Matrix sync replays the room timeline on each startup or `/restart`,
causing already-handled messages to be reprocessed (#3553). Even with
`store_sync_tokens=True`, the sync token isn't reliably re-injected
when restoring a session via access_token + load_store(), so the
client re-reads recent timeline entries.
Filter `event.server_timestamp` against the process start time so old
events are dropped at the `_on_message` / `_on_media_message` entry
points. Trade-off: messages received during downtime won't be
processed, which matches the issue reporter's expectation.
Closes#3553
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
- Anthropic: "none" must not enable extended thinking
- Azure: "none" must not suppress temperature or inject reasoning body
- DeepSeek/DashScope/Kimi: "none" sends thinking disabled, skips reasoning_effort field
- Gemini: gemma keyword enables auto-routing for gemma models
Adds Olostep (https://www.olostep.com) as an optional web_search backend
using the official olostep Python SDK (client.answers.create()).
Changes:
- pyproject.toml: adds olostep>=0.1.0 optional dependency
- schema.py: adds olostep to provider comment in WebSearchConfig
- web.py: adds _search_olostep() with lazy import and provider branching
- docs/configuration.md: documents Olostep setup under web search config
- tests: unit tests for the new provider
Backward compatible: existing users see no behavior change unless they
opt into provider: "olostep". No hard dependency at runtime path.
Co-authored-by: umerkay <umerkk164@gmail.com>
Stream-end events are emitted at the end of every assistant turn. When
the agent has more tool-call rounds queued, the runner sets
`_resuming=True` on the metadata. Without a guard, every intermediate
stream end removed the OnIt reaction (the first one wins, since
`_reaction_ids.pop` empties the slot) and re-added `done_emoji`,
producing a DONE reaction after every tool call instead of only at
final completion.
Wrap the OnIt removal and `done_emoji` add in a `not _resuming` guard
so the OnIt indicator persists across tool-call rounds and DONE fires
exactly once when the agent's final response lands.
`_resuming` already flows through outbound metadata
(`nanobot/agent/loop.py:747`) and survives `_coalesce_stream_deltas`
because pure `_stream_end` messages without `_stream_delta` skip the
merge branch.
Tests:
- test_no_removal_when_resuming
- test_done_emoji_only_on_final_stream_end
Add an `extra_body` field to `ProviderConfig` that merges arbitrary
key-value pairs into every OpenAI-compatible request body. This is the
escape hatch for provider-specific features that nanobot does not have
first-class fields for.
Real-world use cases this unblocks via config alone (no code changes):
- vLLM/TGI `chat_template_kwargs` (e.g. `enable_thinking: false`)
- vLLM guided decoding (`guided_json`, `guided_regex`)
- Local model sampling params (`repetition_penalty`, `top_k`, `min_p`)
- Any future provider-specific param without a new PR each time
The config extra_body is applied last via recursive deep-merge, so it
can extend or override provider-specific defaults (e.g. thinking
params) without clobbering sibling keys set by internal logic.
Changes:
- Add `extra_body: dict[str, Any] | None` to `ProviderConfig`
- Pass it through `factory.py` to `OpenAICompatProvider.__init__`
- Deep-merge into `_build_kwargs` after all internal extra_body entries
- Add `_deep_merge` helper (recursive dict merge, does not mutate inputs)
- 21 tests: deep-merge semantics, provider init, _build_kwargs
integration, thinking coexistence, real-world patterns (guided_json,
repetition_penalty), and schema validation
Treat workspace and safety guard failures as fatal regardless of whether they arrive from tool preparation, returned tool output, or raised exceptions.
Made-with: Cursor
The max_messages config field in AgentDefaults was accepted by the
schema but never threaded through to the actual get_history() calls
in the agent loop. Both call sites in _process_message hardcoded the
default, so sessions with slow or local models accumulated unbounded
history that inflated prompt tokens and caused LLM timeouts.
Changes:
- Add max_messages field to AgentDefaults (default 0 = use built-in
constant, any positive value caps history replay)
- Store the value on AgentLoop and pass it to get_history() when
non-zero
- Wire the config through all three AgentLoop construction sites in
commands.py (gateway, API server, CLI chat)
- 14 focused tests covering schema validation, init storage, history
slicing, boundary alignment, integration wiring, and the
zero/default path
Adds /history [n] to display the last N user/assistant messages from
the current session (default 10, max 50).
- Tool and system messages are filtered out for readability
- Long messages are truncated to 200 characters with an ellipsis
- Multimodal content (image blocks) is collapsed to its text parts
- Invalid count argument returns a usage hint
- /history n uses prefix routing; /history uses exact routing
Also registers /history in build_help_text().
Three failure modes addressed:
1. Model reflects HEARTBEAT.md instructions back as output instead of
executing them ("HEARTBEAT.md has active tasks listed...")
2. Model narrates decision logic ("Best judgment call: stay quiet")
3. Model produces empty output for silence, runner treats it as failure,
finalization retry generates "couldn't produce a final answer" which
gets delivered to the user
Changes:
- Add _is_deliverable() pre-filter in HeartbeatService._tick() that catches
finalization fallback messages and leaked reasoning patterns before they
reach the evaluator
- Wrap Phase 2 task input with a delivery-awareness preamble telling the
model its output goes directly to the user's messaging app
- Add meta-reasoning suppression criterion to evaluator template
No changes to agent/loop.py, runner.py, providers, or config schema.
Move sessionHistoryMaxMessages, sessionHistoryMaxTokens, and
sessionFileMaxMessages out of user-facing config into internal
constants (HISTORY_MAX_MESSAGES=120, FILE_MAX_MESSAGES=2000).
- Remove 3 fields from AgentDefaults and config pipeline
- Sink enforce_file_cap into Session (was AgentLoop)
- Auto-derive token budget from context window (was configurable)
- Net -113 lines across 7 files; 723 tests green
Made-with: Cursor
The PR stores ref freshness in the metadata sidecar, so the merged main test should assert updated_at there instead of in the refs payload.
Made-with: Cursor
Resolve the MSTeams stale-reference cleanup conflict by keeping the PR's locked, atomic sidecar-meta implementation and aligning the merged test expectation locally.
Made-with: Cursor
Past assistant turns in history were prefixed with "[Message Time: ...]"
just like user turns. The model treated these as in-context demos and
started prefixing its own replies with the same marker, leaking
metadata to the user. Prompt-level warnings could not beat dozens of
prior assistant samples.
Annotate only user turns and proactive deliveries
(_channel_delivery=True, i.e. cron / heartbeat pushes whose timing is
the whole point and which are too infrequent to act as demos). Adjacent
user-side timestamps still pin every normal assistant reply for
relative-time reasoning. The now-redundant identity.md warning is
removed along with the demonstration source.
Slack inbound events with subtype=file_share were silently dropped, so
nanobot never saw messages that included attachments. Allow file_share
through, download Slack-private files using the bot token into the
local media dir, and pass them to the agent as media paths plus a
"[file: name]" / "[image: name]" placeholder in the content. Reject
responses that look like Slack's login HTML so an auth page is never
saved as if it were the user's file. Document the required files:read
scope alongside files:write so installs that read attachments are not
quietly missing the permission.
When deployed with Docker and workspace mounted as a volume, sending
media files failed because relative paths (e.g. output/image.png) were
not resolved against the workspace directory. The process CWD differs
from the workspace in containerized environments, causing os.path.isfile
checks to fail in channel handlers. Normalize relative media paths at
the MessageTool entry point using get_workspace_path().
cmd_restart only persisted channel + chat_id across the os.execv boundary, so
when the new process announced "Restart completed" the OutboundMessage had
no Slack thread_ts and the reply fell back to the channel root.
Serialize msg.metadata into NANOBOT_RESTART_NOTIFY_METADATA, restore it on the
RestartNotice, and forward it to OutboundMessage so the completion message
follows the same routing as the original /restart invocation.
Made-with: Cursor
The old prompt framed cron firing as a "task triggered" status report,
which led the agent to reply with things like "Done ✅ 已提醒
U0AV8BJPV8D 喝水" — exposing the user id and reading like a system log
instead of a friendly reminder. Reword it to instruct the agent to
speak directly to the user and forbid status-style language.
Made-with: Cursor
Without writing these fields into jobs.json, cron jobs created in a
Slack thread lost their thread_ts (and original session_key) after the
service was reloaded, so reminders fired into the channel root.
Made-with: Cursor
MCP resource/prompt/tool names containing spaces or special characters
(e.g. "PostgreSQL System Information") were forwarded verbatim to model
provider APIs, causing validation errors from both Anthropic and OpenAI
which require names matching ^[a-zA-Z0-9_-]{1,128}$.
Add _sanitize_name() that replaces invalid characters with underscores
and collapses consecutive underscores. Applied in MCPToolWrapper,
MCPResourceWrapper, MCPPromptWrapper constructors and the enabled_tools
filtering logic.
Closes#3468
