Refactor chat function to streamline message handling and improve clarity

app.py

@@ -15,31 +15,22 @@ SYSTEM_PROMPT = (
 )
 
 def chat(user_message, history):
-    # 1) ignore empty
-    if not user_message or not user_message.strip():
+    if not user_message.strip():
         return
 
-    # 2) build the UI history (what Gradio shows)
     ui_history = history + [{"role":"user","content":user_message}]
 
-    # 3) build the actual text prompt we’ll send to Claude
-    prompt_lines = [SYSTEM_PROMPT]
-    for msg in history:
-        # capitalize role for clarity
-        role = msg["role"].capitalize()
-        prompt_lines.append(f"{role}: {msg['content']}")
-    prompt_lines.append(f"User: {user_message}")
-    prompt_lines.append("Assistant:")         # Claude will continue from here
-    full_prompt = "\n".join(prompt_lines)
+    # build a proper messages array instead of a raw prompt string
+    llm_messages = [{"role":"system","content":SYSTEM_PROMPT}] \
+                 + history \
+                 + [{"role":"user","content":user_message}]
 
-    # 4) stream from the LLM
-    full_resp = ""
-    for token in claude_llm.stream(full_prompt):
-        full_resp += token
-        yield ui_history + [{"role":"assistant","content": full_resp}]
+    full = ""
+    for token in claude_llm.stream(llm_messages):
+        full += token
+        yield [{"role":"assistant","content":full}]
 
-    # 5) final append
-    ui_history.append({"role":"assistant","content": full_resp})
+    ui_history.append({"role":"assistant","content":full})
     yield ui_history