westfarn
d1660792ad
Unit Tests / test (push) Successful in 13s
## Summary Implements [chat_backend#6](#6) Part A: - **uv** packaging (`pyproject.toml` + `uv.lock`), Docker/compose (dev + prod), entrypoint/validate-env, Gitea unit-test + auto-deploy workflows (mirror `scha`) - Env-driven Django settings (`DJANGO_*`, `DATABASE_URL`, CSRF/CORS) - **`OLLAMA_BASE_URL`** wired through all Ollama/LangChain clients (prod → `http://10.0.0.128:11434`) - **DatabaseStorage** — prompt/document file blobs in Postgres (`StoredFile`), not container FS; RAG materializes temp paths for loaders - ASGI via `gunicorn` + `UvicornWorker` (HTTP + WebSockets) Companion server-infra PR registers `app_catalog` / `host_apps` (port **8003**). ## Test plan - [ ] `uv sync && cd llm_be && SKIP_RAG_INIT=1 uv run python manage.py test` - [ ] `docker compose build && docker compose up` against bundled Postgres - [ ] Confirm Ollama calls use `OLLAMA_BASE_URL` (not hardcoded localhost) - [ ] Upload a document / prompt file → row in `chat_backend_storedfile`, no disk under `media/` - [ ] After server-infra merge + secret/Postgres/NPM: deploy via `deploy.sh --app chat_backend --env prod`Reviewed-on: #7
41 lines
1.2 KiB
Python
41 lines
1.2 KiB
Python
from django.db.models.signals import post_save, post_delete
|
|
from django.dispatch import receiver
|
|
from django.conf import settings
|
|
import os
|
|
|
|
from chat_backend.models import Document
|
|
|
|
|
|
def _rag_init_skipped() -> bool:
|
|
return os.environ.get("SKIP_RAG_INIT", "").lower() in {"1", "true", "yes"}
|
|
|
|
|
|
@receiver(post_save, sender=Document)
|
|
def update_vector_on_save(sender, instance, **kwargs):
|
|
"""Update vector store when documents are saved"""
|
|
if _rag_init_skipped():
|
|
return
|
|
if not kwargs.get("created", False):
|
|
return
|
|
try:
|
|
from .services.rag_services import AsyncRAGService
|
|
|
|
rag_service = AsyncRAGService()
|
|
rag_service.ingest_documents()
|
|
except Exception as exc:
|
|
print(f"Skipping vector update on Document save: {exc}")
|
|
|
|
|
|
@receiver(post_delete, sender=Document)
|
|
def delete_vector_on_remove(sender, instance, **kwargs):
|
|
"""Handle document deletion by re-indexing the whole workspace"""
|
|
if _rag_init_skipped():
|
|
return
|
|
try:
|
|
from .services.rag_services import AsyncRAGService
|
|
|
|
rag_service = AsyncRAGService()
|
|
rag_service.ingest_documents()
|
|
except Exception as exc:
|
|
print(f"Skipping vector update on Document delete: {exc}")
|