🚀 Deploy 20260111-v0.0.4

.github/workflows/project-types/flutter/PROJECT-FLUTTER-ANDROID-PLAYSTORE-CICD.yaml

@@ -44,7 +44,7 @@ jobs:
 
       - name: Create .env file
         run: |
-          echo "${{ secrets.ENV_FILE }}" > .env
+          echo "${{ secrets.ENV }}" > .env
           echo ".env file created"
 
       - name: Set up Flutter
@@ -173,7 +173,7 @@ jobs:
       # .env 파일 생성 (보안을 위해 아티팩트가 아닌 시크릿에서 생성)
       - name: Create .env file
         run: |
-          echo "${{ secrets.ENV_FILE }}" > .env
+          echo "${{ secrets.ENV }}" > .env
           echo "✅ .env 파일 생성됨 (크기: $(wc -c < .env) bytes)"
 
       # Release Keystore 설정

.github/workflows/project-types/flutter/PROJECT-FLUTTER-ANDROID-SYNOLOGY-CICD.yaml

@@ -52,7 +52,7 @@ jobs:
       # .env 파일 생성
       - name: Create .env file from GitHub Secret
         run: |
-          echo "${{ secrets.ENV_FILE }}" > .env
+          echo "${{ secrets.ENV }}" > .env
           echo ".env file created"
           ls -la
 

CLAUDE.md

@@ -0,0 +1,94 @@
+# CLAUDE.md
+
+This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
+
+## Project Overview
+
+MapSee-AI is a Python-based SNS content data extraction pipeline that processes Instagram and YouTube content to extract place/location information. It's a FastAPI service that receives URLs, downloads media content, performs speech-to-text (STT), and uses LLM (Gemini) to extract structured place data.
+
+## Development Commands
+
+```bash
+# Install dependencies (Python 3.13+)
+uv sync
+
+# Run the development server
+uv run uvicorn src.main:app --host 0.0.0.0 --port 8001 --reload
+
+# Alternative: run directly
+uv run python -m src.main
+```
+
+### External Dependencies
+- **ffmpeg/ffprobe**: Required for audio/video processing
+- **yt-dlp**: Used for downloading Instagram/YouTube content
+
+## Architecture
+
+### Request Flow
+1. `/api/extract-places` receives `contentId` + `snsUrl`
+2. Request returns immediately (async processing)
+3. Background task runs the extraction pipeline
+4. Results sent to backend via callback URL
+
+### Pipeline Stages (workflow.py)
+```
+URL → sns_router → get_audio → get_transcription (STT) → get_video_narration → get_llm_response → callback
+       ↓
+  Platform detection (YouTube/Instagram)
+  Content type detection (video/image)
+  Download media via yt-dlp
+```
+
+### Key Components
+
+**src/apis/**: FastAPI routers
+- `place_router.py`: Main API endpoint for place extraction
+
+**src/services/**: Business logic
+- `workflow.py`: Main extraction pipeline orchestration
+- `content_router.py`: Routes to appropriate downloader based on platform/content type
+- `background_tasks.py`: Async task execution and callback handling
+- `smb_service.py`: SMB file server integration
+
+**src/services/modules/**: Processing modules
+- `llm.py`: Gemini API integration for place extraction
+- `stt.py`: Faster-Whisper speech-to-text
+
+**src/services/preprocess/**: Media preprocessing
+- `sns.py`: Instagram/YouTube content download (yt-dlp)
+- `audio.py`: FFmpeg audio extraction
+- `video.py`: Video frame extraction (OCR currently disabled)
+
+**src/models/**: Pydantic schemas
+- `ExtractionState`: TypedDict that flows through the pipeline, accumulating data at each stage
+
+**src/core/**: Configuration and utilities
+- `config.py`: Settings from .env (API keys, SMB config, etc.)
+- `exceptions.py`: CustomError class for pipeline errors
+
+### State Flow Pattern
+The pipeline uses `ExtractionState` (TypedDict) as a mutable state object that gets passed through each processing stage. Each stage updates specific fields:
+- `contentStream`/`imageStream`: Downloaded media
+- `captionText`: Post caption/description
+- `audioStream`: Extracted audio
+- `transcriptionText`: STT output
+- `ocrText`: Video text (currently disabled)
+- `result`: Final extracted places
+
+## Configuration
+
+Required environment variables in `.env`:
+- `GOOGLE_API_KEY`: Gemini API key
+- `AI_SERVER_API_KEY`: API key for this service
+- `YOUTUBE_API_KEY`: YouTube Data API key
+- `INSTAGRAM_POST_DOC_ID`, `INSTAGRAM_APP_ID`: Instagram API config
+- `BACKEND_CALLBACK_URL`, `BACKEND_API_KEY`: Callback endpoint config
+- `SMB_*`: SMB file server settings (optional)
+
+## Notes
+
+- OCR functionality is currently disabled (noted with comments throughout)
+- The service uses in-memory BytesIO streams for media processing
+- Faster-Whisper runs on CPU with int8 quantization by default
+- LLM responses are validated against Pydantic schemas using `response_json_schema`

version.yml

@@ -34,11 +34,11 @@
 # - 버전은 항상 높은 버전으로 자동 동기화됩니다
 # ===================================================================
 
-version: "0.0.3"
-version_code: 3 # app build number
+version: "0.0.4"
+version_code: 4 # app build number
 project_type: "python" # spring, flutter, react, react-native, react-native-expo, node, python, basic
 metadata:
-  last_updated: "2026-01-11 12:12:03"
+  last_updated: "2026-01-11 12:18:38"
   last_updated_by: "Cassiiopeia"
   default_branch: "main"
   integrated_from: "SUH-DEVOPS-TEMPLATE"