scrapeRL / .env.example
NeerajCodz's picture
docs: init proto
24f0bf0
# app-identity
APP_NAME=ScrapeRL
APP_VERSION=0.1.0
# server-runtime
DEBUG=false
LOG_LEVEL=INFO
HOST=0.0.0.0
PORT=8000
RELOAD=false
WORKERS=1
# cors
CORS_ORIGINS=["http://localhost:5173","http://localhost:3000"]
CORS_ALLOW_CREDENTIALS=true
CORS_ALLOW_METHODS=["*"]
CORS_ALLOW_HEADERS=["*"]
# llm-provider-keys
OPENAI_API_KEY=
ANTHROPIC_API_KEY=
GOOGLE_API_KEY=
GEMINI_API_KEY=
GROQ_API_KEY=
NVIDIA_API_KEY=
NVIDIA_BASE_URL=https://integrate.api.nvidia.com/v1
# model-defaults
DEFAULT_MODEL=gpt-4o-mini
DEFAULT_TEMPERATURE=0.7
MAX_TOKENS=4096
# search-provider-keys
GOOGLE_SEARCH_API_KEY=
GOOGLE_SEARCH_ENGINE_ID=
BING_SEARCH_API_KEY=
# embeddings
GEMINI_MODEL_EMBEDDING=models/gemini-embedding-2-preview
# storage-and-memory
CHROMA_PERSIST_DIRECTORY=./data/chroma
CHROMA_COLLECTION_NAME=scraperl_memory
SHORT_TERM_MEMORY_SIZE=100
WORKING_MEMORY_SIZE=20
LONG_TERM_MEMORY_TOP_K=10
SESSION_TIMEOUT=3600
MEMORY_TTL=86400
# episode-and-browser
MAX_STEPS_PER_EPISODE=50
DEFAULT_TIMEOUT_SECONDS=30
HEADLESS_BROWSER=true
BROWSER_TIMEOUT_MS=30000
# reward-weights
REWARD_ACCURACY_WEIGHT=0.4
REWARD_EFFICIENCY_WEIGHT=0.2
REWARD_COST_WEIGHT=0.2
REWARD_COMPLETENESS_WEIGHT=0.2
# runtime-flags
SCRAPERL_DISABLE_LIVE_LLM=0
# inferencepy-required
HF_TOKEN=
API_BASE_URL=https://api.openai.com/v1
MODEL_NAME=gpt-4.1-mini
# inferencepy-optional-runtime
ENV_API_BASE_URL=http://localhost:8000/api
TASK_NAME=task_001
BENCHMARK=openenv
MAX_STEPS=12
EPISODE_SEED=42
LLM_TEMPERATURE=0.0
PROMPT_HTML_LIMIT=5000
REQUEST_TIMEOUT_SECONDS=30
USE_OPENENV_SDK=true