Feedback: lemur-examples

Documentation Feedback

Original URL: https://www.assemblyai.com/docs/lemur/examples
Category: lemur
Generated: 05/08/2025, 4:29:02 pm

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Claude Sonnet 4 Feedback

Generated: 05/08/2025, 4:29:01 pm

Technical Documentation Analysis & Feedback

Overall Assessment

This documentation provides a solid foundation for LeMUR custom prompts but has several areas for improvement in clarity, structure, and user experience.

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🔴 Critical Issues

1. Missing Prerequisites & Setup Information

• Issue: No clear explanation of what LeMUR is or how it works
• Fix: Add a brief “What is LeMUR?” section explaining it’s an LLM layer for audio analysis
• Add: Link to pricing information (only mentions “credit card required”)
• Add: API rate limits and usage quotas

2. Incomplete Error Handling

• Issue: Code examples lack comprehensive error handling
• Fix: Add error handling for common scenarios:

  # Add to all examples
  try:
      result = transcript.lemur.task(prompt)
  except aai.LemurError as e:
      print(f"LeMUR processing failed: {e}")
  except aai.TranscriptError as e:
      print(f"Transcript error: {e}")

3. Missing Response Format Documentation

• Issue: Users don’t know what to expect in the response
• Fix: Add a “Response Format” section with example output:

  {
    "request_id": "example-id",
    "response": "The emotional sentiment was predominantly positive...",
    "usage": {
      "input_tokens": 150,
      "output_tokens": 45
    }
  }

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🟡 Structure & Organization Issues

4. Poor Information Hierarchy

• Current flow: Example → Use cases → Ideas table
• Improved flow:
  1. What is LeMUR & Prerequisites
  2. Basic Example with detailed explanation
  3. Response format & error handling
  4. Advanced examples
  5. Use case gallery
  6. Best practices

5. Inconsistent Code Examples

• Issue: Some languages have more complete examples than others
• Fix: Standardize all code examples to include:
  • Error handling
  • Comments explaining each step
  • Expected output examples

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🟠 Clarity & Explanation Issues

6. Insufficient Parameter Documentation

• Missing: Explanation of final_model parameter options
• Add: Table of available models with descriptions:

  | Model | Best For | Token Limit |
  |-------|----------|-------------|
  | claude-sonnet-4 | Complex analysis, long content | 200k |
  | gpt-4 | General purpose | 128k |

7. Vague Example Prompts

• Issue: “What was the emotional sentiment?” is too basic
• Fix: Provide more sophisticated examples:

  # Better examples
  prompt = """Analyze the emotional sentiment of this phone call and provide:
  1. Overall sentiment score (1-10)
  2. Key emotional moments with timestamps
  3. Sentiment progression throughout the call
  4. Specific phrases that indicate sentiment"""

8. Missing Context About Audio Requirements

• Add: Supported audio formats, file size limits, duration limits
• Add: Best practices for audio quality

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🔵 User Experience Improvements

9. No Progressive Learning Path

• Add: “Beginner → Intermediate → Advanced” examples
• Add: Common pitfalls and troubleshooting section

10. Missing Interactive Elements

• Add: “Try it yourself” section with a working example
• Add: Expected execution time estimates

11. Inadequate Use Case Examples

• Current: Just links to other pages
• Improved: Include 2-3 complete examples with actual prompts and outputs

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📋 Specific Recommendations

Add These Sections:

1. Prerequisites & Setup

   ## Before You Begin
   - AssemblyAI account with API key
   - Audio file (supported formats: mp3, wav, m4a, etc.)
   - Credit card on file (LeMUR uses token-based pricing)
   - Estimated processing time: 30-60 seconds per minute of audio

2. Best Practices

   ## Prompt Engineering Tips
   - Be specific about desired output format
   - Include context about the audio content
   - Use structured prompts for complex analysis
   - Test with shorter audio files first

3. Troubleshooting

   ## Common Issues
   - **Long processing times**: Large files may take several minutes
   - **Token limits**: Break long audio into segments
   - **Generic responses**: Make prompts more specific

Improve Code Examples:

• Add timing information
• Show progress indicators for long operations
• Include validation steps
• Add debug output options

Enhanced Table of Ideas:

Replace the simple table with categorized, detailed examples including expected output formats and use case scenarios.

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🎯 Priority Implementation Order

1. High Priority: Add response format documentation and error handling
2. Medium Priority: Restructure information hierarchy and add prerequisites
3. Low Priority: Enhanced examples and interactive elements

This documentation has good bones but needs significant enhancement to reduce user friction and improve success rates.

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