Address PR review feedback by avoiding an async method reference as the OpenAI client api_key.
Initialize the client with a placeholder key, refresh the Copilot token before each chat/chat_stream call, and update the runtime client api_key before dispatch.
Add a regression test that verifies the client api_key is refreshed to a real string before chat requests.
Generated with GitHub Copilot, GPT-5.4.
Implement the real GitHub device flow and Copilot token exchange for the GitHub Copilot provider.
Also route github-copilot models through a dedicated backend and strip the provider prefix before API requests.
Add focused regression coverage for provider wiring and model normalization.
Generated with GitHub Copilot, GPT-5.4.
Remove the fragile barrier-based synchronization that could cause
deadlock when the second request is scheduled first. Instead, rely
on the session lock for serialization and handle either execution
order in assertions.
1. Fix full_url path for non-image media to require AES key and skip download when missing,
instead of persisting encrypted bytes as valid media.
2. Restrict quoted media fallback trigger to only when no top-level media item exists,
not when top-level media download/decryption fails.
Introduce a CompositeHook that fans out lifecycle callbacks to an
ordered list of AgentHook instances with per-hook error isolation.
Extract the nested _LoopHook and _SubagentHook to module scope as
public LoopHook / SubagentHook so downstream users can subclass or
compose them. Add `hooks` parameter to AgentLoop.__init__ for
registering custom hooks at construction time.
Closes#2603
Make the fixed-session API surface explicit, document its usage, exclude api/ from core agent line counts, and remove implicit aiohttp pytest fixture dependencies from API tests.
Reject mismatched models and require a single user message so the OpenAI-compatible endpoint reflects the fixed-session nanobot runtime without extra compatibility noise.
Read serve host, port, and timeout from config by default, keep CLI flags higher priority, and bind the API to localhost by default for safer local usage.
Expose OpenAI-compatible chat completions and models endpoints through a single persistent API session, keeping the integration simple without adding multi-session isolation yet.
* feat(feishu): add streaming support via CardKit PATCH API
Implement send_delta() for Feishu channel using interactive card
progressive editing:
- First delta creates a card with markdown content and typing cursor
- Subsequent deltas throttled at 0.5s to respect 5 QPS PATCH limit
- stream_end finalizes with full formatted card (tables, rich markdown)
Also refactors _send_message_sync to return message_id (str | None)
and adds _patch_card_sync for card updates.
Includes 17 new unit tests covering streaming lifecycle, config,
card building, and edge cases.
Made-with: Cursor
* feat(feishu): close CardKit streaming_mode on stream end
Call cardkit card.settings after final content update so chat preview
leaves default [生成中...] summary (Feishu streaming docs).
Made-with: Cursor
* style: polish Feishu streaming (PEP8 spacing, drop unused test imports)
Made-with: Cursor
* docs(feishu): document cardkit:card:write for streaming
- README: permissions, upgrade note for existing apps, streaming toggle
- CHANNEL_PLUGIN_GUIDE: Feishu CardKit scope and when to disable streaming
Made-with: Cursor
* docs: address PR 2382 review (test path, plugin guide, README, English docstrings)
- Move Feishu streaming tests to tests/channels/
- Remove Feishu CardKit scope from CHANNEL_PLUGIN_GUIDE (plugin-dev doc only)
- README Feishu permissions: consistent English
- feishu.py: replace Chinese in streaming docstrings/comments
Made-with: Cursor
When LLM generates faster than channel can process, asyncio.Queue
accumulates multiple _stream_delta messages. Each delta triggers a
separate API call (~700ms each), causing visible delay after LLM
finishes.
Solution: In _dispatch_outbound, drain all queued deltas for the same
(channel, chat_id) before sending, combining them into a single API
call. Non-matching messages are preserved in a pending buffer for
subsequent processing.
This reduces N API calls to 1 when queue has N accumulated deltas.
Make channel delivery failures raise consistently so retry policy lives in ChannelManager rather than being split across individual channels. Tighten Telegram stream finalization, clarify sendMaxRetries semantics, and align the docs with the behavior the system actually guarantees.
Read the default timezone from the agent context when wiring the cron tool so startup no longer depends on an out-of-scope local variable. Add a regression test to ensure AgentLoop passes the configured timezone through to cron.
Made-with: Cursor
Make cron list output render one-shot and run-state timestamps in the same timezone context used to interpret schedules. This keeps scheduling logic and user-facing time displays consistent.
Made-with: Cursor
Make cron use the configured agent timezone when a cron expression omits tz or a one-shot ISO time has no offset. This keeps runtime context, heartbeat, and scheduling aligned around the same notion of time.
Made-with: Cursor
Replace the flatten/unflatten approach (merging extra_content.google.*
into provider_specific_fields then reconstructing) with direct pass-through:
parse extra_content as-is, store on ToolCallRequest.extra_content, serialize
back untouched. This is lossless, requires no hardcoded field names, and
covers all three parsing branches (str, dict, SDK object) plus streaming.
Handle string and dict-shaped responses from OpenAI-compatible backends so non-standard providers no longer crash on missing choices fields. Add regression tests to keep SDK, dict, and plain-text parsing paths aligned.
