basic-configuration.md

Basic Configuration

This guide covers only the starter configuration pattern.

For complete options and provider-specific details, use canonical references under user configuration docs.

Goals

• Define one reusable global configuration
• Add one project with one source
• Validate settings before first ingest

Step 1. Create .env

QDRANT_URL=http://localhost:6333
QDRANT_COLLECTION_NAME=my_documents

LLM_PROVIDER=openai
LLM_BASE_URL=https://api.openai.com/v1
LLM_API_KEY=your-openai-key
LLM_EMBEDDING_MODEL=text-embedding-3-small
LLM_CHAT_MODEL=gpt-4o-mini

Step 2. Create config.yaml

global:
  qdrant:
    url: "${QDRANT_URL}"
    collection_name: "${QDRANT_COLLECTION_NAME}"
  llm:
    provider: "${LLM_PROVIDER}"
    base_url: "${LLM_BASE_URL}"
    api_key: "${LLM_API_KEY}"
    models:
      embeddings: "${LLM_EMBEDDING_MODEL}"
      chat: "${LLM_CHAT_MODEL}"
    embeddings:
      vector_size: 1536
  chunking:
    chunk_size: 1500
    chunk_overlap: 200

projects:
  default:
    project_id: "default"
    display_name: "Default Project"
    sources:
      localfile:
        docs:
          base_url: "file://./docs"
          include_paths:
            - "**/*.md"

Step 3. Validate and ingest

qdrant-loader init --workspace .
qdrant-loader ingest --workspace .

What to customize next

• Add more sources (Git/Confluence/Jira): Data Sources Guide
• Tune chunking and global settings: Configuration Reference
• Configure provider-specific LLM details: LLM Provider Guide
• Full variable reference: Environment Variables Reference
• Workspace and config loading modes: Workspace Mode
• Secure credentials and file permissions: Security Considerations
• Validation and common config errors: Troubleshooting
• Multi-environment setup patterns: Common Workflows
• Performance tuning guidance: Performance Issues