Environment Variables

Complete guide to configuring DeepWiki-Open environment variables for all supported AI providers and features

DeepWiki-Open uses environment variables to configure AI providers, server settings, authentication, and advanced features. This guide covers all available environment variables and their usage.

Required Environment Variables

At minimum, you need API keys for at least one AI provider:

Minimal Setup

# Choose ONE of these AI providers
GOOGLE_API_KEY=your_google_api_key_here
# OR
OPENAI_API_KEY=your_openai_api_key_here

# AI Provider API Keys (choose at least one)
GOOGLE_API_KEY=your_google_api_key_here
OPENAI_API_KEY=your_openai_api_key_here
OPENROUTER_API_KEY=your_openrouter_api_key_here

# Azure OpenAI (Enterprise)
AZURE_OPENAI_API_KEY=your_azure_openai_api_key_here
AZURE_OPENAI_ENDPOINT=https://your-resource.openai.azure.com
AZURE_OPENAI_VERSION=2024-02-15-preview

# AWS Bedrock
AWS_ACCESS_KEY_ID=your_aws_access_key
AWS_SECRET_ACCESS_KEY=your_aws_secret_key
AWS_REGION=us-east-1

# Local/Self-Hosted Models
OLLAMA_HOST=http://localhost:11434
OPENAI_BASE_URL=https://api.openai.com/v1

# Server Configuration
PORT=8001
SERVER_BASE_URL=http://localhost:8001

# Authorization & Security
DEEPWIKI_AUTH_MODE=false
DEEPWIKI_AUTH_CODE=your_secret_code_here

# Logging & Debugging
LOG_LEVEL=INFO
LOG_FILE_PATH=./api/logs/application.log

# Advanced Configuration
DEEPWIKI_CONFIG_DIR=./api/config
REDIS_URL=redis://localhost:6379

AI Provider Configuration

Google Gemini

Google AI Studio API key for Gemini models.

How to get:

1. Visit Google AI Studio
2. Click “Create API Key”
3. Copy the generated key

Supported models:

• gemini-2.0-flash (default, recommended)
• gemini-1.5-flash
• gemini-1.0-pro

Google Gemini offers generous free tier limits and excellent performance for documentation generation.

OpenAI

OpenAI API key for GPT models.

Custom OpenAI API endpoint (for OpenAI-compatible services).

How to get:

1. Visit OpenAI Platform
2. Create new secret key
3. Copy the key (starts with sk-)

Supported models:

• gpt-4o (default)
• gpt-4.1
• o1
• o3
• o4-mini

OpenAI requires a paid account. Free tier users cannot access the API.

OpenRouter

OpenRouter API key for access to multiple model providers.

How to get:

1. Sign up at OpenRouter
2. Go to Keys section
3. Create new API key

Available models:

• openai/gpt-4o
• anthropic/claude-3.5-sonnet
• deepseek/deepseek-r1
• google/gemini-pro
• And 100+ more models

OpenRouter provides access to multiple AI providers through a single API, perfect for comparing models.

Azure OpenAI

Azure OpenAI service API key.

Your Azure OpenAI resource endpoint URL.

API version (e.g., 2024-02-15-preview).

How to get:

1. Create Azure OpenAI resource in Azure Portal
2. Deploy a model (GPT-4, GPT-3.5-turbo, etc.)
3. Get endpoint and API key from resource overview
4. Note the API version from the deployment

Example configuration:

AZURE_OPENAI_API_KEY=abc123def456ghi789
AZURE_OPENAI_ENDPOINT=https://my-resource.openai.azure.com
AZURE_OPENAI_VERSION=2024-02-15-preview

AWS Bedrock

AWS access key for Bedrock access.

AWS secret access key.

AWS region where Bedrock models are available.

Supported models:

• anthropic.claude-3-sonnet-20240229-v1:0
• anthropic.claude-3-haiku-20240307-v1:0
• anthropic.claude-3-opus-20240229-v1:0
• amazon.titan-text-express-v1

Ollama (Local Models)

Ollama server URL for local AI models.

Setup Ollama:

macOS

# Install Ollama
curl -fsSL https://ollama.ai/install.sh | sh

# Start service
ollama serve

# Pull a model
ollama pull llama3:8b

Linux

# Install Ollama  
curl -fsSL https://ollama.ai/install.sh | sh

# Start as service
sudo systemctl start ollama
sudo systemctl enable ollama

# Pull a model
ollama pull qwen3:8b

Docker

# Run Ollama in container
docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama

# Pull a model
docker exec -it ollama ollama pull llama3:8b

Supported models:

• qwen3:1.7b (lightweight)
• llama3:8b (balanced)
• qwen3:8b (high context)

DashScope (Alibaba)

Alibaba DashScope API key for Qwen models.

How to get:

1. Sign up at DashScope
2. Create API key in console
3. Add key to environment

Supported models:

• qwen-plus
• qwen-turbo
• deepseek-r1

Server Configuration

Port for the FastAPI backend server.

Base URL for API server (used by frontend).

Environment mode (development, production, test).

Example server configuration:

PORT=8002
SERVER_BASE_URL=https://api.deepwiki.example.com
NODE_ENV=production

Security & Authentication

Authorization Mode

Enable authorization requirement for wiki generation.

Secret code required when authorization mode is enabled.

Usage:

DEEPWIKI_AUTH_MODE=true
DEEPWIKI_AUTH_CODE=my-secret-code-123

When enabled, users must enter the auth code to generate wikis.

Authorization mode provides basic frontend protection but doesn’t secure direct API access.

Logging & Debugging

Logging verbosity level.

Options: DEBUG, INFO, WARNING, ERROR, CRITICAL

Path for log file output.

Example logging configuration:

LOG_LEVEL=DEBUG
LOG_FILE_PATH=./logs/deepwiki-debug.log

In production, use INFO or WARNING level to reduce log volume.

Advanced Configuration

Directory containing configuration JSON files.

Redis connection URL for caching (optional).

Example:

DEEPWIKI_CONFIG_DIR=/custom/config/path
REDIS_URL=redis://localhost:6379/0

Environment File Templates

Development

.env.development

# Development Environment
NODE_ENV=development
LOG_LEVEL=DEBUG
LOG_FILE_PATH=./api/logs/development.log

# Server Config
PORT=8001
SERVER_BASE_URL=http://localhost:8001

# API Keys
GOOGLE_API_KEY=your_development_google_key
OPENAI_API_KEY=your_development_openai_key

# Local Ollama
OLLAMA_HOST=http://localhost:11434

# No authentication for dev
DEEPWIKI_AUTH_MODE=false

Production

.env.production

# Production Environment  
NODE_ENV=production
LOG_LEVEL=INFO
LOG_FILE_PATH=/var/log/deepwiki/application.log

# Server Config
PORT=8001
SERVER_BASE_URL=https://api.yourdomain.com

# Production API Keys
GOOGLE_API_KEY=your_production_google_key
OPENAI_API_KEY=your_production_openai_key
AZURE_OPENAI_API_KEY=your_azure_key
AZURE_OPENAI_ENDPOINT=https://your-resource.openai.azure.com
AZURE_OPENAI_VERSION=2024-02-15-preview

# Enable authentication
DEEPWIKI_AUTH_MODE=true
DEEPWIKI_AUTH_CODE=your_secure_production_code

# Redis caching
REDIS_URL=redis://redis-server:6379/0

Docker

.env.docker

# Docker Environment
NODE_ENV=production
LOG_LEVEL=INFO

# Container networking
PORT=8001
SERVER_BASE_URL=http://deepwiki-api:8001

# API Keys
GOOGLE_API_KEY=your_google_key
OPENAI_API_KEY=your_openai_key

# External Ollama
OLLAMA_HOST=http://ollama-server:11434

# Persistent data
LOG_FILE_PATH=/app/logs/application.log
DEEPWIKI_CONFIG_DIR=/app/config

Validation & Testing

1. Validate Environment

   # Check environment variables are loaded
   python -c "
   import os
   from dotenv import load_dotenv
   load_dotenv()
   
   # Check API keys
   providers = {
       'Google': os.getenv('GOOGLE_API_KEY'),
       'OpenAI': os.getenv('OPENAI_API_KEY'),
       'OpenRouter': os.getenv('OPENROUTER_API_KEY'),
       'Azure': os.getenv('AZURE_OPENAI_API_KEY'),
   }
   
   for name, key in providers.items():
       status = '✓ Configured' if key else '✗ Missing'
       print(f'{name}: {status}')
   "
   
2. Test API Connections

   # Test backend startup
   python -m api.main
   
   # Check for successful startup messages
   # Look for: "Starting Streaming API on port 8001"
   # No API key warnings for your configured providers
   
3. Verify Frontend Connection

   # Start frontend
   npm run dev
   
   # Test API connection at http://localhost:3000
   # Model selection should show your configured providers
   

Security Best Practices

API Key Security

• Never commit .env files to version control
• Use different API keys for development and production
• Regularly rotate API keys
• Monitor API usage for unexpected activity
• Use environment-specific keys when possible

Production Security

# Secure file permissions
chmod 600 .env

# Use secrets management in production
# - AWS Secrets Manager
# - Azure Key Vault  
# - Kubernetes secrets
# - Docker secrets

Network Security

• Use HTTPS in production
• Configure proper CORS settings
• Use private networks for internal components
• Enable authorization mode for public deployments

Troubleshooting

Environment Variables Not Loading

Symptoms: API key errors, default values used

Solutions:

1. Verify .env file is in project root
2. Check file permissions (readable by application)
3. Ensure no syntax errors in .env file
4. Restart application after changes

API Key Validation Errors

Symptoms: “Invalid API key” errors

Solutions:

1. Test API keys with provider’s documentation
2. Check for extra spaces or characters
3. Verify key has correct permissions/scopes
4. Confirm key hasn’t expired or been revoked

Port Conflicts

Symptoms: “Port already in use” errors

Solutions:

1. Change PORT environment variable
2. Kill existing processes on the port
3. Use Docker with port mapping
4. Configure reverse proxy

Next Steps

Model Provider Setup

Configure specific AI model providers and their settings

Production Deployment

Deploy DeepWiki with production-ready configuration

Configuration Files

Learn about JSON configuration files for advanced customization

Security Guide

Implement security best practices for production deployments