Update app.py

app.py

@@ -3,6 +3,7 @@ from PIL import Image
 from io import BytesIO
 from huggingface_hub import InferenceApi
 from gtts import gTTS
+import requests
 import tempfile
 
 # —––––––– Page Config —–––––––
@@ -15,26 +16,22 @@ def load_clients():
     hf_token = st.secrets["HF_TOKEN"]
     return (
         InferenceApi("Salesforce/blip-image-captioning-base", token=hf_token),
-        InferenceApi("deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B", token=hf_token)
+        hf_token  # we'll use direct requests for story generation
     )
 
-caption_client, story_client = load_clients()
+caption_client, hf_token = load_clients()
 
 # —––––––– Helper: Generate Caption —–––––––
 def generate_caption(img):
-    """
-    Runs the BLIP caption model on a PIL.Image and returns the generated text.
-    """
     img_bytes = BytesIO()
     img.save(img_bytes, format="JPEG")
     try:
         result = caption_client(data=img_bytes.getvalue())
         if isinstance(result, list) and result:
             return result[0].get("generated_text", "").strip()
-        return ""
     except Exception as e:
-        st.error(f"Caption generation error: {e}")
-        return ""
+        st.error(f"Caption generation error: {type(e).__name__}: {e}")
+    return ""
 
 # —––––––– Helper: Process Image —–––––––
 def process_image(uploaded_file):
@@ -44,16 +41,51 @@ def process_image(uploaded_file):
             img.thumbnail((2048, 2048))
         return img
     except Exception as e:
-        st.error(f"Image processing error: {e}")
+        st.error(f"Image processing error: {type(e).__name__}: {e}")
         st.stop()
 
+# —––––––– Helper: Generate Story via HTTP —–––––––
+def generate_story(prompt: str) -> str:
+    api_url = "https://api-inference.huggingface.co/models/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B"
+    headers = {"Authorization": f"Bearer {hf_token}"}
+    payload = {
+        "inputs": prompt,
+        "parameters": {
+            "max_new_tokens":       200,
+            "temperature":          0.8,
+            "top_p":                0.95,
+            "repetition_penalty":   1.15,
+            "do_sample":            True,
+            "no_repeat_ngram_size": 2
+        }
+    }
+    try:
+        resp = requests.post(api_url, headers=headers, json=payload, timeout=30)
+    except Exception as e:
+        st.error(f"🚨 Story magic failed: {type(e).__name__}: {e}")
+        st.stop()
+    if resp.status_code != 200:
+        st.error(f"🚨 Story magic failed: HTTP {resp.status_code} - {resp.text}")
+        st.stop()
+    data = resp.json()
+    # Expecting list of generations
+    if isinstance(data, list) and data:
+        text = data[0].get("generated_text", "").strip()
+        # extract after "Story:" if present
+        story = text.split("Story:")[-1].strip()
+        if "." in story:
+            story = story.rsplit(".", 1)[0] + "."
+        return story
+    st.error("🚨 Story magic failed: invalid response format")
+    st.stop()
+
 # —––––––– Main App Flow —–––––––
 uploaded = st.file_uploader("Upload an image:", type=["jpg", "png", "jpeg"])
 if uploaded:
     img = process_image(uploaded)
     st.image(img, use_container_width=True)
 
-    # Generate Caption
+    # Caption
     with st.spinner("🔍 Discovering image secrets..."):
         caption = generate_caption(img)
         if not caption:
@@ -61,7 +93,7 @@ if uploaded:
             st.stop()
     st.success(f"**Caption:** {caption}")
 
-    # Prepare Story Prompt
+    # Prepare Prompt
     story_prompt = (
         f"Image description: {caption}\n\n"
         "Write a 50-100 word children's story that:\n"
@@ -72,29 +104,9 @@ if uploaded:
         "Story:\n"
     )
 
-    # Generate Story with full payload dict
-    payload = {
-        "inputs": story_prompt,
-        "parameters": {
-            "max_new_tokens":       200,
-            "temperature":          0.8,
-            "top_p":                0.95,
-            "repetition_penalty":   1.15,
-            "do_sample":            True,
-            "no_repeat_ngram_size": 2
-        }
-    }
-
+    # Generate Story
     with st.spinner("📝 Writing magical story..."):
-        try:
-            story_response = story_client(payload)
-            full_text      = story_response[0].get("generated_text", "")
-            story          = full_text.split("Story:")[-1].strip()
-            if "." in story:
-                story = story.rsplit(".", 1)[0] + "."
-        except Exception as e:
-            st.error(f"🚨 Story magic failed: {e}")
-            st.stop()
+        story = generate_story(story_prompt)
 
     # Display Story
     st.subheader("📚 Your Magical Story")
@@ -108,7 +120,7 @@ if uploaded:
                 tts.save(fp.name)
                 st.audio(fp.name, format="audio/mp3")
         except Exception as e:
-            st.warning("⚠️ Couldn't make audio version: " + str(e))
+            st.warning(f"⚠️ Couldn't make audio version: {type(e).__name__}: {e}")
 
 # Footer
 st.markdown("---\n*Made with ❤️ by your friendly story wizard*")