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import gradio as gr |
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import os |
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import json |
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import requests |
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import xml.etree.ElementTree as ET |
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from huggingface_hub import HfApi, create_repo |
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import schedule |
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import time |
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import threading |
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LOG_FILE = '/data/chat_logs.txt' if os.path.exists('/data') else 'chat_logs.txt' |
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print(f"Dosya yolu: {os.path.abspath(LOG_FILE)}") |
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API_URL = "https://api.openai.com/v1/chat/completions" |
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OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") |
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if not OPENAI_API_KEY: |
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print("Hata: OPENAI_API_KEY çevre değişkeni ayarlanmamış!") |
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url = 'https://www.trekbisiklet.com.tr/output/8582384479' |
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response = requests.get(url) |
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root = ET.fromstring(response.content) |
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products = [] |
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for item in root.findall('item'): |
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if item.find('isOptionOfAProduct').text == '1' and item.find('stockAmount').text > '0': |
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name_words = item.find('rootlabel').text.lower().split() |
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name = name_words[0] |
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full_name = ' '.join(name_words) |
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stockAmount = "stokta" |
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price = item.find('priceWithTax').text |
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item_info = (stockAmount, price) |
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products.append((name, item_info, full_name)) |
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hfapi = os.getenv("hfapi") |
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if not hfapi: |
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raise ValueError("hfapi ortam değişkeni ayarlanmamış!") |
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create_repo("BF", token=hfapi, repo_type="space", space_sdk="gradio", exist_ok=True) |
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def save_chat(chatbot): |
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file_path = os.path.abspath(LOG_FILE) |
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try: |
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with open(LOG_FILE, 'a', encoding='utf-8') as f: |
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f.write("\n--- Zamanlanmış Kayıt: {} ---\n".format(time.strftime("%Y-%m-%d %H:%M:%S"))) |
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for msg in chatbot: |
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f.write(f"{msg['role'].capitalize()}: {msg['content']}\n") |
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print(f"Sohbet dosyaya kaydedildi: {file_path}") |
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return True |
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except Exception as e: |
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print(f"Kayıt hatası: {e}") |
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return False |
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def upload_logs_to_hf(repo_id: str, hf_token: str, local_log_file: str = LOG_FILE): |
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api = HfApi(token=hf_token) |
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try: |
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api.upload_file( |
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path_or_fileobj=local_log_file, |
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path_in_repo="chat_logs.txt", |
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repo_id=repo_id, |
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repo_type="space", |
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commit_message="Otomatik log dosyası güncellemesi - {}".format(time.strftime("%Y-%m-%d %H:%M:%S")) |
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) |
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print(f"Log dosyası HF'ye yüklendi: {local_log_file}") |
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return True |
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except Exception as e: |
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print(f"HF yükleme hatası: {e}") |
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return False |
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def run_scheduler(chatbot_ref): |
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def scheduled_save_and_upload(): |
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if chatbot_ref: |
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print(f"Zamanlayıcı tetiklendi: {time.strftime('%Y-%m-DD %H:%M:%S')}") |
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save_success = save_chat(chatbot_ref) |
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if save_success: |
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HF_REPO_ID = "SamiKoen/BF" |
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upload_logs_to_hf(HF_REPO_ID, hfapi) |
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print(f"Zamanlanmış işlem tamamlandı: {time.strftime('%H:%M:%S')}") |
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schedule.every().day.at("11:32").do(scheduled_save_and_upload) |
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schedule.every().day.at("15:00").do(scheduled_save_and_upload) |
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schedule.every().day.at("21:00").do(scheduled_save_and_upload) |
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print("Zamanlayıcı başlatıldı") |
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while True: |
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schedule.run_pending() |
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print(f"Zamanlayıcı çalışıyor, bekliyor: {time.strftime('%H:%M:%S')}") |
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time.sleep(60) |
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def predict(system_msg, inputs, top_p, temperature, chat_counter, chatbot=None, history=None): |
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if chatbot is None: |
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chatbot = [] |
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if history is None: |
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history = [] |
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headers = { |
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"Content-Type": "application/json", |
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"Authorization": f"Bearer {OPENAI_API_KEY}" |
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} |
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print(f"System message: {system_msg}") |
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multi_turn_message = [ |
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{"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."} |
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] |
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messages = multi_turn_message.copy() |
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input_words = [str(word).lower() for word in inputs.split()] |
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for product_info in products: |
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if product_info[0] in input_words: |
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new_msg = f"{product_info[2]} {product_info[1][0]} ve fiyatı EURO {product_info[1][1]}" |
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print(new_msg) |
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messages.append({"role": "system", "content": new_msg}) |
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for data in chatbot: |
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messages.append({"role": data["role"], "content": data["content"]}) |
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messages.append({"role": "user", "content": inputs}) |
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payload = { |
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"model": "gpt-4o", |
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"messages": messages, |
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"temperature": 0.7, |
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"top_p": 0.9, |
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"n": 1, |
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"stream": True, |
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"presence_penalty": 0, |
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"frequency_penalty": 0, |
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} |
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chat_counter += 1 |
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history.append(inputs) |
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try: |
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with open(LOG_FILE, 'a', encoding='utf-8') as f: |
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f.write(f"User: {inputs}\n") |
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print(f"Kullanıcı mesajı dosyaya yazıldı: {inputs}") |
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except Exception as e: |
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print(f"Dosya yazma hatası (Kullanıcı): {e}") |
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chatbot.append({"role": "user", "content": inputs}) |
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response = requests.post(API_URL, headers=headers, json=payload, stream=True) |
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if response.status_code != 200: |
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print(f"API hatası: {response.text}") |
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return chatbot, history, chat_counter |
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assistant_response = "" |
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for chunk in response.iter_lines(): |
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if not chunk: |
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continue |
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chunk_str = chunk.decode('utf-8') |
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if chunk_str.startswith("data: ") and chunk_str != "data: [DONE]": |
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try: |
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chunk_data = json.loads(chunk_str[6:]) |
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delta = chunk_data['choices'][0]['delta'] |
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if 'content' in delta and delta['content']: |
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assistant_response += delta['content'] |
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except json.JSONDecodeError as e: |
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print(f"JSON parse hatası: {e} - Chunk: {chunk_str}") |
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elif chunk_str == "data: [DONE]": |
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break |
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if assistant_response: |
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history.append(assistant_response) |
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chatbot.append({"role": "assistant", "content": assistant_response}) |
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try: |
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with open(LOG_FILE, 'a', encoding='utf-8') as f: |
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f.write(f"Bot: {assistant_response}\n") |
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print(f"Bot yanıtı dosyaya yazıldı: {assistant_response}") |
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except Exception as e: |
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print(f"Dosya yazma hatası (Bot): {e}") |
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return chatbot, history, chat_counter |
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def reset_textbox(): |
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return gr.update(value='') |
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demo_css = """ |
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#send_button { |
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background-color: #0b93f6; |
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border: none; |
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color: white; |
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font-size: 16px; |
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border-radius: 10%; |
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width: 100px !important; |
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height: 37px !important; |
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display: inline-flex; |
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align-items: center; |
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justify-content: center; |
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cursor: pointer; |
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transition: background-color 0.3s; |
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margin: 5px; |
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} |
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#send_button:hover { |
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background-color: #0077c0; |
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} |
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.fixed_button_container { |
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padding: 0px; |
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margin: 0px 0 0 0px; |
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} |
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#custom_row { |
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width: 150% !important; |
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flex-wrap: nowrap !important; |
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} |
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@media only screen and (max-width: 1000px) { |
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.custom_row { |
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flex-wrap: nowrap !important; |
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} |
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} |
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#chatbot { |
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height: 100vh; |
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overflow-y: auto; |
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} |
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""" |
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theme = gr.themes.Base( |
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neutral_hue="blue", |
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text_size="sm", |
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spacing_size="sm", |
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) |
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with gr.Blocks(css=demo_css, theme=theme) as demo: |
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if not os.path.exists(LOG_FILE): |
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with open(LOG_FILE, 'w', encoding='utf-8') as f: |
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f.write("--- Yeni Sohbet ---\n") |
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with gr.Column(elem_id="col_container"): |
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with gr.Accordion("", open=False, visible=False): |
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system_msg = gr.Textbox(value="") |
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new_msg = gr.Textbox(value="") |
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accordion_msg = gr.HTML(value="", visible=False) |
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chatbot = gr.Chatbot(label='Trek Asistanı', elem_id="chatbot", type="messages") |
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with gr.Row(elem_id="custom_row"): |
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inputs = gr.Textbox( |
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placeholder="Buraya yazın", |
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show_label=False, |
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container=False, |
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) |
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with gr.Column(elem_classes="fixed_button_container"): |
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send_button = gr.Button(value="Gönder", elem_id="send_button") |
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state = gr.State([]) |
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with gr.Accordion("", open=False, visible=False): |
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top_p = gr.Slider(minimum=0, maximum=1.0, value=0.5, step=0.05, interactive=False, visible=False) |
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temperature = gr.Slider(minimum=0, maximum=5.0, value=0.1, step=0.1, interactive=False, visible=False) |
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chat_counter = gr.Number(value=0, visible=False, precision=0) |
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chatbot_ref = [] |
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def update_chatbot_ref(chat): |
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chatbot_ref[:] = chat |
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return chat |
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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]) |
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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]) |
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scheduler_thread = threading.Thread(target=run_scheduler, args=(chatbot_ref,), daemon=True) |
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scheduler_thread.start() |
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demo.launch(debug=True) |
