Files
DocsGPT/docsgpt/agents/agent_creator.py
T
Alex 574f96341e refactor: rename the application package to docsgpt
The backend import package is now docsgpt, the name it will carry on PyPI;
application was far too generic to install into anyone's site-packages.
git mv plus a mechanical rewrite of every import, dotted string and path
reference: 734 Python files, the compose files, Dockerfile, workflows, docs,
setup scripts, devcontainer, k8s manifests, vscode config, pytest and coverage
config, .gitignore. Behaviour is unchanged.

Kept for one release:
- A top-level application package whose meta-path finder resolves
  application.x.y to the already-imported docsgpt.x.y object, so old imports
  and entry points (celery -A application.app.celery,
  uvicorn application.asgi:asgi_app) keep working with a FutureWarning.
- Celery registers every application.* task name as an alias of its
  docsgpt.* task on start-up, so messages queued by the previous release still
  run. The redbeat key prefix moves to redbeat:docsgpt:v2: so schedule entries
  the previous release wrote are left unread instead of firing twice.

The backend image builds from the repository root (docker build -f
docsgpt/Dockerfile .) so it can ship the alias package; a root .dockerignore
allow-lists docsgpt/ and application/ and keeps caches, local data, .env
files, the sample index files and the Dockerfile out. Compose and the image
workflows point at the new context.
2026-09-07 10:20:43 +01:00

26 lines
794 B
Python

import logging
from docsgpt.agents.agentic_agent import AgenticAgent
from docsgpt.agents.classic_agent import ClassicAgent
from docsgpt.agents.research_agent import ResearchAgent
from docsgpt.agents.workflow_agent import WorkflowAgent
logger = logging.getLogger(__name__)
class AgentCreator:
agents = {
"classic": ClassicAgent,
"react": ClassicAgent, # backwards compat: react falls back to classic
"agentic": AgenticAgent,
"research": ResearchAgent,
"workflow": WorkflowAgent,
}
@classmethod
def create_agent(cls, type, *args, **kwargs):
agent_class = cls.agents.get(type.lower())
if not agent_class:
raise ValueError(f"No agent class found for type {type}")
return agent_class(*args, **kwargs)