|
name,
|
|
storage_validation,
|
|
byte_length,
|
|
})),
|
|
);
|
|
const histogram = await call("inspect_analysis_view", {
|
|
source: {
|
|
kind: "retained-evidence",
|
|
evidence_id: parentEvidenceId,
|
|
},
|
|
view: {
|
|
kind: "model-artifact",
|
|
collection: "types",
|
|
types: ["F32"],
|
|
fields: ["type", "tensors", "parameter_count", "bytes"],
|
|
},
|
|
});
|
|
expect(histogram.isError, JSON.stringify(histogram)).not.toBe(true);
|
|
const histogramView = analysisViewResultSchema.parse(
|
|
parseEvidence(histogram.structuredContent).normalized_result,
|
|
);
|
|
if (histogramView.kind !== "model-artifact")
|
|
throw new Error("Incorrect histogram view");
|
|
expect(histogramView.items).toEqual(
|
|
report.totals.by_type.flatMap((row, index) =>
|
|
row.type === "F32" ? [{ index, ...row }] : [],
|
|
),
|
|
);
|
|
};
|
|
|
|
cliTest(
|
|
"shares scoped model facts through real CLI/MCP and pages retained metadata after source removal",
|
|
async ({ cli }) => {
|
|
const root = await createTestTempDirectory("rea-model-cli-");
|
|
const call = await modelMcp.session.call();
|
|
for (const [format, fixture] of [
|
|
["gguf", ggufFixture()],
|
|
["safetensors", safetensorsFixture()],
|
|
[
|
|
"safetensors",
|
|
safetensorsFixture(
|
|
'{"future":{"dtype":"FUTURE4","shape":[2],"data_offsets":[0,4]}}',
|
|
Buffer.alloc(4),
|
|
),
|
|
],
|
|
] as const) {
|
|
const path = join(root, `${format}.arbitrary`);
|
|
await writeFile(path, fixture.bytes);
|
|
const result = await cli.run({
|
|
arguments: [
|
|
"inspect-model-artifact",
|
|
path,
|
|
"--detail",
|
|
"complete",
|
|
"--json",
|
|
],
|
|
});
|
|
expect(result.exitCode, result.stderr).toBe(0);
|
|
const evidence = INSPECT_MODEL_ARTIFACT_CONTRACT.outputSchema.parse(
|
|
result.json,
|
|
);
|
|
const report = modelArtifactSchema.parse(evidence.normalized_result);
|
|
expect(report.format).toBe(format);
|
|
expect(report.artifact.sha256).toBeNull();
|
|
expect(evidence.subject).toBeNull();
|
|
const complete = await call("inspect_model_artifact", {
|
|
path,
|
|
detail: "complete",
|
|
});
|
|
expect(complete.isError, JSON.stringify(complete)).not.toBe(true);
|
|
expect(
|
|
parseEvidence(complete.structuredContent).normalized_result,
|
|
).toEqual(report);
|
|
const hashed = await call("inspect_model_artifact", {
|
|
path,
|
|
detail: "complete",
|
|
hash: "full",
|
|
});
|
|
expect(hashed.isError, JSON.stringify(hashed)).not.toBe(true);
|
|
expect(
|
|
parseEvidence(hashed.structuredContent).subject?.digest.sha256,
|
|
).toBe(createHash("sha256").update(fixture.bytes).digest("hex"));
|
|
const summary = await call("inspect_model_artifact", { path });
|
|
expect(summary.isError, JSON.stringify(summary)).not.toBe(true);
|
|
const retained = modelArtifactSummaryViewResultSchema.parse(
|
|
parseEvidence(summary.structuredContent).normalized_result,
|
|
);
|
|
expect(retained.summary.counts.tensors).toBe(report.tensors.length);
|
|
const direct = await call("inspect_model_artifact", {
|
|
path,
|
|
view: {
|
|
collection: "tensors",
|
|
names: ["weight"],
|
|
fields: ["name", "type", "shape", "file_offset"],
|
|
},
|
|
});
|
|
expect(direct.isError, JSON.stringify(direct)).not.toBe(true);
|
|
const directView = analysisViewResultSchema.parse(
|
|
parseEvidence(direct.structuredContent).normalized_result,
|
|
);
|
|
if (directView.kind !== "model-artifact")
|
|
throw new Error("Incorrect direct selection");
|
|
expect(directView.model.counts.tensors).toBe(report.tensors.length);
|
|
expect(directView.items).toEqual(
|
|
report.tensors
|
|
.filter((row) => row.name === "weight")
|
|
.map(({ index, name, type, shape, file_offset }) => ({
|
|
index,
|
|
name,
|
|
type,
|
|
shape,
|
|
file_offset,
|
|
})),
|
|
);
|
|
expect(directView.parent_evidence_id).toBe(
|
|
parseEvidence(complete.structuredContent).evidence_id,
|
|
);
|
|
await unlink(path);
|
|
await assertHistoricalModelPages(
|
|
call,
|
|
retained.parent_evidence_id,
|
|
report,
|
|
);
|
|
}
|
|
},
|
|
);
|
|
|
|
cliTest(
|
|
"preserves optional safetensors fields and aligns empty GGUF data in CLI and MCP",
|
|
async ({ cli }) => {
|
|
const root = await createTestTempDirectory("rea-model-boundary-compat-");
|
|
const call = await modelMcp.session.call();
|
|
const safetensors = safetensorsFixture(
|
|
'{"__metadata__":null,"weight":{"dtype":"F32","shape":[1],"data_offsets":[0,4],"note":{"source":"local","flags":[null,false,-1,1.25]}}}',
|
|
Buffer.alloc(4),
|
|
);
|
|
const emptyGgufHeader = ggufFixture({ tensors: [], metadata: [] });
|
|
const alignedOffset = Math.ceil(emptyGgufHeader.header.length / 32) * 32;
|
|
const emptyGguf = Buffer.concat([
|
|
emptyGgufHeader.header,
|
|
Buffer.alloc(alignedOffset - emptyGgufHeader.header.length),
|
|
]);
|
|
for (const [name, bytes] of [
|
|
["optional.safetensors", safetensors.bytes],
|
|
["empty.gguf", emptyGguf],
|
|
] as const) {
|
|
const path = join(root, name);
|
|
await writeFile(path, bytes);
|
|
const result = await cli.run({
|
|
arguments: [
|
|
"inspect-model-artifact",
|
|
path,
|
|
"--detail",
|
|
"complete",
|
|
"--json",
|
|
],
|
|
});
|
|
expect(result.exitCode, result.stderr).toBe(0);
|
|
const report = modelArtifactSchema.parse(
|
|
INSPECT_MODEL_ARTIFACT_CONTRACT.outputSchema.parse(result.json)
|
|
.normalized_result,
|
|
);
|
|
if (name.endsWith("safetensors")) {
|
|
expect(report.metadata).toEqual([]);
|
|
expect(report.tensors[0]?.name).toBe("weight");
|
|
expect(report.artifact.header_sha256).toBe(
|
|
createHash("sha256").update(safetensors.header).digest("hex"),
|
|
);
|
|
} else {
|
|
expect(report.tensors).toEqual([]);
|
|
expect(report.tensor_data_offset).toBe(alignedOffset);
|
|
expect(report.artifact.header_length).toBe(
|
|
emptyGgufHeader.header.length,
|
|
);
|
|
expect(report.artifact.header_sha256).toBe(
|
|
createHash("sha256").update(emptyGgufHeader.header).digest("hex"),
|
|
);
|
|
}
|
|
const response = await call("inspect_model_artifact", {
|
|
path,
|
|
detail: "complete",
|
|
});
|
|
expect(response.isError, JSON.stringify(response)).not.toBe(true);
|
|
expect(
|
|
parseEvidence(response.structuredContent).normalized_result,
|
|
).toEqual(report);
|
|
}
|
|
|
|
const mapPath = join(root, "same-key-map.safetensors");
|
|
await writeFile(
|
|
mapPath,
|
|
safetensorsFixture(
|
|
'{"__metadata__":{"json_number":"1.25"}}',
|
|
Buffer.alloc(0),
|
|
).bytes,
|
|
);
|
|
const mapCli = await cli.run({
|
|
arguments: [
|
|
"inspect-model-artifact",
|
|
mapPath,
|
|
"--detail",
|
|
"complete",
|
|
"--json",
|
|
],
|
|
});
|
|
expect(mapCli.exitCode, mapCli.stderr).toBe(0);
|
|
const mapReport = modelArtifactSchema.parse(
|
|
INSPECT_MODEL_ARTIFACT_CONTRACT.outputSchema.parse(mapCli.json)
|
|
.normalized_result,
|
|
);
|
|
expect(
|
|
mapReport.metadata.map(({ key, value }) => ({ key, value })),
|
|
).toEqual([{ key: "json_number", value: "1.25" }]);
|
|
const mapMcp = await call("inspect_model_artifact", {
|
|
path: mapPath,
|
|
detail: "complete",
|
|
});
|
|
expect(mapMcp.isError, JSON.stringify(mapMcp)).not.toBe(true);
|
|
expect(parseEvidence(mapMcp.structuredContent).normalized_result).toEqual(
|
|
mapReport,
|
|
);
|
|
|
|
for (const [name, numeric] of [
|
|
["decimal", "1.25"],
|
|
["negative", "-1"],
|
|
["overflow", "18446744073709551616"],
|
|
] as const) {
|
|
const malformedPath = join(root, `${name}-metadata.safetensors`);
|
|
await writeFile(
|
|
malformedPath,
|
|
safetensorsFixture(`{"__metadata__":${numeric}}`, Buffer.alloc(0))
|
|
.bytes,
|
|
);
|
|
const malformedCli = await cli.run({
|
|
arguments: ["inspect-model-artifact", malformedPath, "--json"],
|
|
});
|
|
expect(malformedCli.exitCode).toBe(1);
|
|
expect(malformedCli.json).toMatchObject({
|
|
code: "target_unavailable",
|
|
category: "unsupported_target",
|
|
details: { constraint: "file_format_rejected" },
|
|
});
|
|
const malformedMcp = parseMcpToolError(
|
|
await call("inspect_model_artifact", { path: malformedPath }),
|
|
);
|
|
expect(malformedMcp.error).toMatchObject({
|
|
code: "target_unavailable",
|
|
category: "unsupported_target",
|
|
details: { constraint: "file_format_rejected" },
|
|
});
|
|
}
|
|
},
|
|
);
|
|
|
|
cliTest(
|
|
"inspects unpadded zero-tensor vocab GGUF through CLI and MCP",
|
|
async ({ cli }) => {
|
|
const root = await createTestTempDirectory("rea-model-vocab-only-");
|
|
const call = await modelMcp.session.call();
|
|
const base = ggufFixture();
|
|
const vocab = ggufFixture({
|
|
tensors: [],
|
|
metadata: [
|
|
{ key: "general.type", type: 8, value: base.text("vocab") },
|
|
{
|
|
key: "tokenizer.ggml.model",
|
|
type: 8,
|
|
value: base.text("gpt2"),
|
|
},
|
|
],
|
|
});
|
|
expect(vocab.header.length).toBe(105);
|
|
expect(vocab.bytes.length).toBe(128);
|
|
const padded = Buffer.concat([
|
|
vocab.header,
|
|
Buffer.alloc(vocab.bytes.length - vocab.header.length),
|
|
]);
|
|
const files = [
|
|
["vocab-unpadded.gguf", vocab.header, vocab.header.length],
|
|
["vocab-padded.gguf", padded, vocab.bytes.length],
|
|
] as const;
|
|
|
|
for (const [name, bytes, expectedOffset] of files) {
|
|
const path = join(root, name);
|
|
await writeFile(path, bytes);
|
|
const cliResult = await cli.run({
|
|
arguments: [
|
|
"inspect-model-artifact",
|
|
path,
|
|
"--detail",
|
|
"complete",
|
|
"--hash",
|
|
"full",
|
|
"--json",
|
|
],
|
|
});
|
|
expect(cliResult.exitCode, cliResult.stderr).toBe(0);
|
|
const report = modelArtifactSchema.parse(
|
|
INSPECT_MODEL_ARTIFACT_CONTRACT.outputSchema.parse(cliResult.json)
|
|
.normalized_result,
|
|
);
|
|
expect(report.metadata.map(({ key, value }) => ({ key, value }))).toEqual(
|
|
[
|
|
{ key: "general.type", value: "vocab" },
|
|
{ key: "tokenizer.ggml.model", value: "gpt2" },
|
|
],
|
|
);
|
|
expect(report.tensors).toEqual([]);
|
|
expect(report.tensor_data_offset).toBe(expectedOffset);
|
|
expect(report.artifact.header_length).toBe(vocab.header.length);
|
|
expect(report.artifact.header_sha256).toBe(
|
|
createHash("sha256").update(vocab.header).digest("hex"),
|
|
);
|
|
expect(report.artifact.sha256).toBe(
|
|
createHash("sha256").update(bytes).digest("hex"),
|
|
);
|
|
const mcpResult = await call("inspect_model_artifact", {
|
|
path,
|
|
detail: "complete",
|
|
hash: "full",
|
|
});
|
|
expect(mcpResult.isError, JSON.stringify(mcpResult)).not.toBe(true);
|
|
expect(
|
|
parseEvidence(mcpResult.structuredContent).normalized_result,
|
|
).toEqual(report);
|
|
}
|
|
|
|
const malformed = [
|
|
["partial-padding.gguf", Buffer.concat([vocab.header, Buffer.alloc(1)])],
|
|
[
|
|
"truncated-tensor.gguf",
|
|
ggufFixture({
|
|
metadata: [],
|
|
tensors: [
|
|
{ name: "weight", type: 0, shape: [4n], offset: 0n, bytes: 16 },
|
|
],
|
|
}).header,
|
|
],
|
|
] as const;
|
|
for (const [name, bytes] of malformed) {
|
|
const path = join(root, name);
|
|
await writeFile(path, bytes);
|
|
const cliResult = await cli.run({
|
|
arguments: ["inspect-model-artifact", path, "--json"],
|
|
});
|
|
expect(cliResult.exitCode).toBe(1);
|
|
expect(cliResult.json).toMatchObject({
|
|
code: "target_unavailable",
|
|
category: "unsupported_target",
|
|
details: { constraint: "file_format_rejected" },
|
|
});
|
|
const mcpResult = parseMcpToolError(
|
|
await call("inspect_model_artifact", { path }),
|
|
);
|
|
expect(mcpResult.error).toMatchObject({
|
|
code: "target_unavailable",
|
|
category: "unsupported_target",
|
|
details: { constraint: "file_format_rejected" },
|
|
});
|
|
}
|
|
},
|
|
);
|
|
|
|
cliTest(
|
|
"exports complete model Evidence for portable paging and returns typed malformed errors",
|
|
async ({ cli }) => {
|
|
const root = await createTestTempDirectory("rea-model-export-");
|
|
const path = join(root, "model");
|
|
const output = join(root, "evidence.json");
|
|
await writeFile(path, ggufFixture().bytes);
|
|
const result = await cli.run({
|
|
arguments: [
|
|
"inspect-model-artifact",
|
|
path,
|
|
"--detail",
|
|
"summary",
|
|
"--view",
|
|
JSON.stringify({
|
|
collection: "metadata",
|
|
keys: ["tokenizer.chat_template"],
|
|
fields: ["key", "value"],
|
|
}),
|
|
"--evidence_output",
|
|
output,
|
|
"--json",
|
|
],
|
|
});
|
|
expect(result.exitCode, result.stderr).toBe(0);
|
|
const receipt = result.json as { summary: unknown };
|
|
const delivered = analysisViewResultSchema.parse(
|
|
parseEvidence(receipt.summary).normalized_result,
|
|
);
|
|
if (delivered.kind !== "model-artifact")
|
|
throw new Error("Missing CLI direct selection");
|
|
expect(delivered.items).toEqual([
|
|
{ index: 5, key: "tokenizer.chat_template", value: "{{ messages }}" },
|
|
]);
|
|
const exported = await readEvidenceBundle(output);
|
|
if (!exported.ok) throw exported.error;
|
|
const complete = exported.value.records.find(
|
|
(evidence) => evidence.operation === "inspect_model_artifact",
|
|
);
|
|
if (complete === undefined)
|
|
throw new Error("Missing complete exported model Evidence");
|
|
const recordPath = join(root, "model-record.json");
|
|
await writeFile(recordPath, JSON.stringify(complete));
|
|
const { call } = await connectLocalToolsMcp();
|
|
await unlink(path);
|
|
const page = await call("inspect_analysis_view", {
|
|
source: { kind: "evidence-file", path: recordPath },
|
|
view: {
|
|
kind: "model-artifact",
|
|
collection: "metadata",
|
|
keys: ["tokenizer.chat_template", "custom.exact"],
|
|
fields: ["key", "type", "value", "source_offset", "source_length"],
|
|
},
|
|
});
|
|
expect(page.isError, JSON.stringify(page)).not.toBe(true);
|
|
const selected = analysisViewResultSchema.parse(
|
|
parseEvidence(page.structuredContent).normalized_result,
|
|
);
|
|
if (selected.kind !== "model-artifact") throw new Error("Incorrect view");
|
|
expect(selected.items.map((row) => ("key" in row ? row.key : ""))).toEqual([
|
|
"custom.exact",
|
|
"tokenizer.chat_template",
|
|
]);
|
|
await writeFile(
|
|
path,
|
|
safetensorsFixture(
|
|
'{"x":{"dtype":"F32","shape":[3],"data_offsets":[4,16]}}',
|
|
).bytes,
|
|
);
|
|
const malformed = parseMcpToolError(
|
|
await call("inspect_model_artifact", { path }),
|
|
);
|
|
expect(malformed.error).toMatchObject({
|
|
code: "target_unavailable",
|
|
category: "unsupported_target",
|
|
details: { constraint: "file_format_rejected" },
|
|
});
|
|
},
|
|
);
|
|
|
|
cliTest(
|
|
"rejects malformed model view JSON before opening the selected path",
|
|
async ({ cli }) => {
|
|
const root = await createTestTempDirectory("rea-model-view-json-");
|
|
const missing = join(root, "not-created.gguf");
|
|
const result = await cli.run({
|
|
arguments: ["inspect-model-artifact", missing, "--view", "{", "--json"],
|
|
});
|
|
|
|
expect(result.exitCode).toBe(1);
|
|
expect(result.json).toMatchObject({
|
|
code: "invalid_request",
|
|
details: {
|
|
operation: "inspect_model_artifact",
|
|
issues: [
|
|
{
|
|
path: ["view"],
|
|
reason: "invalid_format",
|
|
message: "view must be a JSON model page selection",
|
|
},
|
|
],
|
|
},
|
|
});
|
|
expect(JSON.stringify(result.json)).not.toContain("ENOENT");
|
|
},
|
|
);
|