Configuration File Reference

This comprehensive reference covers all configuration options available in QDrant Loader's YAML configuration files. QDrant Loader uses a multi-project configuration structure that allows you to organize multiple data sources into logical projects within a single workspace.

🎯 Overview

QDrant Loader supports YAML configuration files for managing settings in a structured, version-controllable format. The configuration follows a multi-project architecture where:

Global settings apply to all projects (embedding, chunking, state management)
Project-specific settings define data sources and project metadata
All projects share the same QDrant collection for unified search

Configuration Structure

# Multi-project configuration structure
global:
  # Global settings for all projects
  qdrant: {}
  llm: {}
  chunking: {}
  state_management: {}
  file_conversion: {}

projects:
  # Project definitions
  project-1:
    project_id: "project-1"
    display_name: "Project One"
    description: "Project description"
    sources: {}
  project-2:
    project_id: "project-2"
    display_name: "Project Two"
    description: "Another project"
    sources: {}

Configuration Priority

1. Command-line arguments (highest priority)
2. Environment variables
3. Configuration file ← This guide
4. Default values (lowest priority)

📁 Basic Configuration File

Minimal Configuration

# config.yaml - Minimal multi-project configuration
global:
  qdrant:
    url: "http://localhost:6333"
    collection_name: "documents"
  # New unified LLM configuration (provider-agnostic)
  llm:
    provider: ${LLM_PROVIDER}              # openai | ollama | openai_compat | custom
    base_url: ${LLM_BASE_URL}              # e.g. https://api.openai.com/v1, http://localhost:11434/v1
    api_key: ${LLM_API_KEY}                # optional for local providers like Ollama
    models:
      embeddings: ${LLM_EMBEDDING_MODEL}   # e.g. text-embedding-3-small | nomic-embed-text | bge-small-en-v1.5
      chat: ${LLM_CHAT_MODEL}              # e.g. gpt-4o-mini | llama3.1:8b-instruct
    tokenizer: cl100k_base                 # cl100k_base | none
    embeddings:
      vector_size: 1536                    # set according to chosen embedding model

projects:
  my-project:
    project_id: "my-project"
    display_name: "My Project"
    description: "Basic project setup"
    sources:
      git:
        my-repo:
          base_url: "https://github.com/user/repo.git"
          branch: "main"
          token: "${REPO_TOKEN}"
          file_types:
            - "*.md"
            - "*.txt"

Complete Configuration Template

# config.yaml - Complete multi-project configuration template (abridged)
global:
  qdrant:
    url: "http://localhost:6333"
    api_key: "${QDRANT_API_KEY}"
    collection_name: "documents"
  llm:
    provider: ${LLM_PROVIDER}
    base_url: ${LLM_BASE_URL}
    api_key: ${LLM_API_KEY}
    api_version: ${LLM_API_VERSION}  # Required for azure_openai
    headers: {}
    models:
      embeddings: ${LLM_EMBEDDING_MODEL}
      chat: ${LLM_CHAT_MODEL}
    tokenizer: cl100k_base
    request:
      timeout_s: 30
      max_retries: 3
      backoff_s_min: 1
      backoff_s_max: 30
    rate_limits:
      rpm: 1800
      tpm: 2000000
      concurrency: 5
    embeddings:
      vector_size: 1536
    provider_options:
      azure_endpoint: ${AZURE_OPENAI_ENDPOINT}
      native_endpoint: auto

> Azure OpenAI notes:
> - Use the resource root for `base_url`, e.g. `https://<resource>.openai.azure.com` (do not include `/openai/deployments/...`).
> - Set `api_version` (e.g., `2024-05-01-preview`).
> - `models.embeddings` and `models.chat` should be Azure deployment names.

> Ollama notes:
> - If your server exposes OpenAI-compatible `/v1`, set `base_url` to include `/v1` and we will call `/v1/embeddings` and parse `data[].embedding`.
> - In native mode (no `/v1`), we try batch `POST /api/embed` first and parse `{ "embeddings": [[...], ...] }`. If unsupported (404/405/501), we fall back to per-item `POST /api/embeddings` and parse `{ "embedding": [...] }` or `{ "data": { "embedding": [...] } }`.
> - You can override detection with `global.llm.provider_options.native_endpoint: embed | embeddings | auto` (default: auto).

### Troubleshooting

- Azure 404 or 400 with deployment path
  - Symptom: 404 Not Found or confusing errors when calling embeddings/chat
  - Cause: `base_url` incorrectly includes `/openai/deployments/...`
  - Fix: Use resource root `https://<resource>.openai.azure.com` and set `models.*` to deployment names; include `api_version` (e.g., `2024-05-01-preview`).

- Ollama empty or invalid embeddings
  - Symptom: Empty vectors or key errors parsing response
  - Cause: Server endpoint mismatch (`/api/embed` vs `/api/embeddings`)
  - Fix: Set `provider_options.native_endpoint` to `embed` or `embeddings`, or rely on auto-detection.
  chunking:
    chunk_size: 1500
    chunk_overlap: 200
    max_chunks_per_document: 500
    strategies:
      default:
        min_chunk_size: 100
        enable_semantic_analysis: true
        enable_entity_extraction: true
      html:
        simple_parsing_threshold: 100000
        max_html_size_for_parsing: 500000
        max_sections_to_process: 200
        max_chunk_size_for_nlp: 20000
        preserve_semantic_structure: true
      code:
        max_file_size_for_ast: 75000
        max_elements_to_process: 800
        max_recursion_depth: 8
        max_element_size: 20000
        enable_ast_parsing: true
        enable_dependency_analysis: true
      json:
        max_json_size_for_parsing: 1000000
        max_objects_to_process: 200
        max_chunk_size_for_nlp: 20000
        max_recursion_depth: 5
        max_array_items_per_chunk: 50
        max_object_keys_to_process: 100
        enable_schema_inference: true
      markdown:
        min_content_length_for_nlp: 100
        min_word_count_for_nlp: 20
        min_line_count_for_nlp: 3
        min_section_size: 500
        max_chunks_per_section: 1000
        max_overlap_percentage: 0.25
        max_workers: 4
        estimation_buffer: 0.2
        words_per_minute_reading: 200
        header_analysis_threshold_h1: 3
        header_analysis_threshold_h3: 8
        enable_hierarchical_metadata: true
  semantic_analysis:
    num_topics: 3
    lda_passes: 10
    spacy_model: "en_core_web_md"
  state_management:
    database_path: "${STATE_DB_PATH}"
    table_prefix: "qdrant_loader_"
    connection_pool:
      size: 5
      timeout: 30
  file_conversion:
    max_file_size: 52428800
    conversion_timeout: 300
    markitdown:
      enable_llm_descriptions: false
      llm_model: "gpt-4o"
      llm_endpoint: "https://api.openai.com/v1"
      llm_api_key: "${OPENAI_API_KEY}"

projects:
  docs-project:
    project_id: "docs-project"
    display_name: "Documentation Project"
    description: "Company documentation and guides"
    sources:
      git:
        docs-repo:
          base_url: "https://github.com/company/docs.git"
          branch: "main"
          include_paths:
            - "docs/**"
            - "README.md"
          exclude_paths:
            - "docs/archive/**"
          file_types:
            - "*.md"
            - "*.rst"
            - "*.txt"
          max_file_size: 1048576
          depth: 1
          token: "${DOCS_REPO_TOKEN}"
          enable_file_conversion: true
      confluence:
        company-wiki:
          base_url: "https://company.atlassian.net/wiki"
          deployment_type: "cloud"
          space_key: "DOCS"
          content_types:
            - "page"
            - "blogpost"
          include_labels: []
          exclude_labels: []
          token: "${CONFLUENCE_TOKEN}"
          email: "${CONFLUENCE_EMAIL}"
          enable_file_conversion: true
          download_attachments: true
  support-project:
    project_id: "support-project"
    display_name: "Support Knowledge Base"
    description: "Customer support documentation and tickets"
    sources:
      jira:
        support-tickets:
          base_url: "https://company.atlassian.net"
          deployment_type: "cloud"
          project_key: "SUPPORT"
          requests_per_minute: 60
          page_size: 100
          issue_types:
            - "Bug"
            - "Story"
            - "Task"
          include_statuses:
            - "Open"
            - "In Progress"
            - "Done"
          token: "${JIRA_TOKEN}"
          email: "${JIRA_EMAIL}"
          enable_file_conversion: true
          download_attachments: true
      localfile:
        support-docs:
          base_url: "file:///path/to/support/docs"
          include_paths:
            - "**/*.md"
            - "**/*.pdf"
          exclude_paths:
            - "tmp/**"
            - "archive/**"
          file_types:
            - "*.md"
            - "*.pdf"
            - "*.txt"
          max_file_size: 52428800
          enable_file_conversion: true

🔧 Detailed Configuration Sections

Global Configuration (`global`)

QDrant Database Configuration

global:
  qdrant:
    # Required: URL of your QDrant database instance
    url: "http://localhost:6333"
    # Optional: API key for QDrant Cloud or secured instances
    api_key: "${QDRANT_API_KEY}"
    # Required: Name of the QDrant collection (shared by all projects)
    collection_name: "documents"

Required Fields:

url - QDrant instance URL
collection_name - Collection name for all projects

Optional Fields:

api_key - API key for QDrant Cloud (use environment variable)

LLM Configuration (Unified)

global:
  llm:
    # Required: Provider and endpoint
    provider: ${LLM_PROVIDER}
    base_url: ${LLM_BASE_URL}
    api_key: ${LLM_API_KEY}
    # Required: Models
    models:
      embeddings: ${LLM_EMBEDDING_MODEL}
      chat: ${LLM_CHAT_MODEL}
    # Optional: Tokenizer and policies
    tokenizer: cl100k_base
    request:
      timeout_s: 30
      max_retries: 3
    embeddings:
      vector_size: 1536

> Deprecation: `global.embedding.*` is still honored but will be removed in a future release. Migrate to `global.llm.*`.

Required Fields:

provider - LLM provider (openai, azure_openai, ollama, openai_compat)
base_url - API endpoint URL
models.embeddings - Embedding model name
models.chat - Chat model name (optional, for LLM-enabled features)

Optional Fields:

api_key - API key (use environment variable, required for most providers)
api_version - API version (required for azure_openai)
headers - Custom HTTP headers
tokenizer - Tokenizer for token counting (cl100k_base, none)
request - Request policy settings (timeout, retries, backoff)
rate_limits - Rate limiting configuration (rpm, tpm, concurrency)
embeddings.vector_size - Vector dimension size
provider_options - Provider-specific options

Chunking Configuration

global:
  chunking:
    # Optional: Maximum size of text chunks in characters (default: 1500)
    chunk_size: 1500
    # Optional: Overlap between chunks in characters (default: 200)
    chunk_overlap: 200
    # Optional: Maximum chunks per document - safety limit (default: 500)
    max_chunks_per_document: 500
    # Optional: Strategy-specific configurations for different content types
    strategies:
      default:
        min_chunk_size: 100
        enable_semantic_analysis: true
        enable_entity_extraction: true
      html:
        simple_parsing_threshold: 100000
        max_html_size_for_parsing: 500000
        max_sections_to_process: 200
        max_chunk_size_for_nlp: 20000
        preserve_semantic_structure: true
      code:
        max_file_size_for_ast: 75000
        max_elements_to_process: 800
        max_recursion_depth: 8
        max_element_size: 20000
        enable_ast_parsing: true
        enable_dependency_analysis: true
      json:
        max_json_size_for_parsing: 1000000
        max_objects_to_process: 200
        max_chunk_size_for_nlp: 20000
        max_recursion_depth: 5
        max_array_items_per_chunk: 50
        max_object_keys_to_process: 100
        enable_schema_inference: true
      markdown:
        min_content_length_for_nlp: 100
        min_word_count_for_nlp: 20
        min_line_count_for_nlp: 3
        min_section_size: 500
        max_chunks_per_section: 1000
        max_overlap_percentage: 0.25
        max_workers: 4
        estimation_buffer: 0.2
        words_per_minute_reading: 200
        header_analysis_threshold_h1: 3
        header_analysis_threshold_h3: 8
        enable_hierarchical_metadata: true

Strategy-Specific Configuration Details: The strategies section allows you to fine-tune how different content types are processed:

Default Strategy (Text Files):

min_chunk_size: Prevents creation of very small chunks that may lack context
enable_semantic_analysis: Controls topic extraction and semantic analysis
enable_entity_extraction: Controls named entity recognition processing

HTML Strategy:

simple_parsing_threshold: Files below this size use simple text extraction
max_html_size_for_parsing: Maximum size for complex HTML parsing before fallback
max_sections_to_process: Limits processing to prevent infinite loops on malformed HTML
max_chunk_size_for_nlp: Maximum chunk size for semantic analysis
preserve_semantic_structure: Maintains HTML structure relationships in chunks

Code Strategy:

max_file_size_for_ast: Maximum file size for Abstract Syntax Tree parsing
max_elements_to_process: Limits code elements to prevent excessive processing time
max_recursion_depth: Controls AST traversal depth for nested code structures
max_element_size: Maximum size for individual code elements (functions, classes)
enable_ast_parsing: Toggle AST-based code analysis vs simple text splitting
enable_dependency_analysis: Extract import/dependency relationships

JSON Strategy:

max_json_size_for_parsing: Maximum JSON file size for structured parsing
max_objects_to_process: Limits number of JSON objects to prevent memory issues
max_chunk_size_for_nlp: Maximum chunk size for semantic processing
max_recursion_depth: Controls nested structure traversal depth
max_array_items_per_chunk: Groups array items for better context
max_object_keys_to_process: Limits object key processing for large objects
enable_schema_inference: Automatically detect and extract JSON schema information

Markdown Strategy:

min_content_length_for_nlp: Minimum content length required for NLP processing
min_word_count_for_nlp: Minimum word count required for semantic analysis
min_line_count_for_nlp: Minimum line count required for complex text processing
min_section_size: Minimum section size before merging with adjacent sections
max_chunks_per_section: Safety limit to prevent runaway chunking on large sections
max_overlap_percentage: Maximum overlap between adjacent chunks (0.25 = 25%)
max_workers: Number of parallel threads for processing large documents
estimation_buffer: Buffer factor for chunk count estimation accuracy
words_per_minute_reading: Reading speed for estimated reading time calculation
header_analysis_threshold_h1: H1 header count threshold for split level decisions
header_analysis_threshold_h3: H3 header count threshold for split level decisions
enable_hierarchical_metadata: Extract section relationships and breadcrumb navigation

Semantic Analysis Configuration

global:
  semantic_analysis:
    # Optional: Number of topics to extract using LDA (default: 3)
    num_topics: 3
    # Optional: Number of passes for LDA training (default: 10)
    lda_passes: 10
    # Optional: spaCy model for text processing (default: "en_core_web_md")
    spacy_model: "en_core_web_md"

State Management Configuration

global:
  state_management:
    # Required: Path to SQLite database file
    # Supports environment variable expansion (e.g., $HOME, ${STATE_DB_PATH})
    # Special values: ":memory:" for in-memory database
    database_path: "${STATE_DB_PATH}"
    # Optional: Prefix for database tables (default: "qdrant_loader_")
    table_prefix: "qdrant_loader_"
    # Optional: Connection pool settings
    connection_pool:
      size: 5     # Maximum connections (default: 5)
      timeout: 30 # Connection timeout in seconds (default: 30)

Path Validation Notes:

Supports environment variable expansion including $HOME
Automatically creates parent directories if they don't exist
Validates directory permissions before use
Special handling for in-memory databases (:memory:)

File Conversion Configuration

global:
  file_conversion:
    # Optional: Maximum file size for conversion in bytes (default: 50MB)
    # Range: 0 < max_file_size ≤ 100MB (104857600)
    max_file_size: 52428800
    # Optional: Timeout for conversion operations in seconds (default: 300)
    # Range: 0 < conversion_timeout ≤ 3600 seconds
    conversion_timeout: 300
    # Optional: MarkItDown specific settings
    markitdown:
      enable_llm_descriptions: false
      llm_model: "gpt-4o"
      llm_endpoint: "https://api.openai.com/v1"
      llm_api_key: "${OPENAI_API_KEY}"

Project Configuration (`projects`)

Project Structure

projects:
  project-id:
    # Unique project identifier
    project_id: "project-id"  # Must match the key above
    display_name: "Project Name"
    description: "Description"
    sources:
      # Project-specific data sources
      # Source configurations go here

Data Source Types

Git Repository Sources

sources:
  git:
    source-name:
      base_url: "https://github.com/user/repo.git"
      token: "${REPO_TOKEN}"
      file_types:
        - "*.md"
        - "*.rst"
        - "*.txt"
      branch: "main"
      include_paths:
        - "docs/**"
        - "README.md"
      exclude_paths:
        - "node_modules/**"
        - ".git/**"
      max_file_size: 1048576
      depth: 1
      enable_file_conversion: true

Confluence Sources

sources:
  confluence:
    source-name:
      base_url: "https://company.atlassian.net/wiki"
      deployment_type: "cloud"
      space_key: "DOCS"
      token: "${CONFLUENCE_TOKEN}"
      email: "${CONFLUENCE_EMAIL}"
      content_types:
        - "page"
        - "blogpost"
      include_labels: []
      exclude_labels: []
      enable_file_conversion: true
      download_attachments: true

JIRA Sources

sources:
  jira:
    source-name:
      base_url: "https://company.atlassian.net"
      deployment_type: "cloud"
      project_key: "PROJ"
      token: "${JIRA_TOKEN}"
      email: "${JIRA_EMAIL}"
      requests_per_minute: 60
      page_size: 100
      issue_types:
        - "Bug"
        - "Story"
        - "Task"
      include_statuses:
        - "Open"
        - "In Progress"
        - "Done"
      enable_file_conversion: true
      download_attachments: true

Local File Sources

sources:
  localfile:
    source-name:
      base_url: "file:///path/to/files"
      include_paths:
        - "docs/**"
        - "*.md"
      exclude_paths:
        - "tmp/**"
        - ".*"  # Hidden files
      file_types:
        - "*.md"
        - "*.pdf"
        - "*.txt"
      max_file_size: 1048576
      enable_file_conversion: true

Public Documentation Sources

sources:
  publicdocs:
    source-name:
      base_url: "https://docs.example.com"
      version: "1.0"
      content_type: "html"  # Options: html, markdown, rst
      path_pattern: "/docs/{version}/**"
      exclude_paths:
        - "/api/**"
        - "/internal/**"
      selectors:
        content: "article.main-content"
        remove:
          - "nav"
          - "header"
          - "footer"
          - ".sidebar"
        code_blocks: "pre code"
      enable_file_conversion: true
      download_attachments: true
      attachment_selectors:
        - "a[href$='.pdf']"
        - "a[href$='.doc']"
        - "a[href$='.docx']"
        - "a[href$='.xls']"
        - "a[href$='.xlsx']"
        - "a[href$='.ppt']"
        - "a[href$='.pptx']"

🔧 Configuration Management

Using Configuration Files

Workspace Mode (Recommended)

# Create workspace directory
mkdir my-workspace && cd my-workspace

# Download configuration templates
curl -o config.yaml https://raw.githubusercontent.com/martin-papy/qdrant-loader/main/packages/qdrant-loader/conf/config.template.yaml
curl -o .env https://raw.githubusercontent.com/martin-papy/qdrant-loader/main/packages/qdrant-loader/conf/.env.template

# Edit configuration files
# Then use workspace mode
qdrant-loader init --workspace .
qdrant-loader ingest --workspace .

Traditional Mode

# Use specific configuration files
qdrant-loader --config /path/to/config.yaml --env /path/to/.env init
qdrant-loader --config /path/to/config.yaml --env /path/to/.env ingest

Configuration Validation

Validate Configuration

# Display current configuration (shows all projects and their status)
qdrant-loader config --workspace .

# Note: Dedicated project management commands (list, status, validate) 
# are not currently implemented. All project information is displayed 
# through the config command.

Project Management

# View all configured projects and their information
qdrant-loader config --workspace .

# Note: Project-specific filtering (--project-id) is not currently 
# supported in the CLI. All project information is shown together.

📋 Environment Variables

Configuration files support environment variable substitution using ${VARIABLE_NAME} syntax:

Required Environment Variables

# QDrant Configuration
QDRANT_URL=http://localhost:6333
QDRANT_COLLECTION_NAME=documents
QDRANT_API_KEY=your_api_key # Optional: for QDrant Cloud

# LLM Configuration (new unified approach)
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

# Legacy (still supported but deprecated)
OPENAI_API_KEY=your_openai_key

# State Management
STATE_DB_PATH=./data/qdrant-loader.db

Source-Specific Environment Variables

# Git Repositories
REPO_TOKEN=your_github_token

# Confluence (Cloud)
CONFLUENCE_TOKEN=your_confluence_token
CONFLUENCE_EMAIL=your_email

# JIRA (Cloud)
JIRA_TOKEN=your_jira_token
JIRA_EMAIL=your_email

🎯 Configuration Examples

Single Project Setup

global:
  qdrant:
    url: "${QDRANT_URL}"
    collection_name: "${QDRANT_COLLECTION_NAME}"
  llm:
    provider: "openai"
    base_url: "https://api.openai.com/v1"
    api_key: "${LLM_API_KEY}"
    models:
      embeddings: "text-embedding-3-small"
      chat: "gpt-4o-mini"
    embeddings:
      vector_size: 1536
  state_management:
    database_path: "${STATE_DB_PATH}"

projects:
  main:
    project_id: "main"
    display_name: "Main Project"
    description: "Primary documentation project"
    sources:
      git:
        docs:
          base_url: "https://github.com/company/docs.git"
          branch: "main"
          token: "${REPO_TOKEN}"
          file_types:
            - "*.md"
            - "*.rst"
          enable_file_conversion: true

Multi-Project Setup

global:
  qdrant:
    url: "${QDRANT_URL}"
    collection_name: "${QDRANT_COLLECTION_NAME}"
  llm:
    provider: "openai"
    base_url: "https://api.openai.com/v1"
    api_key: "${LLM_API_KEY}"
    models:
      embeddings: "text-embedding-3-small"
      chat: "gpt-4o-mini"
    embeddings:
      vector_size: 1536
  chunking:
    chunk_size: 1500
    chunk_overlap: 200
    max_chunks_per_document: 500
    strategies:
      default:
        min_chunk_size: 100
        enable_semantic_analysis: true
        enable_entity_extraction: true
      html:
        simple_parsing_threshold: 100000
        max_html_size_for_parsing: 500000
        max_sections_to_process: 200
        max_chunk_size_for_nlp: 20000
        preserve_semantic_structure: true
      code:
        max_file_size_for_ast: 75000
        max_elements_to_process: 800
        max_recursion_depth: 8
        max_element_size: 20000
        enable_ast_parsing: true
        enable_dependency_analysis: true
      json:
        max_json_size_for_parsing: 1000000
        max_objects_to_process: 200
        max_chunk_size_for_nlp: 20000
        max_recursion_depth: 5
        max_array_items_per_chunk: 50
        max_object_keys_to_process: 100
        enable_schema_inference: true
      markdown:
        min_content_length_for_nlp: 100
        min_word_count_for_nlp: 20
        min_line_count_for_nlp: 3
        min_section_size: 500
        max_chunks_per_section: 1000
        max_overlap_percentage: 0.25
        max_workers: 4
        estimation_buffer: 0.2
        words_per_minute_reading: 200
        header_analysis_threshold_h1: 3
        header_analysis_threshold_h3: 8
        enable_hierarchical_metadata: true
  state_management:
    database_path: "${STATE_DB_PATH}"
  file_conversion:
    max_file_size: 52428800
    markitdown:
      enable_llm_descriptions: false

projects:
  documentation:
    project_id: "documentation"
    display_name: "Documentation"
    description: "Technical documentation and guides"
    sources:
      git:
        docs-repo:
          base_url: "https://github.com/company/docs.git"
          branch: "main"
          include_paths:
            - "docs/**"
            - "README.md"
          token: "${DOCS_REPO_TOKEN}"
          file_types:
            - "*.md"
            - "*.rst"
          enable_file_conversion: true
      confluence:
        tech-wiki:
          base_url: "https://company.atlassian.net/wiki"
          deployment_type: "cloud"
          space_key: "TECH"
          token: "${CONFLUENCE_TOKEN}"
          email: "${CONFLUENCE_EMAIL}"
          enable_file_conversion: true
  support:
    project_id: "support"
    display_name: "Customer Support"
    description: "Support documentation and tickets"
    sources:
      jira:
        support-tickets:
          base_url: "https://company.atlassian.net"
          deployment_type: "cloud"
          project_key: "SUPPORT"
          token: "${JIRA_TOKEN}"
          email: "${JIRA_EMAIL}"
          enable_file_conversion: true
      localfile:
        support-docs:
          base_url: "file:///path/to/support/docs"
          include_paths:
            - "**/*.md"
            - "**/*.pdf"
          file_types:
            - "*.md"
            - "*.pdf"
          enable_file_conversion: true

Environment Variables Reference - Environment variable configuration
Basic Configuration - Getting started with configuration
Data Sources - Source-specific configuration guides
Workspace Mode - Workspace configuration details

📋 Configuration Checklist

[ ] Global configuration completed (qdrant, llm, state_management)
[ ] Environment variables configured in .env file
[ ] Project definitions created with unique project IDs
[ ] Data source credentials configured for your sources
[ ] Required fields provided (Git token, Confluence email/token, etc.)
[ ] File conversion settings configured if processing non-text files
[ ] Configuration displayed with qdrant-loader config
[ ] Projects reviewed in config output
[ ] File permissions set appropriately (chmod 600 for sensitive configs)
[ ] Version control configured (exclude .env files)

Multi-project configuration complete! 🎉

Your QDrant Loader is now configured using the multi-project structure. This provides organized, scalable configuration management while maintaining unified search across all your projects through a shared QDrant collection.