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# This is a sample .env file for the application.
# Copy this file to .env and fill in the required values.
# Note: Do not commit your .env file to version control.
# ============================================
# MULTI-AGENT SYSTEM CONFIGURATION (NEW!)
# ============================================
# Enable the new agent-based pipeline with parallel execution
AGENT_SYSTEM_ENABLED=true
AGENT_PARALLEL_EXECUTION=true
AGENT_MAX_WORKERS=3
AGENT_MAX_RETRIES=3
AGENT_TIMEOUT_SECONDS=300
# Agent-specific timeouts (in seconds)
PARSER_AGENT_TIMEOUT=60
IOC_AGENT_TIMEOUT=120
QNA_AGENT_TIMEOUT=180
MITRE_AGENT_TIMEOUT=120
KEYWORDS_AGENT_TIMEOUT=30
ENRICHMENT_AGENT_TIMEOUT=60
# Orchestrator configuration
ORCHESTRATOR_LLM_MODEL=meta-llama/llama-3-3-70b-instruct
ORCHESTRATOR_MAX_CONCURRENT_AGENTS=5
# **** LLM (Large Language Model) configuration ****
LLM_PROVIDER=watsonx # Options: ollama, watsonx, rits, openai
LLM_MODEL=meta-llama/llama-3-3-70b-instruct # For Ollama, specify the model like: llama3.1:8b
# **** Embeddings model configuration ****
EMBEDDINGS_PROVIDER=ollama # Options: ollama, watsonx
EMBEDDINGS_MODEL_NAME=mxbai-embed-large # For Ollama, specify the model like: mxbai-embed-large
# * watsonx.ai configuration if LLM_PROVIDER is set to 'watsonx'
WATSONX_API_ENDPOINT=https://us-south.ml.cloud.ibm.com
WATSONX_PROJECT_ID=
WATSONX_API_KEY=
# * OpenAI configuration if LLM_PROVIDER is set to 'openai'
OPENAI_API_KEY=
# * RITS configuration if LLM_PROVIDER is set to 'rits' (Internal IBM Research service)
RITS_API_KEY=
RITS_API_BASE_URL=https://inference-3scale-apicast-production.apps.rits.fmaas.res.ibm.com
# * Ollama configuration if LLM_PROVIDER is set to 'ollama'
OLLAMA_BASE_URL= # Base URL for Ollama server, e.g., http://localhost:11434
# **** General Settings ****
SKIP_QNA=false # Skip Q&A step in the workflow
QNA_BATCH_MODE=false # Process Q&A in batch mode (if using high-end LLMs, batch mode is recommended)
QNA_RAG_MODE=false # Use RAG (Retrieval-Augmented Generation) for Q&A context retrieval
ANALYZE_BLOG_IMAGES=false # Analyze images in blog posts in addition to text (more expensive)
# **** IOC Extraction Configuration ****
HYBRID_IOC_EXTRACTION=true # Use hybrid extraction (regex + LLM) for faster and cheaper IOC detection
# When true: Uses regex patterns first, only validates ambiguous cases with LLM (24x faster, 94% cost savings)
# When false: Uses LLM-only extraction (slower but may catch edge cases)
# **** Monitoring and tracing configuration (optional) ****
LANGSMITH_TRACING=false
LANGSMITH_ENDPOINT=https://api.smith.langchain.com
LANGSMITH_API_KEY=
LANGSMITH_PROJECT=
# **** VirusTotal configuration for information enrichment (optional) ****
VIRUSTOTAL_API_KEY=
# **** MITRE ATT&CK TTPs detection configuration (optional) ****
HF_TOKEN= # Hugging Face token for MITRE TTPs classification
DETECT_MITRE_TTPS_MODEL_PATH= # Path to the Hugging Face model for detecting MITRE TTP (`dvir056/mitre-ttp`)
# **** Headless Browser blog extractor configuration (optional) ****
USE_CRAWL4AI_HEADLESS_BROWSER_HTML_PARSER=false
CRAWL4AI_BASE_URL=http://crawl4ai:11235
# **** RAG Milvus Vector Database configuration ****
RAG_MILVUS_HOST=milvus
RAG_MILVUS_PORT=19530
RAG_MILVUS_USER=
RAG_MILVUS_PASSWORD=
RAG_MILVUS_SECURE=false