marcocosta10000
67e8df36ce
Initial implementation of MultiAgentsAI featuring: - Dynamic agent configuration via environment variables - SQLite database and JSON daily context storage - OpenRouter API integration for multiple AI models - Telegram bot with commands for control, history, and interaction - Autonomous conversation loop with pause/resume and agent silencing - Model testing and statistics commands
52 lines
1.6 KiB
Python
Executable File
52 lines
1.6 KiB
Python
Executable File
# Gerado por IA
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import os
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from datetime import datetime
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from database import get_today_messages, save_message
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from config import settings
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def get_daily_context_path() -> str:
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today = datetime.utcnow().strftime("%Y-%m-%d")
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os.makedirs(settings.CONTEXTS_DIR, exist_ok=True)
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return os.path.join(settings.CONTEXTS_DIR, f"conversas_{today}.json")
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def load_daily_context() -> list[dict]:
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"""Carrega o contexto do dia. SQLite e a fonte da verdade; JSON e um cache sincronizado."""
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# Fonte primaria: SQLite
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context = get_today_messages()
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if context:
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return context
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# Fallback: JSON (caso SQLite esteja vazio)
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path = get_daily_context_path()
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if os.path.exists(path):
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try:
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import json
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with open(path, "r", encoding="utf-8") as f:
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return json.load(f)
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except Exception:
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return []
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return []
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def append_to_context(agent_name: str, message: str) -> None:
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path = get_daily_context_path()
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context = load_daily_context()
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timestamp = datetime.utcnow().isoformat()
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entry = {"agent_name": agent_name, "message": message, "created_at": timestamp}
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context.append(entry)
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import json
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with open(path, "w", encoding="utf-8") as f:
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json.dump(context, f, ensure_ascii=False, indent=2)
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save_message(agent_name, message)
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def get_context_summary(max_messages: int = 50) -> str:
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context = load_daily_context()
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if not context:
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return "Nenhuma conversa registrada para hoje ainda."
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lines = [f"[{c['created_at']}] {c['agent_name']}: {c['message']}" for c in context[-max_messages:]]
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return "\n".join(lines)
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