convert_messages() emitted reasoning items with ``content`` as a plain
string whenever preserve_reasoning was enabled (the DeepSeek spec).
DeepSeek's Responses gateway rejects that shape with a serde error
("input: invalid type: string ..., expected a sequence"), which surfaced
only after token consolidation cleared provider_state and forced the
full-history conversion path; replayed server items already carry list
content, which is why normal multi-turn requests never failed. Serialize
reasoning content as a list of output_text parts, matching the OpenAI
Responses schema and DeepSeek's accepted wire shape (verified live against
api.deepseek.com/responses).
The serde fallback classifier introduced in the previous commit remains as
a last-resort safeguard for any remaining wire incompatibility.
Tests: extend test_preserves_deepseek_reasoning_content to the array shape;
add a full-history regression with the observed failing item, a
replay/consolidation regression covering both replayed and converted
reasoning items, and provider-level request fixtures for both paths.
Full suite: 5773 passed, 22 skipped (only the known local-only
channels/sms packaging failure remains).
DeepSeek's new Responses endpoint (deepseek-v4-flash) intermittently rejects valid request bodies with serde deserialization errors such as 'input: invalid type: string ..., expected a sequence'. These were not classified as compatibility errors, so affected conversations died instead of falling back to Chat Completions.
The wire format is correct (input serializes as a list), so this is a server-side Responses compatibility issue; Chat Completions is strictly more permissive, making fallback safe. Extend the fallback classifier to recognize serde body-parsing markers. Repeated failures still trip the existing circuit breaker.
ModelScope is a fully implemented provider (nanobot/providers/registry.py,
image_generation.py, schema.py) with async image-generation task submission
and polling, but was previously undocumented in docs/providers.md.
This patch adds a ModelScope entry under 'Common Provider Patterns',
covering:
- Default base URL: https://api-inference.modelscope.cn/v1
- OpenAI-compatible chat/completions endpoint
- Async image-generation flow (task submit + status poll)
- Automatic 'modelscope/' prefix stripping when calling the API
- A minimal nanobot.yaml example
No code changes; docs-only.
Eden AI (https://www.edenai.co) is an EU-hosted, OpenAI-compatible gateway exposing 100+ models from many providers through a single endpoint and API key. Models use the provider/model naming scheme (the full id is sent upstream, like OpenRouter).
Adds it following the registry's documented two-step recipe:
- a ProviderSpec in providers/registry.py (backend openai_compat, gateway, default_api_base https://api.edenai.run/v3, EDENAI_API_KEY, reasoning_effort)
- the matching field in ProvidersConfig (config/schema.py)
API key via EDENAI_API_KEY only; never hardcoded.
Signed-off-by: Victor M. SMITH <72023257+MVS-source@users.noreply.github.com>
The helper never waits on the runtime-tasks gather after cancelling it
(its children are bounded individually), so the finished-gather test must
hand the helper an already-complete gather to exercise the bounded
retrieval path, and the cancelled-gather test must settle the gather
itself instead of expecting the helper to await a still-pending future.
Use a pre-completed child for the finished case and suppress(await) for
the cancelled case; both now assert done() and a single close.
Covers the lifecycle contract of _close_gateway_runtime: runtime tasks are
cancelled before shared resources close, pending background work is drained
before the close returns, cancellation-swallowing tasks and hanging cleanup
are bounded by their timeouts, a failing close is logged without blocking the
stop, duplicate cleanup is idempotent, and the runtime_tasks gather await path
is exercised for both completed and cancelled gathers.
