Speech-to-Text Transcription

import requests

def transcribe_file(file_path):
    headers = {"x-api-key": "YOUR_API_KEY"}
    
    with open(file_path, 'rb') as audio_file:
        files = {'audio': ('audio.mp3', audio_file, 'audio/mpeg')}
        data = {
            'model': 'Whisper-Large-V3',
            'language': 'en'
        }
        
        response = requests.post(
            "https://nano-gpt.com/api/transcribe",
            headers=headers,
            files=files,
            data=data
        )
        
        return response.json()

result = transcribe_file("meeting.mp3")
print(result['transcription'])

import requests

def transcribe_url(audio_url):
    headers = {
        "x-api-key": "YOUR_API_KEY",
        "Content-Type": "application/json"
    }
    
    data = {
        "audioUrl": audio_url,
        "model": "Wizper",
        "language": "auto"
    }
    
    response = requests.post(
        "https://nano-gpt.com/api/transcribe",
        headers=headers,
        json=data
    )
    
    return response.json()

result = transcribe_url("https://example.com/audio.mp3")
print(result['transcription'])

import requests
import time

def transcribe_with_speakers(audio_url):
    headers = {
        "x-api-key": "YOUR_API_KEY",
        "Content-Type": "application/json"
    }
    
    # Submit transcription job
    data = {
        "audioUrl": audio_url,
        "model": "Elevenlabs-STT",
        "diarize": True,
        "tagAudioEvents": True
    }
    
    response = requests.post(
        "https://nano-gpt.com/api/transcribe",
        headers=headers,
        json=data
    )
    
    if response.status_code == 202:
        job_data = response.json()
        
        # Poll for results
        status_data = {
            "runId": job_data['runId'],
            "cost": job_data.get('cost'),
            "paymentSource": job_data.get('paymentSource'),
            "isApiRequest": True
        }
        
        while True:
            status_response = requests.post(
                "https://nano-gpt.com/api/transcribe/status",
                headers=headers,
                json=status_data
            )
            
            result = status_response.json()
            if result.get('status') == 'completed':
                return result
            elif result.get('status') == 'failed':
                raise Exception(f"Transcription failed: {result.get('error')}")
            
            time.sleep(5)

result = transcribe_with_speakers("https://example.com/meeting.mp3")

# Access speaker segments
for segment in result['diarization']['segments']:
    print(f"{segment['speaker']}: {segment['text']}")