# ── Debugging ──────────────────────────────────────────────────────────────
# Set to true to enable debug logging and SQLAlchemy echo
DEBUG=false

# ── LLM (OpenAI-compatible) ────────────────────────────────────────────────
LLM_BASE_URL=http://host.docker.internal:11434/v1
LLM_MODEL=llama
# Leave empty for local servers like Ollama / llama.cpp
LLM_API_KEY=

# ── AI Agent ────────────────────────────────────────────────────────────────
# Model used by pydantic-ai for agent reasoning (e.g. gpt-4o, claude-sonnet-4)
AI_MODEL=gpt-4o

# ── Embeddings ─────────────────────────────────────────────────────────────
# If EMBEDDING_BASE_URL is empty, the LLM base URL is used instead
EMBEDDING_BASE_URL=http://host.docker.internal:11434/v1
EMBEDDING_API_KEY=

# ── Observability ──────────────────────────────────────────────────────────
# Set LOGFIRE_TOKEN to enable Logfire telemetry; omit to disable
LOGFIRE_TOKEN=

# ── PostgreSQL ─────────────────────────────────────────────────────────────
DATABASE_URL=postgresql+asyncpg://agent_alpha:agent_alpha@postgres:5432/agent_alpha

# ── Valkey / Redis (cache + chat persistence, also used for RAG status SSE) ─
VALKEY_URL=redis://valkey:6379/0

# ── Milvus (vector database for RAG) ───────────────────────────────────────
MILVUS_URI=http://localhost:19530
MILVUS_TOKEN=

# ── File / Media Storage ──────────────────────────────────────────────────
MEDIA_DIR=media
MAX_UPLOAD_SIZE_MB=50

# ── RAG Parser ─────────────────────────────────────────────────────────────
PDF_PARSER=pymupdf

# ── Cross-Encoder Reranker ─────────────────────────────────────────────────
CROSS_ENCODER_MODEL=cross-encoder/ms-marco-MiniLM-L6-v2
HF_TOKEN=
MODELS_CACHE_DIR=~/.cache/agent-alpha/models

# ── RAG Image Description ──────────────────────────────────────────────────
# Model to use for describing images in RAG documents (empty = disabled)
RAG_IMAGE_DESCRIPTION_MODEL=