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Merge pull request #2161 from NousResearch/hermes/hermes-6757a563

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fix(display): show spinners and tool progress during streaming mode
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Teknium 2026-03-20 05:17:55 -07:00 • committed by GitHub
commit aa6416399e
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1 changed files with 27 additions and 11 deletions
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38
run_agent.py
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@ -518,6 +518,10 @@ class AIAgent:
self.stream_delta_callback = stream_delta_callback
self._last_reported_tool = None # Track for "new tool" mode
# Tool execution state — allows _vprint during tool execution
# even when stream consumers are registered (no tokens streaming then)
self._executing_tools = False
# Interrupt mechanism for breaking out of tool loops
self._interrupt_requested = False
self._interrupt_message = None # Optional message that triggered interrupt
@ -1068,12 +1072,16 @@ class AIAgent:
pass
def _vprint(self, *args, force: bool = False, **kwargs):
"""Verbose print — suppressed when streaming TTS is active.
"""Verbose print — suppressed when actively streaming tokens.
Pass ``force=True`` for error/warning messages that should always be
shown even during streaming playback (TTS or display).
During tool execution (``_executing_tools`` is True), printing is
allowed even with stream consumers registered because no tokens
are being streamed at that point.
"""
if not force and self._has_stream_consumers():
if not force and self._has_stream_consumers() and not self._executing_tools:
return
self._safe_print(*args, **kwargs)
@ -4354,14 +4362,19 @@ class AIAgent:
"""
tool_calls = assistant_message.tool_calls
if not _should_parallelize_tool_batch(tool_calls):
return self._execute_tool_calls_sequential(
# Allow _vprint during tool execution even with stream consumers
self._executing_tools = True
try:
if not _should_parallelize_tool_batch(tool_calls):
return self._execute_tool_calls_sequential(
assistant_message, messages, effective_task_id, api_call_count
)
return self._execute_tool_calls_concurrent(
assistant_message, messages, effective_task_id, api_call_count
)
return self._execute_tool_calls_concurrent(
assistant_message, messages, effective_task_id, api_call_count
)
finally:
self._executing_tools = False
def _invoke_tool(self, function_name: str, function_args: dict, effective_task_id: str) -> str:
"""Invoke a single tool and return the result string. No display logic.
@ -5418,14 +5431,17 @@ class AIAgent:
self._vprint(f"\n{self.log_prefix}🔄 Making API call #{api_call_count}/{self.max_iterations}...")
self._vprint(f"{self.log_prefix} 📊 Request size: {len(api_messages)} messages, ~{approx_tokens:,} tokens (~{total_chars:,} chars)")
self._vprint(f"{self.log_prefix} 🔧 Available tools: {len(self.tools) if self.tools else 0}")
elif not self._has_stream_consumers():
# Animated thinking spinner in quiet mode (skip during streaming)
else:
# Animated thinking spinner in quiet mode
face = random.choice(KawaiiSpinner.KAWAII_THINKING)
verb = random.choice(KawaiiSpinner.THINKING_VERBS)
if self.thinking_callback:
# CLI TUI mode: use prompt_toolkit widget instead of raw spinner
# (works in both streaming and non-streaming modes)
self.thinking_callback(f"{face} {verb}...")
else:
elif not self._has_stream_consumers():
# Raw KawaiiSpinner only when no streaming consumers
# (would conflict with streamed token output)
spinner_type = random.choice(['brain', 'sparkle', 'pulse', 'moon', 'star'])
thinking_spinner = KawaiiSpinner(f"{face} {verb}...", spinner_type=spinner_type)
thinking_spinner.start()