# ── LLM ──────────────────────────────────────────────────────────────────────
# Optional: leave blank to use the free local sentence-transformers embedder.
# Required only for OpenAI embeddings and GPT-4o-mini generation.
OPENAI_API_KEY=sk-replace-me

# ── Personalised style RAG (private tenant library; not OpenAI fine-tuning) ───
# PERSONALISED_STYLE_RAG_ENABLED=true
# ENABLE_RAG_UPLOAD_SANITISATION=true
# RAG_SANITISATION_USE_LLM=false

# ── Production / HF Space — AI features (prioritise these) ───────────────────
# User-facing AI: inspector tool loop, section generation, photo vision, proofread/enhance.
# On Hugging Face Spaces (SPACE_ID set), ingest LLM sanitisation is auto-disabled.
# PRODUCTION_AI_PROFILE=true
# CHAT_MODEL=gpt-4o-mini
# INSPECTOR_TOOL_AGENT=true
# INSPECTOR_BODY_MODEL=gpt-4o-mini
# AGENTIC_INSPECTOR_WHEN_NOTES_ONLY=true
# SECTION_PHOTO_VISION_ENABLED=true
# SECTION_PHOTO_ANALYZE_ON_UPLOAD=true
# SECTION_PHOTO_VISION_MODEL=gpt-4o
# PRIMARY_GENERATE_PIPELINE=agentic
# Dev-only infra (leave off on HF unless you run workers locally):
# ENABLE_JOB_QUEUE=false
# ENABLE_TEMPORAL_WORKFLOW=false
# REDIS_URL=
# ENABLE_RAG_UPLOAD_SANITISATION=true
# RAG_SANITISATION_USE_LLM=false
# HF_TOKEN=   # optional: faster embedding model download on Space boot

# ── Vector store (FAISS default; optional Qdrant for async pipeline) ─────────
# Defaults to ~/.report_genius/faiss_index (cross-platform)
# FAISS_INDEX_PATH=~/.report_genius/faiss_index
# VECTORSTORE_BACKEND=faiss
# QDRANT_URL=http://localhost:6333
# QDRANT_API_KEY=
# QDRANT_COLLECTION=rics_chunks
# QDRANT_CACHE_COLLECTION=rics_semantic_cache
# ENABLE_HYBRID_RETRIEVAL=true
# SEMANTIC_CACHE_ENABLED=true
# SEMANTIC_CACHE_TTL_HOURS=24
# SEMANTIC_CACHE_SIMILARITY_THRESHOLD=0.92

# ── AI phases (see docs/AI_FEATURES_PHASES.md) ───────────────────────────────
# Phase 1: core RAG generate (OPENAI_API_KEY, personalised RAG, sanitisation)
# Phase 2: inspector + vision (INSPECTOR_TOOL_AGENT, AGENTIC_INSPECTOR_WHEN_NOTES_ONLY)
# Phase 3: async LLM, speculation, prompt cache, optional Qdrant hybrid/cache
#
# ── Backend scale (NOT an AI phase; not for HF Spaces) ─────────────────────────
# SCALE_OPTIMIZATION_PROFILE turns on AI Phase 3 flags + job queue when REDIS_URL set.
# SCALE_OPTIMIZATION_PROFILE=false
# SCALE_OPTIMIZATION_PROFILE=true
# REDIS_URL=redis://localhost:6379/0
# docker compose --profile redis --profile jobs up -d

# ── Async pipeline (latency / scale; default off — backward compatible) ─────
# ENABLE_ASYNC_PIPELINE=false
# MAX_CONCURRENT_LLM_CALLS=10

# ── AI Phase 3 flags (requires ENABLE_ASYNC_PIPELINE for speculation + prompt cache) ─
# ENABLE_SPECULATIVE_EXECUTOR=false
# ENABLE_PROMPT_CACHING=false
# PROMPT_CACHE_MIN_SYSTEM_TOKENS=1024
# SPECULATIVE_CONTEXT_WINDOW=3
# SPECULATIVE_PROBABILITY_THRESHOLD=0.75
# SPECULATIVE_LEARN_MIN_OBSERVATIONS=5
# ALLOW_SQLITE_PARALLEL_SECTIONS=false
# AGENTIC_INSPECTOR_WHEN_NOTES_ONLY=true
# NOTES_ONLY_GENERATION=true

# ── Backend: Redis rate limits + job queue (not an AI phase) ─────────────────
# REDIS_URL=redis://localhost:6379/0
# ENABLE_JOB_QUEUE=false
# JOB_QUEUE_KEY=rics:jobs:generation
# JOB_QUEUE_BLOCK_SECONDS=5
# JOB_QUEUE_MAX_CONCURRENT=2
# With ENABLE_JOB_QUEUE=true, run: python jobs_worker.py
# Docker: docker compose --profile redis --profile jobs up -d

# ── Temporal durable workflows (optional; docker compose --profile temporal) ───
# ENABLE_TEMPORAL_WORKFLOW=false
# TEMPORAL_HOST=localhost:7233
# TEMPORAL_NAMESPACE=default
# TEMPORAL_TASK_QUEUE=reports
# GENERATION_SLA_SECONDS=600
# GENERATION_TIMEOUT_SECONDS=720
# GENERATION_STALE_SWEEP_SECONDS=120

# ── RAG upload sanitisation (dev/staging only — competes with generation OpenAI quota) ─
# ENABLE_RAG_UPLOAD_SANITISATION=true
# RAG_SANITISATION_USE_LLM=false
# RAG_SANITISATION_SKIP_KB_TENANT=true
# RAG_SANITISATION_CHUNK_CHARS=20000
# RAG_SANITISATION_MAX_OUTPUT_TOKENS=4096
# RAG_SANITISATION_FAIL_CLOSED=true

# ── Database ──────────────────────────────────────────────────────────────────
DATABASE_URL=sqlite+aiosqlite:///./dev.db

# ── File storage (defaults are cross-platform, override if needed) ────────────
# UPLOAD_DIR=~/.report_genius/uploads

# ── Cache ─────────────────────────────────────────────────────────────────────
# CACHE_DIR=/tmp/section_cache

# ── LLM generation limits ─────────────────────────────────────────────────────
MAX_CONTEXT_TOKENS=400
MAX_OUTPUT_TOKENS=300
# OpenAI embedding model (only used when OPENAI_API_KEY is set)
EMBEDDING_MODEL=text-embedding-3-small
# Local sentence-transformers model (used when no OPENAI_API_KEY is set)
# Options: all-MiniLM-L6-v2 (384-dim, fast), all-mpnet-base-v2 (768-dim, better quality)
LOCAL_EMBEDDING_MODEL=all-MiniLM-L6-v2
CHAT_MODEL=gpt-4o-mini

# Optional: extra LLM compliance validator (PASS/FAIL + reasons) after generation.
# Runs only when OPENAI_API_KEY is set; regenerates once with feedback on FAIL.
# LLM_SECTION_VALIDATOR_ENABLED=false
# LLM_SECTION_VALIDATOR_MAX_RETRIES=1

# Autonomous RICS inspector (agentic): OpenAI tool-calling so the model chooses RAG/KB/duplicate tools.
# Requires OPENAI_API_KEY. Set false to force the legacy fixed pipeline.
# INSPECTOR_TOOL_AGENT=true
# INSPECTOR_MAX_TOOL_ROUNDS=12

# Retrieval
RETRIEVAL_TOP_K=10
RERANK_TOP_N=3
CHUNK_SIZE=500
CHUNK_OVERLAP=75

# Hierarchical RAG (document → section → paragraph). Re-ingest PDFs after enabling if the index predates hierarchy.
# HIERARCHICAL_RAG_ENABLED=true
# HIERARCHICAL_K_DOCUMENT=4
# HIERARCHICAL_K_SECTION=8
# HIERARCHICAL_K_PARAGRAPH_POOL=36
# Comma-separated upload UUIDs for template/exemplar RICS PDFs (always in routing universe), e.g. Behrang RICS reference:
# RICS_EXEMPLAR_DOCUMENT_IDS=

# Standard paragraphs: .docx/.docm read directly; legacy .doc converted (pandoc | LibreOffice | Word+pywin32).
# Default file: Behrang RICS Documents/HB-BS STANDARD PARAS v6 Sept 2015.doc — or place any supported format at repo root with same basename.
# RICS_STANDARD_PARAGRAPHS_DOCX=Behrang RICS Documents/HB-BS STANDARD PARAS v6 Sept 2015.doc
# Leave empty to fall back to glob discovery under KNOWLEDGE_BASE_DIRS instead:
# RICS_STANDARD_PARAGRAPHS_DOCX=
# STANDARD_PARAGRAPHS_DOCX_GLOBS=*standard*paragraph*.docx,*Standard*Paragraph*.docx

# ── Bulk upload & batch processing ────────────────────────────────────────────
# Max logical documents per single POST /upload/batch request (after ZIP expansion)
# MAX_UPLOAD_BATCH_FILES=2000
# Max compressed bytes for a .zip in a batch upload
# MAX_ARCHIVE_UPLOAD_BYTES=524288000   # 500 MB
# Max entries (files) inside one ZIP archive
# MAX_ZIP_MEMBERS=50000
# Max declared uncompressed total bytes in one ZIP (zip-bomb guard)
# MAX_ZIP_UNCOMPRESSED_BYTES=5368709120  # 5 GB
# Parallel ingestion pipelines — each uses embedding + vector-store threads
# MAX_CONCURRENT_INGESTS=16
# Max document IDs per POST /documents/batch-status request
# MAX_BATCH_STATUS_DOCUMENT_IDS=10000
# Max rows returned by GET /documents
# DOCUMENTS_LIST_MAX_LIMIT=500

# ── Section photo policy (tenant RAG uploads only; no letter heuristics) ───
# Scans completed PDF/DOCX in the tenant library for images under each RICS section heading.
# Optional JSON overrides per section: REQUIRES_IMAGE | OPTIONAL_IMAGE | NO_IMAGE_NEEDED
# SECTION_PHOTO_POLICY_OVERRIDES_JSON=
# SECTION_PHOTO_POLICY_DATA_DRIVEN=true
# SECTION_PHOTO_POLICY_MIN_EXAMPLES=3
# Fraction of uploads (where the section appears) that must contain a section image (1.0 = all)
# SECTION_PHOTO_POLICY_TENANT_CONSENSUS_RATIO=1.0

# ── Security ─────────────────────────────────────────────────────────────────
TENANT_SECRET_KEY=change-me-in-production
DEV_MODE=true
# CORS: comma-separated list of allowed origins. Default ["*"] (open).
# In production set to your frontend URL, e.g.: ALLOWED_ORIGINS=["https://app.example.com"]
# ALLOWED_ORIGINS=["*"]