Paddleocr Text Recognition

If the script execution fails (API not configured, network error, etc.):

• Show the error message to the user
• Do NOT offer to help using your vision capabilities
• Do NOT ask "Would you like me to try reading it?"
• Simply stop and wait for user to fix the configuration

Basic Workflow

1. Identify the input source:

   • User provides URL: Use the --file-url parameter
   • User provides local file path: Use the --file-path parameter
   • User uploads image: Save it first, then use --file-path

2. Execute OCR:

   python scripts/ocr_caller.py --file-url "URL provided by user" --pretty
   

   Or for local files:

   python scripts/ocr_caller.py --file-path "file path" --pretty
   

   Save result to file (recommended):

   python scripts/ocr_caller.py --file-url "URL" --output result.json --pretty
   

3. Parse JSON response:

   • Check the ok field: true means success, false means error
   • Extract text: text field contains all recognized text
   • Handle errors: If ok is false, display error.message

4. Present results to user:

   • Display extracted text in a readable format
   • If the text is empty, the image may contain no text

IMPORTANT: Complete Output Display

CRITICAL: Always display the COMPLETE recognized text to the user. Do NOT truncate or summarize the OCR results.

• The script returns the full JSON with complete text content in text field
• You MUST display the entire text content to the user, no matter how long it is
• Do NOT use phrases like "Here's a summary" or "The text begins with..."
• Do NOT truncate with "..." unless the text truly exceeds reasonable display limits
• The user expects to see ALL the recognized text, not a preview or excerpt

Correct approach:

I've extracted the text from the image. Here's the complete content:

[Display the entire text here]

Incorrect approach:

I found some text in the image. Here's a preview:
"The quick brown fox..." (truncated)

Usage Examples

URL OCR:

python scripts/ocr_caller.py --file-url "https://example.com/invoice.jpg" --pretty

Local File OCR:

python scripts/ocr_caller.py --file-path "./document.pdf" --pretty

Understanding the Output

The script outputs JSON structure as follows:

{
  "ok": true,
  "text": "All recognized text here...",
  "result": { ... },
  "error": null
}

Key fields:

• ok: true for success, false for error
• text: Complete recognized text
• result: Raw API response (for debugging)
• error: Error details if ok is false

First-Time Configuration

When API is not configured:

The error will show:

CONFIG_ERROR: PADDLEOCR_OCR_API_URL not configured. Get your API at: https://paddleocr.com

Configuration workflow:

1. Show the exact error message to user (including the URL)

2. Tell user to provide credentials:

   Please visit the URL above to get your PADDLEOCR_OCR_API_URL and PADDLEOCR_ACCESS_TOKEN.
   Once you have them, send them to me and I'll configure it automatically.
   

3. When user provides credentials (accept any format):

   • PADDLEOCR_OCR_API_URL=https://xxx.paddleocr.com/ocr, PADDLEOCR_ACCESS_TOKEN=abc123...
   • Here's my API: https://xxx and token: abc123
   • Copy-pasted code format
   • Any other reasonable format

4. Parse credentials from user's message:

   • Extract PADDLEOCR_OCR_API_URL value (look for URLs with paddleocr.com or similar)
   • Extract PADDLEOCR_ACCESS_TOKEN value (long alphanumeric string, usually 40+ chars)

5. Configure automatically:

   python scripts/configure.py --api-url "PARSED_URL" --token "PARSED_TOKEN"
   

6. If configuration succeeds:

   • Inform user: "Configuration complete! Running OCR now..."
   • Retry the original OCR task

7. If configuration fails:

   • Show the error
   • Ask user to verify the credentials

Error Handling

Authentication failed:

API_ERROR: Authentication failed (403). Check your token.

• Token is invalid, reconfigure with correct credentials

Quota exceeded:

API_ERROR: API rate limit exceeded (429)

• Daily API quota exhausted, inform user to wait or upgrade

No text detected:

• text field is empty
• Image may be blank, corrupted, or contain no text

Tips for Better Results

If recognition quality is poor, suggest:

• Check if the image is clear and contains text
• Provide a higher resolution image if possible

Reference Documentation

For in-depth understanding of the OCR system, refer to:

• references/output_schema.md - Output format specification
• references/provider_api.md - Provider API contract

Note: Model version and capabilities are determined by your API endpoint (PADDLEOCR_OCR_API_URL).

Testing the Skill

To verify the skill is working properly:

python scripts/smoke_test.py

This tests configuration and API connectivity.