# API keys for different providers
OPENAI_API_KEY=
AZURE_OPENAI_API_KEY=
DEEPSEEK_API_KEY=
ANTHROPIC_API_KEY=
GOOGLE_API_KEY=
GROQ_API_KEY=
OPENROUTER_API_KEY=
USE_AWS_BEDROCK=false

#Vertex AI
GOOGLE_APPLICATION_CREDENTIALS=

# Amazon Bedrock Knowledge Base ID
AWS_KB_ID="<knowledge-base-id>"

# Use a fake model for testing
USE_FAKE_MODEL=false

# Set a default model
DEFAULT_MODEL=

# If MODEL is set to "openai-compatible", set the following
# This is just a flexible solution. If you need multiple model options, you still need to add it to models.py
COMPATIBLE_MODEL=
COMPATIBLE_API_KEY=
COMPATIBLE_BASE_URL=

# Web server configuration
HOST=0.0.0.0
PORT=7860

# Authentication secret, HTTP bearer token header is required if set
AUTH_SECRET=
CORS_ORIGINS=http://localhost:3000,http://localhost:8081,http://localhost:5173

# Langsmith configuration
# LANGSMITH_TRACING=true
# LANGSMITH_API_KEY=
# LANGSMITH_PROJECT=default
# LANGSMITH_ENDPOINT=https://api.smith.langchain.com

# Application mode. If the value is "dev", it will enable uvicorn reload
MODE=

# Database type.
# If the value is "postgres", then it will require Postgresql related environment variables.
# If the value is "sqlite", then you can configure optional file path via SQLITE_DB_PATH
DATABASE_TYPE=

# If DATABASE_TYPE=sqlite (Optional)
SQLITE_DB_PATH=

# If DATABASE_TYPE=postgres
# Docker Compose default values (will work with docker-compose setup)
POSTGRES_USER=
POSTGRES_PASSWORD=
POSTGRES_HOST=
POSTGRES_PORT=
POSTGRES_DB=

# you will be able to identify AST connections in Postgres Connection Manager under this Application Name
# POSTGRES_APPLICATION_NAME = "agent-service-toolkit"
# set these values to customize the number of connections in the pool. Saver and store have independent connection pools
# POSTGRES_MIN_CONNECTIONS_PER_POOL=1
# POSTGRES_MAX_CONNECTIONS_PER_POOL= 3

# OpenWeatherMap API key
OPENWEATHERMAP_API_KEY=

# Add for running ollama
# OLLAMA_MODEL=llama3.2
# Note: set OLLAMA_BASE_URL if running service in docker and ollama on bare metal
# OLLAMA_BASE_URL=http://host.docker.internal:11434

# Add for running Azure OpenAI
# AZURE_OPENAI_ENDPOINT=https://your-resource.openai.azure.com
# AZURE_OPENAI_API_VERSION=2024-10-21
# AZURE_OPENAI_DEPLOYMENT_MAP={"gpt-4o": "gpt-4o-deployment", "gpt-4o-mini": "gpt-4o-mini-deployment"}

# Agent URL: used in Streamlit app - if not set, defaults to http://{HOST}:{PORT}
# AGENT_URL=http://localhost:7860

# LANGFUSE Configuration
#LANGFUSE_TRACING=true
#LANGFUSE_PUBLIC_KEY=pk-...
#LANGFUSE_SECRET_KEY=sk-lf-....
#LANGFUSE_HOST=http://localhost:3000

# GitHub MCP Agent Configuration
# GitHub Personal Access Token (required for GitHub MCP server)
# If not set, the GitHub MCP agent will have no tools
GITHUB_PAT=

# Voice Features (Optional)
# NOTE: Voice features are configured on the client (Streamlit app) side, not the server (API).
# Requires OPENAI_API_KEY to be set (see above).
# Set provider name to enable voice input/output. Leave empty to disable.
VOICE_STT_PROVIDER=        # Speech-to-text provider (only 'openai' supported currently)
VOICE_TTS_PROVIDER=        # Text-to-speech provider (only 'openai' supported currently)