LLM-generated tool calls may wrap URLs in markdown backticks or quotes
(e.g. \https://example.com\), causing urlparse to produce empty scheme
and netloc, which leads to all fetch attempts failing silently.
Add URL cleaning at the top of WebFetchTool.execute to strip whitespace,
backticks, double quotes, and single quotes, plus an early rejection guard
for non-http(s) URLs after cleaning.
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
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