These tests guard against catastrophic regex backtracking (seconds/minutes),
not 12ms differences. CI runners with coverage instrumentation (cargo-llvm-cov)
consistently exceed the 100ms threshold due to overhead, causing flaky failures.
500ms still catches real regressions while tolerating CI variability.
[skip-regression-check]
Co-authored-by: Claude Opus 4.6 (1M context) <[email protected]>
* fix: Rate limiter returns retry after None instead of a duration
linter fix
* review fixes
* fix: rate limiter returns None for retry_after duration
Add regression test to src/llm/retry.rs that verifies RateLimited errors
always have a fallback duration (never None) due to the 60-second fallback
applied in all rate limit error creation sites (nearai_chat.rs,
anthropic_oauth.rs, embeddings.rs).
The production code fix adds `.or(Some(Duration::from_secs(60)))` to ensure
the error message never displays "retry after None" to the user.
[skip-regression-check]
Co-Authored-By: Claude Haiku 4.5 <[email protected]>
---------
Co-authored-by: Claude Haiku 4.5 <[email protected]>
- Remove duplicate build_nearai_model_fetch_config() definition from setup/wizard.rs
(function already exists in llm/models.rs and is imported)
- Add missing cheap_model and smart_routing_cascade fields to LlmConfig
initializer in build_nearai_model_fetch_config() (llm/models.rs)
- Pass request_timeout_secs to create_registry_provider() call
(llm/mod.rs:432)
All clippy checks pass with zero warnings (--no-default-features --features libsql).
Co-Authored-By: Claude Haiku 4.5 <[email protected]>
Resolved merge conflicts in 5 files:
1. src/agent/job_monitor.rs - Used is_internal flag approach (HEAD) for safe internal message marking. Removed metadata-based approach which could be spoofed by external channels.
2. src/agent/agent_loop.rs - Used is_internal check (HEAD) for routing internal messages, consistent with security model where is_internal field cannot be spoofed.
3. src/agent/dispatcher.rs - Included notify_metadata in job context (main), needed for job routing through JobMonitorRoute.
4. src/setup/wizard.rs - Added build_nearai_model_fetch_config() function (main) for model selection during setup.
5. src/tools/builtin/job.rs - Used both comments from HEAD (clarifying notify_channel and notify_user logic) while removing metadata field from JobMonitorRoute (consistent with job_monitor.rs).
All conflicts resolved with security-first approach: use is_internal boolean field for internal message marking (cannot be spoofed), while passing routing metadata through context.
Co-Authored-By: Claude Haiku 4.5 <[email protected]>
* feat: add LLM_CHEAP_MODEL for generic smart routing across all backends
Add generic cheap model support that works with any LLM backend, not just
NearAI. New env vars: LLM_CHEAP_MODEL (cheap model for any backend) and
SMART_ROUTING_CASCADE (top-level cascade flag).
Resolution order: LLM_CHEAP_MODEL > NEARAI_CHEAP_MODEL (backward compat).
Registry-based providers (OpenAI, Anthropic, Groq, etc.) clone their
RegistryProviderConfig with the cheap model swapped in. Bedrock returns
an explicit error (not yet supported). All error paths use ok_or_else
with proper LlmError variants -- no unwrap/expect in production code.
* refactor: address Gemini review — remove unnecessary async, extract cheap_model_name()
- Remove async from create_cheap_provider_for_backend() and
create_cheap_llm_provider() — neither contains .await calls
- Extract duplicated cheap model resolution logic into
LlmConfig::cheap_model_name() helper method (DRY)
- Revert tests from tokio::test async back to sync #[test]
- Add test_cheap_model_name_resolution() unit test for the helper
---------
Co-authored-by: SMKRV <[email protected]>
Route messages and replies to the correct Telegram forum topic via
message_thread_id. Key behaviors:
- Parse message_thread_id, is_topic_message, is_forum from incoming updates
- Thread agent sessions by "chat_id:topic_id" for forum groups only
(non-forum reply threads are excluded via is_forum guard)
- Pass message_thread_id through all send methods (text, photo, document)
- Normalize thread_id=1 (General topic) to None for sendMessage/sendPhoto/
sendDocument since Telegram rejects it, but preserve it for sendChatAction
where Telegram requires it for typing indicators
- Hoist bot_username workspace read to avoid duplicate WASM host call per
group message
Co-authored-by: Claude Opus 4.6 (1M context) <[email protected]>
* feat(orchestrator): read ORCHESTRATOR_PORT env var for configurable API port
The orchestrator internal API port was hardcoded to 50051 in two places
(ContainerJobConfig and OrchestratorApi::start call), making it impossible
to run multiple IronClaw instances on the same host — the second instance
fails with "Address already in use".
NETWORK_SECURITY.md already documents ORCHESTRATOR_PORT as configurable,
and ContainerJobConfig.orchestrator_port is propagated to worker containers
via IRONCLAW_ORCHESTRATOR_URL, but the env var was never actually read.
Extract resolve_orchestrator_port() that reads ORCHESTRATOR_PORT and falls
back to 50051. Includes tests for valid, invalid, and out-of-range values.
* test: add ENV_LOCK mutex for env-var test serialization
Address Gemini review: add std::sync::Mutex to serialize env var access
across test threads. Keep unsafe blocks — required in Rust edition 2024
where std::env::set_var/remove_var are unsafe functions.
---------
Co-authored-by: SMKRV <[email protected]>
* feat(transcription): add Chat Completions API provider for audio transcription
The existing transcription pipeline only supports the OpenAI Whisper API
(/v1/audio/transcriptions with multipart upload). Providers like OpenRouter
expose audio transcription through the Chat Completions API instead, using
base64-encoded audio in the `input_audio` content type.
Add `ChatCompletionsTranscriptionProvider` that sends audio as base64 in
a chat completion request and extracts the transcript from the response.
Compatible with OpenRouter, OpenAI GPT-4o-audio, and any provider that
supports audio input via Chat Completions.
Config changes:
- TRANSCRIPTION_PROVIDER=chat_completions selects the new provider
- TRANSCRIPTION_API_KEY overrides provider-specific keys
- LLM_API_KEY used as fallback for chat_completions provider
- Default model per provider (whisper-1 for openai, gemini-2.0-flash for
chat_completions)
* style: address review feedback — formatting, idiomatic patterns
- Fix rustfmt formatting for provider constructor chain
- Use or_else for resolve_api_key priority chain (Gemini review)
- Use trim_end_matches('/') instead of while loop (Gemini review)
---------
Co-authored-by: SMKRV <[email protected]>
* fix(jobs): make completed->completed transition idempotent to prevent race errors
Both execution_loop and the worker wrapper in execute() can race to call
mark_completed(). Previously the second call hit "Cannot transition from
completed to completed" and errored the job despite successful completion.
This narrowly allows only the Completed->Completed self-transition as
idempotent (early return with debug log, no duplicate history entry).
All other self-transitions remain rejected to preserve state machine
strictness.
Co-Authored-By: Claude Opus 4.6 <[email protected]>
* style: fix assert! formatting in idempotent completion test
Co-Authored-By: Claude Opus 4.6 <[email protected]>
---------
Co-authored-by: Claude Opus 4.6 <[email protected]>
* fix(llm): persist refreshed Anthropic OAuth token after Keychain re-read (#1136)
The Anthropic OAuth provider stored its token as an immutable SecretString.
When a 401 triggered a Keychain re-read, the fresh token was used for a
single retry but never persisted — every subsequent request reused the
expired original token, causing repeated auth failures.
Changes:
- Wrap token in RwLock<SecretString> so it can be updated after refresh
- Persist refreshed token via update_token() on successful retry
- Add 500ms delay before Keychain re-read to give Claude Code time to
complete its async token refresh write (reduces race window)
- Add regression test verifying token updates persist across reads
Closes#1136
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* style: fix formatting
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
---------
Co-authored-by: Claude Opus 4.6 (1M context) <[email protected]>
* fix(worker): prevent orphaned tool_results and fix parallel merging
Two fixes for tool result handling in the Worker:
1. Preserve reasoning text from select_tools() in the RespondResult
content field so it appears in the assistant_with_tool_calls message
pushed by execute_tool_calls. Without this, the LLM's reasoning
context was lost when using the select_tools path.
2. Merge consecutive tool_result messages into a single User message
in rig_adapter's convert_messages(). When parallel tools execute,
each produces a separate ChatMessage with role: Tool. Without
merging, these become consecutive User messages which Anthropic
rejects. Now consecutive tool results are merged into one User
message with multiple ToolResult content items.
Includes regression tests for both fixes.
Co-Authored-By: Claude Opus 4.6 <[email protected]>
* fix(worker): use find_map for first non-empty reasoning extraction
The previous code only checked the first ToolSelection's reasoning,
missing cases where the first selection has empty reasoning but
subsequent ones do not. Switch to find_map to get the first non-empty
reasoning across all selections.
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
---------
Co-authored-by: Claude Opus 4.6 <[email protected]>
Coffee