docs: Make example commands more representative
- Add default values to parameter descriptions - Replace generic examples with real-world use cases - Focus on data-source-specific features in examples - Remove redundant demonstrations of common parameters
This commit is contained in:
Andy Lee
82
README.md
82
README.md
@@ -203,25 +203,19 @@ python ./examples/document_rag.py --query "What are the main techniques LEANN ex
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#### Document-Specific Parameters
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```bash
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--data-dir DIR # Directory containing documents to process
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--file-types .ext .ext # File extensions to process (e.g., .pdf .txt .md)
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--data-dir DIR # Directory containing documents to process (default: examples/data)
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--file-types .ext .ext # File extensions to process (default: .pdf .txt .md)
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--chunk-size N # Size of text chunks (default: 2048)
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--chunk-overlap N # Overlap between chunks (default: 25)
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```
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#### Example Commands
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```bash
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# Process custom documents
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python examples/document_rag.py --data-dir "./my_documents" --file-types .pdf .txt .md
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# Process your research papers folder
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python examples/document_rag.py --data-dir "~/Documents/Papers" --file-types .pdf
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# Process with custom chunking
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python examples/document_rag.py --chunk-size 512 --chunk-overlap 256
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# Use local LLM for privacy
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python examples/document_rag.py --llm ollama --llm-model llama3.2:1b
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# Use OpenAI embeddings
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python examples/document_rag.py --embedding-model text-embedding-3-small --embedding-mode openai
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# Process code documentation with smaller chunks
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python examples/document_rag.py --data-dir "./docs" --chunk-size 512 --file-types .md .rst
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```
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</details>
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@@ -248,28 +242,16 @@ python examples/email_rag.py --query "What's the food I ordered by DoorDash or U
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#### Email-Specific Parameters
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```bash
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--mail-path PATH # Path to specific mail directory (auto-detects if omitted)
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--include-html # Include HTML content in processing
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--include-html # Include HTML content in processing (useful for newsletters)
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```
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#### Example Commands
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```bash
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# Auto-detect and process all Apple Mail accounts
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python examples/email_rag.py
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# Search work emails from a specific account
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python examples/email_rag.py --mail-path "~/Library/Mail/V10/WORK_ACCOUNT"
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# Process specific mail directory
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python examples/email_rag.py --mail-path "~/Library/Mail/V10/..."
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# Process all emails (may take time)
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python examples/email_rag.py --max-items -1
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# Include HTML content
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python examples/email_rag.py --include-html
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# Use OpenAI embeddings for better results
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python examples/email_rag.py --embedding-model text-embedding-3-small --embedding-mode openai
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# Use local LLM for privacy
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python examples/email_rag.py --llm ollama --llm-model llama3.2:1b
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# Find all receipts and order confirmations (includes HTML)
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python examples/email_rag.py --query "receipt order confirmation invoice" --include-html
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```
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</details>
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@@ -304,23 +286,11 @@ python examples/browser_rag.py --query "Tell me my browser history about machine
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#### Example Commands
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```bash
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# Auto-detect and process all Chrome profiles
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python examples/browser_rag.py
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# Search work-related browsing in your work profile
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python examples/browser_rag.py --chrome-profile "~/Library/Application Support/Google/Chrome/Profile 1"
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# Process specific Chrome profile
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python examples/browser_rag.py --chrome-profile "~/Library/Application Support/Google/Chrome/Default"
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# Limit history entries for testing
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python examples/browser_rag.py --max-items 500
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# Interactive search mode
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python examples/browser_rag.py # Without --query for interactive mode
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# Use local LLM for privacy
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python examples/browser_rag.py --llm ollama --llm-model llama3.2:1b
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# Use better embeddings
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python examples/browser_rag.py --embedding-model text-embedding-3-small --embedding-mode openai
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# Interactive mode to explore your research history
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python examples/browser_rag.py --query "machine learning papers arxiv"
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```
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</details>
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@@ -388,29 +358,17 @@ Failed to find or export WeChat data. Exiting.
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#### WeChat-Specific Parameters
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```bash
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--export-dir DIR # Directory to store exported WeChat data
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--export-dir DIR # Directory to store exported WeChat data (default: wechat_export_direct)
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--force-export # Force re-export even if data exists
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```
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#### Example Commands
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```bash
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# Auto-export and index WeChat data
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python examples/wechat_rag.py
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# Search for travel plans discussed in group chats
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python examples/wechat_rag.py --query "旅游 travel 机票 酒店" --max-items 10000
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# Use custom export directory
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python examples/wechat_rag.py --export-dir "./my_wechat_exports"
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# Force re-export even if data exists
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python examples/wechat_rag.py --force-export
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# Limit chat entries for testing
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python examples/wechat_rag.py --max-items 1000
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# Use HuggingFace model for Chinese support
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python examples/wechat_rag.py --llm hf --llm-model Qwen/Qwen2.5-1.5B-Instruct
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# Use Qwen embedding model (better for Chinese)
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python examples/wechat_rag.py --embedding-model Qwen/Qwen3-Embedding-0.6B
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# Re-export and search recent chats (useful after new messages)
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python examples/wechat_rag.py --force-export --query "最近的工作安排"
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```
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</details>
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