- Add `ModelPresetConfig` schema for named model presets
- Add `model_presets` dict to `Config` and `model_preset` field to `AgentDefaults`
- Add `resolve_preset()` to return effective model params from preset or defaults
- Add `@model_validator` to reject unknown preset names
- Update `_match_provider()` to use resolved preset model/provider
- Update `make_provider()` and `provider_signature()` to use `resolve_preset()`
- Add `model_preset` property to `AgentLoop` for atomic runtime switching
- Update `AgentLoop.from_config()` to inject a runtime `default` preset
- Wire self-tool to inspect/clear preset state
- Update CLI display strings to show active preset
VolcEngine's OpenAI-compatible gateway rejects requests when both
max_tokens and max_completion_tokens are present (the latter added
by openai-python SDK v2.x serialization). Set the flag so nanobot
sends max_completion_tokens instead of max_tokens for volcengine,
volcengine_coding_plan, and by extension byteplus variants.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit implements a progressive refactoring of the tool system to support
plugin discovery, scoped loading, and protocol-driven runtime context injection.
Key changes:
- Add Tool ABC metadata (tool_name, _scopes) and ToolContext dataclass for
dependency injection.
- Introduce ToolLoader with pkgutil-based builtin discovery and
entry_points-based third-party plugin loading.
- Add scope filtering (core/subagent/memory) so different contexts load
appropriate tool sets.
- Introduce ContextAware protocol and RequestContext dataclass to replace
hardcoded per-tool context injection in AgentLoop.
- Add RuntimeState / MutableRuntimeState protocols to decouple MyTool from
AgentLoop.
- Migrate all built-in tools to declare scopes and implement create()/enabled()
hooks.
- Migrate MessageTool, SpawnTool, CronTool, and MyTool to ContextAware.
- Refactor AgentLoop to use ToolLoader and protocol-driven context injection.
- Refactor SubagentManager to use ToolLoader(scope="subagent") with per-run
FileStates isolation.
- Register all built-in tools via pyproject.toml entry_points.
- Add comprehensive tests for loader scopes, entry_points, ContextAware,
subagent tools, and runtime state sync.
Add a focused regression test for the non-secure-context WebUI entry shim so missing crypto.randomUUID no longer depends on manual verification.
Co-authored-by: Cursor <cursoragent@cursor.com>
`crypto.randomUUID` only exists in secure contexts (HTTPS or localhost).
Over LAN HTTP it is undefined, so `ChatPane`'s welcome-message flush and
streaming-message handlers crash mid-render with `TypeError`, unmounting
the React tree and leaving the user a blank page.
Install a Math.random-backed v4-ish fallback at app entry, gated on the
feature being missing. This mirrors the shim already used in the test
setup and covers all six call sites (`ChatPane.tsx`, `useNanobotStream.ts`)
without touching them. These IDs are client-side message keys with no
security role, so non-cryptographic randomness is fine.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The hosted Xiaomi MiMo API accepts {"thinking": {"type": "enabled"|"disabled"}}
to toggle reasoning, which is exactly the shape produced by the existing
thinking_type style. The xiaomi_mimo ProviderSpec just needed to opt in.
Before this fix, setting reasoning_effort="none" had no effect on MiMo
because no thinking_style was configured, so the disable signal never
reached the server. Default-on models (mimo-v2.5-pro and friends) kept
reasoning regardless of user configuration.
Source: https://platform.xiaomimimo.com/docs/en-US/api/chat/openai-api
Co-authored with Claude Opus 4.7. Strategy and review via Claude Desktop,
implementation via Claude Code.
Both StreamRenderer instantiations in the agent command (single-message
mode and interactive mode) now read bot_name and bot_icon from
config.agents.defaults and forward them to the renderer.
This is the wiring step that makes the schema fields actually take
effect at runtime. With safe defaults of "nanobot" and "🐈", existing
users see no change.
Threads bot_name/bot_icon through ThinkingSpinner and StreamRenderer
with safe defaults that preserve current behavior.
- ThinkingSpinner uses bot_name in its status text
- StreamRenderer header is "<icon> <name>" when icon is set,
or just "<name>" when icon is empty
- Removes the now-unused __logo__ import (the cat emoji is the
default value of bot_icon, not a hardcoded constant)
Two new fields with safe defaults that preserve current branding:
- bot_name: str = "nanobot"
- bot_icon: str = "🐈"
Empty string for bot_icon is allowed and lets users opt out of the
leading icon. camelCase keys (botName, botIcon) bind via the existing
to_camel alias generator.
Six tests covering:
- AgentDefaults preserves 'nanobot' and the cat icon by default
- camelCase config keys (botName/botIcon) bind to the new fields
- Empty bot_icon is accepted (opt-out of the leading icon)
- ThinkingSpinner uses bot_name in its status text
- StreamRenderer header combines icon and name when icon is set
- StreamRenderer header is just the name when icon is empty
- Append [Archived Context Summary] to system prompt instead of injecting
it into the user message runtime context, improving KV cache reuse across
turns and avoiding consecutive same-role messages.
- _last_summary persists in metadata (no pop) for restart survival;
summary is re-injected every turn via the stable system prompt.
- Remove dynamic "Inactive for X minutes" from _format_summary — use
static last_active timestamp instead to preserve KV cache stability.
- Pass session_summary through build_messages() so both normal and
ask_user paths receive the archived summary in the system prompt.
- estimate_session_prompt_tokens now reads _last_summary from metadata
to include the summary in token budget estimation.
- Remove obsolete session_summary parameter from
maybe_consolidate_by_tokens and estimate_session_prompt_tokens
call sites in loop.py (summary flows through build_messages instead).
- Ensure /new (session.clear()) clears _last_summary from metadata.
Add show_reasoning config (default: False) to display model
thinking/reasoning content in the TUI during streaming. Reasoning
is emitted via a new emit_reasoning hook on AgentHook, gated by the
channels config. Display uses ✻ prefix with dim italic styling.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Route progress output through the Live's render hook to fix cursor
misalignment that caused content duplication. The root cause was that
progress/reasoning output used a separate Console instance, bypassing
Rich Live's process_renderables hook. Also fixes pre-existing issue
where multiple headers printed per agent turn.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
The for loop at line 168 never executes because start is assigned
i + 1 immediately before slicing messages[start : i + 1], which
is always an empty list. Remove the dead code.
Fixes#3716
- TurnContext now carries a turn_id (session_key:time_ns)
- All state transition debug logs include [turn_id] prefix
- RuntimeError messages also include turn_id for observability
- State handlers now return event strings ('ok', 'dispatch', 'shortcut')
- Driver loop uses _TRANSITIONS lookup table: (state, event) -> next_state
- State graph is centralized and visible at a glance
- Added StateTraceEntry to record per-state timing and events
- Driver loop logs state duration + event at debug level
- Exception paths are traced with error field for observability
- Fix _assemble_outbound on_stream type annotation (Callable[[str], Awaitable[None]] | None)
- Use last_msg consistently in _state_save instead of re-indexing
- Remove dead fallback in _state_respond (guaranteed non-None by _state_save)
- Change pending_summary type from Any to str | None
- Make session optional in TurnContext to avoid redundant fetch
- Add defensive dispatch with RuntimeError for missing handlers
Re-applies the safe portion of c01f8599 after the revert in 2e8e674e.
Drops the uv cache which broke last time because uv.lock is gitignored
in this repo, and keeps lint as a step inside the test job (matching
the pre-c01f8599 layout).
What's added (all metadata-only, no external dependencies):
- concurrency: cancel superseded runs on the same ref
- permissions: tighten GITHUB_TOKEN to contents: read
- timeout-minutes: 20 to bound runaway jobs
- fail-fast: false so all matrix combinations surface failures
- matrix conditional: PRs run Linux x {3.11, 3.14} for fast feedback;
push to main/nightly still runs the full 2-OS x 4-Python matrix
What's intentionally NOT added (each removed for a reason):
- uv cache: depends on uv.lock which is gitignored
- separate lint job: kept inline as a step, matches original
- workflow_dispatch / paths-ignore: scope creep, not needed now
All jobs continue to run on standard GitHub-hosted runners
(ubuntu-latest, windows-latest), keeping CI within the free tier.
Co-authored-by: Cursor <cursoragent@cursor.com>
The optimized workflow in c01f8599 set astral-sh/setup-uv@v4 with
cache-dependency-glob: "uv.lock", but uv.lock is gitignored in this
repo, so the hosted runner's checkout never contains it and the
Install uv step fails with:
Error: No file matched to [uv.lock], make sure you have
checked out the target repository
Reverting the workflow to the pre-c01f8599 version to unbreak CI.
The "Modifying CI Workflows" section added to CONTRIBUTING.md in the
same commit is left in place; it documents general guidance and is
independent of this specific implementation choice.
Co-authored-by: Cursor <cursoragent@cursor.com>
Workflow changes (.github/workflows/ci.yml):
- Add concurrency to cancel superseded runs on the same ref
- Enable uv dependency caching keyed on uv.lock
- Split lint into a dedicated job; gate test on lint via needs
- Split matrix: PRs run Linux x {3.11, 3.14} for fast feedback;
push to main/nightly still runs the full 2-OS x 4-Python matrix
- Add fail-fast: false so all platforms surface failures together
- Add timeouts (lint: 5m, test: 20m) to bound runaway jobs
- Tighten GITHUB_TOKEN to contents: read
Docs (CONTRIBUTING.md):
- Add a short "Modifying CI Workflows" section so contributors know
to stay within standard runners / no metered storage / no paid
actions before touching .github/workflows/
All jobs continue to run on standard GitHub-hosted runners
(ubuntu-latest, windows-latest), keeping CI within the free tier.
Co-authored-by: Cursor <cursoragent@cursor.com>
- Pop model and context_window_tokens from extra kwargs before
forwarding to __init__, allowing callers like _run_gateway to
pass snapshot-derived values instead of config defaults
- _run_gateway now explicitly passes model/context_window_tokens
from provider_snapshot to preserve pre-refactor behavior
