import os import requests from transformers import pipeline from typing import Dict from together import Together # Image-to-text def img2txt(url: str) -> str: print("Initializing captioning model...") captioning_model = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base") print("Generating text from the image...") text = captioning_model(url, max_new_tokens=20)[0]["generated_text"] print(text) return text # Text-to-story generation with LLM model def txt2story(prompt: str, top_k: int, top_p: float, temperature: float) -> str: client = Together(api_key=os.environ.get("TOGETHER_API_KEY")) story_prompt = f"Write a short story of no more than 250 words based on the following prompt: {prompt}" stream = client.chat.completions.create( model="meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo", messages=[ {"role": "system", "content": '''As an experienced short story writer, write a meaningful story influenced by the provided prompt. Ensure the story does not exceed 250 words.'''}, {"role": "user", "content": story_prompt} ], top_k=top_k, top_p=top_p, temperature=temperature, stream=True ) story = '' for chunk in stream: story += chunk.choices[0].delta.content return story # Text-to-speech def txt2speech(text: str) -> None: print("Initializing text-to-speech conversion...") API_URL = "https://api-inference.huggingface.co/models/espnet/kan-bayashi_ljspeech_vits" headers = {"Authorization": f"Bearer {os.environ['HUGGINGFACEHUB_API_TOKEN']}"} payloads = {'inputs': text} response = requests.post(API_URL, headers=headers, json=payloads) with open('audio_story.mp3', 'wb') as file: file.write(response.content) # Get user preferences for the story def get_user_preferences(st) -> Dict[str, str]: preferences = {} preferences['continent'] = st.selectbox("Continent", ["North America", "Europe", "Asia", "Africa", "Australia"]) preferences['genre'] = st.selectbox("Genre", ["Science Fiction", "Fantasy", "Mystery", "Romance"]) preferences['setting'] = st.selectbox("Setting", ["Future", "Medieval times", "Modern day", "Alternate reality"]) preferences['plot'] = st.selectbox("Plot", ["Hero's journey", "Solving a mystery", "Love story", "Survival"]) preferences['tone'] = st.selectbox("Tone", ["Serious", "Light-hearted", "Humorous", "Dark"]) preferences['theme'] = st.selectbox("Theme", ["Self-discovery", "Redemption", "Love", "Justice"]) preferences['conflict'] = st.selectbox("Conflict Type", ["Person vs. Society", "Internal struggle", "Person vs. Nature", "Person vs. Person"]) preferences['twist'] = st.selectbox("Mystery/Twist", ["Plot twist", "Hidden identity", "Unexpected ally/enemy", "Time paradox"]) preferences['ending'] = st.selectbox("Ending", ["Happy", "Bittersweet", "Open-ended", "Tragic"]) return preferences