Upload 3 files
Browse files- app.py +78 -13
- enhanced_features.py +305 -0
- requirements.txt +1 -1
app.py
CHANGED
@@ -22,6 +22,12 @@ warnings.simplefilter('ignore', InsecureRequestWarning)
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# Prompt dosyasını import et
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from prompts import get_prompt_content_only
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# Gradio uyarılarını bastır
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warnings.filterwarnings("ignore", category=UserWarning, module="gradio.components.chatbot")
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@@ -181,6 +187,9 @@ print(f"Toplam {len(products)} ürün yüklendi")
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if products:
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print(f"İlk ürün örneği: {products[0]}")
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# Hugging Face token
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hfapi = os.getenv("hfapi")
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if not hfapi:
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@@ -303,10 +312,32 @@ def run_scheduler(chat_history_ref):
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time.sleep(60)
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@spaces.GPU(duration=1200)
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-
def chatbot_fn(user_message, history):
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if history is None:
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history = []
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# Log: Kullanıcı mesajını ekle
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try:
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with file_lock:
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@@ -554,18 +585,52 @@ document.addEventListener('DOMContentLoaded', function() {
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"""
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if __name__ == "__main__":
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demo.launch(debug=True)
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# Prompt dosyasını import et
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from prompts import get_prompt_content_only
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# Enhanced features import et
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from enhanced_features import (
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initialize_enhanced_features, process_image_message,
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handle_comparison_request, get_user_recommendations, profile_manager
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)
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# Gradio uyarılarını bastır
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warnings.filterwarnings("ignore", category=UserWarning, module="gradio.components.chatbot")
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if products:
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print(f"İlk ürün örneği: {products[0]}")
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# Enhanced features'ları başlat
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initialize_enhanced_features(OPENAI_API_KEY, products)
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# Hugging Face token
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hfapi = os.getenv("hfapi")
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if not hfapi:
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time.sleep(60)
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@spaces.GPU(duration=1200)
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def chatbot_fn(user_message, history, image=None):
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if history is None:
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history = []
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# Enhanced features - Görsel işleme
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if image is not None:
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user_message = process_image_message(image, user_message)
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# Enhanced features - Karşılaştırma kontrolü
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comparison_result = handle_comparison_request(user_message)
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if comparison_result:
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yield comparison_result
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return
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# Enhanced features - Kişisel öneriler
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user_id = "default_user" # Gerçek uygulamada session ID kullanılır
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recommendation_result = get_user_recommendations(user_id, user_message)
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if recommendation_result:
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# Kullanıcı etkileşimini kaydet
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profile_manager.add_interaction(user_id, "recommendation_request", {
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"message": user_message,
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"timestamp": time.strftime("%Y-%m-%d %H:%M:%S")
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})
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yield recommendation_result
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return
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# Log: Kullanıcı mesajını ekle
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try:
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with file_lock:
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"""
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# Enhanced chatbot fonksiyonu image destekli
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def enhanced_chatbot_fn(message, history, image):
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return chatbot_fn(message, history, image)
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# Demo arayüzü - Özel layout ile image upload destekli
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with gr.Blocks(css=custom_css, theme="soft", title="Trek Asistanı") as demo:
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gr.Markdown("# 🚲 Trek Asistanı AI")
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gr.Markdown("**Yeni özellikler:** Bisiklet fotoğrafı yükleyebilir, ürün karşılaştırması yapabilir ve kişisel öneriler alabilirsiniz!")
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with gr.Row():
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with gr.Column(scale=4):
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chatbot = gr.Chatbot(height=500)
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with gr.Column(scale=1):
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gr.Markdown("### 🖼️ Bisiklet Fotoğrafı")
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image_input = gr.Image(type="filepath", height=200)
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gr.Markdown("### 🔍 Özel Komutlar")
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gr.Markdown("""
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• **Karşılaştırma:** "Émonda ve Madone karşılaştır"
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• **Bütçe:** "50-100K TL bütçem var"
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• **Görsel:** Bisiklet fotoğrafı yükle
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""")
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with gr.Row():
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msg = gr.Textbox(
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placeholder="Sorunuzu yazın veya fotoğraf yükleyip analiz isteyin...",
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show_label=False,
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scale=4
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)
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submit_btn = gr.Button("Gönder", scale=1)
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def respond(message, chat_history, image):
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# Enhanced chatbot fonksiyonunu çağır
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response_generator = chatbot_fn(message, chat_history, image)
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# Generator'dan son cevabı al
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response = ""
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for partial in response_generator:
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response = partial
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# Chat history güncelle
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chat_history.append((message, response))
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return "", chat_history, None
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submit_btn.click(respond, [msg, chatbot, image_input], [msg, chatbot, image_input])
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msg.submit(respond, [msg, chatbot, image_input], [msg, chatbot, image_input])
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if __name__ == "__main__":
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demo.launch(debug=True)
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enhanced_features.py
ADDED
@@ -0,0 +1,305 @@
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# -*- coding: utf-8 -*-
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"""
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Trek Chatbot Enhanced Features
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1. Görsel AI Entegrasyonu
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2. Kişiselleştirilmiş Öneri Motoru
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3. Gelişmiş Ürün Karşılaştırma
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"""
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import os
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import json
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import base64
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import requests
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from datetime import datetime
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import pandas as pd
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# Kullanıcı profili dosyası
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USER_PROFILES_FILE = "user_profiles.json"
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class UserProfileManager:
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"""Kullanıcı profili yönetimi"""
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def __init__(self):
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self.profiles = self.load_profiles()
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def load_profiles(self):
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"""Kullanıcı profillerini yükle"""
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if os.path.exists(USER_PROFILES_FILE):
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with open(USER_PROFILES_FILE, 'r', encoding='utf-8') as f:
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return json.load(f)
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return {}
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def save_profiles(self):
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"""Kullanıcı profillerini kaydet"""
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with open(USER_PROFILES_FILE, 'w', encoding='utf-8') as f:
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json.dump(self.profiles, f, ensure_ascii=False, indent=2)
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def get_or_create_profile(self, user_id="default_user"):
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"""Kullanıcı profili al veya oluştur"""
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if user_id not in self.profiles:
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self.profiles[user_id] = {
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"created_at": datetime.now().isoformat(),
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"preferences": {
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"budget_range": None,
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"bike_category": None,
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"size": None,
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"usage_purpose": None
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},
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"interaction_history": [],
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"favorite_products": [],
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"viewed_products": []
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}
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return self.profiles[user_id]
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def update_user_preference(self, user_id, key, value):
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"""Kullanıcı tercihini güncelle"""
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profile = self.get_or_create_profile(user_id)
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profile["preferences"][key] = value
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self.save_profiles()
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def add_interaction(self, user_id, interaction_type, data):
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"""Kullanıcı etkileşimi ekle"""
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profile = self.get_or_create_profile(user_id)
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interaction = {
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"timestamp": datetime.now().isoformat(),
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"type": interaction_type,
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"data": data
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}
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profile["interaction_history"].append(interaction)
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# Son 50 etkileşimi tut
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profile["interaction_history"] = profile["interaction_history"][-50:]
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self.save_profiles()
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class VisualAI:
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"""Görsel AI işlemleri"""
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def __init__(self, openai_api_key):
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self.api_key = openai_api_key
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def analyze_bike_image(self, image_path):
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"""Bisiklet görselini analiz et"""
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if not self.api_key:
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return "Görsel analiz için OpenAI API key gerekli."
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try:
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# Görseli base64'e çevir
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with open(image_path, "rb") as image_file:
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base64_image = base64.b64encode(image_file.read()).decode('utf-8')
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headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {self.api_key}"
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}
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payload = {
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"model": "gpt-4-vision-preview",
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"messages": [
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{
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"role": "user",
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"content": [
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{
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"type": "text",
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"text": "Bu bisiklet görselini analiz et. Hangi tip bisiklet? Marka, model tahmininde bulun. Trek bisikletleri hakkında uzmanısın."
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},
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{
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"type": "image_url",
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"image_url": {
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"url": f"data:image/jpeg;base64,{base64_image}"
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}
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}
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]
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}
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],
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"max_tokens": 300
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}
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response = requests.post("https://api.openai.com/v1/chat/completions",
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headers=headers, json=payload)
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if response.status_code == 200:
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result = response.json()
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return result["choices"][0]["message"]["content"]
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else:
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return f"Görsel analiz hatası: {response.status_code}"
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except Exception as e:
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return f"Görsel analiz hatası: {str(e)}"
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class ProductComparison:
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"""Ürün karşılaştırma sistemi"""
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def __init__(self, products_data):
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self.products = products_data
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def find_products_by_name(self, product_names):
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"""İsimlere göre ürünleri bul"""
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found_products = []
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for name in product_names:
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for product in self.products:
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if name.lower() in product[2].lower(): # product[2] = full_name
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found_products.append(product)
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break
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return found_products
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def create_comparison_table(self, product_names):
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"""Karşılaştırma tablosu oluştur"""
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products = self.find_products_by_name(product_names)
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147 |
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if len(products) < 2:
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return "Karşılaştırma için en az 2 ürün gerekli."
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# Tablo verilerini hazırla
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comparison_data = []
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for product in products:
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name, item_info, full_name = product
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+
|
156 |
+
# Ürün bilgilerini parse et
|
157 |
+
stock_status = item_info[0] if len(item_info) > 0 else "Bilgi yok"
|
158 |
+
price = item_info[1] if len(item_info) > 1 and item_info[1] else "Fiyat yok"
|
159 |
+
product_link = item_info[2] if len(item_info) > 2 else ""
|
160 |
+
|
161 |
+
comparison_data.append({
|
162 |
+
"Ürün": full_name,
|
163 |
+
"Stok": stock_status,
|
164 |
+
"Fiyat": f"{price} TL" if price != "Fiyat yok" else price,
|
165 |
+
"Link": product_link
|
166 |
+
})
|
167 |
+
|
168 |
+
# DataFrame oluştur
|
169 |
+
df = pd.DataFrame(comparison_data)
|
170 |
+
|
171 |
+
# Markdown tablosu olarak döndür
|
172 |
+
return df.to_markdown(index=False)
|
173 |
+
|
174 |
+
def get_similar_products(self, product_name, category_filter=None):
|
175 |
+
"""Benzer ürünleri bul"""
|
176 |
+
similar_products = []
|
177 |
+
base_name = product_name.lower().split()[0] # İlk kelimeyi al
|
178 |
+
|
179 |
+
for product in self.products:
|
180 |
+
product_full_name = product[2].lower()
|
181 |
+
if base_name in product_full_name and product_name.lower() != product_full_name:
|
182 |
+
if category_filter:
|
183 |
+
if category_filter.lower() in product_full_name:
|
184 |
+
similar_products.append(product)
|
185 |
+
else:
|
186 |
+
similar_products.append(product)
|
187 |
+
|
188 |
+
return similar_products[:5] # İlk 5 benzer ürün
|
189 |
+
|
190 |
+
class PersonalizedRecommendations:
|
191 |
+
"""Kişiselleştirilmiş öneriler"""
|
192 |
+
|
193 |
+
def __init__(self, profile_manager, products_data):
|
194 |
+
self.profile_manager = profile_manager
|
195 |
+
self.products = products_data
|
196 |
+
|
197 |
+
def get_budget_recommendations(self, user_id, budget_min, budget_max):
|
198 |
+
"""Bütçeye uygun öneriler"""
|
199 |
+
suitable_products = []
|
200 |
+
|
201 |
+
for product in self.products:
|
202 |
+
if product[1][0] == "stokta" and product[1][1]: # Stokta ve fiyatı var
|
203 |
+
try:
|
204 |
+
price = float(product[1][1])
|
205 |
+
if budget_min <= price <= budget_max:
|
206 |
+
suitable_products.append(product)
|
207 |
+
except (ValueError, TypeError):
|
208 |
+
continue
|
209 |
+
|
210 |
+
# Kullanıcı tercihlerini kaydet
|
211 |
+
self.profile_manager.update_user_preference(user_id, "budget_range", [budget_min, budget_max])
|
212 |
+
|
213 |
+
return suitable_products[:5] # İlk 5 öneri
|
214 |
+
|
215 |
+
def get_personalized_suggestions(self, user_id):
|
216 |
+
"""Geçmiş davranışlara göre öneriler"""
|
217 |
+
profile = self.profile_manager.get_or_create_profile(user_id)
|
218 |
+
preferences = profile["preferences"]
|
219 |
+
|
220 |
+
suggestions = []
|
221 |
+
|
222 |
+
# Bütçe tercihi varsa ona göre filtrele
|
223 |
+
if preferences.get("budget_range"):
|
224 |
+
budget_min, budget_max = preferences["budget_range"]
|
225 |
+
suggestions.extend(self.get_budget_recommendations(user_id, budget_min, budget_max))
|
226 |
+
|
227 |
+
# Kategori tercihi varsa ona göre filtrele
|
228 |
+
if preferences.get("bike_category"):
|
229 |
+
category = preferences["bike_category"]
|
230 |
+
for product in self.products:
|
231 |
+
if category.lower() in product[2].lower() and product[1][0] == "stokta":
|
232 |
+
suggestions.append(product)
|
233 |
+
|
234 |
+
return list(set(suggestions))[:3] # Duplicate'ları kaldır ve ilk 3'ü al
|
235 |
+
|
236 |
+
# Global instance'lar
|
237 |
+
profile_manager = UserProfileManager()
|
238 |
+
visual_ai = None # OpenAI key ile başlatılacak
|
239 |
+
product_comparison = None # Products data ile başlatılacak
|
240 |
+
personalized_recommendations = None # Profile manager ve products ile başlatılacak
|
241 |
+
|
242 |
+
def initialize_enhanced_features(openai_api_key, products_data):
|
243 |
+
"""Enhanced özellikleri başlat"""
|
244 |
+
global visual_ai, product_comparison, personalized_recommendations
|
245 |
+
|
246 |
+
visual_ai = VisualAI(openai_api_key)
|
247 |
+
product_comparison = ProductComparison(products_data)
|
248 |
+
personalized_recommendations = PersonalizedRecommendations(profile_manager, products_data)
|
249 |
+
|
250 |
+
def process_image_message(image_path, user_message):
|
251 |
+
"""Görsel mesajını işle"""
|
252 |
+
if visual_ai and image_path:
|
253 |
+
image_analysis = visual_ai.analyze_bike_image(image_path)
|
254 |
+
return f"Görsel Analiz: {image_analysis}\n\nSoru: {user_message}"
|
255 |
+
return user_message
|
256 |
+
|
257 |
+
def handle_comparison_request(user_message):
|
258 |
+
"""Karşılaştırma talebini işle"""
|
259 |
+
if "karşılaştır" in user_message.lower() or "compare" in user_message.lower():
|
260 |
+
# Ürün isimlerini çıkarmaya çalış
|
261 |
+
words = user_message.lower().split()
|
262 |
+
potential_products = []
|
263 |
+
|
264 |
+
# Bilinen model isimlerini ara
|
265 |
+
known_models = ["émonda", "madone", "domane", "marlin", "fuel", "powerfly", "fx"]
|
266 |
+
for word in words:
|
267 |
+
for model in known_models:
|
268 |
+
if model in word:
|
269 |
+
potential_products.append(model)
|
270 |
+
|
271 |
+
if len(potential_products) >= 2:
|
272 |
+
comparison_table = product_comparison.create_comparison_table(potential_products)
|
273 |
+
return f"Ürün Karşılaştırması:\n\n{comparison_table}"
|
274 |
+
|
275 |
+
return None
|
276 |
+
|
277 |
+
def get_user_recommendations(user_id, user_message):
|
278 |
+
"""Kullanıcıya özel öneriler al"""
|
279 |
+
# Bütçe sorgusu varsa
|
280 |
+
if "bütçe" in user_message.lower() or "budget" in user_message.lower():
|
281 |
+
# Rakamları çıkarmaya çalış
|
282 |
+
import re
|
283 |
+
numbers = re.findall(r'\d+', user_message)
|
284 |
+
if len(numbers) >= 2:
|
285 |
+
budget_min = int(numbers[0]) * 1000 # K TL formatı için
|
286 |
+
budget_max = int(numbers[1]) * 1000
|
287 |
+
recommendations = personalized_recommendations.get_budget_recommendations(
|
288 |
+
user_id, budget_min, budget_max
|
289 |
+
)
|
290 |
+
|
291 |
+
if recommendations:
|
292 |
+
rec_text = "Bütçenize uygun öneriler:\n\n"
|
293 |
+
for product in recommendations[:3]:
|
294 |
+
rec_text += f"• {product[2]} - {product[1][1]} TL\n"
|
295 |
+
return rec_text
|
296 |
+
|
297 |
+
# Genel kişisel öneriler
|
298 |
+
suggestions = personalized_recommendations.get_personalized_suggestions(user_id)
|
299 |
+
if suggestions:
|
300 |
+
sug_text = "Size özel önerilerimiz:\n\n"
|
301 |
+
for product in suggestions:
|
302 |
+
sug_text += f"• {product[2]} - {product[1][1]} TL\n"
|
303 |
+
return sug_text
|
304 |
+
|
305 |
+
return None
|
requirements.txt
CHANGED
@@ -4,10 +4,10 @@ requests
|
|
4 |
pandas
|
5 |
python-docx
|
6 |
huggingface_hub
|
7 |
-
schedule
|
8 |
openpyxl
|
9 |
spaces
|
10 |
google-auth
|
11 |
google-auth-oauthlib
|
12 |
google-auth-httplib2
|
13 |
google-api-python-client
|
|
|
|
4 |
pandas
|
5 |
python-docx
|
6 |
huggingface_hub
|
|
|
7 |
openpyxl
|
8 |
spaces
|
9 |
google-auth
|
10 |
google-auth-oauthlib
|
11 |
google-auth-httplib2
|
12 |
google-api-python-client
|
13 |
+
tabulate
|