Update app.py

app.py

@@ -39,7 +39,6 @@ ZONES = [
     "Other / Not sure"
 ]
 
-# Carico un modello CPU residente (ZeroGPU non mantiene stato GPU tra invocazioni)
 def load_model_cpu():
     m = models.resnet50(weights=None)
     num_ftrs = m.fc.in_features
@@ -78,17 +77,16 @@ APP_FORCE_LANG = os.environ.get("APP_FORCE_LANG", "").strip()
 # ======================
 
 def predict_on_cpu(img_pil: Image.Image):
-    x = transform(img_pil.convert("RGB")).unsqueeze(0)  # CPU tensor
+    x = transform(img_pil.convert("RGB")).unsqueeze(0)
     with torch.no_grad():
         logits = model_cpu(x)
         probs = torch.softmax(logits, dim=1).cpu().numpy()[0]
     idx = int(probs.argmax())
     return IDX2LABEL.get(idx, f"class_{idx}"), float(probs[idx])
 
-@spaces.GPU(duration=60)  # richiesto da ZeroGPU
+@spaces.GPU(duration=60)
 def predict_on_gpu(img_pil: Image.Image):
     device = "cuda"
-    # ZeroGPU non conserva stato: ricreo il modello su GPU ad ogni chiamata
     m = models.resnet50(weights=None)
     num_ftrs = m.fc.in_features
     m.fc = torch.nn.Linear(num_ftrs, len(IDX2LABEL))
@@ -108,7 +106,6 @@ def predict_image(image: Image.Image):
         if torch.cuda.is_available():
             return predict_on_gpu(image)
     except Exception:
-        # se ZeroGPU o CUDA falliscono, ripiega su CPU
         pass
     return predict_on_cpu(image)
 
@@ -117,11 +114,6 @@ def predict_image(image: Image.Image):
 # ======================
 
 def call_assistant(label, confidence, zone, note, user_question, thread_id=None):
-    """
-    Chiama l'Assistant OpenAI. Se VECTOR_STORE_ID è valorizzato, collega il File Search al thread.
-    Ritorna (reply, thread_id).
-    """
-    # crea o riusa thread, collegando il vector store se presente
     if not thread_id:
         if VECTOR_STORE_ID:
             thread = client.beta.threads.create(
@@ -136,8 +128,7 @@ Classification: {label} ({round(confidence*100,2)}%).
 Zone: {zone or "Not specified"}.
 User note: {note or "(none)"}.
 """
-
-    user_payload = core_context + "\nUser question:\n" + (user_question or "Provide initial advisory based on classification and note.")
+    user_payload = core_context + "\nUser question:\n" + (user_question or "Provide initial advisory.")
 
     client.beta.threads.messages.create(
         thread_id=thread_id,
@@ -150,12 +141,10 @@ User note: {note or "(none)"}.
 
     extra_instructions = (
         "Act as a PPG marine coatings technical specialist for ships (marine environments only). "
-        "Answer ONLY using information found in the attached docs via File Search (TDS/SDS, standard cycles). "
-        "If the docs lack details, reply 'Not in docs' and ask a targeted follow-up. "
-        "ALWAYS ask for the area/zone if it's missing before prescribing a cycle. "
-        "Structure: Diagnosis; Surface Preparation (ISO 8501-1, profile); System (primer/build/top or AF; DFT per coat; coats; recoat windows); Notes; Short disclaimer: "
-        "'Research use only; verify with official PPG specs.' "
-        "Cite file name and section/page when relevant. "
+        "Answer ONLY using information found in the attached docs via File Search. "
+        "If docs lack details, reply 'Not in docs'. "
+        "ALWAYS ask for the zone if missing before prescribing. "
+        "Structure: Diagnosis; Surface Preparation; System; Notes; Disclaimer. "
         "Provide first in English. " + second_lang_clause
     )
 
@@ -163,17 +152,14 @@ User note: {note or "(none)"}.
         thread_id=thread_id,
         assistant_id=ASSISTANT_ID,
         instructions=extra_instructions,
-        # alcune versioni supportano "tool_choice": "file_search"
     )
 
-    # polling semplice
     while True:
         r = client.beta.threads.runs.retrieve(thread_id=thread_id, run_id=run.id)
         if r.status in ["completed", "failed", "cancelled", "expired"]:
             break
         time.sleep(0.6)
 
-    # estrai ultimo messaggio assistant (testo)
     msgs = client.beta.threads.messages.list(thread_id=thread_id)
     reply = None
     for m in msgs.data:
@@ -187,52 +173,38 @@ User note: {note or "(none)"}.
     return reply or "No reply from Assistant.", thread_id
 
 # ======================
-# Pipelines (generator per streaming)
+# Pipelines (generator)
 # ======================
 
 def run_analysis(image, note, zone, chat_history, thread_state):
-    """
-    Generator: fa uno yield immediato per mostrare 'Analyzing...' prima del lavoro vero.
-    Ritorna 2 volte:
-      1) stato intermedio (messaggio di lavorazione)
-      2) risultato finale
-    """
     if image is None:
         yield "No image received.", chat_history, thread_state
         return
-
     if not zone or zone == "Other / Not sure":
-        msg = "**Please select the area/zone first.** The assistant needs the zone to propose a correct cycle."
+        msg = "**Please select the area/zone first.**"
         yield msg, chat_history, thread_state
         return
 
-    # stato intermedio visibile subito
-    yield "**Analyzing image...** Running classification and querying the PPG Assistant.", chat_history, thread_state
+    # messaggio intermedio
+    yield "**Analyzing image...** Please wait.", chat_history, thread_state
 
-    # classificazione + risposta initiale assistant
     label, conf = predict_image(image)
-    reply, thread_id = call_assistant(label, conf, zone, note, "Provide initial advisory based on classification and note.")
+    reply, thread_id = call_assistant(label, conf, zone, note, "Provide initial advisory.")
 
     header = f"**Model result:** `{label}` — confidence **{round(conf*100,2)}%**\n\n"
     out_text = header + (reply or "")
-
     new_history = chat_history[:] if chat_history else []
     new_history.append(("", reply))
-
-    # stato finale
     yield out_text, new_history, {"thread_id": thread_id, "label": label, "confidence": conf, "zone": zone or ""}
 
 def continue_chat(user_msg, chat_history, thread_state, note, zone):
-    if not user_msg or not user_msg.strip():
+    if not user_msg.strip():
         return chat_history, ""
-
     label = (thread_state or {}).get("label") or "unknown"
     conf = (thread_state or {}).get("confidence") or 0.0
     current_zone = zone or (thread_state or {}).get("zone") or "Not specified"
     thread_id = (thread_state or {}).get("thread_id")
-
     reply, thread_id = call_assistant(label, conf, current_zone, note, user_msg, thread_id)
-
     chat_history.append((user_msg, reply))
     thread_state["thread_id"] = thread_id
     return chat_history, ""
@@ -244,24 +216,19 @@ def continue_chat(user_msg, chat_history, thread_state, note, zone):
 WELCOME = """
 # Corrosion Assistant — Beta
 
-**Welcome!** This demo runs a custom **ResNet50 corrosion classifier** and connects to a dedicated **PPG Assistant** on OpenAI.
-- **Model**: ResNet50 classifier, **trained locally** on ~**9,000 images**
-- **Data collection**: a public link for contributing images will open **soon**
-- **Disclaimer**: research & experimental only. No professional advice, no warranty.
-
-After image analysis you can continue chatting with the assistant.
+**Welcome!**  
+ResNet50 classifier trained locally on ~9,000 images.  
+Data collection link coming soon.  
+**Disclaimer**: research & experimental only.
 """
 
 with gr.Blocks(title="Corrosion Assistant", theme=gr.themes.Soft()) as demo:
     gr.Markdown(WELCOME)
 
-    # Mostra automaticamente la coda/stato run (Gradio 5)
-    status = gr.Status()
-
     with gr.Row():
         with gr.Column(scale=2):
             img = gr.Image(type="pil", sources=["upload","webcam"], label="Upload or webcam")
-            note = gr.Textbox(label="Notes / Context (optional)", placeholder="Write in your language.")
+            note = gr.Textbox(label="Notes / Context (optional)")
             zone = gr.Dropdown(choices=ZONES, label="Zone (indicative)", value="Other / Not sure")
             analyze_btn = gr.Button("Analyze image", variant="primary")
         with gr.Column(scale=3):
@@ -271,22 +238,19 @@ with gr.Blocks(title="Corrosion Assistant", theme=gr.themes.Soft()) as demo:
 
     with gr.Row():
         with gr.Column(scale=3):
-            # fix warning: specifica type="tuples"
             chat = gr.Chatbot(height=320, label="Advisor chat", type="tuples")
-            chat_in = gr.Textbox(label="Your message", placeholder="Ask about prep, products, recoats, etc.")
+            chat_in = gr.Textbox(label="Your message")
             send_btn = gr.Button("Send")
             clear_btn = gr.Button("Clear chat")
         with gr.Column(scale=2):
             gr.Markdown(
-                "> **Disclaimer:** Research & experimental use only. Validate with certified PPG specs and local regulations. "
-                "No professional advice is provided and no responsibility is assumed."
+                "> **Disclaimer:** Research & experimental use only. Validate with official PPG specs. "
+                "No professional advice or responsibility assumed."
             )
 
-    # States
     chat_state = gr.State([])
     thread_state = gr.State({"thread_id": None, "label": None, "confidence": 0.0, "zone": ""})
 
-    # Analyze: funzione GENERATOR con streaming (yield)
     analyze_btn.click(
         fn=run_analysis,
         inputs=[img, note, zone, chat_state, thread_state],
@@ -297,7 +261,6 @@ with gr.Blocks(title="Corrosion Assistant", theme=gr.themes.Soft()) as demo:
         outputs=[chat]
     )
 
-    # Chat
     send_btn.click(
         fn=continue_chat,
         inputs=[chat_in, chat_state, thread_state, note, zone],
@@ -313,5 +276,5 @@ with gr.Blocks(title="Corrosion Assistant", theme=gr.themes.Soft()) as demo:
     demo.api_mode = "enabled"
 
 if __name__ == "__main__":
-    # SSR attivo di default in Gradio 5; nessun share link qui
     demo.launch()
+