# apps/ai-service configuration — every setting is a field on `Settings` in
# config.py, which is the authority. Copy to `.env` and edit.
#
#   cp apps/ai-service/.env.example apps/ai-service/.env
#
# Values shown are the CODE DEFAULTS from config.py unless marked otherwise.
# Production uses `.env.prod`, which is gitignored and lives on the host.
# Never commit a real secret to this file.
#
# Reference: docs/15-configuration.md


# ─── Operating mode ──────────────────────────────────────────────────────────
# These three decide which runtime graph bootstrap.py builds. See
# docs/10-rag-orchestration.md.

# `cohere-v4` = semantic query embedding against the corpus's own vector space
#               (needs live AWS Bedrock).
# `disabled`  = no retrieval at all. /ready still returns 200 but
#               POST /v1/rag/query returns 503. This is the setting the test
#               suite uses.
# No other value is accepted — bootstrap.py raises at startup.
EMBEDDING_PROVIDER=disabled

# `disabled`         = retrieval-only, single-turn, verbatim source quotes.
#                      No RagAgent, no query understanding, no multi-turn.
# `stub`             = runs the whole answer path (prompt, schema parsing,
#                      grounding, fallback) with NO cloud call.
# `bedrock-converse` = DeepSeek / Qwen / GLM / Nova via the Converse API.
# `bedrock-claude`   = Anthropic via the Messages path.
ANSWER_PROVIDER=disabled

# Bedrock model id for the generation/understanding/entailment calls.
ANSWER_MODEL_ID=deepseek.v3.2


# ─── Vector store ────────────────────────────────────────────────────────────
QDRANT_URL=http://localhost:6333
QDRANT_COLLECTION=duocthu_v1
# Only needed for a Qdrant instance that requires auth. SECRET.
# QDRANT_API_KEY=

# Must match the `dimensions` recorded in the `<collection>__manifest` sidecar,
# or startup fails with ManifestMismatch and the process does not come up.
EMBEDDING_DIMENSIONS=1024

# Score floor for the dense routes only. The deterministic section route is an
# exact payload match and never compares against this.
EVIDENCE_MINIMUM_SCORE=0.12


# ─── PostgreSQL ──────────────────────────────────────────────────────────────
# Retrieval traces, conversation turns, answer feedback. All three writes are
# fail-open: an outage degrades memory/tracing, never an answer. SECRET.
POSTGRES_DSN=postgresql://duoc_thu:duoc_thu@localhost:5432/duoc_thu


# ─── AWS ─────────────────────────────────────────────────────────────────────
# Credentials come from the standard boto3 chain — in production, the EC2
# instance's IAM role. Do NOT put AWS keys in this file.
AWS_REGION=us-east-1

# Optional cross-encoder rerank (cohere.rerank-v3-5:0) on the similarity /
# overview fallback. Fail-open. The section route never reranks.
RERANK_ENABLED=false


# ─── Per-request budget ──────────────────────────────────────────────────────
# Checked BETWEEN provider calls; it cannot cancel a call already in flight
# (that is bounded by read_timeout=20 in adapters/bedrock_converse.py). The
# browser timeout in ChatPanel.tsx is derived from these — raising them without
# raising that will make the client give up first.
MAX_WALL_CLOCK_MS=40000
MAX_LLM_CALLS_PER_TURN=8


# ─── Drug catalog ────────────────────────────────────────────────────────────
# Defaults to a repo-relative path resolved from config.py. The container image
# flattens apps/ai-service/ into its own root, so that default is wrong there
# and .env.prod must set this explicitly (the Dockerfile bakes the file in):
# ENTITIES_PATH=./ingestion_data/drug_entities.json


# ─── Observability ───────────────────────────────────────────────────────────
METRICS_ENABLED=true

# Optional bearer token for GET /metrics. Empty = unauthenticated, which is the
# current production setting and is only safe because ai-service publishes no
# host port and Caddy proxies only `web`. SET THIS before exposing the service
# through an Ingress — metrics carry query volumes, provider failure counts and
# abstain reasons. SECRET.
METRICS_TOKEN=

# Opt-in so a deployment with no collector keeps answering. The Docker and
# Kubernetes observability profiles turn this on.
OTEL_ENABLED=false
OTEL_SERVICE_NAME=ai-service
OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4318/v1/traces
OTEL_SAMPLE_RATIO=1.0


# ─── Misc ────────────────────────────────────────────────────────────────────
APP_NAME=vsf-duoc-thu-ai-service
# Label only; also sent as `deployment.environment` on the OTel resource.
ENVIRONMENT=local