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This commit is contained in:
marko-kraemer 2025-05-03 02:26:25 +02:00
parent 79ead85912
commit 973861b2d2
1 changed files with 21 additions and 27 deletions
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48
backend/agentpress/thread_manager.py
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@ -260,24 +260,24 @@ Here are the XML tools available with examples:
token_threshold = self.context_manager.token_threshold
logger.info(f"Thread {thread_id} token count: {token_count}/{token_threshold} ({(token_count/token_threshold)*100:.1f}%)")
if token_count >= token_threshold and enable_context_manager:
logger.info(f"Thread token count ({token_count}) exceeds threshold ({token_threshold}), summarizing...")
summarized = await self.context_manager.check_and_summarize_if_needed(
thread_id=thread_id,
add_message_callback=self.add_message,
model=llm_model,
force=True
)
if summarized:
logger.info("Summarization complete, fetching updated messages with summary")
messages = await self.get_llm_messages(thread_id)
# Recount tokens after summarization, using the modified prompt
new_token_count = token_counter(model=llm_model, messages=[working_system_prompt] + messages)
logger.info(f"After summarization: token count reduced from {token_count} to {new_token_count}")
else:
logger.warning("Summarization failed or wasn't needed - proceeding with original messages")
elif not enable_context_manager: # Added condition for clarity
logger.info("Automatic summarization disabled. Skipping token count check and summarization.")
# if token_count >= token_threshold and enable_context_manager:
# logger.info(f"Thread token count ({token_count}) exceeds threshold ({token_threshold}), summarizing...")
# summarized = await self.context_manager.check_and_summarize_if_needed(
# thread_id=thread_id,
# add_message_callback=self.add_message,
# model=llm_model,
# force=True
# )
# if summarized:
# logger.info("Summarization complete, fetching updated messages with summary")
# messages = await self.get_llm_messages(thread_id)
# # Recount tokens after summarization, using the modified prompt
# new_token_count = token_counter(model=llm_model, messages=[working_system_prompt] + messages)
# logger.info(f"After summarization: token count reduced from {token_count} to {new_token_count}")
# else:
# logger.warning("Summarization failed or wasn't needed - proceeding with original messages")
# elif not enable_context_manager:
# logger.info("Automatic summarization disabled. Skipping token count check and summarization.")
except Exception as e:
logger.error(f"Error counting tokens or summarizing: {str(e)}")
@ -305,19 +305,13 @@ Here are the XML tools available with examples:
prepared_messages.append(temp_msg)
logger.debug("Added temporary message to the end of prepared messages")
# 4. Create or use processor config - this is now redundant since we handle it above
# but kept for consistency and clarity
logger.debug(f"Processor config: XML={processor_config.xml_tool_calling}, Native={processor_config.native_tool_calling}, "
f"Execute tools={processor_config.execute_tools}, Strategy={processor_config.tool_execution_strategy}, "
f"XML limit={processor_config.max_xml_tool_calls}")
# 5. Prepare tools for LLM call
# 4. Prepare tools for LLM call
openapi_tool_schemas = None
if processor_config.native_tool_calling:
openapi_tool_schemas = self.tool_registry.get_openapi_schemas()
logger.debug(f"Retrieved {len(openapi_tool_schemas) if openapi_tool_schemas else 0} OpenAPI tool schemas")
# 6. Make LLM API call
# 5. Make LLM API call
logger.debug("Making LLM API call")
try:
llm_response = await make_llm_api_call(
@ -337,7 +331,7 @@ Here are the XML tools available with examples:
logger.error(f"Failed to make LLM API call: {str(e)}", exc_info=True)
raise
# 7. Process LLM response using the ResponseProcessor
# 6. Process LLM response using the ResponseProcessor
if stream:
logger.debug("Processing streaming response")
response_generator = self.response_processor.process_streaming_response(