File size: 1,600 Bytes
3370983 |
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 |
# src/core/configs/agent.py
from typing import List, Optional
from langchain_core.tools import BaseTool
from pydantic import BaseModel, Field, ConfigDict
from src.backend.core.configs.model import ModelConfig
class AgentConfig(BaseModel):
"""
Configuration schema for initializing LangGraph agents.
Notes:
Pydantic setting ``model_config = ConfigDict(arbitrary_types_allowed=True)``
allows this model to include arbitrary Python objects such as LangChain
tools or runtime components that are not JSON-serializable or Pydantic
models. These objects (e.g., `BaseTool` instances) are accepted as-is
without validation or serialization, while all standard fields
(strings, numbers, nested Pydantic models) remain fully validated.
"""
model_config = ConfigDict(
arbitrary_types_allowed=True
)
name: str = Field(
...,
description="Unique name of the agent."
)
description: str = Field(
...,
description="Short description of what the agent does."
)
model_config: ModelConfig = Field(
...,
description="Configuration of the underlying LLM model."
)
tools: Optional[List[BaseTool]] = Field(
default_factory=list,
description="List of tools available to the agent."
)
system_prompt: str = Field(
default="",
description="System prompt to condition the agent's behavior."
)
max_iterations: Optional[int] = Field(
default=None,
description="Optional limit on reasoning iterations."
)
|