fix: harden model catalog projections

backend/test/catalog-repository.integration.test.ts

@@ -1,4 +1,5 @@
 import { spawnSync } from "node:child_process";
+import { randomUUID } from "node:crypto";
 import { PostgreSqlContainer } from "@testcontainers/postgresql";
 import { CamelCasePlugin, Kysely, PostgresDialect, sql } from "kysely";
 import { Pool } from "pg";
@@ -33,7 +34,30 @@ test.skipIf(!dockerAvailable)("PostgreSQL migration enforces one database per wo
     await upDescriptionGeneration(db);
     await upSensitiveSuggestionRuns(db);
     await upAiTokenUsage(db);
+    const historicalDatabaseId = randomUUID();
+    await db.insertInto("workspaceDatabases").values({
+      id: historicalDatabaseId,
+      workspaceId: "migration-history",
+      engine: "postgres",
+      databaseName: "warehouse",
+      schemaName: "public",
+    }).execute();
+    await db.insertInto("descriptionGenerationRuns").values({
+      id: randomUUID(), databaseId: historicalDatabaseId, scope: "all",
+      modelId: "openai-mini", language: "en", status: "completed", total: 1,
+      processed: 1, generated: 1,
+    }).execute();
+    await db.insertInto("sensitiveDataSuggestionRuns").values({
+      id: randomUUID(), databaseId: historicalDatabaseId, scope: "all",
+      modelId: "openai-mini", status: "completed", total: 1,
+      suggestedSensitive: 1,
+    }).execute();
     await upCanonicalModelIds(db);
+    await expect(db.insertInto("descriptionGenerationRuns").values({
+      id: randomUUID(), databaseId: historicalDatabaseId, scope: "all",
+      modelId: "openai/gpt-5-mini", language: "en", status: "completed", total: 1,
+      processed: 1, generated: 1,
+    }).execute()).resolves.toBeDefined();
     await sql`CREATE ROLE thothii_catalog_runtime`.execute(db);
     await upRuntimeSequencePrivileges(db);
     const sequencePrivilege = await sql<{ allowed: boolean }>`

backend/test/list-models.test.ts

@@ -6,6 +6,7 @@ import { join } from "node:path";
 import path from "node:path";
 import { createPiModelLister } from "../src/pi/list-models.js";
 import { loadConfig } from "../src/config.js";
+import type { RuntimeModel, RuntimeModelCatalog } from "../src/models/runtime-model-catalog.js";
 
 const FAKE = path.resolve("../harness/tests/fake_pi/fake_pi_rpc.mjs");
 
@@ -44,6 +45,36 @@ test("createPiModelLister returns mapped PiModel[] from get_available_models", a
   }
 });
 
+test("catalog listing translates upstream Pi IDs back to canonical model keys", async () => {
+  const script = scriptWith([
+    { provider: "local", id: "qwen2.5:7b", name: "Upstream label", reasoning: false },
+  ]);
+  const model: RuntimeModel = {
+    id: "local/qwen", provider: "local", model: "qwen", label: "Catalog Qwen",
+    upstreamModel: "qwen2.5:7b", endpoint: { baseUrl: "http://ollama:11434/v1" },
+    authentication: { mode: "none" }, sessionAdapter: { mode: "openai_compatible" },
+    session: { reasoning: true, contextWindow: 32768, maxTokens: 8192 },
+  };
+  const modelCatalog: RuntimeModelCatalog = {
+    defaultSession: model.id, defaultMetadataGeneration: null, embedding: null,
+    sessionModels: () => [model], metadataModels: () => [], hasSession: (id) => id === model.id,
+  };
+  try {
+    const lister = createPiModelLister(loadConfig({ THT_HARNESS_DIR: "../harness" }), {
+      ...noManagedModels,
+      modelCatalog,
+      loadEnabledModels: enabled("local/qwen2.5:7b"),
+      spawnFn: () => spawn("node", [FAKE, script]) as any,
+    });
+
+    await expect(lister()).resolves.toEqual([{
+      provider: "local", id: "qwen", name: "Catalog Qwen", reasoning: true,
+    }]);
+  } finally {
+    rmSync(path.dirname(script), { recursive: true, force: true });
+  }
+});
+
 test("createPiModelLister caches within ttl (spawns once for two calls)", async () => {
   const script = scriptWith([{ provider: "zai", id: "glm-5.2", name: "GLM 5.2", reasoning: true }]);
   try {

backend/test/pi-process-manager.test.ts

@@ -718,6 +718,54 @@ test.each([["OpenAI", "openai"], ["gemini", "google"]])(
   },
 );
 
+test("set_model translates a canonical catalog key to its upstream Pi model ID", async () => {
+  const root = mkdtempSync(path.join(tmpdir(), "thothii-upstream-model-"));
+  const agentDir = path.join(root, "agent");
+  mkdirSync(agentDir, { mode: 0o700 });
+  writeFileSync(path.join(agentDir, "models.json"), JSON.stringify({
+    providers: {
+      local: {
+        baseUrl: "http://ollama:11434/v1", apiKey: "local",
+        models: [{ id: "qwen2.5:7b" }],
+      },
+    },
+  }), { mode: 0o600 });
+  vi.stubEnv("PI_CODING_AGENT_DIR", agentDir);
+  const child = recordingChild();
+  child.stderr.resume = () => {};
+  child.stdin.write = (data: unknown) => {
+    const request = JSON.parse(String(data));
+    child._writes.push(String(data));
+    if (request.id) {
+      queueMicrotask(() => child.stdout.emit("data", `${JSON.stringify({
+        type: "response", id: request.id, success: true,
+      })}\n`));
+    }
+    return true;
+  };
+  const model: RuntimeModel = {
+    id: "local/qwen", provider: "local", model: "qwen", label: "Qwen",
+    upstreamModel: "qwen2.5:7b", endpoint: { baseUrl: "http://ollama:11434/v1" },
+    authentication: { mode: "none" }, sessionAdapter: { mode: "openai_compatible" },
+    session: { reasoning: false, contextWindow: 32768, maxTokens: 8192 },
+  };
+  const modelCatalog: RuntimeModelCatalog = {
+    defaultSession: model.id, defaultMetadataGeneration: null, embedding: null,
+    sessionModels: () => [model], metadataModels: () => [], hasSession: (id) => id === model.id,
+  };
+  const mgr = new PiProcessManager(loadConfig({ PI_BIN: "/usr/local/bin/pi" }), {
+    modelCatalog, authProviders: () => new Set(), spawnFn: () => child as any,
+  });
+  try {
+    await mgr.spawnFor("upstream-model", { provider: "local", model: "qwen" });
+    expect(child._writes.join("")).toContain('"modelId":"qwen2.5:7b"');
+  } finally {
+    mgr.teardown("upstream-model");
+    vi.unstubAllEnvs();
+    rmSync(root, { recursive: true, force: true });
+  }
+});
+
 test.each(["installation-local", "private-compatible"])(
   "provider %s configured with a literal apiKey spawns without a managed key",
   async (provider) => {

backend/test/pi-provider-smoke.test.ts

@@ -300,11 +300,22 @@ test("provider smoke makes one configured request from an isolated no-capability
       });
     }
   });
+  const smokeModel: RuntimeModel = {
+    id: "zai/catalog-glm", provider: "zai", model: "catalog-glm", label: "GLM",
+    upstreamModel: "glm-5.2", authentication: { mode: "pi_auth" },
+    sessionAdapter: { mode: "pi_builtin" }, session: { reasoning: true },
+  };
+  const smokeCatalog: RuntimeModelCatalog = {
+    defaultSession: smokeModel.id, defaultMetadataGeneration: null, embedding: null,
+    sessionModels: () => [smokeModel], metadataModels: () => [],
+    hasSession: (id) => id === smokeModel.id,
+  };
   const smoke = createPiProviderSmoke(loadConfig({
     THT_HARNESS_DIR: "/app/harness",
     PI_BIN: "/usr/local/bin/pi",
     THT_DATA_ROOT: "/mounted-workflow-state",
   }), {
+    modelCatalog: smokeCatalog,
     spawnFn: (...args) => {
       spawns.push(args);
       expect(args[2].cwd).not.toBe("/app/harness");
@@ -324,7 +335,7 @@ test("provider smoke makes one configured request from an isolated no-capability
   });
 
   await expect(smoke({
-    provider: "zai", model: "glm-5.2", reasoning: "medium", timeoutMs: 750,
+    provider: "zai", model: "catalog-glm", reasoning: "medium", timeoutMs: 750,
   })).resolves.toBeUndefined();
   expect(spawns).toHaveLength(1);
   expect(spawns[0][0]).toBe("/usr/local/bin/pi");

backend/test/workspace-runtime-renderer.test.ts

@@ -73,6 +73,7 @@ test("derives the internal Qdrant and Ollama runtime shape from workspace v4 plu
       vector: { engine: "qdrant", base_url: "http://qdrant:6333", collection: "psd-clinical" },
       embeddings: {
         provider: "ollama_internal", base_url: "http://embedding:11434",
+        id: "ollama/qwen3-embedding:0.6b",
         model: "qwen3-embedding:0.6b", dimensions: 1024,
       },
     },