Add LM Studio setup and blocked research artifacts

.feynman/SYSTEM.md

@@ -15,6 +15,8 @@ Operating rules:
 - Never answer a latest/current question from arXiv or alpha-backed paper search alone.
 - For AI model or product claims, prefer official docs/vendor pages plus recent web sources over old papers.
 - Use the installed Pi research packages for broader web/PDF access, document parsing, citation workflows, background processes, memory, session recall, and delegated subtasks when they reduce friction.
+- You are running inside the Feynman/Pi runtime with filesystem tools, package tools, and configured extensions. Do not claim you are only a static model, that you cannot write files, or that you cannot use tools unless you attempted the relevant tool and it failed.
+- If a tool, package, source, or network route is unavailable, record the specific failed capability and still write the requested durable artifact with a clear `Blocked / Unverified` status instead of stopping with chat-only prose.
 - Feynman ships project subagents for research work. Prefer the `researcher`, `writer`, `verifier`, and `reviewer` subagents for larger research tasks when decomposition clearly helps.
 - Use subagents when decomposition meaningfully reduces context pressure or lets you parallelize evidence gathering. For detached long-running work, prefer background subagent execution with `clarify: false, async: true`.
 - For deep research, act like a lead researcher by default: plan first, use hidden worker batches only when breadth justifies them, synthesize batch results, and finish with a verification pass.
@@ -44,6 +46,7 @@ Operating rules:
 - When citing papers from alpha-backed tools, prefer direct arXiv or alphaXiv links and include the arXiv ID.
 - Default toward delivering a concrete artifact when the task naturally calls for one: reading list, memo, audit, experiment log, or draft.
 - For user-facing workflows, produce exactly one canonical durable Markdown artifact unless the user explicitly asks for multiple deliverables.
+- If a workflow requests a durable artifact, verify the file exists on disk before the final response. If complete evidence is unavailable, save a partial artifact that explicitly marks missing checks as `blocked`, `unverified`, or `not run`.
 - Do not create extra user-facing intermediate markdown files just because the workflow has multiple reasoning stages.
 - Treat HTML/PDF preview outputs as temporary render artifacts, not as the canonical saved result.
 - Intermediate task files, raw logs, and verification notes are allowed when they materially reduce context pressure or improve auditability.

README.md

@@ -25,7 +25,7 @@ curl -fsSL https://feynman.is/install | bash
 irm https://feynman.is/install.ps1 | iex
 ```
 
-The one-line installer fetches the latest tagged release. To pin a version, pass it explicitly, for example `curl -fsSL https://feynman.is/install | bash -s -- 0.2.21`.
+The one-line installer fetches the latest tagged release. To pin a version, pass it explicitly, for example `curl -fsSL https://feynman.is/install | bash -s -- 0.2.23`.
 
 The installer downloads a standalone native bundle with its own Node.js runtime.
 
@@ -33,7 +33,7 @@ To upgrade the standalone app later, rerun the installer. `feynman update` only
 
 To uninstall the standalone app, remove the launcher and runtime bundle, then optionally remove `~/.feynman` if you also want to delete settings, sessions, and installed package state. If you also want to delete alphaXiv login state, remove `~/.ahub`. See the installation guide for platform-specific paths.
 
-Local models are supported through the custom-provider flow. For Ollama, run `feynman setup`, choose `Custom provider (baseUrl + API key)`, use `openai-completions`, and point it at `http://localhost:11434/v1`.
+Local models are supported through the setup flow. For LM Studio, run `feynman setup`, choose `LM Studio`, and keep the default `http://localhost:1234/v1` unless you changed the server port. For Ollama or vLLM, choose `Custom provider (baseUrl + API key)`, use `openai-completions`, and point it at the local `/v1` endpoint.
 
 ### Skills Only
 

package-lock.json

@@ -1,12 +1,12 @@
 {
   "name": "@companion-ai/feynman",
-  "version": "0.2.21",
+  "version": "0.2.23",
   "lockfileVersion": 3,
   "requires": true,
   "packages": {
     "": {
       "name": "@companion-ai/feynman",
-      "version": "0.2.21",
+      "version": "0.2.23",
       "hasInstallScript": true,
       "license": "MIT",
       "dependencies": {

package.json

@@ -1,6 +1,6 @@
 {
   "name": "@companion-ai/feynman",
-  "version": "0.2.21",
+  "version": "0.2.23",
   "description": "Research-first CLI agent built on Pi and alphaXiv",
   "license": "MIT",
   "type": "module",

prompts/deepresearch.md

@@ -53,6 +53,8 @@ Also save the plan with `memory_remember` (type: `fact`, key: `deepresearch.<slu
 
 Present the plan to the user. If this is an unattended or one-shot run, continue automatically. If the user is actively interacting in the terminal, give them a brief chance to request plan changes before proceeding.
 
+Do not stop after planning. If live search, subagents, web access, alphaXiv, or any other capability is unavailable, continue in degraded mode and write a durable blocked/partial report that records exactly which capabilities failed.
+
 ## 2. Scale decision
 
 | Query type | Execution |
@@ -105,6 +107,13 @@ When the work spans multiple rounds, also append a concise chronological entry t
 
 Most topics need 1-2 rounds. Stop when additional rounds would not materially change conclusions.
 
+If no researcher files can be produced because tools, subagents, or network access failed, create `outputs/.drafts/<slug>-draft.md` yourself as a blocked report with:
+- what was requested,
+- which capabilities failed,
+- what evidence was and was not gathered,
+- a proposed source-gathering plan,
+- no invented sources or results.
+
 ## 5. Write the report
 
 Once evidence is sufficient, YOU write the full research brief directly. Do not delegate writing to another agent. Read the research files, synthesize the findings, and produce a complete document:
@@ -190,6 +199,7 @@ Before you stop, verify on disk that all of these exist:
 - `outputs/<slug>.provenance.md` or `papers/<slug>.provenance.md` provenance sidecar
 
 Do not stop at `<slug>-brief.md` alone. If the cited brief exists but the promoted final output or provenance sidecar does not, create them before responding.
+If full verification could not be completed, still create the final deliverable and provenance sidecar with `Verification: BLOCKED` or `PASS WITH NOTES` and list the missing checks. Never end with only an explanation in chat.
 
 ## Background execution
 

scripts/install/install.ps1

@@ -110,7 +110,7 @@ This usually means the release exists, but not all platform bundles were uploade
 Workarounds:
   - try again after the release finishes publishing
   - pass the latest published version explicitly, e.g.:
-    & ([scriptblock]::Create((irm https://feynman.is/install.ps1))) -Version 0.2.21
+    & ([scriptblock]::Create((irm https://feynman.is/install.ps1))) -Version 0.2.23
 "@
   }
 

scripts/install/install.sh

@@ -261,7 +261,7 @@ This usually means the release exists, but not all platform bundles were uploade
 Workarounds:
   - try again after the release finishes publishing
   - pass the latest published version explicitly, e.g.:
-    curl -fsSL https://feynman.is/install | bash -s -- 0.2.21
+    curl -fsSL https://feynman.is/install | bash -s -- 0.2.23
 EOF
   exit 1
 fi

src/model/commands.ts

@@ -83,6 +83,7 @@ const API_KEY_PROVIDERS: ApiKeyProviderInfo[] = [
 	{ id: "openai", label: "OpenAI Platform API", envVar: "OPENAI_API_KEY" },
 	{ id: "anthropic", label: "Anthropic API", envVar: "ANTHROPIC_API_KEY" },
 	{ id: "google", label: "Google Gemini API", envVar: "GEMINI_API_KEY" },
+	{ id: "lm-studio", label: "LM Studio (local OpenAI-compatible server)" },
 	{ id: "__custom__", label: "Custom provider (local/self-hosted/proxy)" },
 	{ id: "amazon-bedrock", label: "Amazon Bedrock (AWS credential chain)" },
 	{ id: "openrouter", label: "OpenRouter", envVar: "OPENROUTER_API_KEY" },
@@ -132,6 +133,8 @@ async function selectApiKeyProvider(): Promise<ApiKeyProviderInfo | undefined> {
 		label: provider.label,
 		hint: provider.id === "__custom__"
 			? "Ollama, vLLM, LM Studio, proxies"
+			: provider.id === "lm-studio"
+				? "http://localhost:1234/v1"
 			: provider.envVar ?? provider.id,
 	}));
 	options.push({ value: "cancel", label: "Cancel" });
@@ -362,6 +365,44 @@ async function promptCustomProviderSetup(): Promise<CustomProviderSetup | undefi
 	return { providerId, modelIds, baseUrl, api, apiKeyConfig, authHeader };
 }
 
+async function promptLmStudioProviderSetup(): Promise<CustomProviderSetup | undefined> {
+	printSection("LM Studio");
+	printInfo("Start the LM Studio local server first, then load a model.");
+
+	const baseUrlRaw = await promptText("Base URL", "http://localhost:1234/v1");
+	const { baseUrl } = normalizeCustomProviderBaseUrl("openai-completions", baseUrlRaw);
+	if (!baseUrl) {
+		printWarning("Base URL is required.");
+		return undefined;
+	}
+
+	const detectedModelIds = await bestEffortFetchOpenAiModelIds(baseUrl, "lm-studio", false);
+	let modelIdsDefault = "local-model";
+	if (detectedModelIds && detectedModelIds.length > 0) {
+		const sample = detectedModelIds.slice(0, 10).join(", ");
+		printInfo(`Detected LM Studio models: ${sample}${detectedModelIds.length > 10 ? ", ..." : ""}`);
+		modelIdsDefault = detectedModelIds[0]!;
+	} else {
+		printInfo("No models detected from /models. Enter the exact model id shown in LM Studio.");
+	}
+
+	const modelIdsRaw = await promptText("Model id(s) (comma-separated)", modelIdsDefault);
+	const modelIds = normalizeModelIds(modelIdsRaw);
+	if (modelIds.length === 0) {
+		printWarning("At least one model id is required.");
+		return undefined;
+	}
+
+	return {
+		providerId: "lm-studio",
+		modelIds,
+		baseUrl,
+		api: "openai-completions",
+		apiKeyConfig: "lm-studio",
+		authHeader: false,
+	};
+}
+
 async function verifyCustomProvider(setup: CustomProviderSetup, authPath: string): Promise<void> {
 	const registry = createModelRegistry(authPath);
 	const modelsError = registry.getError();
@@ -548,6 +589,31 @@ async function configureApiKeyProvider(authPath: string, providerId?: string): P
 		return configureBedrockProvider(authPath);
 	}
 
+	if (provider.id === "lm-studio") {
+		const setup = await promptLmStudioProviderSetup();
+		if (!setup) {
+			printInfo("LM Studio setup cancelled.");
+			return false;
+		}
+
+		const modelsJsonPath = getModelsJsonPath(authPath);
+		const result = upsertProviderConfig(modelsJsonPath, setup.providerId, {
+			baseUrl: setup.baseUrl,
+			apiKey: setup.apiKeyConfig,
+			api: setup.api,
+			authHeader: setup.authHeader,
+			models: setup.modelIds.map((id) => ({ id })),
+		});
+		if (!result.ok) {
+			printWarning(result.error);
+			return false;
+		}
+
+		printSuccess("Saved LM Studio provider.");
+		await verifyCustomProvider(setup, authPath);
+		return true;
+	}
+
 	if (provider.id === "__custom__") {
 		const setup = await promptCustomProviderSetup();
 		if (!setup) {

tests/content-policy.test.ts

@@ -57,3 +57,15 @@ test("research writing prompts forbid fabricated results and unproven figures",
 	assert.match(draftPrompt, /placeholder or proposed experimental plan/i);
 	assert.match(draftPrompt, /source-backed quantitative data/i);
 });
+
+test("deepresearch workflow requires durable artifacts even when blocked", () => {
+	const systemPrompt = readFileSync(join(repoRoot, ".feynman", "SYSTEM.md"), "utf8");
+	const deepResearchPrompt = readFileSync(join(repoRoot, "prompts", "deepresearch.md"), "utf8");
+
+	assert.match(systemPrompt, /Do not claim you are only a static model/i);
+	assert.match(systemPrompt, /write the requested durable artifact/i);
+	assert.match(deepResearchPrompt, /Do not stop after planning/i);
+	assert.match(deepResearchPrompt, /degraded mode/i);
+	assert.match(deepResearchPrompt, /Verification: BLOCKED/i);
+	assert.match(deepResearchPrompt, /Never end with only an explanation in chat/i);
+});

tests/model-harness.test.ts

@@ -79,6 +79,15 @@ test("resolveModelProviderForCommand falls back to API-key providers when OAuth
 	assert.equal(resolved?.id, "google");
 });
 
+test("resolveModelProviderForCommand supports LM Studio as a first-class local provider", () => {
+	const authPath = createAuthPath({});
+
+	const resolved = resolveModelProviderForCommand(authPath, "lm-studio");
+
+	assert.equal(resolved?.kind, "api-key");
+	assert.equal(resolved?.id, "lm-studio");
+});
+
 test("resolveModelProviderForCommand prefers OAuth when a provider supports both auth modes", () => {
 	const authPath = createAuthPath({});
 

website/public/install

@@ -261,7 +261,7 @@ This usually means the release exists, but not all platform bundles were uploade
 Workarounds:
   - try again after the release finishes publishing
   - pass the latest published version explicitly, e.g.:
-    curl -fsSL https://feynman.is/install | bash -s -- 0.2.21
+    curl -fsSL https://feynman.is/install | bash -s -- 0.2.23
 EOF
   exit 1
 fi

website/public/install.ps1

@@ -110,7 +110,7 @@ This usually means the release exists, but not all platform bundles were uploade
 Workarounds:
   - try again after the release finishes publishing
   - pass the latest published version explicitly, e.g.:
-    & ([scriptblock]::Create((irm https://feynman.is/install.ps1))) -Version 0.2.21
+    & ([scriptblock]::Create((irm https://feynman.is/install.ps1))) -Version 0.2.23
 "@
   }
 

website/src/content/docs/getting-started/installation.md

@@ -117,13 +117,13 @@ These installers download the bundled `skills/` and `prompts/` trees plus the re
 The one-line installer already targets the latest tagged release. To pin an exact version, pass it explicitly:
 
 ```bash
-curl -fsSL https://feynman.is/install | bash -s -- 0.2.21
+curl -fsSL https://feynman.is/install | bash -s -- 0.2.23
 ```
 
 On Windows:
 
 ```powershell
-& ([scriptblock]::Create((irm https://feynman.is/install.ps1))) -Version 0.2.21
+& ([scriptblock]::Create((irm https://feynman.is/install.ps1))) -Version 0.2.23
 ```
 
 ## Post-install setup

website/src/content/docs/getting-started/setup.md

@@ -52,9 +52,25 @@ Amazon Bedrock (AWS credential chain)
 
 Feynman verifies the same AWS credential chain Pi uses at runtime, including `AWS_PROFILE`, `~/.aws` credentials/config, SSO, ECS/IRSA, and EC2 instance roles. Once that check passes, Bedrock models become available in `feynman model list` without needing a traditional API key.
 
-### Local models: Ollama, LM Studio, vLLM
+### Local models: LM Studio, Ollama, vLLM
 
-If you want to use a model running locally, choose the API-key flow and then select:
+If you want to use LM Studio, start the LM Studio local server, load a model, choose the API-key flow, and then select:
+
+```text
+LM Studio (local OpenAI-compatible server)
+```
+
+The default settings are:
+
+```text
+Base URL: http://localhost:1234/v1
+Authorization header: No
+API key: lm-studio
+```
+
+Feynman attempts to read LM Studio's `/models` endpoint and prefill the loaded model id.
+
+For Ollama, vLLM, or another OpenAI-compatible local server, choose:
 
 ```text
 Custom provider (baseUrl + API key)
@@ -70,7 +86,7 @@ Model ids: llama3.1:8b
 API key: local
 ```
 
-That same custom-provider flow also works for other OpenAI-compatible local servers such as LM Studio or vLLM. After saving the provider, run:
+After saving the provider, run:
 
 ```bash
 feynman model list