Update app.py

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 import os
 import json
+import uuid
 import requests
 import xml.etree.ElementTree as ET
 
@@ -26,7 +27,28 @@ for item in root.findall('item'):
             # name: ilk kelime (marka), item_info: (stok durumu, fiyat)
             products.append((name, item_info, full_name))
 
-def predict(system_msg, inputs, top_p, temperature, chat_counter, chatbot=[], history=[]):
+# ------------------ Session Yönetimi ------------------ #
+SESSION_DIR = "chat_sessions"
+if not os.path.exists(SESSION_DIR):
+    os.makedirs(SESSION_DIR)
+
+def get_session_id():
+    return str(uuid.uuid4())
+
+def load_session(session_id):
+    filename = os.path.join(SESSION_DIR, f"session_{session_id}.json")
+    if os.path.exists(filename):
+        with open(filename, "r", encoding="utf-8") as f:
+            return json.load(f)
+    return []
+
+def save_session(session_id, history):
+    filename = os.path.join(SESSION_DIR, f"session_{session_id}.json")
+    with open(filename, "w", encoding="utf-8") as f:
+        json.dump(history, f)
+
+# ------------------ Predict Fonksiyonu ------------------ #
+def predict(system_msg, inputs, top_p, temperature, chat_counter, chatbot=[], history=[], session_id=""):
     headers = {
         "Content-Type": "application/json",
         "Authorization": f"Bearer {OPENAI_API_KEY}"
@@ -59,13 +81,15 @@ def predict(system_msg, inputs, top_p, temperature, chat_counter, chatbot=[], hi
         
     messages.append({"role": "user", "content": inputs})
                 
+    # o3-mini modeli için payload'i güncelledik. 
+    # Eğer o3-mini modeli streaming desteklemiyorsa "stream": False yapıyoruz.
     payload = {
-        "model": "gpt-4o",
+        "model": "o3-mini",
         "messages": messages,
         "temperature": 0.7,
         "top_p": 0.9,
         "n": 1,
-        "stream": True,
+        "stream": False,
         "presence_penalty": 0,
         "frequency_penalty": 0,
     }
@@ -74,7 +98,7 @@ def predict(system_msg, inputs, top_p, temperature, chat_counter, chatbot=[], hi
     history.append(inputs)
     print(f"Logging : payload is - {payload}")
 
-    response = requests.post(API_URL, headers=headers, json=payload, stream=True)
+    response = requests.post(API_URL, headers=headers, json=payload, stream=payload["stream"])
     print(f"Logging : response code - {response}")
     
     token_counter = 0
@@ -94,6 +118,7 @@ def predict(system_msg, inputs, top_p, temperature, chat_counter, chatbot=[], hi
                     history[-1] = partial_words
                 chat = [(history[i], history[i + 1]) for i in range(0, len(history) - 1, 2)]
                 token_counter += 1
+                save_session(session_id, history)
                 yield chat, history, chat_counter, response
 
 def reset_textbox():
@@ -190,8 +215,10 @@ theme = gr.themes.Base(
     spacing_size="sm",
 )
 
+# Yeni oturum için benzersiz session ID oluşturuyoruz
+session_id_value = get_session_id()
+
 with gr.Blocks(theme=theme, css=css) as demo:
-    # Modern chat başlığı
     gr.Markdown("<div class='chat-header'>Trek Bike Finder Chatbot</div>")
     
     with gr.Column(elem_id="col_container"):
@@ -199,11 +226,13 @@ with gr.Blocks(theme=theme, css=css) as demo:
             system_msg = gr.Textbox(value="")
             new_msg = gr.Textbox(value="")
             accordion_msg = gr.HTML(value="", visible=False)
-        # Gradio Chatbot bileşeni; CSS ile stil veriliyor.
         chatbot = gr.Chatbot(label='Trek Bike Finder', elem_id="chatbot")
         inputs = gr.Textbox(
             placeholder="Buraya yazın, istediğiniz modeli beraber bulalım.", show_label=False)
-        state = gr.State([])
+        # Oturum geçmişini session_id üzerinden yüklüyoruz.
+        state = gr.State(load_session(session_id_value))
+        # Gizli session ID
+        session_id = gr.Textbox(value=session_id_value, visible=False, label="Session ID")
         with gr.Accordion("", open=False, visible=False):
             top_p = gr.Slider(minimum=0, maximum=1.0, value=0.5, step=0.05, interactive=False, visible=False)
             temperature = gr.Slider(minimum=0, maximum=5.0, value=0.1, step=0.1, interactive=False, visible=False)
@@ -211,9 +240,9 @@ with gr.Blocks(theme=theme, css=css) as demo:
 
     inputs.submit(
         predict,
-        [system_msg, inputs, top_p, temperature, chat_counter, chatbot, state],
+        [system_msg, inputs, top_p, temperature, chat_counter, chatbot, state, session_id],
         [chatbot, state, chat_counter]
     )
     inputs.submit(reset_textbox, [], [inputs])
 
-demo.queue(max_size=10).launch(debug=True)
+demo.queue(max_size=10).launch(debug=True)