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>
- Replace ':' with '_' in store_name to avoid WinError 123
- Pass sanitized store_name via AsyncClientConfig
- Fixes issue #3506 where Matrix channel fails on Windows due to
colon in user_id causing invalid file paths in matrix-nio's DefaultStore
- 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
- Do not send reasoning_effort="none" to APIs (prevents 400 on gemma/Gemini)
- Treat "none" as thinking disabled in thinking_style, Kimi, and reasoning_content backfill paths
- Fix Anthropic extended thinking not respecting "none"
- Fix Azure OpenAI temperature suppression and reasoning body for "none"
- Fix Codex reasoning body for "none"
- Add "gemma" keyword to Gemini ProviderSpec for correct auto routing
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
