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c9802db 2dc2fbc c9802db 2dc2fbc c9802db 2dc2fbc c9802db 2dc2fbc c9802db 381e865 c9802db 381e865 c9802db 381e865 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 | import whisper
import openai
import os
import requests
model = whisper.load_model("base")
openai.api_key = os.getenv("OPENAI_API_KEY")
LEONARDO_API_KEY = os.getenv("LEONARDO_API_KEY")
def transcribe_audio(audio_path):
result = model.transcribe(audio_path)
return result['text']
def split_story_to_pages(story_text):
api_key = os.getenv("GROQ_API_KEY")
prompt = f"""
Divide the following children's story into 4-6 illustrated pages.
For each page, return a JSON list with:
- "text": short narration for that page
- "image_prompt": scene description for image generation
Make it fun and visual.
Story: {story_text}
"""
headers = {
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json"
}
data = {
"messages": [
{"role": "system", "content": "You are a helpful children's book assistant."},
{"role": "user", "content": prompt}
],
"model": "mixtral-8x7b-32768", # Or try "llama3-70b-8192"
}
response = requests.post("https://api.groq.com/openai/v1/chat/completions",
headers=headers, json=data)
output = response.json()
story_data = output["choices"][0]["message"]["content"]
return eval(story_data)
def generate_image(prompt):
api_key = os.getenv("DEEPAI_API_KEY")
response = requests.post(
"https://api.deepai.org/api/text2img",
data={'text': prompt},
headers={'api-key': api_key}
)
if response.status_code == 200:
return response.json().get('output_url')
else:
return "https://via.placeholder.com/512?text=Image+Error"
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