.env.example

# LLM Environment variables

# Reasoning LLM (for complex reasoning tasks)
# If you're using your local Ollama, replace the model name after the slash and base url then you're good to go.
# For wider model support, read https://docs.litellm.ai/docs/providers.
# REASONING_API_KEY=
# REASONING_BASE_URL=
REASONING_MODEL=qwen-max-latest

# Non-reasoning LLM (for straightforward tasks)
# BASIC_API_KEY=
# BASIC_BASE_URL=
BASIC_MODEL=qwen-max-latest

# CODE_API_KEY=
# CODE_BASE_URL=
CODE_MODEL=deepseek-chat

# VIDEO_MODEL=
# Vision-language LLM (for tasks requiring visual understanding)
# VL_API_KEY=
# VL_BASE_URL=
VL_MODEL=qwen2.5-vl-72b-instruct

# Application Settings
DEBUG=False
APP_ENV=development

# browser is default to False, for it's time consuming
USE_BROWSER=False

# Add other environment variables as needed
# TAVILY_API_KEY=
# JINA_API_KEY= # Optional, default is None



# turn off for collecting anonymous usage information
# ANONYMIZED_TELEMETRY=

# SLACK_USER_TOKEN=

#SILICONFLOW_API_KEY=

# Whether to use the agent of MCP tool, default to False
# MCP_AGENT=True