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.env.example2.35 kB
# Embedding Model Configuration # Optional: Format is "provider:model_name" or just "model_name" for OpenAI (default) # Examples: # - openai:text-embedding-3-small (default if no provider specified) # - vertex:text-embedding-004 (Google Cloud Vertex AI) # - gemini:gemini-embedding-exp-03-07 (Google Generative AI) # - aws:amazon.titan-embed-text-v1 # - microsoft:text-embedding-ada-002 DOCS_MCP_EMBEDDING_MODEL= # PostHog Analytics Configuration (Optional) # Get your API key from: https://app.posthog.com/project/settings # Leave empty to disable analytics completely POSTHOG_API_KEY= # OpenAI Provider Configuration (Default) # Required for OpenAI provider or as fallback OPENAI_API_KEY=your-key-here # Optional: Your OpenAI Organization ID OPENAI_ORG_ID= # Optional: Custom base URL for OpenAI-compatible APIs (e.g., Ollama, Azure OpenAI) OPENAI_API_BASE= # Google Cloud Vertex AI Configuration # Required for vertex provider: Path to service account JSON key file GOOGLE_APPLICATION_CREDENTIALS=/path/to/gcp-key.json # Google Generative AI (Gemini) Configuration # Required for gemini provider: Google API key GOOGLE_API_KEY=your-google-api-key # AWS Bedrock Configuration # Required for aws provider AWS_ACCESS_KEY_ID=your-aws-key AWS_SECRET_ACCESS_KEY=your-aws-secret AWS_REGION=us-east-1 # Optional: Use BEDROCK_AWS_REGION instead of AWS_REGION if needed # BEDROCK_AWS_REGION=us-east-1 # Azure OpenAI Configuration # Required for microsoft provider AZURE_OPENAI_API_KEY=your-azure-key AZURE_OPENAI_API_INSTANCE_NAME=your-instance AZURE_OPENAI_API_DEPLOYMENT_NAME=your-deployment AZURE_OPENAI_API_VERSION=2024-02-01 # Optional: Specify a custom directory to store the SQLite database file (documents.db). # If set, this path takes precedence over the default locations. # Default behavior (if unset): # 1. Uses './.store/' in the project root if it exists (legacy). # 2. Falls back to OS-specific data directory (e.g., ~/Library/Application Support/docs-mcp-server on macOS). # DOCS_MCP_STORE_PATH=/path/to/your/desired/storage/directory # Optional: Configure embedding batch limits to prevent "413 Request entity too large" errors # Maximum characters per embedding batch (default: 50000 ~50KB) # Lower this if you get 413 errors, increase for better performance if your API supports it # DOCS_MCP_EMBEDDING_BATCH_CHARS=50000

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