Update app.py

app.py

@@ -13,12 +13,12 @@ emotion_classifier = pipeline("text-classification", model="bhadresh-savani/dist
 
 # Function to generate a comforting story using the pretrained model
 def generate_story(theme):
-    # Construct a prompt for generating a story based on the user's selected theme
-    story_prompt = f"Tell a comforting and inspiring story about {theme}. Make it detailed and heartwarming."
+    # A more detailed prompt for generating a story about courage
+    story_prompt = f"Tell me a detailed, comforting, and heartwarming story about {theme}. The story should include a character facing a tough challenge, showing immense courage, and ultimately overcoming it with a positive resolution. Include specific moments of struggle and inspiration."
     input_ids = tokenizer.encode(story_prompt, return_tensors='pt')
     story_ids = model.generate(
         input_ids,
-        max_length=350,  # Longer story length for richer content
+        max_length=500,  # Increase length for more detailed content
         temperature=0.9,  # Encourage creative storytelling
         repetition_penalty=1.1,
         num_return_sequences=1
@@ -28,6 +28,7 @@ def generate_story(theme):
     return story
 
 
+
 # Streamlit page configuration
 st.set_page_config(page_title="Grief and Loss Support Bot 🌿", page_icon="🌿", layout="centered")
 st.markdown("<style>.css-1d391kg { background-color: #F3F7F6; }</style>", unsafe_allow_html=True)