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import gradio as gr
import os
import json
import requests
import xml.etree.ElementTree as ET
from huggingface_hub import HfApi, create_repo
import schedule
import time
import threading
# Log dosyası adı ve yolu
LOG_FILE = '/data/chat_logs.txt' if os.path.exists('/data') else 'chat_logs.txt'
print(f"Dosya yolu: {os.path.abspath(LOG_FILE)}")
# API ayarları
API_URL = "https://api.openai.com/v1/chat/completions"
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
if not OPENAI_API_KEY:
print("Hata: OPENAI_API_KEY çevre değişkeni ayarlanmamış!")
# Trek bisiklet ürünlerini çekme
url = 'https://www.trekbisiklet.com.tr/output/8582384479'
response = requests.get(url)
root = ET.fromstring(response.content)
products = []
for item in root.findall('item'):
if item.find('isOptionOfAProduct').text == '1' and item.find('stockAmount').text > '0':
name_words = item.find('rootlabel').text.lower().split()
name = name_words[0]
full_name = ' '.join(name_words)
stockAmount = "stokta"
price = item.find('priceWithTax').text
item_info = (stockAmount, price)
products.append((name, item_info, full_name))
# Hugging Face token
hfapi = os.getenv("hfapi")
if not hfapi:
raise ValueError("hfapi ortam değişkeni ayarlanmamış!")
create_repo("BF", token=hfapi, repo_type="space", space_sdk="gradio", exist_ok=True)
def save_chat(chatbot):
file_path = os.path.abspath(LOG_FILE)
try:
with open(LOG_FILE, 'a', encoding='utf-8') as f:
f.write("\n--- Zamanlanmış Kayıt: {} ---\n".format(time.strftime("%Y-%m-%d %H:%M:%S")))
for msg in chatbot:
f.write(f"{msg['role'].capitalize()}: {msg['content']}\n")
print(f"Sohbet dosyaya kaydedildi: {file_path}")
return True
except Exception as e:
print(f"Kayıt hatası: {e}")
return False
def upload_logs_to_hf(repo_id: str, hf_token: str, local_log_file: str = LOG_FILE):
api = HfApi(token=hf_token)
try:
api.upload_file(
path_or_fileobj=local_log_file,
path_in_repo="chat_logs.txt",
repo_id=repo_id,
repo_type="space",
commit_message="Otomatik log dosyası güncellemesi - {}".format(time.strftime("%Y-%m-%d %H:%M:%S"))
)
print(f"Log dosyası HF'ye yüklendi: {local_log_file}")
return True
except Exception as e:
print(f"HF yükleme hatası: {e}")
return False
def run_scheduler(chatbot_ref):
def scheduled_save_and_upload():
if chatbot_ref:
print(f"Zamanlayıcı tetiklendi: {time.strftime('%Y-%m-DD %H:%M:%S')}")
save_success = save_chat(chatbot_ref)
if save_success:
HF_REPO_ID = "SamiKoen/BF"
upload_logs_to_hf(HF_REPO_ID, hfapi)
print(f"Zamanlanmış işlem tamamlandı: {time.strftime('%H:%M:%S')}")
schedule.every().day.at("11:32").do(scheduled_save_and_upload)
schedule.every().day.at("15:00").do(scheduled_save_and_upload)
schedule.every().day.at("21:00").do(scheduled_save_and_upload)
print("Zamanlayıcı başlatıldı")
while True:
schedule.run_pending()
print(f"Zamanlayıcı çalışıyor, bekliyor: {time.strftime('%H:%M:%S')}")
time.sleep(60)
def predict(system_msg, inputs, top_p, temperature, chat_counter, chatbot=None, history=None):
if chatbot is None:
chatbot = []
if history is None:
history = []
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {OPENAI_API_KEY}"
}
print(f"System message: {system_msg}")
multi_turn_message = [
{"role": "system", "content": "Bir önceki sohbeti unut. Vereceğin ürün bilgisi, bu bilginin içinde yan yana yazılmıyorsa veya arada başka bilgiler yazıyor ise, o bilgiyi vermeyeceksin çünkü o bilgi yanlıştır."}
]
messages = multi_turn_message.copy()
input_words = [str(word).lower() for word in inputs.split()]
for product_info in products:
if product_info[0] in input_words:
new_msg = f"{product_info[2]} {product_info[1][0]} ve fiyatı EURO {product_info[1][1]}"
print(new_msg)
messages.append({"role": "system", "content": new_msg})
for data in chatbot:
messages.append({"role": data["role"], "content": data["content"]})
messages.append({"role": "user", "content": inputs})
payload = {
"model": "gpt-4o",
"messages": messages,
"temperature": 0.7,
"top_p": 0.9,
"n": 1,
"stream": True,
"presence_penalty": 0,
"frequency_penalty": 0,
}
chat_counter += 1
history.append(inputs)
try:
with open(LOG_FILE, 'a', encoding='utf-8') as f:
f.write(f"User: {inputs}\n")
print(f"Kullanıcı mesajı dosyaya yazıldı: {inputs}")
except Exception as e:
print(f"Dosya yazma hatası (Kullanıcı): {e}")
chatbot.append({"role": "user", "content": inputs})
response = requests.post(API_URL, headers=headers, json=payload, stream=True)
if response.status_code != 200:
print(f"API hatası: {response.text}")
return chatbot, history, chat_counter
assistant_response = ""
for chunk in response.iter_lines():
if not chunk:
continue
chunk_str = chunk.decode('utf-8')
if chunk_str.startswith("data: ") and chunk_str != "data: [DONE]":
try:
chunk_data = json.loads(chunk_str[6:])
delta = chunk_data['choices'][0]['delta']
if 'content' in delta and delta['content']:
assistant_response += delta['content']
except json.JSONDecodeError as e:
print(f"JSON parse hatası: {e} - Chunk: {chunk_str}")
elif chunk_str == "data: [DONE]":
break
if assistant_response:
history.append(assistant_response)
chatbot.append({"role": "assistant", "content": assistant_response})
try:
with open(LOG_FILE, 'a', encoding='utf-8') as f:
f.write(f"Bot: {assistant_response}\n")
print(f"Bot yanıtı dosyaya yazıldı: {assistant_response}")
except Exception as e:
print(f"Dosya yazma hatası (Bot): {e}")
return chatbot, history, chat_counter
def reset_textbox():
return gr.update(value='')
demo_css = """
#send_button {
background-color: #0b93f6;
border: none;
color: white;
font-size: 16px;
border-radius: 10%;
width: 100px !important;
height: 37px !important;
display: inline-flex;
align-items: center;
justify-content: center;
cursor: pointer;
transition: background-color 0.3s;
margin: 5px;
}
#send_button:hover {
background-color: #0077c0;
}
.fixed_button_container {
padding: 0px;
margin: 0px 0 0 0px;
}
#custom_row {
width: 150% !important;
flex-wrap: nowrap !important;
}
@media only screen and (max-width: 1000px) {
.custom_row {
flex-wrap: nowrap !important;
}
}
#chatbot {
height: 100vh;
overflow-y: auto;
}
"""
theme = gr.themes.Base(
neutral_hue="blue",
text_size="sm",
spacing_size="sm",
)
with gr.Blocks(css=demo_css, theme=theme) as demo:
if not os.path.exists(LOG_FILE):
with open(LOG_FILE, 'w', encoding='utf-8') as f:
f.write("--- Yeni Sohbet ---\n")
with gr.Column(elem_id="col_container"):
with gr.Accordion("", open=False, visible=False):
system_msg = gr.Textbox(value="")
new_msg = gr.Textbox(value="")
accordion_msg = gr.HTML(value="", visible=False)
chatbot = gr.Chatbot(label='Trek Asistanı', elem_id="chatbot", type="messages")
with gr.Row(elem_id="custom_row"):
inputs = gr.Textbox(
placeholder="Buraya yazın",
show_label=False,
container=False,
)
with gr.Column(elem_classes="fixed_button_container"):
send_button = gr.Button(value="Gönder", elem_id="send_button")
state = gr.State([])
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)
chat_counter = gr.Number(value=0, visible=False, precision=0)
chatbot_ref = []
def update_chatbot_ref(chat):
chatbot_ref[:] = chat
return chat
inputs.submit(predict, [system_msg, inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter]).then(update_chatbot_ref, chatbot, chatbot).then(reset_textbox, [], [inputs])
send_button.click(predict, [system_msg, inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter]).then(update_chatbot_ref, chatbot, chatbot).then(reset_textbox, [], [inputs])
scheduler_thread = threading.Thread(target=run_scheduler, args=(chatbot_ref,), daemon=True)
scheduler_thread.start()
demo.launch(debug=True) # HF Spaces için share=True kaldırıldı |