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docs: update README to use proper module imports for apps

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- Change from 'python apps/xxx.py' to 'python -m apps.xxx'
- More professional and pythonic module calling
- Ensures proper module resolution and imports
- Better separation between apps/ (production tools) and examples/ (demos)
This commit is contained in:
Andy Lee
2025-08-03 23:05:48 -07:00
parent d68af63d05
commit 0877960547
1 changed files with 12 additions and 12 deletions
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24
README.md
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@@ -220,7 +220,7 @@ The example below asks a question about summarizing our paper (uses default data
```bash
source .venv/bin/activate # Don't forget to activate the virtual environment
python ./apps/document_rag.py --query "What are the main techniques LEANN explores?"
python -m apps.document_rag --query "What are the main techniques LEANN explores?"
```
<details>
@@ -235,10 +235,10 @@ python ./apps/document_rag.py --query "What are the main techniques LEANN explor
#### Example Commands
```bash
# Process all documents with larger chunks for academic papers
python apps/document_rag.py --data-dir "~/Documents/Papers" --chunk-size 1024
python -m apps.document_rag --data-dir "~/Documents/Papers" --chunk-size 1024
# Filter only markdown and Python files with smaller chunks
python apps/document_rag.py --data-dir "./docs" --chunk-size 256 --file-types .md .py
python -m apps.document_rag --data-dir "./docs" --chunk-size 256 --file-types .md .py
```
</details>
@@ -255,7 +255,7 @@ python apps/document_rag.py --data-dir "./docs" --chunk-size 256 --file-types .m
Before running the example below, you need to grant full disk access to your terminal/VS Code in System Preferences → Privacy & Security → Full Disk Access.
```bash
python apps/email_rag.py --query "What's the food I ordered by DoorDash or Uber Eats mostly?"
python -m apps.email_rag --query "What's the food I ordered by DoorDash or Uber Eats mostly?"
```
**780K email chunks → 78MB storage.** Finally, search your email like you search Google.
@@ -271,10 +271,10 @@ python apps/email_rag.py --query "What's the food I ordered by DoorDash or Uber
#### Example Commands
```bash
# Search work emails from a specific account
python apps/email_rag.py --mail-path "~/Library/Mail/V10/WORK_ACCOUNT"
python -m apps.email_rag --mail-path "~/Library/Mail/V10/WORK_ACCOUNT"
# Find all receipts and order confirmations (includes HTML)
python apps/email_rag.py --query "receipt order confirmation invoice" --include-html
python -m apps.email_rag --query "receipt order confirmation invoice" --include-html
```
</details>
@@ -295,7 +295,7 @@ Once the index is built, you can ask questions like:
</p>
```bash
python apps/browser_rag.py --query "Tell me my browser history about machine learning?"
python -m apps.browser_rag --query "Tell me my browser history about machine learning?"
```
**38K browser entries → 6MB storage.** Your browser history becomes your personal search engine.
@@ -310,10 +310,10 @@ python apps/browser_rag.py --query "Tell me my browser history about machine lea
#### Example Commands
```bash
# Search academic research from your browsing history
python apps/browser_rag.py --query "arxiv papers machine learning transformer architecture"
python -m apps.browser_rag --query "arxiv papers machine learning transformer architecture"
# Track competitor analysis across work profile
python apps/browser_rag.py --chrome-profile "~/Library/Application Support/Google/Chrome/Work Profile" --max-items 5000
python -m apps.browser_rag --chrome-profile "~/Library/Application Support/Google/Chrome/Work Profile" --max-items 5000
```
</details>
@@ -353,7 +353,7 @@ Once the index is built, you can ask questions like:
</p>
```bash
python apps/wechat_rag.py --query "Show me all group chats about weekend plans"
python -m apps.wechat_rag --query "Show me all group chats about weekend plans"
```
**400K messages → 64MB storage** Search years of chat history in any language.
@@ -394,10 +394,10 @@ sudo packages/wechat-exporter/wechattweak-cli install
#### Example Commands
```bash
# Search for travel plans discussed in group chats
python apps/wechat_rag.py --query "travel plans" --max-items 10000
python -m apps.wechat_rag --query "travel plans" --max-items 10000
# Re-export and search recent chats (useful after new messages)
python apps/wechat_rag.py --force-export --query "work schedule"
python -m apps.wechat_rag --force-export --query "work schedule"
```
</details>