Create app.py

app.py

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+import streamlit as st
+from PIL import Image
+from io import BytesIO
+from transformers import pipeline
+from gtts import gTTS
+import tempfile
+
+# —––––––– Page config and title
+st.set_page_config(page_title="Storyteller for Kids", layout="centered")
+st.title("🖼️ ➡️ 📖 Interactive Storyteller")
+
+# —––––––– Load pipelines (cached)
+@st.experimental_singleton
+def load_pipelines():
+    # 1. Image captioning
+    captioner = pipeline(
+        "image-captioning",
+        model="Salesforce/blip-image-captioning-base",
+        device=0 if not st.session_state.get("CPU_ONLY", False) else -1
+    )
+    # 2. Story generation (you can swap to a kid-friendly fine-tuned model)
+    storyteller = pipeline(
+        "text-generation",
+        model="gpt2",
+        device=0 if not st.session_state.get("CPU_ONLY", False) else -1
+    )
+    return captioner, storyteller
+
+captioner, storyteller = load_pipelines()
+
+# —––––––– Sidebar: CPU/GPU toggle (optional)
+st.sidebar.write("### Settings")
+st.sidebar.checkbox("Force CPU only", key="CPU_ONLY")
+
+# —––––––– Main UI: image upload
+uploaded = st.file_uploader("Upload an image:", type=["jpg","jpeg","png"])
+if uploaded:
+    image = Image.open(uploaded).convert("RGB")
+    st.image(image, caption="Your picture", use_column_width=True)
+
+    # —––––––– 1. Caption
+    with st.spinner("🔍 Looking at the image..."):
+        caption = captioner(image)[0]["generated_text"]
+    st.markdown(f"**Caption:** {caption}")
+
+    # —––––––– 2. Story generation
+    prompt = (
+        f"Use the following description to write a playful story (50–100 words) "
+        f"for 3–10 year-old children:\n\n“{caption}”\n\nStory:"
+    )
+    with st.spinner("✍️ Writing a story..."):
+        output = storyteller(
+            prompt,
+            max_length= prompt.count(" ") + 100,  # approx ~100 words
+            num_return_sequences=1,
+            do_sample=True,
+            top_p=0.9,
+            temperature=0.8
+        )
+        story = output[0]["generated_text"].split("Story:")[-1].strip()
+    st.markdown("**Story:**")
+    st.write(story)
+
+    # —––––––– 3. Text-to-Speech
+    with st.spinner("🔊 Converting to speech..."):
+        tts = gTTS(story, lang="en")
+        tmp = tempfile.NamedTemporaryFile(suffix=".mp3", delete=False)
+        tts.write_to_fp(tmp)
+        tmp.flush()
+    st.audio(tmp.name, format="audio/mp3")