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@ -1,4 +1,3 @@
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import concurrent.futures
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import asyncio
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import json
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import logging
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@ -54,11 +53,11 @@ from swarms.utils.file_processing import create_file_in_folder
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from swarms.utils.formatter import formatter
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from swarms.utils.history_output_formatter import (
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history_output_formatter,
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HistoryOutputType,
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)
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from swarms.utils.litellm_tokenizer import count_tokens
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from swarms.utils.litellm_wrapper import LiteLLM
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from swarms.utils.pdf_to_text import pdf_to_text
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from swarms.structs.output_types import OutputType
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from swarms.utils.str_to_dict import str_to_dict
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from swarms.tools.mcp_client import (
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execute_mcp_tool,
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@ -337,7 +336,7 @@ class Agent:
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# [Tools]
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custom_tools_prompt: Optional[Callable] = None,
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tool_schema: ToolUsageType = None,
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output_type: HistoryOutputType = "str-all-except-first",
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output_type: OutputType = "str-all-except-first",
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function_calling_type: str = "json",
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output_cleaner: Optional[Callable] = None,
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function_calling_format_type: Optional[str] = "OpenAI",
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@ -529,12 +528,32 @@ class Agent:
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# Initialize the feedback
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self.feedback = []
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# Initialize the executor
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self.executor = ThreadPoolExecutor(
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max_workers=executor_workers
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)
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# self.init_handling()
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# Define tasks as pairs of (function, condition)
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# Each task will only run if its condition is True
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self.setup_config()
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if exists(self.docs_folder):
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self.get_docs_from_doc_folders()
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if exists(self.tools):
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self.handle_tool_init()
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if exists(self.tool_schema) or exists(self.list_base_models):
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self.handle_tool_schema_ops()
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if exists(self.sop) or exists(self.sop_list):
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self.handle_sop_ops()
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self.init_handling()
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# Run sequential operations after all concurrent tasks are done
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# self.agent_output = self.agent_output_model()
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log_agent_data(self.to_dict())
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if self.llm is None:
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self.llm = self.llm_handling()
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if self.mcp_url or self.mcp_servers is not None:
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self.add_mcp_tools_to_memory()
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def short_memory_init(self):
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if (
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@ -561,57 +580,20 @@ class Agent:
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# Each task will only run if its condition is True
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self.setup_config()
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tasks = [
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(self.setup_config, True), # Always run setup_config
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(
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self.get_docs_from_doc_folders,
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exists(self.docs_folder),
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),
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(self.handle_tool_init, True), # Always run tool init
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(
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self.handle_tool_schema_ops,
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exists(self.tool_schema)
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or exists(self.list_base_models),
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),
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# (
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# self.handle_sop_ops,
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# exists(self.sop) or exists(self.sop_list),
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# ),
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]
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if exists(self.docs_folder):
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self.get_docs_from_doc_folders()
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# Filter out tasks whose conditions are False
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filtered_tasks = [
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task for task, condition in tasks if condition
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]
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if exists(self.tools):
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self.handle_tool_init()
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# Execute all tasks concurrently
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with self.executor as executor:
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# Map tasks to futures and collect results
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results = {}
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future_to_task = {
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executor.submit(task): task.__name__
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for task in filtered_tasks
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}
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if exists(self.tool_schema) or exists(self.list_base_models):
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self.handle_tool_schema_ops()
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# Wait for each future to complete and collect results/exceptions
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for future in concurrent.futures.as_completed(
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future_to_task
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):
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task_name = future_to_task[future]
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try:
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result = future.result()
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results[task_name] = result
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logging.info(
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f"Task {task_name} completed successfully"
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)
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except Exception as e:
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results[task_name] = None
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logging.error(
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f"Task {task_name} failed with error: {e}"
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)
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if exists(self.sop) or exists(self.sop_list):
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self.handle_sop_ops()
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# Run sequential operations after all concurrent tasks are done
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self.agent_output = self.agent_output_model()
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# self.agent_output = self.agent_output_model()
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log_agent_data(self.to_dict())
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if self.llm is None:
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@ -1808,10 +1790,11 @@ class Agent:
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)
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# Reinitialize executor if needed
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if not hasattr(self, "executor") or self.executor is None:
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self.executor = ThreadPoolExecutor(
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# if not hasattr(self, "executor") or self.executor is None:
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with ThreadPoolExecutor(
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max_workers=os.cpu_count()
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)
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) as executor:
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self.executor = executor
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# # Reinitialize tool structure if needed
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# if hasattr(self, 'tools') and (self.tools or getattr(self, 'list_base_models', None)):
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Kye Gomez
4 days ago