On terminals that send a bare LF for plain Enter (WSL is the case
prompt_toolkit itself calls out), Alt+Enter arrives as ESC + LF
("\x1b\x0a" = Escape + ControlJ), not the ESC + CR the existing
"escape","enter" binding matches. The Escape was swallowed and the bare
LF hit prompt_toolkit's default submit, so the documented "universally
supported" Alt+Enter newline fallback failed on exactly the terminal path
plain Enter is preserved for.
Bind ESC + ControlJ to insert a newline too, and add a real-PromptSession
regression test covering the WSL Alt+Enter path.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
"\x1b[27;2;13~" (the older xterm modifyOtherKeys / rxvt encoding of
Shift+Enter) is already registered by prompt_toolkit by default -- as
Keys.ControlM, i.e. plain Enter/submit. The previous `setdefault()` call was
therefore a silent no-op against it: this Shift+Enter variant kept behaving
like a submit instead of inserting a newline, even after the ControlJ/WSL
fix, since setdefault only sets missing keys.
Assign directly to override that default for both known Shift+Enter
sequences, since inserting a newline is the whole point of the binding.
Add a regression test driving a real PromptSession/parser with this exact
sequence, since a mocked-buffer test can't observe prompt_toolkit's default
ANSI_SEQUENCES entries taking priority.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Keys.ControlJ is also the literal LF byte ("\x0a") that some terminals send
for a plain Enter keypress -- prompt_toolkit's own default bindings handle
this by re-feeding it as ControlM/submit, and calls out WSL by name as the
case that needs it. Binding our Shift+Enter handler to ControlJ shadowed
that default, so on any terminal sending LF for Enter, pressing Enter only
ever inserted a newline and the prompt could never be submitted.
Register the CSI-u Shift+Enter sequences against Keys.ControlF3 instead: an
enum member prompt_toolkit declares but never wires to a default ANSI
sequence or key binding, so it's only reachable through our own mapping.
Also add a regression test that drives a real PromptSession/Vt100Parser
with a raw LF byte -- the existing key-binding test invoked handlers
directly against a mocked buffer, which exercises the handler logic but not
prompt_toolkit's key-resolution precedence, so it couldn't have caught this.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The interactive prompt used a single-line buffer (multiline=False), so
there was no way to compose a multi-line message before submitting.
Switch to a multiline-capable buffer with custom key bindings: Enter still
submits (unchanged feel), Alt+Enter always inserts a newline, and
Shift+Enter inserts a newline on terminals that emit a distinguishable
CSI-u sequence for it (kitty, iTerm2 with the fixterms protocol) by mapping
those sequences onto the otherwise-unused ControlJ key.
send_delta popped the buffer before self.send ran, so a transient WeChat
send failure dropped the completed streamed reply: ChannelManager
_send_with_retry re-invokes the same _stream_end message, but the buffer
was already gone, so the retry sent empty content and returned — turning a
delivery retry into silent message loss.
Build `full` from the buffer without popping, send, then clear only after a
successful send. The _stream_end message's own content (set when the manager
coalesces deltas into the end message) is folded into `full` via addition
rather than appended to the buffer, so a retry recomputes the same `full`
from an unchanged buffer instead of double-counting it.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
WeixinConfig lacked a streaming field, so channels.weixin.streaming was
silently dropped by pydantic and supports_streaming stayed False, forcing the
non-streaming Messages API. Some upstream Anthropic relays drop tool_use
id/name/input on the non-stream path (but handle SSE fine), breaking WeChat
tool calls.
Two parts:
1. Add a streaming field (default True) so WeChat routes LLM calls through the
streaming API. WeChat iLink has no native incremental delivery, so this is
user-invisible — it only changes how the LLM is called.
2. WeChat send_delta previously dropped content, and the manager bypasses send
for the _streamed final answer, so a streamed reply never reached the user.
send_delta now buffers content deltas and flushes the full reply in one shot
at _stream_end (also stopping the typing indicator via send).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Combine malformed tool-call handling with placeholder filtering and a
no-tools fallback so a relay that returns tool_use blocks with null
id/name/input can no longer crash a turn or permanently wedge a session.
Adapted to the ContextGovernor architecture (context governance now lives
in nanobot/agent/context_governance.py, not runner.py):
- ToolCallRequest.has_valid_name(): single source of truth for "usable
name" (non-empty string).
- tool_hints.format_tool_hints(): skip tool calls with a non-string/empty
name instead of raising AttributeError on the whole turn.
- ContextGovernor.strip_placeholder_assistant_messages() and
strip_malformed_tool_calls() (plus the _tool_call_name_is_valid helper):
history-cleaning staticmethods invoked at the START of
prepare_for_model() — strip_placeholder, then strip_malformed, then the
existing drop_orphan/backfill chain. Both only repair the model-facing
copy and leave persisted history untouched (return a copy, or the same
list when nothing changes). Also wired into runner's minimal-repair path.
- AgentRunner._drop_malformed_tool_calls(): returns
(dropped, all_dropped, original_finish_reason); clears finish_reason to
"stop" when all calls are dropped.
- AgentRunner._malformed_tool_call_retry_messages() + _request_model
malformed_retry flag: when an all-dropped tool_calls response comes back,
retry once with a corrective note; if the retry STILL comes back
all-dropped, fall back to _request_no_tools for graceful text degradation.
Tests for the history-cleaning methods live with ContextGovernor in
tests/agent/test_runner_governance.py; response-layer and tool-hint tests
stay on AgentRunner / tool_hints.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
