APEX/BrowserUse_and_ComputerUse_skills
5
0
Fork 0
Code Issues 4 Pull requests 2 Projects 1 Releases Packages Wiki Activity Actions

Merge branch 'main' into feat/honcho-integration

Browse source
This commit is contained in:
Teknium 2026-02-27 23:32:49 -08:00 • committed by GitHub
commit 4a9086b848
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
73 changed files with 7080 additions and 280 deletions
Download patch file Download diff file Expand all files Collapse all files

129
run_agent.py
View file

@ -186,6 +186,13 @@ class AIAgent:
# Store effective base URL for feature detection (prompt caching, reasoning, etc.)
# When no base_url is provided, the client defaults to OpenRouter, so reflect that here.
self.base_url = base_url or OPENROUTER_BASE_URL
if base_url and "api.anthropic.com" in base_url.strip().lower():
raise ValueError(
"Anthropic's native /v1/messages API is not supported yet (planned for a future release). "
"Hermes currently requires OpenAI-compatible /chat/completions endpoints. "
"To use Claude models now, route through OpenRouter (OPENROUTER_API_KEY) "
"or any OpenAI-compatible proxy that wraps the Anthropic API."
)
self.tool_progress_callback = tool_progress_callback
self.clarify_callback = clarify_callback
self._last_reported_tool = None # Track for "new tool" mode
@ -493,6 +500,21 @@ class AIAgent:
else:
print(f"📊 Context limit: {self.context_compressor.context_length:,} tokens (auto-compression disabled)")
def _max_tokens_param(self, value: int) -> dict:
"""Return the correct max tokens kwarg for the current provider.
OpenAI's newer models (gpt-4o, o-series, gpt-5+) require
'max_completion_tokens'. OpenRouter, local models, and older
OpenAI models use 'max_tokens'.
"""
_is_direct_openai = (
"api.openai.com" in self.base_url.lower()
and "openrouter" not in self.base_url.lower()
)
if _is_direct_openai:
return {"max_completion_tokens": value}
return {"max_tokens": value}
def _has_content_after_think_block(self, content: str) -> bool:
"""
Check if content has actual text after any <think></think> blocks.
@ -624,7 +646,7 @@ class AIAgent:
if not self._session_db:
return
try:
start_idx = (len(conversation_history) if conversation_history else 0) + 1
start_idx = len(conversation_history) if conversation_history else 0
for msg in messages[start_idx:]:
role = msg.get("role", "unknown")
content = msg.get("content")
@ -971,8 +993,6 @@ class AIAgent:
if not content:
return content
content = convert_scratchpad_to_think(content)
# Strip extra newlines before/after think blocks
import re
content = re.sub(r'\n+(<think>)', r'\n\1', content)
content = re.sub(r'(</think>)\n+', r'\1\n', content)
return content.strip()
@ -1290,11 +1310,11 @@ class AIAgent:
"model": self.model,
"messages": api_messages,
"tools": self.tools if self.tools else None,
"timeout": 600.0,
"timeout": 900.0,
}
if self.max_tokens is not None:
api_kwargs["max_tokens"] = self.max_tokens
api_kwargs.update(self._max_tokens_param(self.max_tokens))
extra_body = {}
@ -1394,7 +1414,8 @@ class AIAgent:
"[System: The session is being compressed. "
"Please save anything worth remembering to your memories.]"
)
flush_msg = {"role": "user", "content": flush_content}
_sentinel = f"__flush_{id(self)}_{time.monotonic()}"
flush_msg = {"role": "user", "content": flush_content, "_flush_sentinel": _sentinel}
messages.append(flush_msg)
try:
@ -1428,7 +1449,7 @@ class AIAgent:
"messages": api_messages,
"tools": [memory_tool_def],
"temperature": 0.3,
"max_tokens": 1024,
**self._max_tokens_param(1024),
}
response = self.client.chat.completions.create(**api_kwargs, timeout=30.0)
@ -1460,10 +1481,13 @@ class AIAgent:
except Exception as e:
logger.debug("Memory flush API call failed: %s", e)
finally:
# Strip flush artifacts: remove everything from the flush message onward
while messages and messages[-1] is not flush_msg and len(messages) > 0:
# Strip flush artifacts: remove everything from the flush message onward.
# Use sentinel marker instead of identity check for robustness.
while messages and messages[-1].get("_flush_sentinel") != _sentinel:
messages.pop()
if messages and messages[-1] is flush_msg:
if not messages:
break
if messages and messages[-1].get("_flush_sentinel") == _sentinel:
messages.pop()
def _compress_context(self, messages: list, system_message: str, *, approx_tokens: int = None) -> tuple:
@ -1560,14 +1584,17 @@ class AIAgent:
tool_duration = time.time() - tool_start_time
if self.quiet_mode:
print(f" {_get_cute_tool_message_impl('todo', function_args, tool_duration, result=function_result)}")
elif function_name == "session_search" and self._session_db:
from tools.session_search_tool import session_search as _session_search
function_result = _session_search(
query=function_args.get("query", ""),
role_filter=function_args.get("role_filter"),
limit=function_args.get("limit", 3),
db=self._session_db,
)
elif function_name == "session_search":
if not self._session_db:
function_result = json.dumps({"success": False, "error": "Session database not available."})
else:
from tools.session_search_tool import session_search as _session_search
function_result = _session_search(
query=function_args.get("query", ""),
role_filter=function_args.get("role_filter"),
limit=function_args.get("limit", 3),
db=self._session_db,
)
tool_duration = time.time() - tool_start_time
if self.quiet_mode:
print(f" {_get_cute_tool_message_impl('session_search', function_args, tool_duration, result=function_result)}")
@ -1659,12 +1686,19 @@ class AIAgent:
try:
function_result = handle_function_call(function_name, function_args, effective_task_id)
_spinner_result = function_result
except Exception as tool_error:
function_result = f"Error executing tool '{function_name}': {tool_error}"
logger.error("handle_function_call raised for %s: %s", function_name, tool_error)
finally:
tool_duration = time.time() - tool_start_time
cute_msg = _get_cute_tool_message_impl(function_name, function_args, tool_duration, result=_spinner_result)
spinner.stop(cute_msg)
else:
function_result = handle_function_call(function_name, function_args, effective_task_id)
try:
function_result = handle_function_call(function_name, function_args, effective_task_id)
except Exception as tool_error:
function_result = f"Error executing tool '{function_name}': {tool_error}"
logger.error("handle_function_call raised for %s: %s", function_name, tool_error)
tool_duration = time.time() - tool_start_time
result_preview = function_result[:200] if len(function_result) > 200 else function_result
@ -1756,7 +1790,7 @@ class AIAgent:
"messages": api_messages,
}
if self.max_tokens is not None:
summary_kwargs["max_tokens"] = self.max_tokens
summary_kwargs.update(self._max_tokens_param(self.max_tokens))
if summary_extra_body:
summary_kwargs["extra_body"] = summary_extra_body
@ -1985,7 +2019,7 @@ class AIAgent:
retry_count = 0
max_retries = 6 # Increased to allow longer backoff periods
while retry_count <= max_retries:
while retry_count < max_retries:
try:
api_kwargs = self._build_api_kwargs(api_messages)
@ -2079,6 +2113,7 @@ class AIAgent:
if self._interrupt_requested:
print(f"{self.log_prefix}⚡ Interrupt detected during retry wait, aborting.")
self._persist_session(messages, conversation_history)
self.clear_interrupt()
return {
"final_response": "Operation interrupted.",
"messages": messages,
@ -2181,6 +2216,7 @@ class AIAgent:
if self._interrupt_requested:
print(f"{self.log_prefix}⚡ Interrupt detected during error handling, aborting retries.")
self._persist_session(messages, conversation_history)
self.clear_interrupt()
return {
"final_response": "Operation interrupted.",
"messages": messages,
@ -2189,11 +2225,45 @@ class AIAgent:
"interrupted": True,
}
# Check for 413 payload-too-large BEFORE generic 4xx handler.
# A 413 is a payload-size error — the correct response is to
# compress history and retry, not abort immediately.
status_code = getattr(api_error, "status_code", None)
is_payload_too_large = (
status_code == 413
or 'request entity too large' in error_msg
or 'payload too large' in error_msg
or 'error code: 413' in error_msg
)
if is_payload_too_large:
print(f"{self.log_prefix}⚠️ Request payload too large (413) - attempting compression...")
original_len = len(messages)
messages, active_system_prompt = self._compress_context(
messages, system_message, approx_tokens=approx_tokens
)
if len(messages) < original_len:
print(f"{self.log_prefix} 🗜️ Compressed {original_len} → {len(messages)} messages, retrying...")
continue # Retry with compressed messages
else:
print(f"{self.log_prefix}❌ Payload too large and cannot compress further.")
logging.error(f"{self.log_prefix}413 payload too large. Cannot compress further.")
self._persist_session(messages, conversation_history)
return {
"messages": messages,
"completed": False,
"api_calls": api_call_count,
"error": "Request payload too large (413). Cannot compress further.",
"partial": True
}
# Check for non-retryable client errors (4xx HTTP status codes).
# These indicate a problem with the request itself (bad model ID,
# invalid API key, forbidden, etc.) and will never succeed on retry.
status_code = getattr(api_error, "status_code", None)
is_client_status_error = isinstance(status_code, int) and 400 <= status_code < 500
# Note: 413 is excluded — it's handled above via compression.
is_client_status_error = isinstance(status_code, int) and 400 <= status_code < 500 and status_code != 413
is_client_error = is_client_status_error or any(phrase in error_msg for phrase in [
'error code: 400', 'error code: 401', 'error code: 403',
'error code: 404', 'error code: 422',
@ -2201,7 +2271,7 @@ class AIAgent:
'invalid api key', 'invalid_api_key', 'authentication',
'unauthorized', 'forbidden', 'not found',
])
if is_client_error:
self._dump_api_request_debug(
api_kwargs, reason="non_retryable_client_error", error=api_error,
@ -2221,8 +2291,9 @@ class AIAgent:
# Check for non-retryable errors (context length exceeded)
is_context_length_error = any(phrase in error_msg for phrase in [
'context length', 'maximum context', 'token limit',
'too many tokens', 'reduce the length', 'exceeds the limit'
'context length', 'maximum context', 'token limit',
'too many tokens', 'reduce the length', 'exceeds the limit',
'request entity too large', # OpenRouter/Nous 413 safety net
])
if is_context_length_error:
@ -2257,9 +2328,10 @@ class AIAgent:
raise api_error
wait_time = min(2 ** retry_count, 60) # Exponential backoff: 2s, 4s, 8s, 16s, 32s, 60s, 60s
print(f"⚠️ OpenAI-compatible API call failed (attempt {retry_count}/{max_retries}): {str(api_error)[:100]}")
print(f"⏳ Retrying in {wait_time}s...")
logging.warning(f"API retry {retry_count}/{max_retries} after error: {api_error}")
if retry_count >= max_retries:
print(f"{self.log_prefix}⚠️ API call failed after {retry_count} attempts: {str(api_error)[:100]}")
print(f"{self.log_prefix}⏳ Final retry in {wait_time}s...")
# Sleep in small increments so we can respond to interrupts quickly
# instead of blocking the entire wait_time in one sleep() call
@ -2268,6 +2340,7 @@ class AIAgent:
if self._interrupt_requested:
print(f"{self.log_prefix}⚡ Interrupt detected during retry wait, aborting.")
self._persist_session(messages, conversation_history)
self.clear_interrupt()
return {
"final_response": "Operation interrupted.",
"messages": messages,