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created empty __init__.py files
Backend FastAPI ve temel dosyalar eklendi
… oluşturuldu - Temel sentetik veri yapısı tasarlandı (10 veri noktası) - Genişletilmiş veri seti oluşturuldu (37 veri noktası, 16 Telekom odaklı) - Tam fine-tuning veri seti hazırlandı (47 veri noktası) - E-ticaret ve Telekom domainlerini kapsayan 12 kategori - Backend API uyumlu tool_code formatı - Veri doğrulama ve birleştirme scriptleri - Kapsamlı dokümantasyon eklendi Kategoriler: - Kullanıcı, Ürün, Sipariş Yönetimi - Analitik, Stok, Promosyon Yönetimi - Müşteri Hizmetleri - Paket/Tarife, Fatura Yönetimi - Teknik Destek, Hat Yönetimi - İnternet/TV Hizmetleri
… oluşturuldu - Temel sentetik veri yapısı tasarlandı (10 veri noktası) - Genişletilmiş veri seti oluşturuldu (37 veri noktası, 16 Telekom odaklı) - Tam fine-tuning veri seti hazırlandı (47 veri noktası) - E-ticaret ve Telekom domainlerini kapsayan 12 kategori - Backend API uyumlu tool_code formatı - Veri doğrulama ve birleştirme scriptleri - Kapsamlı dokümantasyon eklendi Kategoriler: - Kullanıcı, Ürün, Sipariş Yönetimi - Analitik, Stok, Promosyon Yönetimi - Müşteri Hizmetleri - Paket/Tarife, Fatura Yönetimi - Teknik Destek, Hat Yönetimi - İnternet/TV Hizmetleri
- Added centralized API_MAP in api_mapping.py for flexible backend integration - Version v0.1 with temporary backend_api.* function names - Prepared for seamless v0.2 upgrade when backend API is finalized - Added helper functions for dynamic tool_code generation - Updated README with version strategy and upgrade path
- Created structured template for tracking API alignment tasks - Includes checklist for backend API analysis and data updates - Provides timeline estimates and success criteria - Facilitates systematic tracking of API changes impact on AI/ML data
- Created TurkishPreprocessor class with Zemberek integration prep - Includes fallback methods for basic Turkish text normalization - Added keyword extraction capabilities - Provides synthetic data preprocessing pipeline - Ready for Zemberek integration in day 4 tasks
This reverts commit de4fa1d.
This commit introduces the `grandmaster_dataset_generator_v3.py` script and the initial 2500-sample dataset it generated. The new script is designed to create high-quality, "Grandmaster" level training data, focusing on advanced AI assistant capabilities. It incorporates a wide range of strategies to enhance model intelligence: - **Conditional Logic & Error Handling (Strateji 4):** Enables the model to handle API errors gracefully and make decisions based on preconditions. - **Proactive Assistance & Natural Chit-Chat (Strateji 6):** Allows the model to offer unsolicited, helpful suggestions and manage non-tool-related conversations. - **Tool Chaining:** Includes complex scenarios where multiple tools are used sequentially to resolve a user's request. The generated dataset (`grandmaster_dataset_v3_*.json`) provides a rich foundation for training a more sophisticated and capable model.
- Adds `gm_dataset_generator_v4.py` script to generate datasets with emotional intelligence and proactive assistance. - Includes the generated 2500-sample `gm_dataset_v4.json` to enhance model's conversational abilities.
…qeAI/UniqeAi into feature/ai-ml/model-training
Bu commit, modelin ezber yeteneğini kırmak ve gerçek dünya koşullarına karşı dayanıklılığını artırmak için tasarlanmış "Grandmaster v3" jeneratörünü ve nihai veri setini ekler. Yeni yetenekler: - **Kaos Motoru:** Çoklu ve alakasız görevleri tek bir talepte birleştirerek dinamik senaryolar üretir. - **Kişilik Simülasyonu:** Sabırsızlık, kafa karışıklığı gibi gerçekçi kullanıcı davranışlarını diyaloglara enjekte eder. - **Bağlamsal Hafıza:** Tekrarlayan sorunları "hatırlayan" ve daha akıllı yanıtlar veren senaryolar oluşturur. - **Veri Kirletme:** Kullanıcı cümlelerine yazım hataları, argo ve kısaltmalar ekleyerek modeli gerçek dünya diline karşı eğitir.
…qeAI/UniqeAi into feature/ai-ml/model-training
…qeAI/UniqeAi into feature/ai-ml/model-training
…qeAI/UniqeAi into feature/ai-ml/model-training
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