mirror of
https://github.com/tiennm99/DocsGPT.git
synced 2026-10-05 14:14:39 +00:00
Alex
574f96341e
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.
23 lines
780 B
Python
23 lines
780 B
Python
from __future__ import annotations
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from typing import Optional
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from docsgpt.llm.docsgpt_provider import DocsGPTAPILLM
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from docsgpt.llm.providers.base import Provider
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class DocsGPTProvider(Provider):
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name = "docsgpt"
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llm_class = DocsGPTAPILLM
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def get_api_key(self, settings) -> Optional[str]:
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# No provider-specific key; the LLM class can use the generic
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# API_KEY fallback if it needs one. Mirrors model_utils' historical
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# behavior of returning settings.API_KEY when no specific key exists.
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return settings.API_KEY
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def is_enabled(self, settings) -> bool:
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# The hosted DocsGPT model is hidden when the deployment is
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# pointed at a custom OpenAI-compatible endpoint.
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return not settings.OPENAI_BASE_URL
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