# Docling-Graph environment variables
#
# Copy this file to `.env` and fill in only the values for the provider(s)
# you use. Local inference (vLLM, Ollama, LM Studio) needs none of this.
# See docs/fundamentals/installation/api-keys.md for full setup details.

# --- OpenAI ---
OPENAI_API_KEY=

# --- Mistral AI ---
MISTRAL_API_KEY=

# --- Google Gemini ---
GEMINI_API_KEY=

# --- IBM watsonx ---
WATSONX_API_KEY=
WATSONX_PROJECT_ID=
WATSONX_URL=

# --- Amazon Bedrock (AWS credential chain; install with docling-graph[bedrock]) ---
# Region is required. Use either static keys or AWS_PROFILE / AWS_BEARER_TOKEN_BEDROCK
# instead of the access/secret key pair below.
AWS_ACCESS_KEY_ID=
AWS_SECRET_ACCESS_KEY=
AWS_REGION_NAME=

# --- Custom / on-prem OpenAI-compatible endpoint ---
CUSTOM_LLM_BASE_URL=
CUSTOM_LLM_API_KEY=

# --- LM Studio (optional, only if the server requires auth or a non-default URL) ---
LM_STUDIO_API_BASE=
LM_STUDIO_API_KEY=

# --- vLLM / Ollama (optional, only if servers run on a non-default host/port) ---
VLLM_BASE_URL=
OLLAMA_BASE_URL=

# --- docling-serve (optional; delegates document conversion to a remote
# docling-serve instance instead of converting locally) ---
DOCLING_SERVE_URL=
DOCLING_SERVE_API_KEY=