Update app.py

app.py

@@ -1,26 +1,30 @@
 import streamlit as st
 import requests
 
-# Open-source LLM endpoint (replace if needed)
-API_URL = "https://api-inference.huggingface.co/models/google/flan-t5-small"
+# Set your OpenRouter API key here
+API_KEY = "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"  # 🔁 Replace with your key
+API_URL = "https://openrouter.ai/api/v1/chat/completions"
 
-# If you have a Hugging Face token, include it here. If not, this model works without one.
-headers = {"Authorization": ""}
+HEADERS = {
+    "Authorization": f"Bearer {API_KEY}",
+    "Content-Type": "application/json"
+}
 
 def query_llm(prompt):
-    payload = {"inputs": prompt}
-    response = requests.post(API_URL, headers=headers, json=payload)
+    data = {
+        "model": "mistralai/mistral-7b-instruct",
+        "messages": [
+            {"role": "system", "content": "You are a helpful science teacher for school students."},
+            {"role": "user", "content": prompt}
+        ]
+    }
 
     try:
-        output = response.json()
-        if isinstance(output, list) and 'generated_text' in output[0]:
-            return output[0]['generated_text']
-        elif isinstance(output, dict) and "error" in output:
-            return f"❌ API Error: {output['error']}"
-        else:
-            return "❌ Unexpected API response format."
+        response = requests.post(API_URL, headers=HEADERS, json=data)
+        res = response.json()
+        return res["choices"][0]["message"]["content"]
     except Exception as e:
-        return f"❌ Failed to parse response: {str(e)}"
+        return f"❌ Error: {str(e)}"
 
 # Streamlit UI
 st.set_page_config(page_title="Science Lab Assistant", page_icon="🧪")
@@ -33,7 +37,7 @@ with st.form("lab_form"):
     submitted = st.form_submit_button("Explain Experiment")
 
 if submitted and experiment:
-    prompt = f"Explain the experiment '{experiment}' for a school science class. The student hypothesizes: '{hypothesis}'. Provide an explanation and possible result."
+    prompt = f"Explain the experiment '{experiment}' for a school science class. The student hypothesizes: '{hypothesis}'. Provide an explanation and expected results."
     result = query_llm(prompt)
     st.markdown("### 🧠 AI Explanation")
     st.write(result)