Spaces:
Sleeping
Sleeping
| import requests | |
| import tempfile | |
| from openai import OpenAI | |
| from elevenlabs import generate, play, set_api_key, voices, Models | |
| # Function to get GPT response | |
| def get_text_response(client, model, prompt, messages): | |
| messages.append({"role": "user", "content": prompt}) | |
| response = client.chat.completions.create( | |
| model=model, | |
| messages=messages | |
| ) | |
| response_text = response.choices[0].message.content | |
| messages.append({"role": "assistant", "content": response_text}) | |
| return response_text, messages | |
| def text_to_audio(api_key, voice_id, response_text): | |
| # Convert response to audio | |
| CHUNK_SIZE = 1024 | |
| url = "https://api.elevenlabs.io/v1/text-to-speech/" + voice_id | |
| headers = { | |
| "Accept": "audio/mpeg", | |
| "Content-Type": "application/json", | |
| "xi-api-key": api_key | |
| } | |
| data = { | |
| "text": response_text, | |
| "model_id" : "eleven_multilingual_v1", | |
| "voice_settings": { | |
| "stability": 0.4, | |
| "similarity_boost": 1.0 | |
| } | |
| } | |
| response = requests.post(url, json=data, headers=headers) | |
| # Save audio data to a temporary file | |
| with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as f: | |
| for chunk in response.iter_content(chunk_size=CHUNK_SIZE): | |
| if chunk: | |
| f.write(chunk) | |
| f.flush() | |
| temp_filename = f.name | |
| return temp_filename |