Upload app.py
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app.py
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import streamlit as st
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from transformers import pipeline
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import textwrap
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import numpy as np
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import soundfile as sf
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import tempfile
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import os
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# Initialize pipelines
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@st.cache_resource
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def load_pipelines():
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captioner = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base")
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storyer = pipeline("text-generation", model="aspis/gpt2-genre-story-generation")
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tts = pipeline("text-to-speech", model="facebook/mms-tts-eng")
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return captioner, storyer, tts
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captioner, storyer, tts = load_pipelines()
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# Main logic
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def generate_content(image):
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# Generate caption
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caption = captioner(image)[0]["generated_text"]
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st.write("**Caption:**", caption)
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# Generate story
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prompt = (
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f"Write a funny, warm children's story for ages 3-10, 50–100 words, "
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f"in third-person narrative, that describes this scene exactly: {caption} "
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f"mention the exact place or venue within {caption}"
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)
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raw = storyer(
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prompt,
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max_new_tokens=150,
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temperature=0.7,
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top_p=0.9,
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no_repeat_ngram_size=2,
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return_full_text=False
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)[0]["generated_text"].strip()
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# Trim to max 100 words
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words = raw.split()
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story = " ".join(words[:100])
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st.write("**Story:**", story)
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# Convert story to speech
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chunks = textwrap.wrap(story, width=200)
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audio = np.concatenate([tts(chunk)["audio"].squeeze() for chunk in chunks])
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# Save audio to temporary file
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with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as temp_file:
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sf.write(temp_file.name, audio, tts.model.config.sampling_rate)
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temp_file_path = temp_file.name
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return caption, story, temp_file_path
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# Streamlit UI
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st.title("Image to Children's Story and Audio")
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st.write("Upload an image to generate a caption, a children's story, and an audio narration.")
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uploaded_image = st.file_uploader("Choose an image", type=["jpg", "jpeg", "png"])
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if uploaded_image is not None:
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st.image(uploaded_image, caption="Uploaded Image", use_column_width=True)
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if st.button("Generate Story and Audio"):
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with st.spinner("Generating content..."):
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caption, story, audio_path = generate_content(uploaded_image)
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st.audio(audio_path, format="audio/wav")
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# Clean up temporary file
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os.remove(audio_path)
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