Feedback: guides-task-endpoint-structured-QA

Documentation Feedback

Original URL: https://www.assemblyai.com/docs/guides/task-endpoint-structured-QA
Category: guides
Generated: 05/08/2025, 4:35:37 pm

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Claude Sonnet 4 Feedback

Generated: 05/08/2025, 4:35:36 pm

Technical Documentation Analysis & Feedback

Overall Assessment

This documentation provides a functional walkthrough but lacks the polish and completeness expected for production developer documentation. The content is more tutorial-like than comprehensive reference material.

Critical Issues

1. Missing Prerequisites & Setup Information

Current Problem: Jumps directly into code without proper setup context.

Recommendations:

## Prerequisites
- Python 3.7+ installed
- AssemblyAI account with API key
- Basic familiarity with XML parsing in Python

## Required Dependencies
```bash
pip install assemblyai>=0.17.0

Environment Setup

# Set your API key as an environment variable (recommended)
export ASSEMBLYAI_API_KEY="your_api_key_here"

# Or set it in your code (less secure)
import assemblyai as aai
aai.settings.api_key = "your_api_key_here"

2. Unclear Value Proposition & Use Cases

Current Problem: Doesn’t explain when/why to use structured Q&A vs other LeMUR endpoints.

Add Section:

## When to Use Structured Q&A
- **Automated reporting**: Extract specific metrics from meeting recordings
- **Compliance auditing**: Ask standardized questions across multiple transcripts
- **Data extraction**: Pull structured information for databases or dashboards
- **Quality assurance**: Ensure consistent answer formats for downstream processing

## Comparison with Other LeMUR Endpoints
| Endpoint | Best For | Output Format |
|----------|----------|---------------|
| Task | Custom prompts, flexible responses | Unstructured text |
| Q&A | Simple questions | Basic text answers |
| **Structured Q&A** | **Multiple questions, consistent formatting** | **Structured XML/JSON** |

3. Incomplete Error Handling

Current Problem: No error handling for common failure scenarios.

Add Comprehensive Error Handling:

import assemblyai as aai
import xml.etree.ElementTree as ET
from xml.parsers.expat import ExpatError

def safe_transcribe_and_query(audio_url, questions, max_retries=3):
    """
    Safely transcribe audio and run structured Q&A with error handling
    """
    try:
        # Transcribe with error handling
        transcript = aai.Transcriber().transcribe(audio_url)

        if transcript.status == aai.TranscriptStatus.error:
            raise Exception(f"Transcription failed: {transcript.error}")

        # Run LeMUR task with retry logic
        for attempt in range(max_retries):
            try:
                result = transcript.lemur.task(prompt, final_model=aai.LemurModel.claude3_5_sonnet)
                return parse_xml_response(result.response)
            except Exception as e:
                if attempt == max_retries - 1:
                    raise
                print(f"Attempt {attempt + 1} failed: {e}. Retrying...")

    except aai.exceptions.AuthenticationError:
        raise Exception("Invalid API key. Check your AssemblyAI credentials.")
    except aai.exceptions.RateLimitError:
        raise Exception("Rate limit exceeded. Please wait before trying again.")
    except Exception as e:
        raise Exception(f"Unexpected error: {str(e)}")

def parse_xml_response(response_text):
    """Parse XML response with proper error handling"""
    try:
        clean_response = escape_xml_characters(response_text).strip()
        root = ET.fromstring(clean_response)

        results = []
        for response_elem in root.findall('response'):
            question_elem = response_elem.find('question')
            answer_elem = response_elem.find('answer')

            if question_elem is None or answer_elem is None:
                print("Warning: Found response element missing question or answer")
                continue

            results.append({
                'question': question_elem.text or "",
                'answer': answer_elem.text or ""
            })

        return results

    except ExpatError as e:
        raise Exception(f"Invalid XML response from LeMUR: {e}")
    except Exception as e:
        raise Exception(f"Failed to parse response: {e}")

4. Limited Examples & Use Cases

Current Problem: Only one basic example with meeting audio.

Add Multiple Examples:

# Example 1: Financial earnings call analysis
financial_questions = [
    aai.LemurQuestion(
        question="What was the revenue growth percentage?",
        answer_format="percentage with one decimal place",
        context="Revenue growth compared to previous quarter"
    ),
    aai.LemurQuestion(
        question="What were the main growth drivers?",
        answer_format="bullet points, maximum 3 items"
    ),
    aai.LemurQuestion(
        question="Is the company profitable?",
        answer_options=["Yes", "No", "Break-even", "Not mentioned"]
    )
]

# Example 2: Customer support call analysis
support_questions = [
    aai.LemurQuestion(
        question="What was the customer's main issue?",
        answer_format="one sentence summary"
    ),
    aai.LemurQuestion(
        question="Was the issue resolved?",
        answer_options=["Resolved", "Partially resolved", "Unresolved", "Escalated"]
    ),
    aai.LemurQuestion(
        question="Customer satisfaction level",
        answer_options=["Very satisfied", "Satisfied", "Neutral", "Dissatisfied", "Very dissatisfied", "Not indicated"]
    )
]

5. Missing Configuration Options

Current Problem: Doesn’t explain available models or configuration parameters.

Add Configuration Section:

## Configuration Options

### Available Models
```python
# Choose the best model for your use case
models = {
    aai.LemurModel.default: "Balanced performance and cost",
    aai.LemurModel.claude3_5_sonnet: "Highest accuracy, best for complex analysis",
    aai.LemurModel.claude3_haiku: "Fastest responses, good for simple questions"
}

# Usage
result = transcript.lemur.task(prompt, final_model=aai.LemurModel.claude3_haiku)

Advanced Parameters

result = transcript.lemur.task(
    prompt,
    final_model=aai.LemurModel.claude3_5_sonnet,
    max_output_size=3000,  # Limit response length
    temperature=0.1        # Lower temperature for more consistent responses
)

6. Poor Code Organization

Current Problem: All code in one block without modular structure.

Provide Modular Structure:

class StructuredQAProcessor:
    def __init__(self, api_key):
        aai.settings.api_key = api_key
        self.transcriber = aai.Transcriber()

    def process_audio(self, audio_url, questions, model=aai.LemurModel.claude3_5_sonnet):
        """Complete pipeline from audio to structured answers"""
        transcript = self._transcribe(audio_url)
        prompt = self._build_prompt(questions)
        response = self._query_lemur(transcript, prompt, model)
        return self._parse_response(response)

    def _transcribe(self, audio_url):
        # Implementation with error handling
        pass

    def _build_prompt(self, questions):
        # Implementation
        pass

    # ... other methods

Structural Improvements

1. Add Missing Sections

## Table of Contents
1. [Overview](#overview)
2. [Prerequisites](#prerequisites)
3. [Quick Start](#quick-start)
4. [Step-by-Step Guide](#step-by-step-guide)
5. [Configuration Options](#configuration-options)
6. [Examples](#examples)
7. [Error Handling](#error-handling)
8. [Best Practices](#best-practices)
9

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