ac779dec7e
Why: - Any test using the client/api_client fixtures runs the app's real lifespan, which calls the production configure_logging() -- setting cache_logger_on_first_use=True (ADR-0011). That permanently monkeypatches the .bind method on whichever module-level logger = structlog.get_logger(__name__) instance is used first. structlog.reset_defaults() only resets *global* config, not that per-instance mutation, so once triggered, structlog.testing.capture_logs() silently stops intercepting events in every test that runs afterward in the same pytest process -- order-dependent flakiness with no useful failure message (assertions just see an empty list). Changes: - Added two autouse fixtures: one no-ops configure_logging for tests that spin up the app via LifespanManager (they test HTTP behavior, not logging output, so they don't need the real thing), one resets structlog defaults after every test as defense in depth. Impact: - Test-only; makes capture_logs()-based assertions reliable regardless of test execution order.
Talie chatbot service
Architecture decisions live in docs/adr. The first implementation
milestone is documented in the ingestion vertical-slice plan.
Provisioning the datastores
Both schema steps run as explicit deployment steps. The application performs no DDL at startup — not for Postgres (ADR-0009) and not for Qdrant (ADR-0001, "Collection provisioning").
docker compose up -d # Postgres, MinIO, Qdrant
uv run alembic upgrade head # Postgres schema
uv run python -m src.cli.qdrant_bootstrap # the `chunks` collection
uv run fastapi dev src/main.py
Before a tenant can upload, its domains must be registered — POST /v1/files
rejects an unregistered or disabled domain with 400. The calling backend
manages them over /v1/domains using a key with the domains:write scope:
curl -X POST http://localhost:8000/v1/domains \
-H "Authorization: Bearer $API_KEY" \
-H 'Content-Type: application/json' \
-d '{"domain": "fire", "display_name": "Fire insurance"}'
Both bootstrap commands are idempotent and safe to re-run. qdrant_bootstrap verifies an
existing collection against the pinned schema and exits non-zero on a mismatch,
rather than leaving a silently degraded sparse index in place.
Local Langfuse
This repo includes a root-level development Compose file for Langfuse:
Start Langfuse locally:
cp .env.langfuse.example .env.langfuse
# edit .env.langfuse and replace CHANGE_ME values
docker compose --env-file .env.langfuse -f docker-compose.langfuse.yml up -d
Open:
http://localhost:3000
If the chatbot app runs on your host machine, configure it with:
LANGFUSE_HOST=http://localhost:3000
If the chatbot app later runs inside the same Compose project/network as Langfuse, configure it with:
LANGFUSE_HOST=http://langfuse-web:3000
A future app stack can be launched together with Langfuse using multiple Compose files:
docker compose \
-f docker-compose.yml \
-f docker-compose.langfuse.yml \
--env-file .env \
--env-file .env.langfuse \
up -d