mirror of
https://github.com/NousResearch/hermes-agent.git
synced 2026-04-25 00:51:20 +00:00
Merge branch 'feat/ink-refactor' of github.com:NousResearch/hermes-agent into feat/ink-refactor
This commit is contained in:
Brooklyn Nicholson
commit
aca479c1ae
110 changed files with 6295 additions and 3193 deletions
111
run_agent.py
111
run_agent.py
|
|
@ -87,6 +87,7 @@ from agent.model_metadata import (
|
|||
fetch_model_metadata,
|
||||
estimate_tokens_rough, estimate_messages_tokens_rough, estimate_request_tokens_rough,
|
||||
get_next_probe_tier, parse_context_limit_from_error,
|
||||
parse_available_output_tokens_from_error,
|
||||
save_context_length, is_local_endpoint,
|
||||
query_ollama_num_ctx,
|
||||
)
|
||||
|
|
@ -621,6 +622,7 @@ class AIAgent:
|
|||
self.tool_progress_callback = tool_progress_callback
|
||||
self.tool_start_callback = tool_start_callback
|
||||
self.tool_complete_callback = tool_complete_callback
|
||||
self.suppress_status_output = False
|
||||
self.thinking_callback = thinking_callback
|
||||
self.reasoning_callback = reasoning_callback
|
||||
self._reasoning_deltas_fired = False # Set by _fire_reasoning_delta, reset per API call
|
||||
|
|
@ -1459,7 +1461,14 @@ class AIAgent:
|
|||
After the main response has been delivered and the remaining tool
|
||||
calls are post-response housekeeping (``_mute_post_response``),
|
||||
all non-forced output is suppressed.
|
||||
|
||||
``suppress_status_output`` is a stricter CLI automation mode used by
|
||||
parseable single-query flows such as ``hermes chat -q``. In that mode,
|
||||
all status/diagnostic prints routed through ``_vprint`` are suppressed
|
||||
so stdout stays machine-readable.
|
||||
"""
|
||||
if getattr(self, "suppress_status_output", False):
|
||||
return
|
||||
if not force and getattr(self, "_mute_post_response", False):
|
||||
return
|
||||
if not force and self._has_stream_consumers() and not self._executing_tools:
|
||||
|
|
@ -1485,6 +1494,17 @@ class AIAgent:
|
|||
except (AttributeError, ValueError, OSError):
|
||||
return False
|
||||
|
||||
def _should_emit_quiet_tool_messages(self) -> bool:
|
||||
"""Return True when quiet-mode tool summaries should print directly.
|
||||
|
||||
When the caller provides ``tool_progress_callback`` (for example the CLI
|
||||
TUI or a gateway progress renderer), that callback owns progress display.
|
||||
Emitting quiet-mode summary lines here duplicates progress and leaks tool
|
||||
previews into flows that are expected to stay silent, such as
|
||||
``hermes chat -q``.
|
||||
"""
|
||||
return self.quiet_mode and not self.tool_progress_callback
|
||||
|
||||
def _emit_status(self, message: str) -> None:
|
||||
"""Emit a lifecycle status message to both CLI and gateway channels.
|
||||
|
||||
|
|
@ -4969,9 +4989,21 @@ class AIAgent:
|
|||
# Swap OpenAI client and config in-place
|
||||
self.api_key = fb_client.api_key
|
||||
self.client = fb_client
|
||||
# Preserve provider-specific headers that
|
||||
# resolve_provider_client() may have baked into
|
||||
# fb_client via the default_headers kwarg. The OpenAI
|
||||
# SDK stores these in _custom_headers. Without this,
|
||||
# subsequent request-client rebuilds (via
|
||||
# _create_request_openai_client) drop the headers,
|
||||
# causing 403s from providers like Kimi Coding that
|
||||
# require a User-Agent sentinel.
|
||||
fb_headers = getattr(fb_client, "_custom_headers", None)
|
||||
if not fb_headers:
|
||||
fb_headers = getattr(fb_client, "default_headers", None)
|
||||
self._client_kwargs = {
|
||||
"api_key": fb_client.api_key,
|
||||
"base_url": fb_base_url,
|
||||
**({"default_headers": dict(fb_headers)} if fb_headers else {}),
|
||||
}
|
||||
|
||||
# Re-evaluate prompt caching for the new provider/model
|
||||
|
|
@ -5386,15 +5418,22 @@ class AIAgent:
|
|||
if self.api_mode == "anthropic_messages":
|
||||
from agent.anthropic_adapter import build_anthropic_kwargs
|
||||
anthropic_messages = self._prepare_anthropic_messages_for_api(api_messages)
|
||||
# Pass context_length so the adapter can clamp max_tokens if the
|
||||
# user configured a smaller context window than the model's output limit.
|
||||
# Pass context_length (total input+output window) so the adapter can
|
||||
# clamp max_tokens (output cap) when the user configured a smaller
|
||||
# context window than the model's native output limit.
|
||||
ctx_len = getattr(self, "context_compressor", None)
|
||||
ctx_len = ctx_len.context_length if ctx_len else None
|
||||
# _ephemeral_max_output_tokens is set for one call when the API
|
||||
# returns "max_tokens too large given prompt" — it caps output to
|
||||
# the available window space without touching context_length.
|
||||
ephemeral_out = getattr(self, "_ephemeral_max_output_tokens", None)
|
||||
if ephemeral_out is not None:
|
||||
self._ephemeral_max_output_tokens = None # consume immediately
|
||||
return build_anthropic_kwargs(
|
||||
model=self.model,
|
||||
messages=anthropic_messages,
|
||||
tools=self.tools,
|
||||
max_tokens=self.max_tokens,
|
||||
max_tokens=ephemeral_out if ephemeral_out is not None else self.max_tokens,
|
||||
reasoning_config=self.reasoning_config,
|
||||
is_oauth=self._is_anthropic_oauth,
|
||||
preserve_dots=self._anthropic_preserve_dots(),
|
||||
|
|
@ -6328,7 +6367,7 @@ class AIAgent:
|
|||
|
||||
# Start spinner for CLI mode (skip when TUI handles tool progress)
|
||||
spinner = None
|
||||
if self.quiet_mode and not self.tool_progress_callback and self._should_start_quiet_spinner():
|
||||
if self._should_emit_quiet_tool_messages() and self._should_start_quiet_spinner():
|
||||
face = random.choice(KawaiiSpinner.KAWAII_WAITING)
|
||||
spinner = KawaiiSpinner(f"{face} ⚡ running {num_tools} tools concurrently", spinner_type='dots', print_fn=self._print_fn)
|
||||
spinner.start()
|
||||
|
|
@ -6378,7 +6417,7 @@ class AIAgent:
|
|||
logging.debug(f"Tool result ({len(function_result)} chars): {function_result}")
|
||||
|
||||
# Print cute message per tool
|
||||
if self.quiet_mode:
|
||||
if self._should_emit_quiet_tool_messages():
|
||||
cute_msg = _get_cute_tool_message_impl(name, args, tool_duration, result=function_result)
|
||||
self._safe_print(f" {cute_msg}")
|
||||
elif not self.quiet_mode:
|
||||
|
|
@ -6535,7 +6574,7 @@ class AIAgent:
|
|||
store=self._todo_store,
|
||||
)
|
||||
tool_duration = time.time() - tool_start_time
|
||||
if self.quiet_mode:
|
||||
if self._should_emit_quiet_tool_messages():
|
||||
self._vprint(f" {_get_cute_tool_message_impl('todo', function_args, tool_duration, result=function_result)}")
|
||||
elif function_name == "session_search":
|
||||
if not self._session_db:
|
||||
|
|
@ -6550,7 +6589,7 @@ class AIAgent:
|
|||
current_session_id=self.session_id,
|
||||
)
|
||||
tool_duration = time.time() - tool_start_time
|
||||
if self.quiet_mode:
|
||||
if self._should_emit_quiet_tool_messages():
|
||||
self._vprint(f" {_get_cute_tool_message_impl('session_search', function_args, tool_duration, result=function_result)}")
|
||||
elif function_name == "memory":
|
||||
target = function_args.get("target", "memory")
|
||||
|
|
@ -6563,7 +6602,7 @@ class AIAgent:
|
|||
store=self._memory_store,
|
||||
)
|
||||
tool_duration = time.time() - tool_start_time
|
||||
if self.quiet_mode:
|
||||
if self._should_emit_quiet_tool_messages():
|
||||
self._vprint(f" {_get_cute_tool_message_impl('memory', function_args, tool_duration, result=function_result)}")
|
||||
elif function_name == "clarify":
|
||||
from tools.clarify_tool import clarify_tool as _clarify_tool
|
||||
|
|
@ -6573,7 +6612,7 @@ class AIAgent:
|
|||
callback=self.clarify_callback,
|
||||
)
|
||||
tool_duration = time.time() - tool_start_time
|
||||
if self.quiet_mode:
|
||||
if self._should_emit_quiet_tool_messages():
|
||||
self._vprint(f" {_get_cute_tool_message_impl('clarify', function_args, tool_duration, result=function_result)}")
|
||||
elif function_name == "delegate_task":
|
||||
from tools.delegate_tool import delegate_task as _delegate_task
|
||||
|
|
@ -6584,7 +6623,7 @@ class AIAgent:
|
|||
goal_preview = (function_args.get("goal") or "")[:30]
|
||||
spinner_label = f"🔀 {goal_preview}" if goal_preview else "🔀 delegating"
|
||||
spinner = None
|
||||
if self.quiet_mode and not self.tool_progress_callback and self._should_start_quiet_spinner():
|
||||
if self._should_emit_quiet_tool_messages() and self._should_start_quiet_spinner():
|
||||
face = random.choice(KawaiiSpinner.KAWAII_WAITING)
|
||||
spinner = KawaiiSpinner(f"{face} {spinner_label}", spinner_type='dots', print_fn=self._print_fn)
|
||||
spinner.start()
|
||||
|
|
@ -6606,13 +6645,13 @@ class AIAgent:
|
|||
cute_msg = _get_cute_tool_message_impl('delegate_task', function_args, tool_duration, result=_delegate_result)
|
||||
if spinner:
|
||||
spinner.stop(cute_msg)
|
||||
elif self.quiet_mode:
|
||||
elif self._should_emit_quiet_tool_messages():
|
||||
self._vprint(f" {cute_msg}")
|
||||
elif self._memory_manager and self._memory_manager.has_tool(function_name):
|
||||
# Memory provider tools (hindsight_retain, honcho_search, etc.)
|
||||
# These are not in the tool registry — route through MemoryManager.
|
||||
spinner = None
|
||||
if self.quiet_mode and not self.tool_progress_callback:
|
||||
if self._should_emit_quiet_tool_messages() and self._should_start_quiet_spinner():
|
||||
face = random.choice(KawaiiSpinner.KAWAII_WAITING)
|
||||
emoji = _get_tool_emoji(function_name)
|
||||
preview = _build_tool_preview(function_name, function_args) or function_name
|
||||
|
|
@ -6630,11 +6669,11 @@ class AIAgent:
|
|||
cute_msg = _get_cute_tool_message_impl(function_name, function_args, tool_duration, result=_mem_result)
|
||||
if spinner:
|
||||
spinner.stop(cute_msg)
|
||||
elif self.quiet_mode:
|
||||
elif self._should_emit_quiet_tool_messages():
|
||||
self._vprint(f" {cute_msg}")
|
||||
elif self.quiet_mode:
|
||||
spinner = None
|
||||
if not self.tool_progress_callback:
|
||||
if self._should_emit_quiet_tool_messages() and self._should_start_quiet_spinner():
|
||||
face = random.choice(KawaiiSpinner.KAWAII_WAITING)
|
||||
emoji = _get_tool_emoji(function_name)
|
||||
preview = _build_tool_preview(function_name, function_args) or function_name
|
||||
|
|
@ -6657,7 +6696,7 @@ class AIAgent:
|
|||
cute_msg = _get_cute_tool_message_impl(function_name, function_args, tool_duration, result=_spinner_result)
|
||||
if spinner:
|
||||
spinner.stop(cute_msg)
|
||||
else:
|
||||
elif self._should_emit_quiet_tool_messages():
|
||||
self._vprint(f" {cute_msg}")
|
||||
else:
|
||||
try:
|
||||
|
|
@ -8295,6 +8334,48 @@ class AIAgent:
|
|||
compressor = self.context_compressor
|
||||
old_ctx = compressor.context_length
|
||||
|
||||
# ── Distinguish two very different errors ───────────
|
||||
# 1. "Prompt too long": the INPUT exceeds the context window.
|
||||
# Fix: reduce context_length + compress history.
|
||||
# 2. "max_tokens too large": input is fine, but
|
||||
# input_tokens + requested max_tokens > context_window.
|
||||
# Fix: reduce max_tokens (the OUTPUT cap) for this call.
|
||||
# Do NOT shrink context_length — the window is unchanged.
|
||||
#
|
||||
# Note: max_tokens = output token cap (one response).
|
||||
# context_length = total window (input + output combined).
|
||||
available_out = parse_available_output_tokens_from_error(error_msg)
|
||||
if available_out is not None:
|
||||
# Error is purely about the output cap being too large.
|
||||
# Cap output to the available space and retry without
|
||||
# touching context_length or triggering compression.
|
||||
safe_out = max(1, available_out - 64) # small safety margin
|
||||
self._ephemeral_max_output_tokens = safe_out
|
||||
self._vprint(
|
||||
f"{self.log_prefix}⚠️ Output cap too large for current prompt — "
|
||||
f"retrying with max_tokens={safe_out:,} "
|
||||
f"(available_tokens={available_out:,}; context_length unchanged at {old_ctx:,})",
|
||||
force=True,
|
||||
)
|
||||
# Still count against compression_attempts so we don't
|
||||
# loop forever if the error keeps recurring.
|
||||
compression_attempts += 1
|
||||
if compression_attempts > max_compression_attempts:
|
||||
self._vprint(f"{self.log_prefix}❌ Max compression attempts ({max_compression_attempts}) reached.", force=True)
|
||||
self._vprint(f"{self.log_prefix} 💡 Try /new to start a fresh conversation, or /compress to retry compression.", force=True)
|
||||
logging.error(f"{self.log_prefix}Context compression failed after {max_compression_attempts} attempts.")
|
||||
self._persist_session(messages, conversation_history)
|
||||
return {
|
||||
"messages": messages,
|
||||
"completed": False,
|
||||
"api_calls": api_call_count,
|
||||
"error": f"Context length exceeded: max compression attempts ({max_compression_attempts}) reached.",
|
||||
"partial": True
|
||||
}
|
||||
restart_with_compressed_messages = True
|
||||
break
|
||||
|
||||
# Error is about the INPUT being too large — reduce context_length.
|
||||
# Try to parse the actual limit from the error message
|
||||
parsed_limit = parse_context_limit_from_error(error_msg)
|
||||
if parsed_limit and parsed_limit < old_ctx:
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue