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Commit History
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feat: Add LongCat API as primary model with Qwen fallback + cross-map fix
249b12a
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feat: Add 3-tier quantization with auto hardware detection
- Tier 1: Qwen2.5-7B with 4-bit NF4 quantization (needs GPU 5.5GB+) - Tier 2: Qwen2.5-1.5B with 8-bit quantization (GPU or CPU) - Tier 3: Qwen2.5-0.5B bfloat16 fallback (CPU, default) - Auto-detect GPU/CPU and select optimal quantization - Auto-fallback: 7B→1.5B if GPU VRAM insufficient - Configurable via .env: QUANTIZATION=auto/4bit/8bit/none - Graceful fallback if bitsandbytes not installed - Update requirements.txt with bitsandbytes>=0.43.0 - Update Dockerfile with GPU base image optionefb4fe4
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feat: Add multi-platform social media analysis with 7 platform-specific endpoints
- Add 7 new platform analyzers: YouTube, Instagram, LinkedIn, Facebook, X/Twitter, TikTok, Pinterest - Create shared model loader with .env configurable MODEL_ID (0.5B/1.5B/7B) - Refactor services with shared JSON repair and validation utilities - Update schemas with 7 platform-specific Pydantic response models - Add temperature tuning per platform (precise 0.3 to creative 0.45) - Implement professional error handling with safe_analyze wrapper - Add .env.example for model configuration documentation - Keep backward-compatible original /analyze-seo route38098b4