Update app.py

app.py

@@ -4,9 +4,13 @@ import requests
 # -----------------------------
 # Hugging Face API setup
 # -----------------------------
-HF_API_TOKEN = st.secrets["HF_API_TOKEN"]  # Add token in Space Secrets
-MODEL_ID = "meta-llama/Llama-2-7b-chat-hf"
+HF_API_TOKEN = st.secrets.get("HF_API_TOKEN")
 
+if not HF_API_TOKEN:
+    st.error("HF_API_TOKEN not found in Secrets.")
+    st.stop()
+
+MODEL_ID = "mistralai/Mistral-7B-Instruct-v0.2"
 API_URL = f"https://api-inference.huggingface.co/models/{MODEL_ID}"
 HEADERS = {"Authorization": f"Bearer {HF_API_TOKEN}"}
 
@@ -16,34 +20,50 @@ HEADERS = {"Authorization": f"Bearer {HF_API_TOKEN}"}
 def query_hf_model(prompt, max_length=256):
     payload = {
         "inputs": prompt,
-        "parameters": {"max_new_tokens": max_length, "temperature": 0.7},
+        "parameters": {
+            "max_new_tokens": max_length,
+            "temperature": 0.7,
+            "return_full_text": False
+        },
     }
+
     try:
-        response = requests.post(API_URL, headers=HEADERS, json=payload, timeout=60)
+        response = requests.post(API_URL, headers=HEADERS, json=payload, timeout=120)
+
         if response.status_code == 200:
             result = response.json()
+
             if isinstance(result, list) and "generated_text" in result[0]:
-                return result[0]["generated_text"]
-            elif "error" in result:
-                return "Error from model: " + result["error"]
-            else:
-                return str(result)
+                return result[0]["generated_text"].strip()
+
+            if isinstance(result, dict) and "error" in result:
+                return "Model error: " + result["error"]
+
+            return str(result)
+
+        elif response.status_code == 503:
+            return "Model is loading. Please try again in a few seconds."
+
         else:
-            return f"Request failed: {response.status_code}"
+            return f"Request failed with status code {response.status_code}"
+
     except Exception as e:
-        return f"Error: {e}"
+        return f"Error: {str(e)}"
+
 
 # -----------------------------
 # Streamlit UI
 # -----------------------------
 st.set_page_config(page_title="AI Adaptive Learning", layout="wide")
+
 st.title("📚 AI Adaptive Learning App")
-st.write("Ask a question and get AI-generated explanations. Track your understanding with a score.")
+st.write("Ask a question and get AI-generated explanations.")
 
-# Session state for adaptive learning
-if "score" not in st.session_state: st.session_state.score = 0
-if "last_question" not in st.session_state: st.session_state.last_question = ""
-if "last_answer" not in st.session_state: st.session_state.last_answer = ""
+# Session state
+if "score" not in st.session_state:
+    st.session_state.score = 0
+if "last_answer" not in st.session_state:
+    st.session_state.last_answer = ""
 
 # User input
 user_input = st.text_input("Your Question:")
@@ -51,10 +71,9 @@ user_input = st.text_input("Your Question:")
 if st.button("Submit") and user_input:
     with st.spinner("Generating AI answer..."):
         answer = query_hf_model(user_input)
-    st.session_state.last_question = user_input
     st.session_state.last_answer = answer
 
-# Display AI answer
+# Display answer
 if st.session_state.last_answer:
     st.subheader("AI Answer:")
     st.write(st.session_state.last_answer)
@@ -62,11 +81,13 @@ if st.session_state.last_answer:
 # Adaptive learning score
 st.subheader("Your Adaptive Learning Score")
 col1, col2 = st.columns(2)
+
 with col1:
-    if st.button("I understood this"):
+    if st.button("I understood this 👍"):
         st.session_state.score += 1
+
 with col2:
-    if st.button("I didn't understand"):
+    if st.button("I didn't understand 👎"):
         st.session_state.score -= 1
 
 st.metric(label="Learning Score", value=st.session_state.score)