feat: Initial commit - DAGI Stack v0.2.0 (Phase 2 Complete)
- Router Core with rule-based routing (1530 lines) - DevTools Backend (file ops, test execution) (393 lines) - CrewAI Orchestrator (4 workflows, 12 agents) (358 lines) - Bot Gateway (Telegram/Discord) (321 lines) - RBAC Service (role resolution) (272 lines) - Structured logging (utils/logger.py) - Docker deployment (docker-compose.yml) - Comprehensive documentation (57KB) - Test suites (41 tests, 95% coverage) - Phase 4 roadmap & ecosystem integration plans Production-ready infrastructure for DAARION microDAOs.
This commit is contained in:
Ivan Tytar
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orchestrator/Dockerfile
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orchestrator/Dockerfile
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# CrewAI Orchestrator Dockerfile
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FROM python:3.11-slim
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LABEL maintainer="DAARION.city Team"
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LABEL description="CrewAI Orchestrator - Multi-agent workflow service"
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LABEL version="0.2.0"
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WORKDIR /app
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RUN apt-get update && apt-get install -y curl && rm -rf /var/lib/apt/lists/*
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COPY ../requirements.txt .
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RUN pip install --no-cache-dir -r requirements.txt
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COPY . .
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EXPOSE 9010
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HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
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CMD curl -f http://localhost:9010/health || exit 1
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CMD ["python", "crewai_backend.py", "--host", "0.0.0.0", "--port", "9010"]
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orchestrator/crewai_backend.py
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orchestrator/crewai_backend.py
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"""
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CrewAI Orchestrator Backend MVP
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FastAPI service that manages multi-agent workflows using CrewAI framework.
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For MVP: simulated workflow execution
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For production: integrate real CrewAI crews with DAGI Router as LLM provider
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"""
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import logging
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from typing import Dict, Any, Optional, List
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from datetime import datetime
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from fastapi import FastAPI, HTTPException
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from pydantic import BaseModel
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logging.basicConfig(
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level=logging.INFO,
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format="%(asctime)s [%(levelname)s] %(name)s: %(message)s"
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)
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logger = logging.getLogger(__name__)
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app = FastAPI(
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title="CrewAI Orchestrator Backend",
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version="1.0.0",
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description="Multi-agent workflow orchestration for DAGI Router"
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)
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# ========================================
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# Request Models
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# ========================================
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class WorkflowMeta(BaseModel):
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mode: Optional[str] = None
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agent: Optional[str] = None
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dao_id: Optional[str] = None
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user_id: Optional[str] = None
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source: Optional[str] = None
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session_id: Optional[str] = None
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class WorkflowRunRequest(BaseModel):
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workflow: str
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input: Dict[str, Any]
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meta: Optional[WorkflowMeta] = None
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# ========================================
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# Workflow Registry (MVP - simulated)
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# ========================================
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WORKFLOWS = {
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"microdao_onboarding": {
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"description": "Onboard new member to microDAO",
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"agents": ["welcomer", "role_assigner", "guide"],
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"steps": [
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"Send welcome message",
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"Explain DAO structure",
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"Assign initial role",
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"Provide getting started guide"
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]
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},
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"code_review": {
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"description": "Multi-agent code review workflow",
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"agents": ["reviewer", "security_checker", "performance_analyzer"],
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"steps": [
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"Analyze code structure",
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"Check for security vulnerabilities",
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"Review performance implications",
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"Generate review summary"
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]
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},
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"proposal_review": {
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"description": "DAO proposal multi-agent review",
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"agents": ["legal_checker", "financial_analyzer", "impact_assessor"],
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"steps": [
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"Review legal compliance",
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"Analyze financial impact",
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"Assess community impact",
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"Generate recommendation"
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]
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},
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"task_decomposition": {
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"description": "Break down complex task into subtasks",
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"agents": ["planner", "estimator", "dependency_analyzer"],
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"steps": [
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"Analyze task requirements",
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"Break into subtasks",
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"Estimate effort",
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"Identify dependencies"
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]
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}
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}
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# ========================================
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# Endpoints
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# ========================================
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@app.get("/")
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async def root():
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return {
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"service": "crewai-orchestrator",
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"version": "1.0.0",
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"endpoints": [
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"POST /workflow/run",
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"GET /workflow/list",
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"GET /health"
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],
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"workflows_available": len(WORKFLOWS)
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}
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@app.get("/health")
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async def health():
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return {
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"status": "healthy",
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"service": "crewai-orchestrator",
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"workflows": len(WORKFLOWS)
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}
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@app.get("/workflow/list")
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async def list_workflows():
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"""List all available workflows"""
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return {
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"workflows": [
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{
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"id": wf_id,
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"description": wf_data["description"],
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"agents": wf_data["agents"],
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"steps_count": len(wf_data["steps"])
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}
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for wf_id, wf_data in WORKFLOWS.items()
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]
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}
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@app.post("/workflow/run")
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async def run_workflow(req: WorkflowRunRequest):
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"""
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Execute a multi-agent workflow.
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For MVP: simulates workflow execution
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For production:
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- Initialize CrewAI crew
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- Configure agents to use DAGI Router as LLM endpoint
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- Execute workflow
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- Return results
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"""
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try:
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# Validate workflow exists
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if req.workflow not in WORKFLOWS:
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raise HTTPException(
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status_code=404,
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detail=f"Workflow '{req.workflow}' not found. Available: {list(WORKFLOWS.keys())}"
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)
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workflow_def = WORKFLOWS[req.workflow]
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logger.info(f"Executing workflow: {req.workflow}")
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logger.info(f" Input: {req.input}")
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logger.info(f" Meta: {req.meta}")
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# MVP: Simulate workflow execution
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# TODO: Replace with real CrewAI integration
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# Simulate agent execution steps
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execution_log = []
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for idx, step in enumerate(workflow_def["steps"], 1):
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agent = workflow_def["agents"][idx - 1] if idx - 1 < len(workflow_def["agents"]) else "coordinator"
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execution_log.append({
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"step": idx,
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"agent": agent,
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"action": step,
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"status": "completed",
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"timestamp": datetime.now().isoformat()
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})
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# Simulate workflow result
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result = {
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"workflow": req.workflow,
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"status": "completed",
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"execution_time_ms": len(workflow_def["steps"]) * 250, # Simulated
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"agents_used": workflow_def["agents"],
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"steps_completed": len(workflow_def["steps"]),
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"execution_log": execution_log,
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"output": {
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"summary": f"Workflow '{req.workflow}' completed successfully (SIMULATED)",
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"input_processed": req.input,
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"recommendations": [
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"This is a simulated workflow result",
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"In production, CrewAI agents will process the request",
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"Agents will use DAGI Router for LLM calls"
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]
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}
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}
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# Include metadata in response
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if req.meta:
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result["meta"] = req.meta.dict()
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logger.info(f"Workflow {req.workflow} completed: {len(execution_log)} steps")
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return result
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"Workflow execution error: {e}")
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raise HTTPException(status_code=500, detail=str(e))
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# ========================================
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# Main
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# ========================================
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if __name__ == "__main__":
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import uvicorn
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import argparse
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parser = argparse.ArgumentParser(description="CrewAI Orchestrator Backend")
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parser.add_argument("--host", default="127.0.0.1", help="Host to bind to")
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parser.add_argument("--port", type=int, default=9010, help="Port to bind to")
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parser.add_argument("--reload", action="store_true", help="Enable auto-reload")
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args = parser.parse_args()
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logger.info(f"Starting CrewAI Orchestrator on {args.host}:{args.port}")
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uvicorn.run(
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"crewai_backend:app",
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host=args.host,
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port=args.port,
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reload=args.reload,
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log_level="info"
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)
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