File size: 2,338 Bytes
5374a2d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 |
"""
Configuration settings for the EvoAgentX application.
"""
# import os
from pydantic import BaseModel, Field, validator
from pydantic_settings import BaseSettings
from typing import Optional, Dict, Any, List
class Settings(BaseSettings):
# Application settings
APP_NAME: str
DEBUG: bool
API_PREFIX: str
HOST: str
PORT: int
# MongoDB settings
MONGODB_URL: str
MONGODB_DB_NAME: str
# JWT Authentication
SECRET_KEY: str
ACCESS_TOKEN_EXPIRE_MINUTES: int
ALGORITHM: str
# Logging configuration
LOG_LEVEL: str
# Add CORS settings
CORS_ORIGINS: List[str] = ["http://localhost:3000", "http://localhost:8000"]
CORS_ALLOW_CREDENTIALS: bool = True
class Config:
env_file = ".env"
case_sensitive = True
env_delimiter = ","
# Global settings instance
settings = Settings()
# Agent and Workflow configuration
class AgentConfig(BaseModel):
"""Base configuration for an LLM agent."""
model_name: str
temperature: float = 0.7
max_tokens: int = 2048
api_key_env_var: Optional[str] = None
system_prompt: Optional[str] = None
extra_params: Dict[str, Any] = Field(default_factory=dict)
@validator('temperature')
def validate_temperature(cls, v):
if v < 0 or v > 1:
raise ValueError('Temperature must be between 0 and 1')
return v
class WorkflowStepConfig(BaseModel):
"""Configuration for a single step in a workflow."""
step_id: str
agent_id: str
action: str
input_mapping: Dict[str, str] = Field(default_factory=dict)
output_mapping: Dict[str, str] = Field(default_factory=dict)
timeout_seconds: int = 300
retry_count: int = 3
class WorkflowConfig(BaseModel):
"""Configuration for a workflow composed of agent steps."""
name: str
description: Optional[str] = None
steps: List[WorkflowStepConfig]
parallel_execution: bool = False
timeout_seconds: int = 3600 # Default to 1 hour total timeout
class ExecutionConfig(BaseModel):
"""Configuration for a workflow execution."""
workflow_id: str
input_params: Dict[str, Any] = Field(default_factory=dict)
user_id: Optional[str] = None
priority: int = 1 # Higher number means higher priority
callback_url: Optional[str] = None |