Update app.py

app.py

@@ -27,17 +27,15 @@ model = AutoModelForCausalLM.from_pretrained(
 ).to(device)
 
 # --- Define llm generation function ---
-def llm(prompt, max_new_tokens=1000, temperature=0.3, do_sample=True):
-    # Qwen does not require special prompt wrapping like [INST] ... [/INST]
+def llm(prompt, max_new_tokens=400, do_sample=False):
     inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
 
     output = model.generate(
         **inputs,
         max_new_tokens=max_new_tokens,
-        temperature=temperature,
         do_sample=do_sample,
-        top_p=0.95,
-        top_k=50,
+        top_p=0.95 if do_sample else None,
+        top_k=50 if do_sample else None,
         pad_token_id=tokenizer.eos_token_id
     )
 
@@ -46,6 +44,7 @@ def llm(prompt, max_new_tokens=1000, temperature=0.3, do_sample=True):
     return [{"generated_text": generated_text}]
 
 
+
 # Define all the screening questions
 questions = [
     # Generalized Anxiety & Somatic Concerns
@@ -119,10 +118,12 @@ def format_yes_responses():
     return "\n".join(yes_topics)
 
 def run_final_analysis():
+    # Initial: "Analyzing" screen
     yield (
         gr.update(value="🧠 AI is analyzing your responses... Please wait. ⏳"),
         gr.update(value=""),
-        *[gr.update(visible=False) for _ in range(6)]
+        *[gr.update(visible=False) for _ in range(5)],
+        gr.update(visible=False)
     )
 
     time.sleep(1)
@@ -139,17 +140,20 @@ def run_final_analysis():
         "Finally, provide a Hindi translation of your full response.\n"
     )
 
-    output = llm(prompt, max_new_tokens=1500, temperature=0.1, do_sample=False)
+    output = llm(prompt, max_new_tokens=300, temperature=0.1, do_sample=False)
     ai_result = output[0]["generated_text"]
 
+    # After generation complete
     yield (
         gr.update(value="✅ AI Analysis Completed."),
         gr.update(value=""),
-        *[gr.update(visible=False) for _ in range(5)],
+        *[gr.update(visible=False) for _ in range(4)],
+        gr.update(visible=True),  # result_btn stays visible now
         gr.update(value=ai_result, visible=True)
     )
 
 
+
 def go_back():
     if state["index"] > 0:
         state["index"] -= 1