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Stirling-PDF/engine/.env
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2026-06-16 16:48:30 +01:00

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###############################################################################
# Environment variables used within the AI Engine.
# Values can be overridden in the uncommitted sibling `.env.local` file.
# Note: This file is committed to Git, so should not contain any private keys.
###############################################################################
# Configure the model strings passed to pydantic-ai. Provider credentials are handled by
# pydantic-ai and should be set using the provider's native environment variables, for example
# ANTHROPIC_API_KEY or OPENAI_API_KEY.
STIRLING_SMART_MODEL=anthropic:claude-haiku-4-5
STIRLING_FAST_MODEL=anthropic:claude-haiku-4-5
# Default output token limits applied by the engine for each model tier.
STIRLING_SMART_MODEL_MAX_TOKENS=8192
STIRLING_FAST_MODEL_MAX_TOKENS=2048
# RAG Configuration — retrieval-augmented generation is always on.
# Embedding provider credentials are handled natively (e.g. VOYAGE_API_KEY for VoyageAI).
STIRLING_RAG_EMBEDDING_MODEL=voyageai:voyage-4
# Vector store backend: "sqlite" (embedded) or "pgvector" (external Postgres).
STIRLING_RAG_BACKEND=sqlite
# Path to the sqlite-vec database file (used when backend=sqlite).
STIRLING_RAG_STORE_PATH=data/rag.db
# Postgres DSN for pgvector (used when backend=pgvector). Leave empty when backend=sqlite.
# Example: postgresql://user:password@host:5432/dbname
STIRLING_RAG_PGVECTOR_DSN=
STIRLING_RAG_CHUNK_SIZE=512
STIRLING_RAG_CHUNK_OVERLAP=64
STIRLING_RAG_TOP_K=20
# Per-run cap on ``search_knowledge`` calls. After this many calls the tool is
# removed from the agent's toolset so it must answer from what it already retrieved
# rather than chain more searches.
STIRLING_RAG_MAX_SEARCHES=5
# Chunked reasoner settings: how big each per-worker slice is (in characters),
# how many workers may run in parallel against the fast model, and how long
# any single worker is allowed to wait for a response before being abandoned.
# Worker timeouts protect gather_notes from upstream model stalls (which
# otherwise hang at the provider's ~10 minute HTTP default); the affected
# slice is dropped and the rest of the document still answers.
STIRLING_CHUNKED_REASONER_CHARS_PER_SLICE=16000
STIRLING_CHUNKED_REASONER_CONCURRENCY=10
STIRLING_CHUNKED_REASONER_WORKER_TIMEOUT_SECONDS=60
# When the rendered slice notes would exceed this many characters, the
# reasoner folds them hierarchically with fast-model calls until they fit.
# This keeps the synthesis prompt under the model's context limit on long
# documents (a 3000-page novel produces ~900k chars of raw notes).
STIRLING_CHUNKED_REASONER_NOTES_CHAR_BUDGET=250000
# Upper bounds on PDF page text the engine will request per extraction round.
STIRLING_MAX_PAGES=200
STIRLING_MAX_CHARACTERS=200000
# PostHog analytics. Set STIRLING_POSTHOG_ENABLED=true and provide an API key to enable.
STIRLING_POSTHOG_ENABLED=false
STIRLING_POSTHOG_API_KEY=phc_VOdeYnlevc2T63m3myFGjeBlRcIusRgmhfx6XL5a1iz
STIRLING_POSTHOG_HOST=https://eu.i.posthog.com
# Log level for the stirling logger hierarchy (DEBUG, INFO, WARNING, ERROR)
STIRLING_LOG_LEVEL=INFO
# Path to log file. Rolls daily, keeps 1 backup. Leave empty for console only.
STIRLING_LOG_FILE=
# Set true to log every outgoing httpx / Anthropic SDK request with timing.
# Use when diagnosing worker stalls: a hung call shows a "Request" line with
# no matching "Response" line. Noisy; leave off in normal use.
STIRLING_HTTP_DEBUG=false