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.
The gateway shutdown path never closed agent resources explicitly: it relied
on the agent loop task's own finally to run close_mcp() when that task is
cancelled. When the service stops with an in-flight exec session or MCP
subprocess, that path can be skipped or cut short, leaving asyncio subprocess
transports alive after the event loop closes. They are then finalized by
__del__ against a closed loop, producing "RuntimeError: Event loop is closed"
noise in the shutdown log, and in the worst case orphaned subprocesses with
the stop stalling until systemd's timeout kills the cgroup.
The teardown is now extracted into _close_gateway_runtime() with explicit
ordering and bounds:
- Runtime tasks (including the agent loop and any in-flight turn) are
cancelled and awaited -- bounded -- before exec sessions, subagents, and MCP
servers are closed, so no active turn is using a shared resource when it
closes.
- Channel transports are closed before waiting for their runners to exit, since
some SDKs swallow task cancellation while attempting to reconnect.
- agent.close_mcp() is invoked explicitly, bounded to 15s, and is idempotent:
it is a no-op when the agent loop's own cleanup already ran, and the
guaranteed final close otherwise.
- A coroutine that swallows cancellation (e.g. an SDK reconnect loop) can no
longer hold the stop open until systemd's timeout kills the cgroup; cleanup
failures are logged instead of blocking shutdown.
On Windows, mimetypes.guess_type() reads the Content Type value from
HKEY_CLASSES_ROOT\.js (and other extensions) in the registry, which is
commonly set to text/plain because .js is associated with Windows Script
Host rather than web JavaScript. The registry value overrides Python's
built-in mapping and causes browsers to reject ES module scripts.
Fix by explicitly registering correct MIME types via mimetypes.add_type()
at module import time for common web static extensions (.js, .mjs, .css,
.html, .json, .svg, .wasm). Using strict=True ensures the values replace
the registry-backed standard mappings used by mimetypes.guess_type(). This
benefits all callers of mimetypes.guess_type() in the gateway process, not
just _serve_static.
Closes#5190
Co-authored-by: amkile <44280409+amkile@users.noreply.github.com>
The live v1beta API rejects the legacy responseFormat.image block
(enum-based aspectRatio/imageSize fields) for gemini-3.1-flash-lite-image
with INVALID_ARGUMENT, even for documented plain-string values. Gemini
Flash image models accept plain-string hints under
generationConfig.imageConfig instead (e.g. aspectRatio 16:9, imageSize
1K), which the API accepts. Switch the flash path to imageConfig and
update the provider tests accordingly. Other providers (aihubmix,
ollama, imagen) are untouched.
