Update app.py

app.py

@@ -517,13 +517,26 @@ def perform_ai_lookup(q, vocal_summary=True, extended_refs=False,
         api_name="/update_with_rag_md"
     )[0]
 
-    r2 = client.predict(
-        q, 
-        "mistralai/Mixtral-8x7B-Instruct-v0.1", 
-        True, 
-        api_name="/ask_llm"
-    )
-
+    #r2 = client.predict(
+    #    q, 
+    #    "mistralai/Mixtral-8x7B-Instruct-v0.1", 
+    #    True, 
+    #    api_name="/ask_llm"
+    #)
+
+    # --- 3) Claude API with arxiv list of papers to app.py
+    client = anthropic.Anthropic(api_key=anthropic_key)
+    user_input = q + '\n\n' + 'Use the paper list below to answer the question thinking through step by step how to create a streamlit app.py and requirements.txt for the solution that answers the questions with a working app to demonstrate.'+ '\n\n'
+    response = client.messages.create(
+        model="claude-3-sonnet-20240229",
+        max_tokens=1000,
+        messages=[
+            {"role": "user", "content": user_input}
+        ])
+    r2 = response.content[0].text
+    st.write("Claude's reply 🧠:")
+    st.markdown(r2)
+    
     result = f"### 🔎 {q}\n\n{r2}\n\n{refs}"
     md_file, audio_file = save_qa_with_audio(q, result)
     st.subheader("📝 Main Response Audio")