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https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git
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4bb2442313
Complete AI-powered personal brand automation for Sami Assiri.\n\n7 agents: LinkedIn, Email, Social Media, WhatsApp, CV Optimizer, Content Strategist, Opportunity Scout.\nInfra: FastAPI + APScheduler + Docker + Ollama/Groq LLM + GitHub Pages landing page.\n83 files, ~10K lines. Cost: $0-5/month.
94 lines
2.8 KiB
Python
94 lines
2.8 KiB
Python
"""Task dispatcher - maps agent_name + task_name to actual agent execution."""
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from __future__ import annotations
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import logging
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import time
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import traceback
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from config.settings import get_settings
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from llm.client import get_llm_client
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from storage.database import get_db, init_db
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from storage.models import AgentLog
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logger = logging.getLogger(__name__)
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# Agent registry - lazy imports to avoid circular dependencies
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AGENT_REGISTRY = {
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"linkedin": "agents.linkedin.LinkedInAgent",
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"email": "agents.email.EmailAgent",
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"social_media": "agents.social_media.SocialMediaAgent",
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"whatsapp": "agents.whatsapp.WhatsAppAgent",
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"cv_optimizer": "agents.cv_optimizer.CVOptimizerAgent",
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"content_strategist": "agents.content_strategist.ContentStrategistAgent",
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"opportunity_scout": "agents.opportunity_scout.OpportunityScoutAgent",
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}
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def _import_agent(dotted_path: str):
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"""Dynamically import an agent class from its dotted path."""
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module_path, class_name = dotted_path.rsplit(".", 1)
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import importlib
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module = importlib.import_module(module_path)
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return getattr(module, class_name)
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async def execute_agent_task(agent_name: str, task_name: str):
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"""Execute a specific task for a specific agent."""
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logger.info("Executing: %s.%s", agent_name, task_name)
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start_time = time.time()
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init_db()
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db = get_db()
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try:
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agent_path = AGENT_REGISTRY.get(agent_name)
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if not agent_path:
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logger.error("Unknown agent: %s", agent_name)
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return
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agent_class = _import_agent(agent_path)
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settings = get_settings()
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llm_client = get_llm_client()
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agent = agent_class(config=settings, llm_client=llm_client, db_session=db)
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result = await agent.run(task=task_name)
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duration = time.time() - start_time
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log_entry = AgentLog(
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agent_name=agent_name,
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task=task_name,
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status="success",
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details=str(result)[:2000] if result else "OK",
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duration_seconds=round(duration, 2),
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)
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db.add(log_entry)
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db.commit()
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logger.info(
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"Completed: %s.%s in %.2fs", agent_name, task_name, duration
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)
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return result
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except Exception as e:
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duration = time.time() - start_time
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error_detail = f"{type(e).__name__}: {e}\n{traceback.format_exc()}"
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logger.error("Failed: %s.%s - %s", agent_name, task_name, e)
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try:
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log_entry = AgentLog(
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agent_name=agent_name,
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task=task_name,
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status="failed",
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details=error_detail[:2000],
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duration_seconds=round(duration, 2),
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)
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db.add(log_entry)
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db.commit()
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except Exception:
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logger.error("Failed to log error to database")
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finally:
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db.close()
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