diff --git a/argus_agent.py b/argus_agent.py index 0669046..d75746c 100644 --- a/argus_agent.py +++ b/argus_agent.py @@ -7,7 +7,6 @@ detects bias, and generates comprehensive intelligence reports with confidence scoring, source attribution, and exportable markdown output. Named after Argus Panoptes, the all-seeing giant of Greek mythology. -Built on the Swarms framework for production-ready agent orchestration. Author: ARGUS Labs Version: 2.0.0 @@ -18,13 +17,15 @@ import os import re import json import hashlib +import inspect import requests import time import functools from collections import Counter from typing import Dict, List, Optional, Any, Callable from datetime import datetime, timezone -from swarms import Agent + +from openai import OpenAI # ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ @@ -75,11 +76,7 @@ def _retry(max_attempts: int = 3, delay: float = 1.0): _HEADERS = { - "User-Agent": ( - "Mozilla/5.0 (Windows NT 10.0; Win64; x64) " - "AppleWebKit/537.36 (KHTML, like Gecko) " - "Chrome/124.0.0.0 Safari/537.36" - ) + "User-Agent": "ARGUS/2.0 (+https://github.com/ClawArgus/ClawArgus)" } _STOP_WORDS = frozenset({ @@ -974,7 +971,108 @@ Prioritize sources in this order: # AGENT INITIALIZATION # ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ -argus_agent = Agent( +_JSON_TYPE_MAP = { + str: "string", + int: "integer", + float: "number", + bool: "boolean", +} + + +def _build_tool_schema(func: Callable) -> Dict[str, Any]: + sig = inspect.signature(func) + properties: Dict[str, Any] = {} + required: List[str] = [] + for name, param in sig.parameters.items(): + json_type = _JSON_TYPE_MAP.get(param.annotation, "string") + properties[name] = {"type": json_type} + if param.default is inspect.Parameter.empty: + required.append(name) + doc = (func.__doc__ or "").strip().split("\n\n", 1)[0] + return { + "type": "function", + "function": { + "name": func.__name__, + "description": doc[:1024], + "parameters": { + "type": "object", + "properties": properties, + "required": required, + }, + }, + } + + +class ArgusAgent: + """ + Minimal tool-calling loop around the OpenAI Chat Completions API. + + Holds the system prompt, the tool registry, and a .run(task) entry point + that drives the model-tool-model cycle until the model returns a final + answer or max_loops is exceeded. + """ + + def __init__( + self, + agent_name: str, + agent_description: str, + system_prompt: str, + model_name: str, + tools: List[Callable], + max_loops: int = 5, + verbose: bool = True, + ): + self.agent_name = agent_name + self.agent_description = agent_description + self.system_prompt = system_prompt + self.model_name = model_name + self.max_loops = max_loops + self.verbose = verbose + self._tools_by_name = {t.__name__: t for t in tools} + self._tool_schemas = [_build_tool_schema(t) for t in tools] + self._client = OpenAI() + + def run(self, task: str) -> str: + messages: List[Dict[str, Any]] = [ + {"role": "system", "content": self.system_prompt}, + {"role": "user", "content": task}, + ] + + for loop in range(self.max_loops): + response = self._client.chat.completions.create( + model=self.model_name, + messages=messages, + tools=self._tool_schemas, + tool_choice="auto", + ) + msg = response.choices[0].message + messages.append(msg.model_dump(exclude_none=True)) + + if not msg.tool_calls: + return msg.content or "" + + for call in msg.tool_calls: + fn = self._tools_by_name.get(call.function.name) + if self.verbose: + print(f" 🔧 [loop {loop + 1}] {call.function.name}({call.function.arguments})") + if fn is None: + result = f"Unknown tool: {call.function.name}" + else: + try: + args = json.loads(call.function.arguments or "{}") + result = fn(**args) + except Exception as exc: + result = f"Error running {call.function.name}: {exc}" + messages.append({ + "role": "tool", + "tool_call_id": call.id, + "content": str(result), + }) + + return "Max tool loops reached without a final answer." + + +argus_agent = ArgusAgent( agent_name="ARGUS", agent_description=( "ARGUS — The All-Seeing Research & Intelligence Agent v2.0. " @@ -987,13 +1085,6 @@ argus_agent = Agent( system_prompt=ARGUS_SYSTEM_PROMPT, model_name="gpt-4o-mini", max_loops=5, - autosave=True, - verbose=True, - dynamic_temperature_enabled=True, - saved_state_path="argus_state.json", - retry_attempts=3, - context_length=128000, - output_type="string", tools=[ web_search, fetch_url_content, @@ -1003,7 +1094,6 @@ argus_agent = Agent( compare_sources, generate_report, ], - tool_choice="auto", )