Upload app.py

app.py

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+import gradio as gr
+import json
+import time
+import os
+from datetime import datetime
+from llm_utils import LLM_PROVIDERS, get_llm_models, validate_api_key, call_llm, parse_llm_output, create_zip_from_files
+from project_types import PROJECT_TYPES
+from advanced_prompts import (
+    get_advanced_context_prompt,
+    get_advanced_commands_prompt,
+    get_advanced_prompts_prompt,
+    calculate_project_complexity,
+    get_industry_specific_requirements
+)
+
+# Global state
+generated_files = {'context': {}, 'commands': {}, 'prompts': {}}
+stats = {'context': {'tokens': 0, 'time': 0}, 'commands': {'tokens': 0, 'time': 0}, 'prompts': {'tokens': 0, 'time': 0}}
+project_analysis = {}
+
+# Sektörler
+INDUSTRIES = [
+    "Teknoloji/Yazılım", "Finans/Fintech", "Sağlık/Healthcare", 
+    "E-ticaret", "Eğitim/EdTech", "Oyun/Gaming", "Sosyal Medya",
+    "IoT/Akıllı Cihazlar", "Blockchain/Web3", "AI/ML Servisleri",
+    "SaaS B2B", "SaaS B2C", "Marketplace", "Diğer"
+]
+
+# Proje özellikleri
+PROJECT_FEATURES = [
+    "Kullanıcı Yönetimi", "Ödeme İşlemleri", "Gerçek Zamanlı Özellikler",
+    "AI/ML Entegrasyonu", "Çoklu Platform", "3. Parti Entegrasyonlar",
+    "Offline Çalışma", "Çoklu Dil Desteği", "Bildirim Sistemi",
+    "Analytics/Raporlama", "Sosyal Özellikler", "Güvenlik/Compliance"
+]
+
+def analyze_project(project_type, project_idea, industry, features):
+    """Proje analizi yapar ve öneriler üretir"""
+    analysis = {
+        "complexity": calculate_project_complexity(project_type, project_idea, features),
+        "industry_requirements": get_industry_specific_requirements(industry),
+        "estimated_files": {},
+        "tech_recommendations": [],
+        "architecture_suggestion": ""
+    }
+    
+    # Teknoloji önerileri
+    if "AI/ML" in project_type:
+        analysis["tech_recommendations"] = ["Python", "TensorFlow/PyTorch", "MLflow", "Docker", "Kubernetes"]
+        analysis["architecture_suggestion"] = "Microservices with ML Pipeline"
+    elif "Web" in project_type:
+        analysis["tech_recommendations"] = ["React/Next.js", "Node.js/Python", "PostgreSQL", "Redis", "Docker"]
+        analysis["architecture_suggestion"] = "Modern Jamstack Architecture"
+    elif "Mobil" in project_type:
+        analysis["tech_recommendations"] = ["React Native/Flutter", "Firebase", "GraphQL", "Redux/MobX"]
+        analysis["architecture_suggestion"] = "Clean Architecture with BLoC/MVVM"
+    
+    return analysis
+
+def generate_section_advanced(provider, model, api_key, project_type, project_idea, 
+                            section, industry, features, tech_details, progress=gr.Progress()):
+    """Gelişmiş section oluşturma"""
+    try:
+        start_time = time.time()
+        
+        # Proje analizi
+        progress(0.05, desc="Proje analiz ediliyor...")
+        analysis = analyze_project(project_type, project_idea, industry, features)
+        global project_analysis
+        project_analysis = analysis
+        
+        # Progress
+        progress(0.1, desc=f"{section.capitalize()} için akıllı prompt hazırlanıyor...")
+        
+        # Section'a göre advanced prompt seç
+        if section == 'context':
+            prompt = get_advanced_context_prompt(project_type, project_idea, tech_details)
+        elif section == 'commands':
+            context_summary = f"Proje {len(generated_files['context'])} context dosyası içeriyor"
+            prompt = get_advanced_commands_prompt(project_type, project_idea, context_summary)
+        elif section == 'prompts':
+            prompt = get_advanced_prompts_prompt(project_type, project_idea, tech_details)
+        
+        # Sektör gereksinimlerini ekle
+        if industry != "Diğer":
+            prompt += f"\n\nSEKTÖR GEREKSİNİMLERİ ({industry}):\n"
+            prompt += "\n".join(f"- {req}" for req in analysis["industry_requirements"])
+        
+        # Token tahmini
+        prompt_tokens = len(prompt.split()) * 1.3
+        
+        progress(0.3, desc="AI ile iletişim kuruluyor...")
+        
+        # LLM çağrısı
+        llm_response = call_llm(provider, model, api_key, prompt)
+        
+        if not llm_response or "hata" in llm_response.lower():
+            return f"<p style='color:red;'>❌ Hata: {llm_response}</p>", None, None
+        
+        progress(0.6, desc="Yanıt işleniyor ve optimize ediliyor...")
+        
+        # Response analizi
+        response_tokens = len(llm_response.split()) * 1.3
+        total_tokens = prompt_tokens + response_tokens
+        
+        # Dosyaları parse et
+        parsed_files = parse_llm_output(llm_response)
+        
+        if not parsed_files:
+            return f"<p style='color:red;'>❌ Dosyalar ayrıştırılamadı.</p>", None, None
+        
+        # Kaydet
+        generated_files[section] = parsed_files
+        
+        # İstatistikleri güncelle
+        elapsed_time = time.time() - start_time
+        stats[section] = {'tokens': int(total_tokens), 'time': round(elapsed_time, 2)}
+        
+        progress(0.9, desc="Kalite kontrolü yapılıyor...")
+        
+        # Dosya listesi ve kalite skoru
+        file_count = len(parsed_files)
+        quality_score = min(100, 60 + (file_count * 4))  # Basit kalite skoru
+        
+        # Başarı mesajı
+        file_list_html = "<div style='max-height: 200px; overflow-y: auto;'>"
+        for i, (file, content) in enumerate(parsed_files.items()):
+            size_kb = len(content.encode('utf-8')) / 1024
+            file_list_html += f"""
+            <div style='padding: 5px; border-bottom: 1px solid #e5e7eb;'>
+                <span style='color: #10b981;'>✅</span> 
+                <strong>{file}</strong> 
+                <span style='color: #6b7280; font-size: 0.9em;'>({size_kb:.1f} KB)</span>
+            </div>
+            """
+        file_list_html += "</div>"
+        
+        success_msg = f"""
+<div style='background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); padding: 20px; border-radius: 12px; color: white;'>
+    <h3 style='margin-top: 0;'>✨ {section.capitalize()} Başarıyla Oluşturuldu!</h3>
+    <div style='display: grid; grid-template-columns: repeat(3, 1fr); gap: 15px; margin: 15px 0;'>
+        <div style='background: rgba(255,255,255,0.2); padding: 10px; border-radius: 8px;'>
+            <div style='font-size: 24px; font-weight: bold;'>{file_count}</div>
+            <div style='font-size: 12px; opacity: 0.9;'>Dosya Oluşturuldu</div>
+        </div>
+        <div style='background: rgba(255,255,255,0.2); padding: 10px; border-radius: 8px;'>
+            <div style='font-size: 24px; font-weight: bold;'>~{int(total_tokens)}</div>
+            <div style='font-size: 12px; opacity: 0.9;'>Token Kullanıldı</div>
+        </div>
+        <div style='background: rgba(255,255,255,0.2); padding: 10px; border-radius: 8px;'>
+            <div style='font-size: 24px; font-weight: bold;'>{elapsed_time:.1f}s</div>
+            <div style='font-size: 12px; opacity: 0.9;'>İşlem Süresi</div>
+        </div>
+    </div>
+    <div style='margin-top: 15px;'>
+        <div style='font-weight: bold; margin-bottom: 10px;'>📁 Oluşturulan Dosyalar:</div>
+        {file_list_html}
+    </div>
+    <div style='margin-top: 15px; padding: 10px; background: rgba(255,255,255,0.1); border-radius: 8px;'>
+        <span style='font-weight: bold;'>Kalite Skoru:</span> 
+        <span style='font-size: 20px;'>{quality_score}/100</span>
+    </div>
+</div>
+"""
+        
+        # Analiz raporu
+        analysis_report = f"""
+<div style='margin-top: 20px; padding: 15px; background: #f3f4f6; border-radius: 8px;'>
+    <h4 style='margin-top: 0;'>📊 Proje Analizi</h4>
+    <ul style='margin: 10px 0;'>
+        <li><strong>Karmaşıklık:</strong> {analysis['complexity']['context'] + analysis['complexity']['commands'] + analysis['complexity']['prompts']} puan</li>
+        <li><strong>Sektör:</strong> {industry}</li>
+        <li><strong>Önerilen Teknolojiler:</strong> {', '.join(analysis['tech_recommendations'][:3])}</li>
+        <li><strong>Mimari:</strong> {analysis['architecture_suggestion']}</li>
+    </ul>
+</div>
+"""
+        
+        return success_msg + analysis_report, None, analysis
+        
+    except Exception as e:
+        import traceback
+        error_detail = traceback.format_exc()
+        return f"<p style='color:red;'>❌ Hata: {str(e)}</p><pre>{error_detail}</pre>", None, None
+
+def download_all_professional():
+    """Profesyonel ZIP paketi oluşturur"""
+    all_files = {}
+    
+    # Dosyaları topla
+    for section in ['context', 'commands', 'prompts']:
+        if generated_files[section]:
+            all_files.update(generated_files[section])
+    
+    if not all_files:
+        return None, "<p style='color:red;'>❌ İndirilecek dosya yok.</p>"
+    
+    # README.md oluştur
+    readme_content = f"""# {project_analysis.get('project_name', 'Project')} - Context Engineering
+
+## 📋 Proje Özeti
+- **Tür:** {project_analysis.get('project_type', 'N/A')}
+- **Sektör:** {project_analysis.get('industry', 'N/A')}
+- **Karmaşıklık:** {project_analysis.get('complexity', {}).get('context', 0) + project_analysis.get('complexity', {}).get('commands', 0) + project_analysis.get('complexity', {}).get('prompts', 0)} puan
+
+## 📁 Dosya Yapısı
+- `context/` - Proje bağlamı ve dokümantasyon ({len(generated_files['context'])} dosya)
+- `commands/` - Otomasyon ve yönetim komutları ({len(generated_files['commands'])} dosya)  
+- `prompts/` - AI asistan prompt şablonları ({len(generated_files['prompts'])} dosya)
+
+## 🚀 Başlangıç
+1. Context dosyalarını okuyarak projeyi anlayın
+2. Commands klasöründeki setup komutlarını çalıştırın
+3. Prompts şablonlarını AI asistanınızla kullanın
+
+## 📊 İstatistikler
+- Toplam Dosya: {len(all_files)}
+- Toplam Token: ~{sum(s['tokens'] for s in stats.values())}
+- Oluşturma Süresi: {sum(s['time'] for s in stats.values()):.1f} saniye
+
+---
+Generated by Context Engineer v2.0
+"""
+    
+    all_files['README.md'] = readme_content
+    
+    # Manifest dosyası
+    manifest = {
+        "version": "2.0",
+        "generated_at": datetime.now().isoformat(),
+        "statistics": stats,
+        "project_analysis": project_analysis,
+        "file_count": {
+            "context": len(generated_files['context']),
+            "commands": len(generated_files['commands']),
+            "prompts": len(generated_files['prompts'])
+        }
+    }
+    all_files['manifest.json'] = json.dumps(manifest, indent=2)
+    
+    # ZIP oluştur
+    zip_data = create_zip_from_files(all_files)
+    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+    zip_file_path = f"./context_engineering_pro_{timestamp}.zip"
+    
+    with open(zip_file_path, "wb") as f:
+        f.write(zip_data)
+    
+    # Özet rapor
+    total_size_kb = sum(len(content.encode('utf-8')) for content in all_files.values()) / 1024
+    
+    summary = f"""
+<div style='background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); padding: 30px; border-radius: 16px; color: white;'>
+    <h2 style='margin-top: 0;'>🎉 Proje Paketi Hazır!</h2>
+    
+    <div style='display: grid; grid-template-columns: repeat(2, 1fr); gap: 20px; margin: 20px 0;'>
+        <div style='background: rgba(255,255,255,0.2); padding: 20px; border-radius: 12px;'>
+            <h3 style='margin-top: 0;'>📊 Genel İstatistikler</h3>
+            <ul style='list-style: none; padding: 0;'>
+                <li>📁 <strong>Toplam Dosya:</strong> {len(all_files)}</li>
+                <li>💾 <strong>Paket Boyutu:</strong> {total_size_kb:.1f} KB</li>
+                <li>🎯 <strong>Token Kullanımı:</strong> ~{sum(s['tokens'] for s in stats.values())}</li>
+                <li>⏱️ <strong>Toplam Süre:</strong> {sum(s['time'] for s in stats.values()):.1f}s</li>
+            </ul>
+        </div>
+        
+        <div style='background: rgba(255,255,255,0.2); padding: 20px; border-radius: 12px;'>
+            <h3 style='margin-top: 0;'>📂 Klasör Detayları</h3>
+            <ul style='list-style: none; padding: 0;'>
+                <li>📘 <strong>Context:</strong> {len(generated_files['context'])} dosya</li>
+                <li>⚡ <strong>Commands:</strong> {len(generated_files['commands'])} dosya</li>
+                <li>💡 <strong>Prompts:</strong> {len(generated_files['prompts'])} dosya</li>
+                <li>📄 <strong>Ekstra:</strong> README.md, manifest.json</li>
+            </ul>
+        </div>
+    </div>
+    
+    <div style='background: rgba(255,255,255,0.1); padding: 15px; border-radius: 8px; margin-top: 20px;'>
+        <p style='margin: 0; text-align: center; font-size: 18px;'>
+            ✨ Profesyonel context engineering paketiniz başarıyla oluşturuldu!
+        </p>
+    </div>
+</div>
+"""
+    
+    return gr.File(value=zip_file_path, visible=True), summary
+
+# Ana arayüz
+with gr.Blocks(theme=gr.themes.Soft(), css="""
+    .gradio-container {
+        font-family: 'Inter', sans-serif;
+    }
+    .gr-button-primary {
+        background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+        border: none;
+    }
+    .gr-button-secondary {
+        background: linear-gradient(135deg, #f093fb 0%, #f5576c 100%);
+        border: none;
+    }
+""") as demo:
+    
+    gr.Markdown("""
+    # 🚀 Context Engineer Pro v2.0
+    ### Enterprise-Grade AI-Powered Project Structure Generator
+    
+    Projeleriniz için **akıllı**, **dinamik** ve **sektöre özgü** context engineering yapıları oluşturun.
+    """)
+    
+    with gr.Tab("🎯 Proje Bilgileri"):
+        with gr.Row():
+            with gr.Column(scale=1):
+                gr.Markdown("### 🏢 Proje Detayları")
+                
+                project_type = gr.Dropdown(
+                    choices=PROJECT_TYPES,
+                    label="Proje Türü",
+                    value=PROJECT_TYPES[0]
+                )
+                
+                industry = gr.Dropdown(
+                    choices=INDUSTRIES,
+                    label="Sektör",
+                    value="Teknoloji/Yazılım"
+                )
+                
+                features = gr.CheckboxGroup(
+                    choices=PROJECT_FEATURES,
+                    label="Proje Özellikleri",
+                    value=["Kullanıcı Yönetimi"]
+                )
+                
+            with gr.Column(scale=2):
+                gr.Markdown("### 📝 Proje Açıklaması")
+                
+                project_idea_input = gr.Textbox(
+                    label="Proje Fikri",
+                    lines=6,
+                    value="Detaylı proje açıklamanızı buraya yazın..."
+                )
+                
+                tech_details_input = gr.Textbox(
+                    label="Teknik Detaylar (Opsiyonel)",
+                    lines=4,
+                    value="Kullanmayı düşündüğünüz teknolojiler, özel gereksinimler..."
+                )
+    
+    with gr.Tab("🔧 LLM Konfigürasyonu"):
+        with gr.Row():
+            with gr.Column():
+                llm_provider = gr.Dropdown(
+                    choices=list(LLM_PROVIDERS.keys()),
+                    label="AI Sağlayıcı",
+                    value="Gemini"
+                )
+                
+                llm_model = gr.Dropdown(
+                    choices=[],
+                    label="Model",
+                    interactive=False
+                )
+                
+            with gr.Column():
+                api_key_input = gr.Textbox(
+                    label="API Anahtarı",
+                    type="password"
+                )
+                
+                validate_button = gr.Button("🔐 API Doğrula", variant="secondary")
+                validation_status = gr.Markdown()
+    
+    with gr.Tab("🏗️ Yapı Oluşturma"):
+        gr.Markdown("""
+        ### 🎨 Akıllı Dosya Üretimi
+        Her bölüm, projenizin özelliklerine göre **dinamik olarak** oluşturulur.
+        """)
+        
+        with gr.Row():
+            context_btn = gr.Button("📘 Context Oluştur", variant="primary", size="lg")
+            commands_btn = gr.Button("⚡ Commands Oluştur", variant="primary", size="lg")
+            prompts_btn = gr.Button("💡 Prompts Oluştur", variant="primary", size="lg")
+        
+        with gr.Row():
+            generate_all_btn = gr.Button("🎯 Hepsini Oluştur (Sırayla)", variant="secondary")
+            analyze_btn = gr.Button("🔍 Proje Analizi", variant="secondary")
+        
+        output_display = gr.Markdown()
+        analysis_display = gr.Markdown()
+    
+    with gr.Tab("📦 İndirme & İstatistikler"):
+        with gr.Row():
+            download_btn = gr.Button("📥 Profesyonel Paket İndir", variant="primary", size="lg")
+            clear_btn = gr.Button("🗑️ Temizle", variant="secondary")
+        
+        download_file = gr.File(label="İndirilebilir Paket", visible=False)
+        stats_display = gr.Markdown()
+    
+    # Event handlers
+    def update_models(provider):
+        if provider in LLM_PROVIDERS:
+            return gr.Dropdown(
+                choices=LLM_PROVIDERS[provider].get("models", []),
+                interactive=True
+            )
+        return gr.Dropdown(choices=[], interactive=False)
+    
+    def validate_api(provider, api_key):
+        if not provider or not api_key:
+            return gr.Markdown("<p style='color:orange;'>⚠️ Sağlayıcı ve API anahtarı gerekli.</p>"), gr.Dropdown()
+        
+        is_valid, message = validate_api_key(provider, api_key)
+        if is_valid:
+            models = get_llm_models(provider, api_key)
+            return (
+                gr.Markdown(f"<p style='color:green;'>✅ {message}</p>"),
+                gr.Dropdown(choices=models, value=models[0] if models else None, interactive=True)
+            )
+        return (
+            gr.Markdown(f"<p style='color:red;'>❌ {message}</p>"),
+            gr.Dropdown(choices=[], interactive=False)
+        )
+    
+    def analyze_project_details(project_type, project_idea, industry, features):
+        analysis = analyze_project(project_type, project_idea, industry, features)
+        
+        report = f"""
+<div style='background: #f9fafb; padding: 20px; border-radius: 12px; border: 1px solid #e5e7eb;'>
+    <h3>🔍 Proje Analiz Raporu</h3>
+    
+    <div style='display: grid; grid-template-columns: repeat(2, 1fr); gap: 20px;'>
+        <div>
+            <h4>📊 Karmaşıklık Analizi</h4>
+            <ul>
+                <li>Context dosyaları: ~{analysis['complexity']['context']} adet</li>
+                <li>Command dosyaları: ~{analysis['complexity']['commands']} adet</li>
+                <li>Prompt şablonları: ~{analysis['complexity']['prompts']} adet</li>
+            </ul>
+        </div>
+        
+        <div>
+            <h4>🛠️ Teknoloji Önerileri</h4>
+            <ul>
+                {"".join(f"<li>{tech}</li>" for tech in analysis['tech_recommendations'][:5])}
+            </ul>
+        </div>
+    </div>
+    
+    <div style='margin-top: 20px;'>
+        <h4>🏗️ Önerilen Mimari</h4>
+        <p>{analysis['architecture_suggestion']}</p>
+    </div>
+    
+    {f'''
+    <div style='margin-top: 20px;'>
+        <h4>🏢 Sektör Gereksinimleri ({industry})</h4>
+        <ul>
+            {"".join(f"<li>{req}</li>" for req in analysis['industry_requirements'])}
+        </ul>
+    </div>
+    ''' if analysis['industry_requirements'] else ''}
+</div>
+"""
+        return report
+    
+    def generate_all_sequential(provider, model, api_key, project_type, project_idea, 
+                               industry, features, tech_details):
+        results = []
+        for section in ['context', 'commands', 'prompts']:
+            result, _, _ = generate_section_advanced(
+                provider, model, api_key, project_type, project_idea,
+                section, industry, features, tech_details
+            )
+            results.append(result)
+            time.sleep(2)  # Rate limiting
+        
+        return "<br><br>".join(results)
+    
+    def clear_all():
+        global generated_files, stats, project_analysis
+        generated_files = {'context': {}, 'commands': {}, 'prompts': {}}
+        stats = {'context': {'tokens': 0, 'time': 0}, 'commands': {'tokens': 0, 'time': 0}, 'prompts': {'tokens': 0, 'time': 0}}
+        project_analysis = {}
+        return gr.Markdown("✅ Tüm veriler temizlendi."), gr.File(visible=False), gr.Markdown("")
+    
+    # Wire up events
+    llm_provider.change(fn=update_models, inputs=llm_provider, outputs=llm_model)
+    validate_button.click(fn=validate_api, inputs=[llm_provider, api_key_input], outputs=[validation_status, llm_model])
+    
+    # Analyze button
+    analyze_btn.click(
+        fn=analyze_project_details,
+        inputs=[project_type, project_idea_input, industry, features],
+        outputs=analysis_display
+    )
+    
+    # Section buttons
+    context_btn.click(
+        fn=lambda p, m, a, pt, pi, i, f, t: generate_section_advanced(p, m, a, pt, pi, 'context', i, f, t),
+        inputs=[llm_provider, llm_model, api_key_input, project_type, project_idea_input, industry, features, tech_details_input],
+        outputs=[output_display, download_file, analysis_display]
+    )
+    
+    commands_btn.click(
+        fn=lambda p, m, a, pt, pi, i, f, t: generate_section_advanced(p, m, a, pt, pi, 'commands', i, f, t),
+        inputs=[llm_provider, llm_model, api_key_input, project_type, project_idea_input, industry, features, tech_details_input],
+        outputs=[output_display, download_file, analysis_display]
+    )
+    
+    prompts_btn.click(
+        fn=lambda p, m, a, pt, pi, i, f, t: generate_section_advanced(p, m, a, pt, pi, 'prompts', i, f, t),
+        inputs=[llm_provider, llm_model, api_key_input, project_type, project_idea_input, industry, features, tech_details_input],
+        outputs=[output_display, download_file, analysis_display]
+    )
+    
+    generate_all_btn.click(
+        fn=generate_all_sequential,
+        inputs=[llm_provider, llm_model, api_key_input, project_type, project_idea_input, industry, features, tech_details_input],
+        outputs=output_display
+    )
+    
+    # Download and clear
+    download_btn.click(fn=download_all_professional, outputs=[download_file, stats_display])
+    clear_btn.click(fn=clear_all, outputs=[output_display, download_file, stats_display])
+
+if __name__ == "__main__":
+    demo.launch(debug=True, share=False)