# Docker Spaces > Settings > Secrets
API_TOKEN=replace-with-random-long-secret
# OpenAI-compatible APIs, not local model weights.
# Model IDs below are examples of REAL models on HF Inference Providers;
# check current availability and price in the provider catalog.
FAST_LLM_BASE_URL=https://router.huggingface.co/v1
FAST_LLM_MODEL=openai/gpt-oss-20b:fastest
FAST_LLM_KEY_ENV=HF_TOKEN
STRONG_LLM_BASE_URL=https://router.huggingface.co/v1
STRONG_LLM_MODEL=openai/gpt-oss-120b:fastest
STRONG_LLM_KEY_ENV=HF_TOKEN
# Add HF_TOKEN as a Space SECRET; no credentials in files.
# Supply current provider-specific per-1-million-token prices; never assume example pricing.
FAST_INPUT_USD_PER_1M=
FAST_OUTPUT_USD_PER_1M=
STRONG_INPUT_USD_PER_1M=
STRONG_OUTPUT_USD_PER_1M=
# External retrieval service - POST {query,top_k} -> {documents:[{id,title,text,score}]}
RETRIEVAL_URL=https://your-retriever.example/search
RETRIEVAL_API_KEY=
# Enter per-search retrieval charge, or explicitly set 0 if retrieval is free.
RETRIEVAL_USD_PER_CALL=
# A calibrated table for these particular models and retriever, generated by fit_policy.py
# CALIBRATION_FILE=config/policy.json   # Enable only after uploading calibrated policy.json
ACTIONS_FILE=config/actions.json
MAX_INFLIGHT_REQUESTS=64
HTTP_MAX_CONNECTIONS=128
QUEUE_WAIT_SEC=2
BACKEND_TIMEOUT_SEC=90