Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,28 +1,26 @@
 import streamlit as st
-from transformers import pipeline
+import requests
 
-# Cache model to avoid reloading
-@st.cache_resource
-def load_model():
-    return pipeline(
-        "text2text-generation",
-        model="google/flan-t5-small"   # smaller & safer for HF Spaces
-    )
-
-generator = load_model()
+API_URL = "https://api-inference.huggingface.co/models/google/flan-t5-small"
+headers = {
+    "Authorization": f"Bearer {st.secrets['HF_API_TOKEN']}"
+}
 
 st.set_page_config(page_title="Fitness Plan AI", layout="centered")
 
 st.title("🏋️ Fitness Plan AI Generator")
 st.write("Generate a personalized fitness plan using AI")
 
-# User Inputs
-age = st.number_input("Age", min_value=15, max_value=80, value=22)
+age = st.number_input("Age", 15, 80, 22)
 gender = st.selectbox("Gender", ["Male", "Female"])
 goal = st.selectbox("Fitness Goal", ["Weight Loss", "Muscle Gain", "General Fitness"])
 level = st.selectbox("Fitness Level", ["Beginner", "Intermediate", "Advanced"])
 days = st.slider("Workout Days per Week", 1, 7, 4)
 
+def query(payload):
+    response = requests.post(API_URL, headers=headers, json=payload)
+    return response.json()
+
 if st.button("Generate Fitness Plan"):
     prompt = (
         f"Create a {days}-day fitness workout plan for a "
@@ -32,7 +30,7 @@ if st.button("Generate Fitness Plan"):
         f"Include warm-up, main workout, and cool-down."
     )
 
-    with st.spinner("Generating your fitness plan..."):
-        result = generator(prompt, max_length=300, do_sample=True)
+    with st.spinner("Generating plan..."):
+        output = query({"inputs": prompt})
         st.success("✅ Your Fitness Plan")
-        st.write(result[0]["generated_text"])
+        st.write(outp