# Copy to .env and fill in the keys you use. Do not commit real secrets.
OPENROUTER_API_KEY=

# Default target model:
# MODEL=openrouter/meta-llama/llama-3.3-70b-instruct
# ROUTER_MODEL=openrouter/meta-llama/llama-3.3-70b-instruct
# SOLVER_MODEL=openrouter/meta-llama/llama-3.3-70b-instruct
# ERROR_MODEL=openrouter/meta-llama/llama-3.3-70b-instruct
# VERIFIER_MODEL=openrouter/meta-llama/llama-3.3-70b-instruct
# DISTILLER_MODEL=openrouter/meta-llama/llama-3.3-70b-instruct
#
# Override if OpenRouter changes the model slug:
# OPENROUTER_LLAMA_MODEL=meta-llama/llama-3.3-70b-instruct
# OPENROUTER_BASE_URL=https://openrouter.ai/api/v1

# Other direct-client backends are still supported for local experiments:
GROQ_API_KEY=
# ANTHROPIC_API_KEY=
# OPENAI_API_KEY=

# Optional model routing:
# MODEL and role model env vars are provider/model strings. Examples:
# SOLVER_MODEL=groq/llama-3.3-70b-versatile
# SOLVER_MODEL=openai/gpt-5.4-mini
# VERIFIER_MODEL=anthropic/claude-opus-4-8

# --- Azure AI Foundry / Llama 3.3 70B (legacy optional backend) ---
# AZURE_LLAMA_API_KEY=
# AZURE_LLAMA_BASE_URL=        # endpoint root, e.g. https://.../v1
# AZURE_LLAMA_MODEL=           # model/deployment name shown in Azure

# ENABLE_COMPLETION_VERIFIER=1
# APPWORLD_EXPERIMENT=team_yourname
# APPWORLD_DATASET=dev
# MAX_TASKS=0
# MAX_INTERACTIONS=30
# MAX_MODEL_TURNS=60          # LLM retries/verifier revisions; AppWorld executions use MAX_INTERACTIONS
# OBSERVATION_CHARS=2500       # cap tool output fed back to the model
# OUTPUT_PREVIEW_CHARS=500     # cap console logging only
# VERIFIER_CONTEXT_CHARS=3500  # recent evidence shown to verifier

# --- HydraDB self-improving memory ---
# Get a key from HydraDB and paste it here to enable skill recall + storage.
# Without a key the agent still runs using a local on-disk skill cache only.
HYDRA_DB_API_KEY=
# HYDRA_TENANT_ID=appworld_agentathon
# HYDRA_SUB_TENANT=dev
# HYDRA_RECALL_MODE=fast
# ENABLE_MEMORY=1            # master switch for retrieval + capture
# ENABLE_MEMORY_CAPTURE=1    # store skills after each task during a run
# MEMORY_TOP_K=3             # how many skills to inject into the solver prompt
# MEMORY_CHAR_BUDGET=900     # per-skill char cap in the prompt

# --- Local API-doc snapshot (extra retrieval source) ---
# Injects authoritative API signatures for the task's likely apps from the
# committed assets/api_docs.json snapshot. Regenerate the snapshot with
# `python snapshot_api_docs.py` after an AppWorld version bump.
# ENABLE_API_DOCS=1           # master switch for the snapshot retriever
# API_DOCS_TOP_K=6            # how many API signatures to inject
# API_DOCS_CHAR_BUDGET=2500   # char cap on the injected API-reference block