feat: configure models with NOOA Connect library and CLI - #332
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Signed-off-by: Paul Furgale <pfurgale@nvidia.com>
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Included review availability: Your plan provides up to 12 included reviews per hour; 11 remain after this review. 📝 WalkthroughWalkthroughThis change adds model discovery, bounded probes, session checks, atomic registry updates, the ChangesModel connection workflow
Priority: ➖ Normal Estimated code review effort: 5 (Critical) | ~90 minutes Change: Feature Suggested reviewers: Sequence Diagram(s)sequenceDiagram
participant Operator
participant ConnectCLI
participant ConnectModule
participant ProviderEndpoint
participant ModelRegistry
Operator->>ConnectCLI: configure connection and approve checks
ConnectCLI->>ConnectModule: discover, probe, and validate
ConnectModule->>ProviderEndpoint: send bounded requests
ProviderEndpoint-->>ConnectModule: return responses and usage
ConnectModule->>ModelRegistry: atomically save model alias
ModelRegistry-->>ConnectCLI: return persisted configuration
Merge Risk: 🔵 Low · up to Connect can fail for malformed catalogue entries, reused checks, or certain provider rejection formats. These are bounded onboarding failures but should be corrected before merge. 🚥 Pre-merge checks | ✅ 4 | ❌ 1❌ Failed checks (1 warning)
✅ Passed checks (4 passed)
Full details: Docstring CoverageExplanation Docstring coverage is 11.16% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 242 functions across 17 files. (1 skipped: 1 unsupported.)
✨ Finishing Touches 💡 1📝 Generate docstrings 💡
🧪 Generate unit tests (beta)
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Signed-off-by: Paul Furgale <pfurgale@nvidia.com>
Signed-off-by: Paul Furgale <pfurgale@nvidia.com>
Signed-off-by: Paul Furgale <pfurgale@nvidia.com>
Signed-off-by: Paul Furgale <pfurgale@nvidia.com>
Signed-off-by: Paul Furgale <pfurgale@nvidia.com>
Signed-off-by: Paul Furgale <pfurgale@nvidia.com>
Signed-off-by: Paul Furgale <pfurgale@nvidia.com>
Signed-off-by: Paul Furgale <pfurgale@nvidia.com>
Signed-off-by: Paul Furgale <pfurgale@nvidia.com>
Signed-off-by: Paul Furgale <pfurgale@nvidia.com>
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Reviewed this head with 128 focused tests passing. The three findings below were reproduced locally; HTTP was mocked and no paid API calls were made.
| elif alias in data["models"]: | ||
| key, value = next((key, value) for key, value in models_node.value if key.value == alias) | ||
| lines = dumped.splitlines() | ||
| replacement = "\n".join([lines[0], *(" " + line for line in lines[1:])]) |
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[P2] Preserve the existing YAML indentation when saving
The replacement hardcodes two spaces, as does insertion via indented. For a valid registry whose aliases are indented four spaces beneath models, replacing an alias raises ValueError, and adding an alias raises a YAML ParserError. I reproduced both cases. This prevents the wizard from saving at its final step, potentially after paid checks. Derive the alias and field indentation from the existing mapping instead of assuming two spaces.
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Fixed in fcefd24: derive the alias indentation from the existing YAML mapping for both insertion and replacement. Regression coverage exercises 2-, 4-, and 6-space indentation and verifies that every other parsed value is unchanged.
| suffix = source[value.end_mark.index :] | ||
| if suffix and not suffix.startswith("\n"): | ||
| replacement += "\n" + " " * value.end_mark.column | ||
| text = source[: key.start_mark.index] + replacement + suffix |
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[P2] Preserve comments preceding the next alias
PyYAML’s value.end_mark can extend past comments preceding the next alias, so this splice silently deletes comments belonging to that neighbor. For example, replacing local in the following registry removes the description above other:
models:
local:
model_name: openai/old
# Important description for other
other:
model_name: openai/otherI reproduced the loss. The parsed-data equality check cannot catch it because YAML comments are discarded during parsing. Preserve trailing comments when calculating the replacement boundary.
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Fixed in fcefd24: replacement and insertion boundaries now use the last actual YAML value rather than a mapping end mark that consumes neighboring comments. Tests assert that the next alias's description and the following top-level section's comment stay intact.
| needs_key = ( | ||
| not yes and approval != "none" and api_key_env and not os.environ.get(api_key_env) | ||
| ) | ||
| api_key = ( | ||
| prompt("API key (used only for this setup)", hide_input=True) | ||
| if prompt_key or needs_key |
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[P2] Collect discovery credentials even with --no-probe
With NVIDIA_API_KEY unset, nooa connect --provider nvidia --no-probe --no-catalogue skips the temporary-key prompt because approval is none, then sends an unauthenticated GET to /v1/models and exits on 401. I reproduced this with mocked HTTP. Disabling generation checks should still allow authenticated model discovery; request credentials when MODEL is absent and discovery needs them, even when paid probes are disabled.
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Fixed in fcefd24: interactive discovery collects an unset credential even with --no-probe. A mocked HTTP regression asserts authenticated GET-only discovery, masked input, cancellation without a save, and no key in output.
Signed-off-by: Paul Furgale <pfurgale@nvidia.com>
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Inline comments:
In `@src/nooa/connect.py`:
- Around line 415-434: Normalize catalogue records before they reach the CLI
consumers, using the catalogue-loading/normalization flow around catalogue() and
preserving connect.plan()’s existing guards for direct callers. Require each
record to have a string id; replace non-dict top_provider and reasoning values
with empty dictionaries; filter supported_efforts to non-empty strings only; and
retain default_effort only when it is a string. Ensure invalid required fields
surface as ValueError for the existing CLI handler, while preserving valid
catalogue metadata and reasoning behavior.
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docs/model-configuration.mddocs/model-connect.mdpackages/nooa-cli/pyproject.tomlpackages/nooa-cli/src/nooa_cli/commands/_connect_prompts.pypackages/nooa-cli/src/nooa_cli/commands/_connect_view.pypackages/nooa-cli/src/nooa_cli/commands/connect.pypackages/nooa-cli/tests/test_connect_command.pypackages/nooa-cli/tests/test_connect_prompts.pypackages/nooa-cli/tests/test_connect_view.pyskills/nooa-agent-authoring/SKILL.mdsrc/nooa/connect.pytests/test_connect.pytests/test_connect_interfaces.pytests/test_model_configuration_doc.py
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Signed-off-by: Paul Furgale <pfurgale@nvidia.com>
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Added the cache/reasoning conversation checks at f6f81f0. Connect now asks once before generation calls, with a fixed shared estimated-token budget (65,536 by default). Full setup includes three bounded seed/replay/repeat calls through the candidate UnifiedLLM client and default cached renderer, without forcing cache or replay settings. It reports cache-read fraction and marker presence; a small tool-schema-only hit is not confirmation. Reasoning retention requires the seed reasoning state to reach the follow-up reasoning fields unchanged, with configured controls retained. Ordinary text fallback does not count. No tools are executed and native state/raw captured bodies are not persisted in provenance. --no-probe remains available; --yes approves the chosen checks as well as saving. Validation: 251 offline Connect, CLI/prompt and reasoning-level tests passed; lint clean. No paid live calls made for this increment. Wren has been asked to review the frozen delta; review is pending. |
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Inline comments:
In `@src/nooa/connect.py`:
- Around line 707-712: Update run_steps to resolve entry["api_key_env"] before
the accepted-probe reuse checks and any continue path, then pass the resolved
API key to session_steps. Preserve the existing ValueError behavior when the
configured key cannot be resolved and ensure client_from_config does not receive
an explicit None override.
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Encrypted reasoning default added at 85e0215. Responses plans now set store:false and include:[reasoning.encrypted_content], with source connect in provenance; the wizard explains the choice without another question. An explicit 400/422 rejection of the option persists include:[] and reports it. That empty list now suppresses the runtime automatic include and omits the field on the wire, tested for both native and gateway URLs. A single no-include routing check is allowed only within the original approved budget; session rejection stops rather than rerunning. Authentication/rate/server errors and rejected model or input-history fields do not disable the option. No raw error bodies are recorded. Validation: 1171 broad offline tests passed, plus the expanded 13-case feature suite; lint and format clean. Wren has the frozen commit for delta review; the full PR review remains on hold. No paid calls made. Existing caveat: this branch still needs #341 incorporated to obtain the new Responses cache default; the checks report the current runtime rather than forcing that default. |
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Inline comments:
In `@src/nooa/connect.py`:
- Around line 56-61: Update _include_rejected to use the already validated
structured param when determining whether an include-related rejection occurred,
rather than relying only on str(exc). Ensure both routing and session paths
detect the rejection, disable include, and preserve the bounded retry behavior.
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Connection recovery added at 54629fa. If no interface works, interactive setup offers Change key / Edit server and model / Retry / Cancel instead of a terminal error. Failed attempts remain charged to the initial budget; budget exhaustion or cancellation saves nothing. Existing model listing is described as listing, not credential validation. CLI shows safe authentication/routing/rate/timeout explanations and temporarily suppresses legacy help banners, restoring the flag after progress iteration. Responses explanation now appears only for the chosen Responses interface. Validation: 209 offline Connect/library/CLI/prompt tests passed, lint and format clean. Wren has the frozen delta for review; full PR review remains on hold. No paid calls made. Output-token preset selector is a separate design proposal, not part of this patch. |
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| return client_from_config(name, config, client_type=client_type, **overrides) | ||
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| def client_from_config( |
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How is this different from the get_llm that we had?
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get_llm_client remains the public alias lookup. client_from_config is the extracted construction half: it accepts a detached, unsaved entry and builds the identical client without registering the candidate globally or writing a file before the user approves. get_llm_client delegates to that same factory after lookup, so Connect does not maintain a second client-construction path.
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| __all__ = ["load_secrets_into_env"] | ||
| def write_secret_env(path, name: str, value: str) -> None: |
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This is only for the wizard's optional, separately confirmed Save this key action. It updates the named variable in the existing secrets.yaml, preserves other variables, and atomically writes owner-only permissions; transient keys and --yes never save implicitly. In 8893f15 it also follows symlinks and accepts a scaffold with env: null. The registry still stores only the environment-variable name.
| if probe.name.startswith("level:"): | ||
| settings_sent.append(settings_on_wire(settings, json.loads(request.content))) | ||
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| hooks = client._http.httpx_async.event_hooks["request"] |
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Capture hook never fires when there is no API key — every reasoning level and the whole conversation check are falsely reported as failures on unauthenticated endpoints.
The CLI explicitly offers - for "no authentication" (connect.py:363) — i.e. local vLLM / Ollama / llama.cpp. On that path client_from_config(alias, entry, api_key=None, …) reaches unifiedllm.py:262-277, AsyncOpenAI(...) raises "The api_key client option must be set", and the documented fallback sets async_client = None so litellm builds its own httpx client. Verified:
>>> c = client_from_config('local', {'model_name':'openai/local-model','client_type':'completion',
... 'api_style':'chat','api_base':'http://localhost:8000/v1','api_key_env':''}, api_key=None)
>>> c._http.async_client, c._http._openai_clients
(None, [])
So the hook installed here (and the identical one at _session.py:240) never runs. Consequences:
_run_probereturnssettings_sent=False→run_steps:1191-1195rewrites every acceptedlevel:*probe tooutcome: not_confirmed, reason "The client did not send the requested settings; check parameter filtering" — pointing the user at parameter filtering for a bug that is purely a missing hook._session.py:328seeslen(bodies) != before + 1→ the cache and reasoning-retention checks abort with "request capture missing or server exceeded the reply cap".
No test exercises an empty api_key_env through the probe path. Either detect that the hook is not installed (client._http.async_client is None) and record "could not observe the request" instead of "settings not sent", or capture at a layer litellm cannot bypass.
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Addressed conservatively in 8893f15: when no request is captured, settings_sent is unknown and the result says the actual request could not be observed because the runtime bypassed the instrumented client. It no longer asserts parameter filtering removed settings. The regression constructs the real keyless client, verifies its owned SDK client is absent, then exercises an accepted fallback response without capture. Full wire verification on that legacy fallback remains unconfirmed; no dummy credential is invented.
| "click>=8.1.0", | ||
| # CLI config files | ||
| "pyyaml>=6.0", | ||
| "prompt-toolkit>=3.0.50", |
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prompt-toolkit>=3.0.50 is two releases too low — show_frame first exists in 3.0.52.
_connect_prompts.py:152 passes show_frame=True unconditionally. Verified by downloading the sdists:
| version | show_frame in shortcuts/prompt.py |
|---|---|
| 3.0.50 | absent |
| 3.0.51 | absent |
| 3.0.52 | present |
PromptSession.prompt() in 3.0.51 is keyword-only with no **kwargs, so the call raises TypeError: prompt() got an unexpected keyword argument 'show_frame'. Any environment that already satisfies >=3.0.50 (e.g. a venv with ipython/jupyter, which commonly pin 3.0.51) will not upgrade, and nooa connect dies on its first question. TypeError is not in the caught tuple at connect.py:1051, so it surfaces as a raw traceback. The committed uv.lock pins 3.0.53, which is why CI never sees it.
| "prompt-toolkit>=3.0.50", | |
| "prompt-toolkit>=3.0.52", |
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Fixed in 8893f15: nooa-cli now requires prompt-toolkit>=3.0.52 and uv.lock metadata matches. This only raises the CLI's existing minimum; NOOA core gains no dependency.
| data = {} | ||
| except yaml.YAMLError: | ||
| raise ValueError(f"Secrets file {path} contains invalid YAML; no changes made") from None | ||
| if not isinstance(data, dict) or not isinstance(data.get("env", {}), dict): |
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A secrets.yaml with a present-but-null env: key aborts the whole onboarding run — after the paid checks.
Verified by execution:
>>> p.write_text("env:\n") # scaffold file, or all keys commented out
>>> write_secret_env(p, "MY_KEY", "sk-123")
ValueError: Secrets file …/secrets.yaml must contain an env mappingyaml.safe_load("env:\n") is {'env': None}, so data.get("env", {}) returns None, not {}. load_secrets_into_env in this same module (line 51) explicitly tolerates that shape and returns [].
The damage is amplified by call ordering: in the wizard write_secret_env runs at connect.py:1031 (inside if save_key:) while connect.write(result.entry, path, alias=alias) is only at connect.py:1040. The ValueError propagates to the handler at connect.py:1051, so the model alias is never written — the user answered every prompt, paid for every probe, and ends up with neither the key nor the alias.
| if not isinstance(data, dict) or not isinstance(data.get("env", {}), dict): | |
| if not isinstance(data, dict) or not isinstance(data.get("env") or {}, dict): |
Worth also writing the registry entry before the secret, so a failure in either write can't silently discard the other.
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Fixed the reported abort in 8893f15: write_secret_env treats env: null as an empty mapping, consistently with the loader. The regression writes a key through that real path and verifies the file contents. Secret persistence still needs separate consent; the two-file save is not claimed to be a cross-file atomic transaction.
| data = yaml.safe_load(source) | ||
| if data is None: | ||
| data = {} | ||
| if not isinstance(data, dict) or not isinstance(data.get("models", {}), dict): |
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A registry file whose models: key is present but empty (models:\n) is rejected everywhere, and crashes --stage save with a TypeError.
yaml.safe_load("models:\n") → {'models': None}, so data.get("models", {}) returns None, not {}. The runtime loader explicitly tolerates this shape (registry._load_models_from_yaml: if models is None: return {}), so reload_registry() happily returns {} for the same file. Five sites in this PR disagree:
| site | behaviour (verified) |
|---|---|
connect/__init__.py:1310 (write) |
ValueError: Registry must be a mapping with a models mapping — cannot populate an empty scaffold |
_connect_registry.py:21 (entries) |
ValueError: Registry <path> must contain a models mapping |
connect.py:270, :982 |
ClickException("Registry must contain a models mapping.") |
_connect_stages.py:117 |
alias in None → TypeError: argument of type 'NoneType' is not iterable |
entries() is called at connect.py:221 for every file in llm_config_chain(), so one such file anywhere in the chain makes nooa connect unusable end-to-end — even with --no-probe, even when saving to an unrelated --output. Reproduced --stage save returning {"error": {"type": "TypeError", …}}.
That write() intends to support this state is visible three lines below, at 1321: alias_indent = models_node.start_mark.column if models_node and models_node.value else 2 explicitly handles an empty models node.
Fix is data.get("models") or {} at all five sites (and the matching env case in secrets.py).
| if not isinstance(data, dict) or not isinstance(data.get("models", {}), dict): | |
| if not isinstance(data, dict) or not isinstance(data.get("models") or {}, dict): |
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Fixed in 8893f15 across the writer, registry reader, both wizard reads and stage-save collision check. Null models mappings are treated as empty while non-mapping values are still rejected. Library and stage-save regressions populate models: successfully.
| if not isinstance(data, dict) or not isinstance(data.get("models", {}), dict): | ||
| raise ValueError(f"Registry {path} must contain a models mapping") | ||
| for alias, entry in data.get("models", {}).items(): | ||
| if isinstance(alias, str) and isinstance(entry, dict): |
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entries() resurrects aliases that a higher layer has tombstoned with null.
reload_registry treats models: {alias: null} as a deletion (registry.py:233-238 — if cfg is None: fresh.pop(name, None), and the same for any non-mapping). This loop only skips those values, so the lower layer's entry survives. Verified:
low.yaml: models: {ghost: {model_name: openai/ghost}}
high.yaml: models: {ghost: null}
NEMO_OO_LLM_CONFIG=low.yaml,high.yaml
runtime registry sees ghost: False
connect entries() sees ghost: True
Concretely: a project that nulls out a bundled alias still sees it offered by nooa connect --edit-model, edits it, and writes the resurrected entry back into llm_config.yaml; shadowing_source warns that a deleted definition "currently defines this alias and takes precedence"; and credential_names suggests an api_key_env from an alias the runtime cannot resolve.
Rather than re-implementing the merge, consider reusing registry._load_models_from_yaml + the same pop semantics, so the two copies cannot drift on the next layering rule.
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Fixed in 8893f15: a higher-layer non-mapping alias removes the lower-layer entry, matching runtime tombstone semantics. A regression verifies the alias is absent both from editor entries and credential suggestions.
| + source[models_node.end_mark.index :] | ||
| ) | ||
| elif alias in data["models"]: | ||
| key, value = next((key, value) for key, value in models_node.value if key.value == alias) |
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next(...) with no default → bare StopIteration, and YAML anchors make write() fail outright — both after the paid checks.
Reproduced with a registry that uses a merge key inside models::
defaults: &base
shared: {model_name: openai/base, api_style: chat}
models:
<<: *base
other: {model_name: openai/other}yaml.safe_load resolves data['models'] to {'shared', 'other'}, so line 1343's alias in data["models"] is True — but models_node.value contains only the << key, so no key.value == 'shared' match exists and this next() raises a bare StopIteration with an empty message. StopIteration is not in the caught tuple at connect.py:1051, so the user gets a raw traceback and loses a run they already paid for.
Separately, an anchored entry value:
defaults: &d
model_name: openai/a
models:
a: *dmakes content_end() descend into the anchored node, whose end_mark points earlier in the file, so the splice lands in the wrong place. The yaml.safe_load(text) != expected net catches it (good), but the result is that even adding a brand-new, unrelated alias fails with "Could not construct the registry update without changing other entries" — i.e. nooa connect cannot save into any registry that uses anchors.
At minimum use next(…, None) and raise the same descriptive ValueError; ideally detect a merge key / anchored value and fall back to a whole-file rewrite.
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Handled safely in 8893f15, with a deliberate limitation: Connect detects YAML anchors/aliases and refuses the update with instructions to expand them first. It does not flatten the whole file and discard comments. Both reported shapes now produce an actionable ValueError and leave the original bytes intact, rather than StopIteration or a broken splice. Full anchor-preserving editing is not implemented.
| # Reply-limit aliases are one setting, even when the destination API names | ||
| # it differently. A level's cap replaces inherited defaults as a unit. | ||
| caps = {"max_tokens", "max_completion_tokens", "max_output_tokens"} | ||
| if caps & patch.keys(): |
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The new cap-alias unification never looks inside extra_body, so a level's reply cap is silently defeated.
The block three lines above deliberately strips replaced defaults out of extra_body ("SDKs otherwise merge those back over the selected top-level values"). The new cap-alias rule doesn't do the same for sibling aliases. Verified by running apply_reasoning_level directly with levels={'high': {'reasoning': {'effort':'high'}, 'max_tokens': 65536}}:
| input | result |
|---|---|
defaults={'max_output_tokens': 4096} |
✅ scrubbed → {'reasoning': …, 'max_tokens': 65536} |
overrides={'extra_body': {'max_tokens': 500}} |
✅ ValueError: … conflicts with explicit request field(s) |
defaults={'extra_body': {'max_output_tokens': 4096}} |
❌ {'extra_body': {'max_output_tokens': 4096}, 'max_tokens': 65536} |
overrides={'extra_body': {'max_output_tokens': 500}} |
❌ same, no error |
litellm merges extra_body into the HTTP body, so the effective Responses cap is 4 096 while the level asked for 65 536 — high-effort replies burn the reasoning budget and return finish_reason='length'. Connect-written entries are shielded by configure_entry's managed & extra.keys() check, so this only bites hand-written aliases, i.e. every non-Connect user of this shared module.
Extend the caps handling to the extra_body mapping the same way the patch.keys() & extra.keys() branch already does.
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Resolved by merging main/#331 in 59f8567 and retaining its shared limits.py resolver. Inherited extra_body cap aliases are promoted/replaced before level application; an explicit per-call cap alias, including inside extra_body, conflicts with a level cap. The old duplicate Connect-only normalization was removed at the conflict. The UnifiedLLM limit/reasoning suites pass in the final 1457-test selection.
| REASONING_CHECK_PROMPT | ||
| ) | ||
| level_body.update(params) | ||
| probes.append(Probe(f"level:{label}", level_body, reasoning_output_tokens + 512, 120)) |
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--reasoning-template budget can never actually check a level at the documented defaults.
level_body.update(params) on the line above overwrites the body's cap with the level's own cap, but Probe.token_estimate here is still sized from reasoning_output_tokens. Verified:
>>> connect.reasoning_settings('budget', 'chat', 'high')
{'thinking': {'type': 'enabled', 'budget_tokens': 4096}, 'max_tokens': 5120}
>>> [p for p in plan(..., reasoning_levels=…).probes if p.name.startswith('level:')]
probe level:high caps [5120] token_estimate 4608 -> guard `cap > est-512` : True
run_steps:1115-1122 therefore records outcome: not_probed, reason "declared output cap exceeds the approved probe cap" for every level. The CLI renders that as a grey skip, exits 0, and writes the alias with an entirely unverified reasoning level.
The thinking budget is hard-coded — reasoning_settings' budget=4096 kwarg is never passed from the CLI (connect.py:741) — so there is no flag to lower it; the user would have to know to pass --reasoning-output-tokens 5632. The same path fires for any level whose thinking budget triggers configure_entry's documented auto-bump at line 510.
Only the effort template is covered by tests, and the reason string "declared output cap exceeds the approved probe cap" appears nowhere in the test suite. Size token_estimate from the effective (post-merge) cap instead of reasoning_output_tokens.
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Fixed in 8893f15. refresh_plan builds each request and its reservation from the effective saved/level cap after configuration normalization, so a thinking-budget bump is included in token_estimate. Reasoning-output-tokens no longer silently substitutes a different cap. Wire regressions exercise level-specific caps across all three styles, and stale requests are rejected rather than sent above their reservation.
| spent += max(0, tokens - probe.token_estimate) | ||
| yield ProbeUpdate(probe.name, deepcopy(record)) | ||
| if probe.name == "routing" and entry.get("include"): | ||
| provenance["encrypted_reasoning"]["outcome"] = "accepted" |
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provenance["encrypted_reasoning"] is written unguarded, but configure_entry only creates it when it adds the include.
run_steps calls configure_entry(proposal.entry) itself, and configure_entry (lines 520-538) writes provenance["encrypted_reasoning"] only in the two branches where it inserts reasoning.encrypted_content. If include is already ['reasoning.encrypted_content'] — which is exactly what a previously-saved entry looks like — none of the branches fire, and this line raises KeyError: 'encrypted_reasoning' after the routing request has already been sent and billed, so the caller loses the result. The same unguarded write is at line 1080 in the probe-reuse branch.
Repro shape (the module docstring advertises this library as "shared by the CLI and TUI", so any second frontend that round-trips an entry hits it):
e = connect.configure_entry(connect.plan(..., 'responses', ...).entry)
e['provenance'].pop('encrypted_reasoning') # or: entry loaded from YAML
async for _ in connect.run_steps(replace(p, entry=e), approved='minimal', api_key=k): ...
# KeyError: 'encrypted_reasoning'A hand-written chat-style entry carrying an include key reaches the same line too, since configure_entry only manages include for Responses entries. Use provenance.setdefault("encrypted_reasoning", {})["outcome"] = "accepted", or have configure_entry always establish the key.
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Fixed in 8893f15: accepted routing records establish encrypted_reasoning provenance with setdefault, including the reuse path. A real mocked-HTTP regression removes that provenance before running the saved Responses entry and verifies the accepted result is retained.
| def add_encrypted_reasoning_include(api_params: dict[str, Any], scope: str | None) -> None: | ||
| """Request OpenAI encrypted reasoning only on endpoints known to support it.""" | ||
| configured = api_params.get("include") | ||
| if configured == []: |
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The opt-out matches only a literal list; an empty tuple or set falls through and gets the include added back.
The very next line already treats list/tuple/set as equivalent, so the two checks disagree on adjacent lines. Verified against scope responses:openai:https://api.openai.com/v1:
include=[] -> key removed ✅
include=() -> ['reasoning.encrypted_content'] ❌
include=set() -> ['reasoning.encrypted_content'] ❌
get_llm_client('alias', include=()), or any config layer that normalises sequences to tuples, therefore sends the exact field the opt-out exists to suppress — and on the endpoint Connect already recorded as rejecting it (provenance.encrypted_reasoning.outcome == 'rejected', written by _disable_encrypted_reasoning) the call fails with the very 400 this opt-out was added to avoid.
| if configured == []: | |
| if isinstance(configured, (list, tuple, set)) and not configured: |
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Fixed in 8893f15: empty list, tuple and set values are all explicit opt-outs before native endpoint defaults are added. A parametrized regression verifies include is omitted in all three cases.
| raise click.UsageError( | ||
| "New reasoning levels need request settings; supply --levels-file" | ||
| ) | ||
| patches = {label: deepcopy(original_levels[label]) for label in labels} |
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KeyError on exactly the recovery path the error message four lines above recommends.
The guard on line 727 is skipped when levels_file is truthy, but this comprehension still indexes original_levels[label] for every label. Sequence:
nooa connect --edit-model saved --levels-file levels.yaml- At the interactive "Reasoning levels" prompt the user adds
ultra, which the saved entry doesn't have — precisely what lines 728-730 instruct: "New reasoning levels need request settings; supply --levels-file". original_levels['ultra']→KeyError: 'ultra'.
KeyError is not in the except (ValueError, OSError, yaml.YAMLError, httpx.HTTPError) handler at line 1051, so the command dies with a raw traceback and exit 1.
The comprehension's result is immediately overwritten by lines 732-734 on this branch anyway, so it is pure dead work:
| patches = {label: deepcopy(original_levels[label]) for label in labels} | |
| if not levels_file: | |
| patches = {label: deepcopy(original_levels[label]) for label in labels} |
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Fixed in 8893f15: editing only copies original level blocks when no levels file is supplied. The regression adds ultra via the file while the original entry lacks it and verifies the resulting proposal uses the supplied settings.
| return missing | ||
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| def configure_entry(entry: dict, *, reply_tokens: int | None = None) -> dict: |
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A literal api_key: survives configure_entry and is written straight into llm_config.yaml — only --stage save rejects it.
Verified by execution:
entry = {..., 'api_key': 'sk-LITERAL-SECRET'}
configure_entry(entry) # -> 'api_key' still present
connect.write(entry, p, alias='mine')
'sk-LITERAL-SECRET' in p.read_text() # True_connect_stages.py:108 is the only guard in the PR:
if "api_key" in entry:
raise click.UsageError("Use api_key_env, never a literal key")The interactive path never checks — --edit-model deep-copies the existing entry into merged at connect.py:763, preserving every custom field. So nooa connect --edit-model foo cheerfully rewrites a plaintext credential into llm_config.yaml (a file that is frequently committed), while nooa connect --stage save refuses the byte-identical entry.
Move the check into configure_entry, which both frontends already call, so every future save-time rule protects both.
(Distinct from the existing thread on _connect_stages.py:108, which is about nested keys inside that one frontend's check: this is about the check not existing at all on the interactive path, for a plain top-level api_key.)
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Fixed in 8893f15 at the shared configure_entry boundary, including recursive nested fields. Both interactive/library writes and stage save now reject literal credentials before persistence. Error messages name the rule without echoing credential values; stage-save regressions verify no file or secret output.
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| document = json.loads(Path(path).read_text()) | ||
| data = document.get("data", document) | ||
| if not isinstance(data, dict) or connect.normalize_endpoint( |
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A discovery file produced by --stage discover is rejected when replayed with the same --endpoint the user originally typed.
discover() rewrites its base on a 404 (connect/__init__.py:264-267: base += "/v1") and returns Discovery(base, …), so the saved JSON records the rewritten form. This comparison then fails on exact normalized equality:
$ nooa connect --stage discover --endpoint https://api.test # GET /models -> 404, falls back to /v1
... d.json: {"data": {"api_base": "https://api.test/v1", ...}}
$ nooa connect MODEL --discovery-file d.json --endpoint https://api.test
ValueError: Discovery metadata belongs to a different endpoint
The endpoint is in fact identical; only the adapter's normalization of discover()'s own /v1 fallback differs. Accept a match after removesuffix("/v1") on both sides (the way _connect_registry.credential_names already does).
Minor, same line: data.get("api_base", "") on a document without that key calls normalize_endpoint(""), which raises the generic "Endpoint must be an HTTP(S) URL without credentials, query or fragment" instead of the intended message.
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Fixed in 8893f15: discovery reuse compares normalized endpoints with the terminal /v1 removed, matching discovery's own fallback. Missing api_base gets the discovery-specific validation error. Tests accept the original root endpoint and still reject a different host.
| if yaml.safe_load(text) != expected: | ||
| raise ValueError("Could not construct the registry update without changing other entries") | ||
| path.parent.mkdir(parents=True, exist_ok=True) | ||
| with tempfile.NamedTemporaryFile( |
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write() silently narrows the registry file to 0600, replaces a symlink with a regular file, and leaks the temp file on I/O errors.
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Mode.
tempfile.NamedTemporaryFilecreates 0600 andos.replacecarries the temp inode's mode onto the destination. Verified: anllm_config.yamlat 0644 comes back as 0600 afterconnect.write(), with no warning and no mention in the "Saved <alias> to <path>" message. Contrastwrite_secret_env, which chmods 0600 deliberately because it holds a credential — the registry holds onlyapi_key_envnames. A project- or system-level registry readable by a service account or another user silently loses access. Capturepath.stat().st_modefirst and restore it (or use0o666 & ~umaskfor new files). -
Symlink.
~/.config/nooa/llm_config.yamlsymlinked into a dotfiles repo is replaced by a regular file; the tracked target keeps the old content and silently stops receiving updates.path.resolve()before writing. -
Temp leak.
temporary_path = Path(temporary.name)is the last statement inside thewith, so anOSErrorduringwrite/flush/fsync(ENOSPC, EDQUOT, EIO) escapes before thetry/finallythat unlinks it — allm_config.yaml.<random>droppings file is left next to the registry on every failed attempt.nooa.secrets.write_secret_envgets this right by bindingtemporary = Nonebefore thetryand assigning it as the first statement inside thewith.
(Distinct from the existing thread on line 1368 about the concurrent-write race — these three are independent of the optimistic-lock question.)
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Fixed in 8893f15: resolve symlinks before the update, preserve the existing registry mode and CRLF newlines, and bind the temp path before any write/flush/fsync inside the cleanup try/finally. An injected fsync failure leaves the registry unchanged and no staging file. New registries remain conservatively owner-only; secrets remain deliberately 0600.
| record["elapsed_seconds"] = round(time.monotonic() - started, 3) | ||
| if isinstance(status, int): | ||
| record["status_code"] = status | ||
| record["outcome"] = "rejected" if status == 400 else "not_probed" |
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A 422 rejection is persisted and displayed as "Not checked".
Only 400 maps to rejected; every other status falls to not_probed, whose documented meaning is we never checked. But the request was sent and refused. 422 is the common shape for an unsupported tools schema or reasoning field on vLLM/FastAPI-based gateways — and _include_rejected at line 58 explicitly treats {400, 422} as a field rejection, so the two halves of the same feature disagree about what a 422 means.
The display compounds it: _connect_view.check_failure has arms for 401/403, 404, 429, >=500, Timeout, ReasoningReplayError and APIConnectionError — none for 422 — and the record carries no reason, so detail is None and the row renders from the fallback table:
! Tool use: Not checked
The same mislabel goes into --stage's JSON report and into the diagnostic prompt handed to an agent. Suggest treating any 4xx that isn't 401/403/429 as rejected (or at least adding 422), and giving check_failure a generic 4xx arm.
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Fixed in 8893f15: actual 422 responses are rejected and the CLI gives a request-settings explanation. A response hook also records the observed HTTP status: malformed HTTP-200 replies that LiteLLM labels 422 are instead not_confirmed (reply not understood), so local parse failure is not confused with provider rejection. Timeout wording retains priority over generic 4xx text.
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Overall looks good to me. A few comments from me and AI.
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[AI Take] Follow-up sweep at head Each mechanism below was confirmed by reading the code at this head. 1. You cannot answer
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Signed-off-by: Paul Furgale <pfurgale@nvidia.com>
Signed-off-by: Paul Furgale <pfurgale@nvidia.com>
Signed-off-by: Paul Furgale <pfurgale@nvidia.com>
3 participants
Summary
Add
nooa connect: an interactive model-configuration wizard, independent JSON stages, and the reusablenooa.unifiedllm.connectlibrary. All prompts and terminal dependencies remain innooa-cli; core gains no dependencies. UnifiedLLM is not made separately installable.Current main (including #331) is merged and conflicts are resolved. Frozen head:
8893f15e53baa50859fd7f83e845c09063443424. The dedicatednooa-model-configurationskill owns model setup and diagnostics; agent authoring only links to it.Configuration and checks
transport: direct. Earlier runtimes ignore this sidecar and use LiteLLM; feat(llm): add opt-in direct provider SDK transports #337 will honor it. Edits preserve explicit transport choices. Completed checks record the actual runtime transport separately.includeis a persisted opt-out. No model tools are executed.Review fixes
modelsandenvmappings work; layered tombstones are respected./v1fallback reuse, missing encrypted-reasoning provenance and 422 reporting are fixed. Unobserved request capture is distinguished from settings proven absent; malformed HTTP-200 replies are not described as provider rejection.verdict(entry)and a documentedProbeRecordshape. CLI prompt-toolkit minimum is corrected to 3.0.52, with no core dependency change.Review guide
skills/nooa-model-configuration/SKILL.mdanddocs/model-connect.md.src/nooa/unifiedllm/connect/__init__.py: configuration, plans, evidence, persistence._session.pyand_records.py: bounded conversation checks and shared evidence/verdict policy.packages/nooa-cli/src/nooa_cli/commands/_connect_wizard.pyand_connect_stages.py: terminal steps and JSON contract.test_connect_final_review.py, bothtest_connect_severin_review.pyfiles, and wizard transcript tests.Validation
Exact offline selection:
LITELLM_LOCAL_MODEL_COST_MAP=True \ PYTHONPATH=src:packages/nooa-cli/src:. \ uv run --no-sync --with prompt-toolkit --with msgpack pytest \ tests/unifiedllm packages/nooa-cli/tests/test_connect* \ tests/test_secrets.py tests/test_model_configuration_doc.py -q1,457 passed, 5 deselected on the frozen head. Ruff lint/format,
git diff --check, and dedicated skill validation passed. These are offline HTTP-contract tests, not new live-provider evidence. Fresh reviewer approval and CI are still required; previous approvals do not automatically cover this larger revision.