.env.example

# ===========================
# 🔑 API KEYS & LLM PROVIDERS
# ===========================

# LLM Providers Configuration (JSON format)
# Each provider entry contains: providerName, endpoint, apiKey, desc, and name
# providerName: unique identifier used in model records (e.g., "openai", "deepseek")
# endpoint: API endpoint URL
# apiKey: authentication key for the provider
# desc: description of the provider
# name: display name shown in the UI
LLM_PROVIDERS='[
  {
    "providerName": "openai",
    "endpoint": "https://api.openai.com/v1/",
    "apiKey": "",
    "desc": "OpenAI Official API",
    "name": "OpenAI"
  },
  {
    "providerName": "deepseek",
    "endpoint": "https://api.deepseek.com/",
    "apiKey": "",
    "desc": "DeepSeek API",
    "name": "DeepSeek"
  },
  {
    "providerName": "bielik",
    "endpoint": "http://your-bielik-endpoint:4000/",
    "apiKey": "",
    "desc": "Bielik Institute Hosting",
    "name": "Bielik"
  },
  {
    "providerName": "replicate",
    "endpoint": "https://api.replicate.com/v1/",
    "apiKey": "",
    "desc": "Replicate API",
    "name": "Replicate"
  },
  {
    "providerName": "anthropic",
    "endpoint": "https://api.anthropic.com/v1/",
    "apiKey": "",
    "desc": "Anthropic Claude API",
    "name": "Anthropic"
  },
  {
    "providerName": "google",
    "endpoint": "https://generativelanguage.googleapis.com/v1beta/",
    "apiKey": "",
    "desc": "Google Gemini API",
    "name": "Google"
  },
  {
    "providerName": "fp",
    "endpoint": "",
    "apiKey": "",
    "desc": "Feature Preview Provider",
    "name": "Feature Preview"
  },
  {
    "providerName": "pcss",
    "endpoint": "https://llm.hpc.pcss.pl",
    "apiKey": "",
    "desc": "PCSS HPC LLM Service",
    "name": "PCSS",
    "requireCustomLlmProvider": true
  }
]'

# Model to Provider Mapping (JSON format)
# Maps each model to its provider and defines a unique identifier/alias
# modelName: the actual model name used in API calls (e.g., "gpt-5-mini", "deepseek-chat")
# providerName: must match a providerName from LLM_PROVIDERS
# modelIdentifier: unique alias/identifier for referencing this model in env vars
#                  (e.g., "gpt-5-mini" can be referenced as "openai-gpt5" vs "deepseek-gpt5")
#                  This allows you to use the same model from different providers:
#                  OPENAI_CHAT_MODEL_CURRENT=openai-gpt5
#                  DEEPSEEK_CHAT_MODEL_CURRENT=deepseek-gpt5
#
# Optional model configuration fields:
# supportsToolChoice: false - Indicates model doesn't support automatic tool calling
# assistantsToolChoiceOverride: "none"|"auto"|"required" - Override tool_choice for Assistants API
# assistantsFallbackModel: "model-identifier" - Use another model to decide which tools to call
#                          When set, the fallback model analyzes queries and decides if tools
#                          (code_interpreter, retrieval) are needed, while the main model does
#                          the actual research work. This allows vLLM models without tool support
#                          to benefit from intelligent tool routing via a capable fallback model.
MODEL_PROVIDER_MAP='[
  {
    "modelName": "gpt-5-mini",
    "providerName": "openai",
    "modelIdentifier": "openai-gpt5-mini"
  },
  {
    "modelName": "gpt-5.2",
    "providerName": "openai",
    "modelIdentifier": "openai-gpt5.2"
  },
  {
    "modelName": "gpt-4o-mini-transcribe",
    "providerName": "openai",
    "modelIdentifier": "openai-gpt4o-mini-transcribe"
  },
  {
    "modelName": "claude-3-5-sonnet-20241022",
    "providerName": "anthropic",
    "modelIdentifier": "claude-sonnet-3.5"
  },
  {
    "modelName": "claude-3-opus-20240229",
    "providerName": "anthropic",
    "modelIdentifier": "claude-opus-3"
  },
  {
    "modelName": "claude-3-haiku-20240307",
    "providerName": "anthropic",
    "modelIdentifier": "claude-haiku-3"
  },
  {
    "modelName": "gemini-2.0-flash-exp",
    "providerName": "google",
    "modelIdentifier": "gemini-2.0-flash"
  },
  {
    "modelName": "gemini-1.5-pro",
    "providerName": "google",
    "modelIdentifier": "gemini-1.5-pro"
  },
  {
    "modelName": "gemini-1.5-flash",
    "providerName": "google",
    "modelIdentifier": "gemini-1.5-flash"
  },
  {
    "modelName": "deepseek-chat",
    "providerName": "deepseek",
    "modelIdentifier": "deepseek-chat"
  },
  {
    "modelName": "bielik-11b-v2.3-instruct",
    "providerName": "bielik",
    "modelIdentifier": "bielik-11b-instruct"
  },
  {
    "modelName": "gpt-oss_120b",
    "providerName": "pcss",
    "modelIdentifier": "pcss_gpt-oss_120b",
    "supportsToolChoice": false,
    "assistantsToolChoiceOverride": "none"
  },
  {
    "modelName": "Qwen3-VL-235B-A22B-Instruct",
    "providerName": "pcss",
    "modelIdentifier": "pcss_Qwen3-VL-235B-A22B-Instruct",
    "supportsToolChoice": false,
    "assistantsToolChoiceOverride": "none"
  },
  {
    "modelName": "DeepSeek-V3.1-vLLM",
    "providerName": "pcss",
    "modelIdentifier": "pcss_DeepSeek-V3.1-vLLM",
    "supportsToolChoice": false
  }
]'

# ===========================
# MODEL PROFILE CONFIGURATION
# ===========================

# Which profile to use at startup: legacy/current
MODEL_PROFILE=current

# Backend type: completions or responses
LLM_BACKEND=completions

# Default fallback model for tool choice decisions
# Used when a model has supportsToolChoice=false but no specific assistantsFallbackModel configured
# The fallback model analyzes queries and decides if tools (code_interpreter, retrieval) are needed
DEFAULT_ASSISTANTS_FALLBACK_MODEL=openai-gpt5-mini

# Model profiles are now defined in profiles.json
# Use MODEL_PROFILE to select which profile to use (e.g., current, current_mixed, legacy)
# You can add custom profiles in profiles.json with your preferred model combinations

# ===========================
# EXTERNAL SERVICES API KEYS
# ===========================

# SerpAPI key (required for web search)
SERPAPI_API_KEY=your_serpapi_api_key_here

#Shodan API: used by shodan.Shodan() (required for webSearch)
SHODAN_API_KEY=your_shodan_api_key_here

#NVD (USA GOV)
NVD_API_KEY=your_nvd_api_key_here

#Wpscan Token: 25 scan per day
WPSCAN_API_TOKEN=your_api_token_here

# ===========================
# 🗣️ AUDIO SETTINGS
# ===========================

# Enable speech-to-text (microphone input)
# Set to "true" to use speech_recognition with PyAudio, or "false" to disable microphone input.
ENABLE_LISTEN=false

# Enable text-to-speech (audio output)
# Set to "true" to allow pyttsx3 or playsound3 to speak responses aloud.
ENABLE_SPEAK=true

# Enable clipboard (Read/Write)
ENABLE_CLIPBOARD=true

# Enable screenshot, vision, ocr etc.
ENABLE_VISUAL_PERCEPTION=false

# ===========================
#  LOG SETTINGS
# ===========================

LOG_LEVEL=DEBUG

# ===========================
#  LLM SETTINGS
# ===========================

# Warning Threshold
CONTEXT_WARN_THRESHOLD=0.75

# ===========================
#  Core SETTINGS
# ===========================

REDACT_MODE=off

# User types "redactedIP", ECHO sends "127.0.0.1" to tools/LLM
REDACT_MAP='{"redactedIP": "127.0.0.1", "redactedOrg": "MegaCorp S.A."}'

SHOW_EXTRA_WINDOWS=false

#How many entires will be remembered
HISTORY_ENTRIES_LIMIT=100

# ===========================
#  WEBSOCKET LOG STREAM
# ===========================
# Enable/disable WebSocket log streaming
WEBSOCKET_LOG_ENABLED=false

# Where to bind the WebSocket server
WEBSOCKET_LOG_HOST=127.0.0.1
WEBSOCKET_LOG_PORT=9876