from verbalisai import VerbalisAI

client = VerbalisAI(api_key="your-api-key")

# Transcribe audio file
transcription = await client.transcriptions.create(
    audio_url="https://example.com/audio.mp3",
    model="mini",
    topics=True,
    summarization=True
)

print(transcription.text)
print(transcription.topics)
print(transcription.summary.text)

import { VerbalisAI } from 'verbalisai';

const client = new VerbalisAI({
  apiKey: 'your-api-key'
});

// Transcribe audio file
const transcription = await client.transcriptions.create({
  audioUrl: 'https://example.com/audio.mp3',
  model: 'mini',
  topics: true,
  summarization: true
});

console.log(transcription.text);
console.log(transcription.topics);
console.log(transcription.summary.text);

# Python - Set up webhook for long audio processing
transcription = await client.transcriptions.create(
    audio_url="https://example.com/long-audio.mp3",
    model="pro",
    webhook_url="https://yoursite.com/webhook",
    webhook_auth_header_name="Authorization",
    webhook_auth_header_value="Bearer your-webhook-secret",
    wait_until_complete=False  # Don't wait, use webhook
)

print(f"Transcription started: {transcription.id}")

// JavaScript - Set up webhook for long audio processing
const transcription = await client.transcriptions.create({
  audioUrl: 'https://example.com/long-audio.mp3',
  model: 'pro',
  webhookUrl: 'https://yoursite.com/webhook',
  webhookAuthHeaderName: 'Authorization',
  webhookAuthHeaderValue: 'Bearer your-webhook-secret',
  waitUntilComplete: false  // Don't wait, use webhook
});

console.log(`Transcription started: ${transcription.id}`);

# Python - Identify different speakers
transcription = await client.transcriptions.create(
    audio_url="https://example.com/meeting.mp3",
    model="mini",
    diarize=True,
    timestamp_style="word"
)

for segment in transcription.segments:
    print(f"Speaker {segment.speaker_id}: {segment.text}")

# Python - Remove sensitive information
transcription = await client.transcriptions.create(
    audio_url="https://example.com/call.mp3",
    redact_pii=True,
    redact_pii_policies=["person", "email", "phone_number", "ssn"],
    redact_pii_sub="hash"
)

# Sensitive data will be automatically redacted
print(transcription.text)  # "Hi my name is [REDACTED] and my phone is [REDACTED]"

# Python - Upload and transcribe local file
with open("audio.mp3", "rb") as audio_file:
    # Upload file to storage
    file_info = await client.files.upload(
        file=audio_file,
        filename="audio.mp3"
    )
    
    # Transcribe uploaded file
    transcription = await client.transcriptions.create(
        audio_url=file_info.url,
        model="mini"
    )

// JavaScript - Upload and transcribe local file
const fileInput = document.getElementById('audioFile');
const file = fileInput.files[0];

// Upload file to storage
const fileInfo = await client.files.upload({
  file: file,
  filename: file.name
});

// Transcribe uploaded file
const transcription = await client.transcriptions.create({
  audioUrl: fileInfo.url,
  model: 'mini'
});

# Python - Track your usage
usage = await client.usage.get_overview()
print(f"Credits used this month: {usage.credits_used}")
print(f"Total transcriptions: {usage.total_transcriptions}")

# Get detailed analytics
analytics = await client.usage.get_analytics(
    start_date="2024-01-01",
    end_date="2024-01-31"
)

# Python - Advanced client configuration
client = VerbalisAI(
    api_key="your-api-key",
    base_url="https://api.verbalisai.com/api",  # Custom base URL
    timeout=60,  # Request timeout in seconds
    max_retries=3,  # Retry failed requests
    retry_delay=1.0  # Delay between retries
)

// JavaScript - Advanced client configuration
const client = new VerbalisAI({
  apiKey: 'your-api-key',
  baseUrl: 'https://api.verbalisai.com/api',  // Custom base URL
  timeout: 60000,  // Request timeout in milliseconds
  maxRetries: 3,  // Retry failed requests
  retryDelay: 1000  // Delay between retries
});

VERBALISAI_API_KEY=your-api-key
VERBALISAI_BASE_URL=https://api.verbalisai.com/api
VERBALISAI_TIMEOUT=30
VERBALISAI_MAX_RETRIES=3

# Python - Comprehensive error handling
from verbalisai import VerbalisAI, VerbalisAIError

client = VerbalisAI(api_key="your-api-key")

try:
    transcription = await client.transcriptions.create(
        audio_url="https://example.com/audio.mp3"
    )
except VerbalisAIError as e:
    if e.status_code == 429:
        print("Rate limit exceeded, please try again later")
    elif e.status_code == 401:
        print("Invalid API key")
    elif e.status_code == 400:
        print(f"Bad request: {e.message}")
    else:
        print(f"API error: {e.message}")
except Exception as e:
    print(f"Unexpected error: {e}")

# Python - Use context manager for automatic cleanup
async with VerbalisAI(api_key="your-api-key") as client:
    transcription = await client.transcriptions.create(
        audio_url="https://example.com/audio.mp3"
    )
    print(transcription.text)
# Client automatically cleaned up

# Python - Process multiple files efficiently
audio_urls = [
    "https://example.com/audio1.mp3",
    "https://example.com/audio2.mp3",
    "https://example.com/audio3.mp3"
]

import asyncio

async def transcribe_batch(urls):
    tasks = []
    for url in urls:
        task = client.transcriptions.create(audio_url=url, model="mini")
        tasks.append(task)
    
    results = await asyncio.gather(*tasks, return_exceptions=True)
    return results

transcriptions = await transcribe_batch(audio_urls)

# Python SDK development
git clone https://github.com/verbalisai/python-sdk.git
cd python-sdk
pip install -e ".[dev]"
pytest

# JavaScript SDK development
git clone https://github.com/verbalisai/js-sdk.git
cd js-sdk
npm install
npm test