File: //opt/agenticSeek/sources/agents/agent.py
from typing import Tuple, Callable
from abc import abstractmethod
import os
import random
import time
import asyncio
from concurrent.futures import ThreadPoolExecutor
from sources.memory import Memory
from sources.utility import pretty_print
from sources.schemas import executorResult
random.seed(time.time())
class Agent():
"""
An abstract class for all agents.
"""
def __init__(self, name: str,
prompt_path:str,
provider,
verbose=False,
browser=None) -> None:
"""
Args:
name (str): Name of the agent.
prompt_path (str): Path to the prompt file for the agent.
provider: The provider for the LLM.
recover_last_session (bool, optional): Whether to recover the last conversation.
verbose (bool, optional): Enable verbose logging if True. Defaults to False.
browser: The browser class for web navigation (only for browser agent).
"""
self.agent_name = name
self.browser = browser
self.role = None
self.type = None
self.current_directory = os.getcwd()
self.llm = provider
self.memory = Memory(self.load_prompt(prompt_path),
recover_last_session=False, # session recovery in handled by the interaction class
memory_compression=False)
self.tools = {}
self.blocks_result = []
self.success = True
self.last_answer = ""
self.status_message = "Haven't started yet"
self.verbose = verbose
self.executor = ThreadPoolExecutor(max_workers=1)
@property
def get_agent_name(self) -> str:
return self.agent_name
@property
def get_agent_type(self) -> str:
return self.type
@property
def get_agent_role(self) -> str:
return self.role
@property
def get_last_answer(self) -> str:
return self.last_answer
@property
def get_blocks(self) -> list:
return self.blocks_result
@property
def get_status_message(self) -> str:
return self.status_message
@property
def get_tools(self) -> dict:
return self.tools
@property
def get_success(self) -> bool:
return self.success
def get_blocks_result(self) -> list:
return self.blocks_result
def add_tool(self, name: str, tool: Callable) -> None:
if tool is not Callable:
raise TypeError("Tool must be a callable object (a method)")
self.tools[name] = tool
def load_prompt(self, file_path: str) -> str:
try:
with open(file_path, 'r', encoding="utf-8") as f:
return f.read()
except FileNotFoundError:
raise FileNotFoundError(f"Prompt file not found at path: {file_path}")
except PermissionError:
raise PermissionError(f"Permission denied to read prompt file at path: {file_path}")
except Exception as e:
raise e
@abstractmethod
def process(self, prompt, speech_module) -> str:
"""
abstract method, implementation in child class.
Process the prompt and return the answer of the agent.
"""
pass
def remove_reasoning_text(self, text: str) -> None:
"""
Remove the reasoning block of reasoning model like deepseek.
"""
end_tag = "</think>"
end_idx = text.rfind(end_tag)+8
return text[end_idx:]
def extract_reasoning_text(self, text: str) -> None:
"""
Extract the reasoning block of a reasoning model like deepseek.
"""
start_tag = "<think>"
end_tag = "</think>"
start_idx = text.find(start_tag)
end_idx = text.rfind(end_tag)+8
return text[start_idx:end_idx]
async def llm_request(self) -> Tuple[str, str]:
"""
Asynchronously ask the LLM to process the prompt.
"""
self.status_message = "Thinking..."
loop = asyncio.get_event_loop()
return await loop.run_in_executor(self.executor, self.sync_llm_request)
def sync_llm_request(self) -> Tuple[str, str]:
"""
Ask the LLM to process the prompt and return the answer and the reasoning.
"""
memory = self.memory.get()
thought = self.llm.respond(memory, self.verbose)
reasoning = self.extract_reasoning_text(thought)
answer = self.remove_reasoning_text(thought)
self.memory.push('assistant', answer)
return answer, reasoning
async def wait_message(self, speech_module):
if speech_module is None:
return
messages = ["Please be patient, I am working on it.",
"Computing... I recommand you have a coffee while I work.",
"Hold on, Iām crunching numbers.",
"Working on it, please let me think."]
loop = asyncio.get_event_loop()
return await loop.run_in_executor(self.executor, lambda: speech_module.speak(messages[random.randint(0, len(messages)-1)]))
def get_last_tool_type(self) -> str:
return self.blocks_result[-1].tool_type if len(self.blocks_result) > 0 else None
def raw_answer_blocks(self, answer: str) -> str:
"""
Return the answer with all the blocks inserted, as text.
"""
if self.last_answer is None:
return
raw = ""
lines = self.last_answer.split("\n")
for line in lines:
if "block:" in line:
block_idx = int(line.split(":")[1])
if block_idx < len(self.blocks_result):
raw += self.blocks_result[block_idx].__str__()
else:
raw += line + "\n"
return raw
def show_answer(self):
"""
Show the answer in a pretty way.
Show code blocks and their respective feedback by inserting them in the ressponse.
"""
if self.last_answer is None:
return
lines = self.last_answer.split("\n")
for line in lines:
if "block:" in line:
block_idx = int(line.split(":")[1])
if block_idx < len(self.blocks_result):
self.blocks_result[block_idx].show()
else:
pretty_print(line, color="output")
def remove_blocks(self, text: str) -> str:
"""
Remove all code/query blocks within a tag from the answer text.
"""
tag = f'```'
lines = text.split('\n')
post_lines = []
in_block = False
block_idx = 0
for line in lines:
if tag in line and not in_block:
in_block = True
continue
if not in_block:
post_lines.append(line)
if tag in line:
in_block = False
post_lines.append(f"block:{block_idx}")
block_idx += 1
return "\n".join(post_lines)
def show_block(self, block: str) -> None:
"""
Show the block in a pretty way.
"""
pretty_print('ā'*64, color="status")
pretty_print(block, color="code")
pretty_print('ā'*64, color="status")
def execute_modules(self, answer: str) -> Tuple[bool, str]:
"""
Execute all the tools the agent has and return the result.
"""
feedback = ""
success = True
blocks = None
if answer.startswith("```"):
answer = "I will execute:\n" + answer # there should always be a text before blocks for the function that display answer
self.success = True
for name, tool in self.tools.items():
feedback = ""
blocks, save_path = tool.load_exec_block(answer)
if blocks != None:
for block in blocks:
self.show_block(block)
output = tool.execute([block])
feedback = tool.interpreter_feedback(output) # tool interpreter feedback
success = not tool.execution_failure_check(output)
self.blocks_result.append(executorResult(block, feedback, success, name))
if not success:
self.success = False
self.memory.push('user', feedback)
return False, feedback
self.memory.push('user', feedback)
if save_path != None:
tool.save_block(blocks, save_path)
return True, feedback