Create app.py

app.py

@@ -0,0 +1,45 @@
+import streamlit as st
+import requests
+import os
+
+# Groq API configuration
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+GROQ_MODEL = "mixtral-8x7b-32768"  # or "llama3-70b-8192", etc.
+
+API_URL = "https://api.groq.com/openai/v1/chat/completions"
+HEADERS = {
+    "Authorization": f"Bearer {GROQ_API_KEY}",
+    "Content-Type": "application/json"
+}
+
+def query_groq(prompt):
+    payload = {
+        "model": GROQ_MODEL,
+        "messages": [
+            {"role": "system", "content": "You are a helpful mechanical fault diagnosis assistant. When a user describes a mechanical issue, provide possible causes, recommended fixes, and required tools."},
+            {"role": "user", "content": prompt}
+        ],
+        "temperature": 0.5
+    }
+    response = requests.post(API_URL, headers=HEADERS, json=payload)
+    if response.status_code == 200:
+        return response.json()["choices"][0]["message"]["content"]
+    else:
+        return f"Error: {response.status_code} - {response.text}"
+
+# Streamlit UI
+st.set_page_config(page_title="Failure Diagnosis Bot", page_icon="🤖")
+
+st.title("🤖 Failure Diagnosis Bot")
+st.markdown("Diagnose machine faults based on symptoms.")
+
+user_input = st.text_area("Describe your machine's issue:")
+
+if st.button("Diagnose"):
+    if not user_input.strip():
+        st.warning("Please enter a description of the issue.")
+    else:
+        with st.spinner("Analyzing..."):
+            result = query_groq(user_input)
+        st.success("Diagnosis:")
+        st.markdown(result)