Create app.py

app.py

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+import streamlit as st
+from PIL import Image
+from transformers import pipeline
+from gtts import gTTS
+import tempfile
+
+# —––––––– Page config
+st.set_page_config(page_title="Storyteller for Kids", layout="centered")
+st.title("🖼️ ➡️ 📖 Interactive Storyteller")
+
+# —––––––– Cache model loading
+@st.cache_resource
+def load_pipelines():
+    # 1) Image captioning
+    captioner = pipeline(
+        "image-captioning",
+        model="Salesforce/blip-image-captioning-base"
+    )
+    # 2) Story generation with Flan-T5
+    storyteller = pipeline(
+        "text2text-generation",
+        model="google/flan-t5-base"
+    )
+    return captioner, storyteller
+
+captioner, storyteller = load_pipelines()
+
+# —––––––– 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 image", use_column_width=True)
+
+    # —––––––– 1. Caption
+    with st.spinner("🔍 Looking at the image..."):
+        cap = captioner(image)[0]["generated_text"]
+    st.markdown(f"**Caption:** {cap}")
+
+    # —––––––– 2. Story generation
+    prompt = (
+        "Write a playful, 50–100 word story for 3–10 year-old children "
+        f"based on this description:\n\n“{cap}”\n\nStory:"
+    )
+    with st.spinner("✍️ Writing a story..."):
+        out = storyteller(
+            prompt,
+            max_length=200,
+            do_sample=True,
+            top_p=0.9,
+            temperature=0.8,
+            num_return_sequences=1
+        )
+        story = out[0]["generated_text"].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")