ProviderConfig.thinking_style defaults to None (Optional field), but
create_dynamic_spec expects a string. Coalesce None to "" at all call
sites (factory.py, settings_api.py) and fix the test assertion to
expect None from the config default.
The onboard wizard dispatched field handlers by bare field name, so
WebSearchConfig.provider was hijacked by the LLM-provider handler and
showed LLM providers instead of search engines. Keenable was also never
wired into the CLI wizard when it landed in the WebUI.
- Add a single source of truth for selectable search providers
(SEARCH_PROVIDER_OPTIONS in web.py); WebUI settings now import it.
- Add a WebSearchConfig-aware search-provider picker to the wizard and
resolve handlers by (model type, field name) so the LLM and search
provider fields no longer collide.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
maintainer edit: Settings reads local Codex token storage to avoid refresh work, so expired access tokens with refresh credentials still need to count as configured until real provider use refreshes them.
Bring the Keenable search provider in line with the established
multi-file provider pattern so it surfaces everywhere the others do:
- settings_api.py: register in the web-search provider options so it
appears in the WebUI settings dropdown (credential: api_key, optional).
- WebUI provider-brand: add keenable brand entry + brand test.
- docs/configuration.md: provider table row + config example.
- Harden _search_keenable: honor config.timeout and return explicit
messages on HTTP status errors (429 / other), matching peer providers.
- Add env-key and HTTP-error tests; add the websocket settings whitelist
assertion.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Mistral's API constrains reasoning_effort to "high"/"none", rejects the
kwarg entirely for Magistral (reasoning is implicit), returns assistant
content as a mixed array of {type:"thinking",...}/{type:"text",...}
blocks, and 400s on the reasoning_content key in history.
- Remap user-supplied reasoning_effort (low/medium/minimal) onto Mistral's
two-tier vocabulary; strip the kwarg for Magistral models
- Lift thinking blocks into reasoning_content for both batch and streaming
responses; pass only text through on_content_delta callbacks
- Drop reasoning_content from outbound history when the spec asks for it
- Expose per-preset reasoning_effort_values so the UI can render the
provider-specific option set
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
maintainer edit: keep the WebUI dynamic-provider behavior unchanged while reducing repeated test setup and tightening the small dynamic-provider helper.
maintainer edit: WebUI settings still treated non-registry custom providers as unknown, so users could not select them in model configurations or fetch their model list. Reuse dynamic provider specs for settings payloads, model-list requests, and provider updates.
Add AssemblyAI as a third transcription provider option alongside
OpenAI and Groq. AssemblyAI offers better accuracy for certain
audio types (distant voices, noisy environments) and serves as a
reliable fallback when other providers struggle.
Changes:
- Add AssemblyAITranscriptionProvider class in providers/transcription.py
- Add 'assemblyai' option in base channel's transcribe_audio()
- Per-channel configuration via transcriptionProvider in config
Usage:
Set transcriptionProvider: 'assemblyai' and provide an AssemblyAI
API key via transcriptionApiKey in the channel config.
Add support for Xiaomi MiMo ASR as a third transcription backend alongside
Groq and OpenAI Whisper. Xiaomi ASR uses the /v1/chat/completions endpoint
with base64-encoded audio input, rather than the standard Whisper multipart
upload format.
Co-Authored-By:连 <lian@tangping.homes>
Add a `transcriptionModel` channel setting and an OpenRouter transcription
backend so voice messages can be transcribed through OpenRouter's
speech-to-text endpoint (e.g. nvidia/parakeet-tdt-0.6b-v3, openai/whisper-1),
alongside the existing Groq/OpenAI Whisper providers.
- schema: add channels.transcriptionModel (None = provider default)
- providers/transcription: extract a shared POST/retry skeleton; add a
JSON+base64 OpenRouterTranscriptionProvider; make the STT model a
constructor param on all providers instead of hardcoding it
- channels: route transcriptionProvider="openrouter" and thread the model
through the manager to each channel
- docs + tests
Only dedicated STT models work on OpenRouter's transcription endpoint;
chat LLMs (e.g. google/gemini-3.5-flash) are rejected there.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* refactor(dream): replace two-phase Dream class with simple cron + process_direct
- Remove the heavyweight Dream class (AgentRunner-based two-phase system)
from nanobot/agent/memory.py
- Delete dream_phase1.md and dream_phase2.md templates
- New dream.md template serves as the consolidation prompt
- Cron callback uses agent.process_direct(prompt, session_key=\"dream\")
instead of agent.dream.run()
- Always performs git auto_commit after execution
- /dream command updated to use process_direct + git commit
- DreamConfig kept for backward compatibility; deprecated fields
(model_override, max_batch_size, max_iterations, annotate_line_ages)
are ignored but accepted in config
- interval_h remains configurable via agents.defaults.dream.interval_h
- Update tests and webui settings to match new architecture
* feat(loop): add ephemeral mode to process_direct, skip history writes for Dream
When ephemeral=True, _state_save skips enforce_file_cap (which calls
raw_archive -> append_history) and consolidator.maybe_consolidate_by_tokens.
This prevents Dream sessions from creating a positive feedback loop where
they process their own output. The session IS still saved to disk.
* fix(loop): skip extra hooks for ephemeral sessions (Dream)
* feat(dream): per-run timestamped sessions with rotation for WebUI
* test(config): restore DreamConfig schedule and alias tests
* fix(dream): include LLM response summary in git auto-commit message
The old two-phase Dream class included the Phase 1 analysis in the git
commit message body. The new single-phase version lost this. Restore it
by extracting resp.content from the process_direct return value and
appending it to the commit message in both the cron handler and the
/dream command.
* fix(test): accept ephemeral kwarg in test_openai_api fake_process
* refactor(dream): merge dream_session.py into MemoryStore
The standalone dream_session.py module only contained three small helpers
that all revolve around MemoryStore concerns (session keys, commit messages,
file pruning). Fold them into MemoryStore as @staticmethod to reduce
indirection and avoid a 35-line module with no independent reason to exist.
* fix(test): address code review — patch correct instance, use actual function
- Fix test_ephemeral_skips_raw_archive to patch loop.context.memory
instead of the fixture's separate MemoryStore instance
- Fix TestDreamCommitMessage to call MemoryStore.build_dream_commit_message
instead of reimplementing the logic inline
- Move Dream helpers in memory.py above the Consolidator section comment
to avoid misleading visual boundary
* fix(dream): gate cursor advancement and restrict tools
maintainer edit: Dream now processes backlog from the oldest unprocessed entries, only advances the cursor after a completed ephemeral run, and uses a restricted file-only tool registry for background consolidation.
* fix(dream): skip idle compact for dream sessions
Dream runs use internal dream:* sessions that are pruned by Dream retention. Exclude them from AutoCompact scheduling, archive execution, and summary injection so idle-session compaction cannot truncate Dream transcripts.
* fix(dream): keep batched history isolated
* feat(dream): tag archived memory for single-phase Dream
---------
Co-authored-by: Xubin Ren <52506698+Re-bin@users.noreply.github.com>
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