feat(llm): retain Anthropic/Gemini state and portable plain-text reasoning

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Summary

Retain opaque provider state for compatible replay and persist/replay plain-text reasoning across models. Readable reasoning is also exported through OTLP; encrypted state and signatures are not.

• extend feat(llm): retain compatibility-scoped OpenAI reasoning state #310's Chat envelope to Anthropic signed/redacted thinking and Gemini thought signatures
• preserve provider-readable reasoning text on canonical LLMResponse.reasoning
• restore opaque state only when provider, API style, exact model, and complete public carrier match
• keep Gemini's private inline tool-call IDs out of NOOA's public tool API, then restore both call and result IDs at dispatch
• strip direct provider-private fields that did not arrive through a validated envelope
• warn on expected compatibility fallback and hard-fail malformed current state
• redact opaque state from HTTP, journal, tracing, and flattened diagnostics

Why this layer exists

A provider response has public conversational meaning and sometimes private protocol state. Anthropic returns signed thinking blocks; Gemini returns thought signatures, including signatures embedded by LiteLLM in tool-call IDs. Those artifacts may be required for the next compatible request, but they are not ordinary prompt text and must never reach another provider.

NOOA therefore needs two representations at two different boundaries:

• the durable, provider-independent LLMResponse used by events, SQLite sessions, formatters, middleware, and strategies;
• the provider-native message reconstructed only at the final UnifiedLLM dispatch edge.

The event record stores readable reasoning as text and the provider artifact as one opaque llm_state blob. It does not grow Anthropic/Gemini fields. The replay adapter opens that blob only after the target scope and the unchanged public assistant carrier prove that it belongs.

This also protects cache stability. Reconstructing the original provider message at the edge preserves the provider's expected turn shape; the public event history remains canonical and does not accumulate synthetic or partially translated provider messages.

Code walkthrough: what changed and why

1. Anthropic capture and replay.
   What: CompletionClient captures native thinking and redacted-thinking blocks, including signatures, and restores them only on a matching Anthropic Chat scope and unchanged carrier.
   Why: signed thinking must remain paired with the exact turn that produced it and is unsafe outside that compatibility boundary.

2. Gemini capture and replay.
   What: UnifiedLLM captures message-level and per-tool thought signatures. When provider evidence identifies LiteLLM's inline signature suffix, NOOA exposes a clean public tool-call ID, stores the suffix privately, and restores the private ID on both the assistant tool call and its later tool-result message.
   Why: Gemini requires matching signed call/result IDs, while NOOA tools, event storage, and other providers need stable public IDs with no opaque payload embedded in them. A non-Gemini ID merely containing __thought__ remains an ordinary ID, even with an empty suffix.

3. Shared full-carrier proof.
   What: feat(llm): retain compatibility-scoped OpenAI reasoning state #310's exact carrier binding is generalized across supported Chat state: assistant text plus each ordered tool call's ID, name, and arguments must still match.
   Why: checking only IDs or list length could attach stale signatures after middleware changes the actual request.

4. Plain-text reasoning: persistence, cross-model replay, and OTLP export.
   What: Chat reasoning and OpenAI Responses summaries populate LLMResponse.reasoning. When opaque replay is unavailable, refactor(llm): make LLMResponse the canonical assistant turn #312's provider-independent path demotes that text to ordinary assistant context. The tracing adapter emits Chat reasoning and native Responses summaries as llm.reasoning_content, including when journal mode strips the full LLM message attributes.
   Why: readable reasoning can remain useful after model/provider switching without teaching the target a foreign private schema. A valid summary without encrypted content is ordinary text, not a corrupt response; mixed summary-only/encrypted sequences demote together instead of partially losing reasoning. OTLP is observational, not a replay archive, so human-readable reasoning must remain available without exporting opaque protocol state.

5. Direct wire-state stripping.
   What: raw thinking blocks, provider-specific fields, and confirmed inline signatures supplied directly in public messages are removed and reported. Only a validated NOOA envelope can restore them.
   Why: otherwise callers, old middleware, or archives could bypass the compatibility gate.

6. Visible failure policy.
   What: expected model/API incompatibility or a changed carrier warns and safely demotes text. Malformed current envelopes, unsupported known-provider shapes, ambiguous tool identity, unsupported Responses items/content blocks, invalid stored ordering, and unscopable opaque output raise ReasoningReplayError rather than retaining a partial turn; strategies do not retry that deterministic error.
   Why: model switching is recoverable. Corrupt state or a newly changed provider contract is a framework defect and must not be silently swallowed.

7. Trace privacy.
   What: scrubbers cover OpenAI encrypted content, Anthropic signature/data fields, Gemini snake/camel-case signatures, JSON-string attributes, and flattened inline IDs.
   Why: excluding blobs from repr is insufficient if HTTP or tracing diagnostics can export them.

8. No provider leakage into the event system.
   What: provider details remain concentrated in unifiedllm/replay_state.py; storage and rendering continue to depend only on canonical LLMResponse.
   Why: NOOA should expose one durable turn interface, not LiteLLM objects or a catalog of provider message classes.

9. Keep result IDs and turn bookkeeping consistent.
   What: structurally confirmed inline-signature removal also updates the matching tool result; an aborted CodeAct replay emits a final failed turn. HTTP logging reuses the shared tracing scrubber.
   Why: a cleaned assistant ID must still match its result, failed generations must not look resumable, and one redaction implementation prevents provider handling from drifting between logs and traces.

Supported surface

• OpenAI/Azure: Responses summaries here; encrypted OpenAI replay remains in feat(llm): retain compatibility-scoped OpenAI reasoning state #310
• Anthropic: Chat thinking and redacted-thinking blocks
• Gemini: Chat thought signatures, including per-tool/call-result alignment
• every provider exposing readable reasoning: generic text persistence and replay inherited from refactor(llm): make LLMResponse the canonical assistant turn #312

Native Bedrock and Vertex opaque replay remain fail-closed until their issuer compatibility is established. NVIDIA's OpenAI-compatible routes work when the response itself carries the supported Anthropic/Gemini structure; no model-name condition is used.

Non-goals

• no model capability catalog
• no TUI changes
• no reasoning-effort controls
• no speculative Bedrock/Vertex compatibility groups

Validation

• OTLP/copy-reduction round (2026-09-11): 724 passed across tracing and UnifiedLLM; eight OTLP cases exercise real span finalization, secret scrubbing, journal-mode filtering, and HTTP JSON serialization for Chat reasoning fields, <think> text, and native Responses summaries. No inference calls. Ruff and targeted Pyright pass.

• latest regression round: real SDK → JSON/SQLite → serialized HTTP tests cover multi-block text, ordered/phased messages, summary-only reasoning, unsupported whole-turn rejection, and eligible Anthropic cache-marker fallback; independent repeat review found no remaining blockers

• focused replay/formatter/tracing/strategy set after review: 152 passed

• final combined stack: 7,364 passed, 10 skipped, 239 deselected, 3 expected xfails

• mutations of text, tool name, arguments, IDs, order, count, state-only carriers, and direct thinking fields withhold opaque state

• Ruff, targeted Pyright, DCO trailers, and diff checks pass

• top-stack live NVIDIA Inference Hub SQLite close/reopen tests: Sonnet 5 and Gemini 3.1 Pro retained exact opaque state and stable wire requests; resumed calls reported 10,847 and 24,491 cached input tokens respectively. Sonnet 5 used the hub's native Anthropic Messages endpoint.

• additional previously verified NVIDIA Inference Hub coverage:

  • Claude Sonnet-class signed thinking survived JSON resume and an accepted follow-up
  • Gemini 3.1 Pro opaque state survived JSON resume; clean public IDs were restored to matching signed assistant/tool-result IDs and the follow-up was accepted
  • Gemini opaque state was withheld from Nemotron, which accepted the public turn

Stacked on #310.

Summary by CodeRabbit

• New Features

  • Preserves portable reasoning text across supported chat and responses workflows.
  • Supports safer provider-specific reasoning-state replay, with compatibility checks and fallback behavior.
  • Exposes ReasoningReplayError for malformed or unsupported replay state.

• Bug Fixes

  • Normalizes missing tool-call arguments to empty strings.
  • Prevents replay errors from being hidden by automatic strategy retries.

• Security

  • Redacts additional provider-specific reasoning signatures and opaque thinking data from logs and traces.

• Documentation

  • Clarifies reasoning portability, replay compatibility, warnings, and error behavior.

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📝 Walkthrough

Walkthrough

The change adds provider-scoped reasoning replay for Chat and Responses APIs. It validates and demotes incompatible state, preserves portable reasoning text, propagates replay errors, and expands opaque-state redaction for HTTP logs and traces.

Changes

Provider reasoning replay

Layer / File(s)	Summary
Replay contracts and provider validation src/nooa/unifiedllm/replay_state.py	Replay scopes and provider-specific reasoning state now support OpenAI, Azure, Anthropic, and Gemini. Validation distinguishes malformed state from expected incompatibility.
Client replay integration src/nooa/unifiedllm/unifiedllm.py, src/nooa/unifiedllm/__init__.py, tests/unifiedllm/test_finish_reason_propagation.py	Chat tool-call IDs use replay scopes, missing arguments become empty strings, and Responses results preserve reasoning text. Untrusted reasoning items are removed.
Cross-provider replay validation tests/unifiedllm/test_cross_provider_reasoning.py, tests/unifiedllm/test_reasoning_state_replay.py	Tests cover provider formats, scope stability, carrier mutation, malformed state, state demotion, Responses ordering, and warning behavior.
Replay error propagation src/nooa/strategies/codeact.py, src/nooa/strategies/pure_python.py, tests/strategies/test_error_recovery_gl106.py, skills/nooa-context-and-state/SKILL.md	Strategies now propagate ReasoningReplayError without generic recovery or retries. Documentation describes portable reasoning and opaque state handling.
Provider state redaction src/nooa/unifiedllm/http_logging.py, src/nooa/tracing/*, tests/unifiedllm/test_http_logging.py, tests/tracing/*	HTTP logging and tracing redact provider signatures, encrypted state, Gemini inline signatures, and redacted-thinking data while preserving readable thinking text.

Estimated code review effort: 5 (Critical) | ~90 minutes

Sequence Diagram(s)

sequenceDiagram
  participant Provider
  participant UnifiedLLM
  participant ReplayState
  participant Strategy
  Provider->>UnifiedLLM: Return reasoning, tool calls, and provider state
  UnifiedLLM->>ReplayState: Capture or prepare replay state
  ReplayState->>UnifiedLLM: Restore compatible state or portable reasoning
  UnifiedLLM->>Strategy: Raise ReasoningReplayError for malformed state
  Strategy->>Strategy: Stop generic recovery and retries

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Suggested reviewers: rdasilveiracabral

Merge Risk: 🟡 Moderate · up to dce53

Several reachable replay paths can lose reasoning or produce mismatched tool-call state, so these issues should be corrected before merge. CodeAct terminal telemetry is also inaccurate on replay failure.

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 24.24% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 132 functions across 29 files. (1 skipped…	Write docstrings for the functions missing them to satisfy the coverage threshold.

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Check name	Status	Explanation
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title clearly summarizes the main change: retaining Anthropic and Gemini provider state while preserving portable plain-text reasoning.

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Explanation

Docstring coverage is 24.24% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 132 functions across 29 files. (1 skipped: 1 unsupported.)

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src/nooa/runtime/actor.py (1)

1247-1247: 🎯 Functional Correctness | 🟡 Minor | ⚡ Quick win

Preserve assistant text in tool-call responses.

When CompletionClient or ResponsesClient returns tool calls with visible assistant text, set LLMResponse.content to that extracted text. ActorRuntime.generate persists only response.content, and the formatter replays tool-call turns from LLMOutput.content, not assistant_message. The next request then omits the assistant text. Use the provider-specific text extraction for Chat and Responses responses before constructing LLMResponse.

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In `@src/nooa/runtime/actor.py` at line 1247, Update the CompletionClient and
ResponsesClient tool-call response handling to extract visible assistant text
using each provider’s existing text-extraction logic, then assign it to
LLMResponse.content before construction. Ensure ActorRuntime.generate can
persist and replay this text through LLMOutput.content while preserving existing
assistant_message behavior.

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Outside diff comments:
In `@src/nooa/runtime/actor.py`:
- Line 1247: Update the CompletionClient and ResponsesClient tool-call response
handling to extract visible assistant text using each provider’s existing
text-extraction logic, then assign it to LLMResponse.content before
construction. Ensure ActorRuntime.generate can persist and replay this text
through LLMOutput.content while preserving existing assistant_message behavior.

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In `@src/nooa/unifiedllm/unifiedllm.py`:
- Line 3198: Update the native function-call carrier handling around
_responses_function_call_carriers so LLM_REASONING_KEY is removed before the
carrier is indexed or replayed. Ensure _responses_event_replay produces input
without this internal field, and add a regression test asserting the replayed
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src/nooa/unifiedllm/unifiedllm.py (1)

3211-3213: 🗄️ Data Integrity & Integration | 🟠 Major | ⚡ Quick win

Preserve reasoning when carrier replay fails.

demoted_reasoning is cleared whenever replay_items is present. If _responses_event_replay cannot find a matching call_id, it discards the pending reasoning and returns no replay. The later fallback does not run because replay_items is still non-empty. The function-call carrier then reaches the provider without its readable reasoning summary.

Preserve or demote pending reasoning when carrier replay fails. Add a regression test with a missing or changed call_id.

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In `@src/nooa/unifiedllm/unifiedllm.py` around lines 3211 - 3213, The
demoted_reasoning assignment must retain pending readable reasoning when carrier
replay fails to produce a valid replay, rather than clearing it solely because
replay_items is non-empty. Update the surrounding replay/fallback logic near
_responses_event_replay so a missing or changed call_id preserves or demotes
reasoning and still reaches the provider, and add a regression test covering
that mismatch.

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In `@src/nooa/unifiedllm/unifiedllm.py`:
- Around line 3211-3213: The demoted_reasoning assignment must retain pending
readable reasoning when carrier replay fails to produce a valid replay, rather
than clearing it solely because replay_items is non-empty. Update the
surrounding replay/fallback logic near _responses_event_replay so a missing or
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🧹 Nitpick comments (1)

src/nooa/strategies/codeact.py (1)

924-925: 📐 Maintainability & Code Quality | 🔵 Trivial | ⚡ Quick win

Mark the turn as final before re-raising ReasoningReplayError.

This branch ends the call, but it does not set turn_state.is_final. session.turn records exception_type and emits AfterTurn with is_final=False. Every other terminal raise in this loop sets turn_state.is_final = True first (Lines 958, 981, 998, 1110), and PurePythonStrategy sets turn_final = True on the same replay-error path. Observability consumers that read AfterTurn.is_final therefore see no final turn for CodeAct on this path.

♻️ Proposed fix for consistent terminal-turn telemetry

                 except ReasoningReplayError:
+                    turn_state.is_final = True
                     raise

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In `@src/nooa/strategies/codeact.py` around lines 924 - 925, Update the
ReasoningReplayError handler in the turn-processing loop to set
turn_state.is_final = True before re-raising the exception. Preserve the
existing re-raise behavior and align this path with the other terminal raises
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Inline comments:
In `@src/nooa/unifiedllm/replay_state.py`:
- Line 413: Update capture_chat_state around _sanitize_chat_payload so it skips
opaque chat-state capture when replay_scope returns None, including responses
containing thinking_blocks. Avoid validating or recording payload fields for an
unsupported provider while preserving capture behavior for supported scopes.

In `@src/nooa/unifiedllm/unifiedllm.py`:
- Line 1886: Update public_tool_call_id to permit empty or missing tool-call IDs
for non-Gemini provider scopes, while retaining strict validation and suffix
parsing for Gemini scopes. Ensure _chat_public_carrier normalizes a missing ID
to an empty string before capturing opaque state, and apply the behavior
consistently in both sync and async response mappers when constructing ToolCall
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Nitpick comments:
In `@src/nooa/strategies/codeact.py`:
- Around line 924-925: Update the ReasoningReplayError handler in the
turn-processing loop to set turn_state.is_final = True before re-raising the
exception. Preserve the existing re-raise behavior and align this path with the
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In `@src/nooa/strategies/codeact.py`:
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exception, then extend the existing codeact test to assert that the aborted turn
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In `@src/nooa/unifiedllm/replay_state.py`:
- Around line 724-726: Update prepare_chat_messages() so private-to-public
tool-call ID remapping does not depend on message order: pre-scan all messages
to build the carrier ID map before applying the existing tool_call_id
replacement, or reject/reorder inputs that place tool results before their
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