From 60918f69b1467d5e0156d19a957e76ea6938bc74 Mon Sep 17 00:00:00 2001 From: puke Date: Sat, 25 Oct 2025 19:39:13 +0800 Subject: [PATCH] init --- .gitignore | 67 + README.md | 243 ++ config.example.yaml | 116 + docs/capabilities-guide.md | 346 +++ pyproject.toml | 51 + reelforge/__init__.py | 23 + reelforge/capabilities/__init__.py | 4 + reelforge/capabilities/book_fetcher.py | 173 ++ reelforge/capabilities/image.py | 141 + reelforge/capabilities/llm.py | 111 + reelforge/capabilities/tts.py | 263 ++ reelforge/cli.py | 38 + reelforge/config.py | 85 + reelforge/config_manager.py | 281 ++ reelforge/core/__init__.py | 4 + reelforge/core/config_manager.py | 173 ++ reelforge/core/conventions.py | 117 + reelforge/core/discovery.py | 119 + reelforge/core/mcp_server.py | 9 + reelforge/i18n/__init__.py | 117 + reelforge/i18n/locales/en_US.json | 159 ++ reelforge/i18n/locales/zh_CN.json | 159 ++ reelforge/llm_presets.py | 74 + reelforge/models/progress.py | 51 + reelforge/models/storyboard.py | 119 + reelforge/prompts/__init__.py | 4 + reelforge/prompts/image_prompt_template.py | 174 ++ reelforge/prompts/narration_template.py | 323 +++ reelforge/service.py | 157 + reelforge/services/__init__.py | 40 + reelforge/services/base.py | 85 + reelforge/services/book_fetcher.py | 221 ++ reelforge/services/book_video.py | 464 +++ reelforge/services/book_video_workflow.py | 454 +++ reelforge/services/final_image_prompt.py | 206 ++ reelforge/services/frame_composer.py | 166 ++ reelforge/services/frame_html.py | 131 + reelforge/services/image.py | 75 + reelforge/services/image_prompt_generator.py | 149 + reelforge/services/llm.py | 97 + reelforge/services/narration_generator.py | 200 ++ reelforge/services/storyboard_processor.py | 299 ++ reelforge/services/tts.py | 103 + reelforge/services/video.py | 563 ++++ reelforge/services/video/compositor.py | 405 +++ reelforge/utils/__init__.py | 3 + reelforge/utils/os_util.py | 167 ++ start_web.sh | 19 + templates/README.md | 274 ++ templates/classic.html | 541 ++++ templates/modern.html | 572 ++++ templates/neon.html | 936 ++++++ uv.lock | 2684 ++++++++++++++++++ web.py | 789 +++++ workflows/t2i_by_local_flux.json | 208 ++ 55 files changed, 13552 insertions(+) create mode 100644 .gitignore create mode 100644 README.md create mode 100644 config.example.yaml create mode 100644 docs/capabilities-guide.md create mode 100644 pyproject.toml create mode 100644 reelforge/__init__.py create mode 100644 reelforge/capabilities/__init__.py create mode 100644 reelforge/capabilities/book_fetcher.py create mode 100644 reelforge/capabilities/image.py create mode 100644 reelforge/capabilities/llm.py create mode 100644 reelforge/capabilities/tts.py create mode 100644 reelforge/cli.py create mode 100644 reelforge/config.py create mode 100644 reelforge/config_manager.py create mode 100644 reelforge/core/__init__.py create mode 100644 reelforge/core/config_manager.py create mode 100644 reelforge/core/conventions.py create mode 100644 reelforge/core/discovery.py create mode 100644 reelforge/core/mcp_server.py create mode 100644 reelforge/i18n/__init__.py create mode 100644 reelforge/i18n/locales/en_US.json create mode 100644 reelforge/i18n/locales/zh_CN.json create mode 100644 reelforge/llm_presets.py create mode 100644 reelforge/models/progress.py create mode 100644 reelforge/models/storyboard.py create mode 100644 reelforge/prompts/__init__.py create mode 100644 reelforge/prompts/image_prompt_template.py create mode 100644 reelforge/prompts/narration_template.py create mode 100644 reelforge/service.py create mode 100644 reelforge/services/__init__.py create mode 100644 reelforge/services/base.py create mode 100644 reelforge/services/book_fetcher.py create mode 100644 reelforge/services/book_video.py create mode 100644 reelforge/services/book_video_workflow.py create mode 100644 reelforge/services/final_image_prompt.py create mode 100644 reelforge/services/frame_composer.py create mode 100644 reelforge/services/frame_html.py create mode 100644 reelforge/services/image.py create mode 100644 reelforge/services/image_prompt_generator.py create mode 100644 reelforge/services/llm.py create mode 100644 reelforge/services/narration_generator.py create mode 100644 reelforge/services/storyboard_processor.py create mode 100644 reelforge/services/tts.py create mode 100644 reelforge/services/video.py create mode 100644 reelforge/services/video/compositor.py create mode 100644 reelforge/utils/__init__.py create mode 100644 reelforge/utils/os_util.py create mode 100755 start_web.sh create mode 100644 templates/README.md create mode 100644 templates/classic.html create mode 100644 templates/modern.html create mode 100644 templates/neon.html create mode 100644 uv.lock create mode 100644 web.py create mode 100644 workflows/t2i_by_local_flux.json diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..2bb4250 --- /dev/null +++ b/.gitignore @@ -0,0 +1,67 @@ +# Python +__pycache__/ +*.py[cod] +*$py.class +*.so +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +*.egg-info/ +.installed.cfg +*.egg + +# Virtual environments +venv/ +ENV/ +env/ +.venv/ + +# IDEs +.vscode/ +.idea/ +*.swp +*.swo +*~ +.cursorrules +.cursorignore + +# OS +.DS_Store +Thumbs.db + +# Config files with sensitive data +config.yaml +.env + +# Logs +*.log + +# Test outputs +test_outputs/ +*.mp4 +*.mp3 +*.wav +*.bak +test_*.py + +# Temp files +temp/ +tmp/ +.cache/ + +data +output + +plans/ +examples/ +repositories/ diff --git a/README.md b/README.md new file mode 100644 index 0000000..e105d77 --- /dev/null +++ b/README.md @@ -0,0 +1,243 @@ +# ReelForge 🔨 + +> **Forge Your Perfect Reel Engine** +> +> The modular video creation platform where every creator forges differently. + +[![License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE) +[![Python](https://img.shields.io/badge/python-3.11+-blue.svg)](https://www.python.org/downloads/) + +[English](README.md) | [简体中文](README_CN.md) + +--- + +## 🔥 What is ReelForge? + +ReelForge is not just another video generation tool. + +**It's a forge** - where you choose your materials (LLM, TTS, image generators), +heat them in your fire (configuration), and hammer them into your perfect +video creation engine. + +### vs Traditional Tools + +``` +Traditional Tools ReelForge +━━━━━━━━━━━━━━━ ━━━━━━━━━━━━ +Fixed workflow → Modular & Customizable +One-size-fits-all → Forge Your Own +Closed system → Open & Extensible +``` + +--- + +## ⚒️ Core Philosophy + +**Every creator forges differently.** + +- 🎯 **Modular by Design** - Swap TTS, image gen, frame templates +- 🔧 **Plug & Play** - Use built-in or bring your own +- 🎨 **DIY Workflows** - Customize every step of generation +- 🌐 **Open Source** - Community-driven and transparent + +--- + +## 🚀 Quick Start + +### Installation + +```bash +# Clone the repository +git clone https://github.com/YOUR_USERNAME/ReelForge.git +cd ReelForge + +# Install dependencies with uv +uv sync + +# Copy config example +cp config.example.yaml config.yaml + +# Edit config.yaml and fill in your API keys +``` + +### Your First Forge + +```bash +# Run the web interface +uv run python web.py + +# Or use CLI +uv run reelforge --help +``` + +### Programmatic Usage + +```python +from reelforge.service import reelforge + +# Initialize +await reelforge.initialize() + +# Generate a video +result = await reelforge.book_video_workflow.generate( + book_name="Atomic Habits", + n_storyboard=5 +) + +print(f"Forged: {result.video_path}") +``` + +--- + +## 🔨 What Makes ReelForge Different? + +### 1. **Truly Modular Architecture** + +Swap components like changing tools in your forge: + +```yaml +# config.yaml +llm: + api_key: your_key + model: qwen-max + +tts: + default: edge # or azure, elevenlabs + +image: + default: comfykit + comfykit: + comfyui_url: http://localhost:8188 +``` + +### 2. **Capability-Based System** + +Every capability follows a simple naming convention: + +``` +{type}_{id} + +Examples: + llm_qwen → LLM capability, ID: qwen + tts_edge → TTS capability, ID: edge + image_comfykit → Image capability, ID: comfykit +``` + +### 3. **Storyboard-Based Generation** + +Unlike simple template filling, ReelForge uses AI to: +- Understand your topic deeply +- Generate narrative storyboards +- Create scene-by-scene visuals +- Compose professional videos + +--- + +## 🏗️ Architecture + +``` +ReelForge Core +├── Capabilities (Pluggable) +│ ├── LLM (OpenAI, Qwen, Ollama, ...) +│ ├── TTS (Edge, Azure, ElevenLabs, ...) +│ ├── Image (ComfyUI, SD, DALL-E, ...) +│ └── Custom (Your own!) +├── Services (Composable) +│ ├── Narration Generator +│ ├── Image Prompt Generator +│ ├── Storyboard Processor +│ ├── Frame Composer +│ └── Video Compositor +└── Workflows (Customizable) + └── Define your own pipeline +``` + +--- + +## 🎨 Built-in Capabilities + +### LLM (Large Language Models) + +| Provider | ID | API Key Required | +|----------|----|----| +| 通义千问 | `qwen` | ✅ DASHSCOPE_API_KEY | +| OpenAI GPT | `openai` | ✅ OPENAI_API_KEY | +| DeepSeek | `deepseek` | ✅ DEEPSEEK_API_KEY | +| Ollama | `ollama` | ❌ No (runs locally) | + +### TTS (Text-to-Speech) + +| Provider | ID | Features | +|----------|----|----| +| Edge TTS | `edge` | Free, Multiple voices | +| Azure TTS | `azure` | Premium quality | + +### Image Generation + +| Provider | ID | Features | +|----------|----|----| +| ComfyKit | `comfykit` | Custom workflows, Local | +| (More coming) | - | - | + +--- + +## 📚 Examples + +Check out the `examples/` directory: + +- `generate_video_simple.py` - Basic video generation +- `generate_video_with_bgm.py` - Add background music +- `generate_video_with_image_style.py` - Custom image styles +- `generate_video_custom.py` - Full customization + +--- + +## 🤝 Contributing + +ReelForge is **community-driven**. + +- 🐛 [Report bugs](https://github.com/YOUR_USERNAME/ReelForge/issues) +- 💡 [Request features](https://github.com/YOUR_USERNAME/ReelForge/discussions) +- 🔧 [Build components](CONTRIBUTING.md) +- 🎨 Share your forge configurations + +--- + +## 🗺️ Roadmap + +- [x] Core modular architecture +- [x] Built-in LLM/TTS/Image capabilities +- [x] Storyboard-based generation +- [x] Web interface (Streamlit) +- [ ] Visual forge builder +- [ ] Community forge marketplace +- [ ] Plugin ecosystem +- [ ] Cloud hosting + +--- + +## 📄 License + +MIT License - see [LICENSE](LICENSE) + +--- + +## 🙏 Acknowledgments + +Built with ❤️ by the creator community. + +Inspired by: +- [MoneyPrinterTurbo](https://github.com/harry0703/MoneyPrinterTurbo) +- [NarratoAI](https://github.com/linyqh/NarratoAI) + +--- + +

+ Forge Your Way +
+ Every creator forges differently. What will you forge? +

+ +--- + +**Star us if you like what we're building!** ⭐ diff --git a/config.example.yaml b/config.example.yaml new file mode 100644 index 0000000..50b7a16 --- /dev/null +++ b/config.example.yaml @@ -0,0 +1,116 @@ +# ReelForge Configuration Example +# 复制此文件为 config.yaml 并填入你的配置 + +# Project name +project_name: ReelForge + +# ==================== LLM Configuration ==================== +# Simple 3-field configuration - works with any OpenAI SDK compatible LLM +# +# Popular choices (copy one of these): +# +# Qwen Max (推荐中文): +# api_key: "sk-xxx" +# base_url: "https://dashscope.aliyuncs.com/compatible-mode/v1" +# model: "qwen-max" +# # Get API key: https://dashscope.console.aliyun.com/apiKey +# +# OpenAI GPT-4o: +# api_key: "sk-xxx" +# base_url: "https://api.openai.com/v1" +# model: "gpt-4o" +# # Get API key: https://platform.openai.com/api-keys +# +# Claude Sonnet 4: +# api_key: "sk-ant-xxx" +# base_url: "https://api.anthropic.com/v1/" +# model: "claude-sonnet-4-5" +# # Get API key: https://console.anthropic.com/settings/keys +# +# DeepSeek (超高性价比): +# api_key: "sk-xxx" +# base_url: "https://api.deepseek.com" +# model: "deepseek-chat" +# # Get API key: https://platform.deepseek.com/api_keys +# +# Ollama (本地免费): +# api_key: "ollama" # Any value works +# base_url: "http://localhost:11434/v1" +# model: "llama3.2" +# # Install: https://ollama.com/download +# # Then: ollama pull llama3.2 +# +llm: + api_key: "" # Fill in your API key + base_url: "" # LLM API endpoint + model: "" # Model name + +# ==================== TTS Configuration ==================== +tts: + default: edge + + # Edge TTS - Free, good quality + edge: + # No configuration needed + + # Azure TTS - Premium quality (optional) + # azure: + # api_key: your_azure_key + # region: eastus + # voice: zh-CN-XiaoxiaoNeural + +# ==================== Image Generation Configuration ==================== +image: + default: comfykit + + # ComfyKit - Local or cloud ComfyUI + comfykit: + comfyui_url: http://127.0.0.1:8188 # Local ComfyUI server + # runninghub_api_key: "" # Optional: RunningHub cloud API key + +# ==================== Book Fetcher Configuration ==================== +book_fetcher: + default: google + + # Google Books API (free, no key needed, works for English/Chinese books) + # Will automatically fallback to LLM if API fails or book not found + google: + # No configuration needed + + # Douban (requires custom implementation) + douban: + # Implement your own logic in reelforge/capabilities/book_fetcher.py + +# ==================== External MCP Servers (Optional) ==================== +mcp_servers: [] + # Example: Add custom MCP server + # - name: custom_llm_server + # url: http://localhost:8080/mcp + # protocol: sse + # enabled: true + # description: My custom LLM server + + # Example: Add Pixelle MCP server + # - name: pixelle + # url: http://localhost:8888/mcp + # protocol: sse + # enabled: false + # description: Pixelle image generation + +# ==================== Notes ==================== +# 1. LLM Configuration: +# - Simple 3-field config: api_key, base_url, model +# - Works with ANY OpenAI SDK compatible LLM +# - Popular choices listed in comments above +# - Switch LLM: just copy-paste different values from comments +# - WebUI provides quick preset selection +# +# 2. Ollama (Recommended for Privacy): +# - FREE: No API costs +# - PRIVATE: Data never leaves your machine +# - Install: https://ollama.com/download +# - Usage: ollama pull llama3.2 +# +# 3. Security: +# - Never commit config.yaml to version control +# - All sensitive data (API keys) should stay local diff --git a/docs/capabilities-guide.md b/docs/capabilities-guide.md new file mode 100644 index 0000000..d09a2ab --- /dev/null +++ b/docs/capabilities-guide.md @@ -0,0 +1,346 @@ +# ReelForge Capabilities Guide + +> Complete guide to using LLM, TTS, and Image generation capabilities + +## Overview + +ReelForge provides three core AI capabilities: +- **LLM**: Text generation using LiteLLM (supports 100+ models) +- **TTS**: Text-to-speech using Edge TTS (free, 400+ voices) +- **Image**: Image generation using ComfyKit (local or cloud) + +## Quick Start + +```python +from reelforge.service import reelforge + +# LLM - Generate text +answer = await reelforge.llm("Summarize 'Atomic Habits' in 3 sentences") + +# TTS - Generate speech +audio_path = await reelforge.tts("Hello, world!") + +# Image - Generate images +image_url = await reelforge.image( + workflow="workflows/book_cover_simple.json", + prompt="minimalist book cover design" +) +``` + +--- + +## 1. LLM (Large Language Model) + +### Configuration + +Edit `config.yaml`: + +```yaml +llm: + default: qwen # Choose: qwen, openai, deepseek, ollama + + qwen: + api_key: "your-dashscope-api-key" + base_url: "https://dashscope.aliyuncs.com/compatible-mode/v1" + model: "openai/qwen-max" + + openai: + api_key: "your-openai-api-key" + model: "gpt-4" + + deepseek: + api_key: "your-deepseek-api-key" + base_url: "https://api.deepseek.com" + model: "openai/deepseek-chat" + + ollama: + base_url: "http://localhost:11434" + model: "ollama/llama3.2" +``` + +### Usage + +```python +# Basic usage +answer = await reelforge.llm("What is machine learning?") + +# With parameters +answer = await reelforge.llm( + prompt="Explain atomic habits", + temperature=0.7, # 0.0-2.0 (lower = more deterministic) + max_tokens=2000 +) + +# Check active LLM +print(f"Using: {reelforge.llm.active}") +print(f"Available: {reelforge.llm.available}") +``` + +### Environment Variables (Alternative) + +Instead of `config.yaml`, you can use environment variables: + +```bash +# Qwen +export DASHSCOPE_API_KEY="your-key" + +# OpenAI +export OPENAI_API_KEY="your-key" + +# DeepSeek +export DEEPSEEK_API_KEY="your-key" +``` + +--- + +## 2. TTS (Text-to-Speech) + +### Configuration + +Edit `config.yaml`: + +```yaml +tts: + default: edge + + edge: + # No configuration needed - free to use! +``` + +### Usage + +```python +# Basic usage (auto-generates temp path) +audio_path = await reelforge.tts("Hello, world!") +# Returns: "temp/abc123def456.mp3" + +# With Chinese text +audio_path = await reelforge.tts( + text="你好，世界！", + voice="zh-CN-YunjianNeural" +) + +# With custom parameters +audio_path = await reelforge.tts( + text="Welcome to ReelForge", + voice="en-US-JennyNeural", + rate="+20%", # Speed: +50% = faster, -20% = slower + volume="+0%", + pitch="+0Hz" +) + +# Specify output path +audio_path = await reelforge.tts( + text="Hello", + output_path="output/greeting.mp3" +) +``` + +### Popular Voices + +**Chinese:** +- `zh-CN-YunjianNeural` (male, default) +- `zh-CN-XiaoxiaoNeural` (female) +- `zh-CN-YunxiNeural` (male) +- `zh-CN-XiaoyiNeural` (female) + +**English:** +- `en-US-JennyNeural` (female) +- `en-US-GuyNeural` (male) +- `en-GB-SoniaNeural` (female, British) + +### List All Voices + +```python +# Get all available voices +voices = await reelforge.tts.list_voices() + +# Get Chinese voices only +voices = await reelforge.tts.list_voices(locale="zh-CN") + +# Get English voices only +voices = await reelforge.tts.list_voices(locale="en-US") +``` + +--- + +## 3. Image Generation + +### Configuration + +Edit `config.yaml`: + +```yaml +image: + default: comfykit + + comfykit: + # Local ComfyUI (optional, default: http://127.0.0.1:8188) + comfyui_url: "http://127.0.0.1:8188" + + # RunningHub cloud (optional) + runninghub_api_key: "rh-key-xxx" +``` + +### Usage + +```python +# Basic usage (local ComfyUI) +image_url = await reelforge.image( + workflow="workflows/book_cover_simple.json", + prompt="minimalist book cover design, blue and white" +) + +# With full parameters +image_url = await reelforge.image( + workflow="workflows/book_cover_simple.json", + prompt="book cover for 'Atomic Habits', professional, minimalist", + negative_prompt="ugly, blurry, low quality", + width=1024, + height=1536, + steps=20, + seed=42 +) + +# Using RunningHub cloud +image_url = await reelforge.image( + workflow="12345", # RunningHub workflow ID + prompt="a beautiful landscape" +) + +# Check active generator +print(f"Using: {reelforge.image.active}") +``` + +### Environment Variables (Alternative) + +```bash +# Local ComfyUI +export COMFYUI_BASE_URL="http://127.0.0.1:8188" + +# RunningHub cloud +export RUNNINGHUB_API_KEY="rh-key-xxx" +``` + +### Workflow DSL + +ReelForge uses ComfyKit's DSL for workflow parameters: + +```json +{ + "6": { + "class_type": "CLIPTextEncode", + "_meta": { + "title": "$prompt!" + }, + "inputs": { + "text": "default prompt", + "clip": ["4", 1] + } + } +} +``` + +**DSL Markers:** +- `$param!` - Required parameter +- `$param` - Optional parameter +- `$param~` - Upload parameter (for images/audio/video) +- `$output.name` - Output variable + +--- + +## Combined Workflow Example + +Generate a complete book cover with narration: + +```python +import asyncio +from reelforge.service import reelforge + +async def create_book_content(book_title, author): + """Generate book summary, audio, and cover image""" + + # 1. Generate book summary with LLM + summary = await reelforge.llm( + prompt=f"Write a compelling 2-sentence summary for a book titled '{book_title}' by {author}", + max_tokens=100 + ) + print(f"Summary: {summary}") + + # 2. Generate audio narration with TTS + audio_path = await reelforge.tts( + text=summary, + voice="en-US-JennyNeural" + ) + print(f"Audio: {audio_path}") + + # 3. Generate book cover image + image_url = await reelforge.image( + workflow="workflows/book_cover_simple.json", + prompt=f"book cover for '{book_title}' by {author}, professional, modern design", + width=1024, + height=1536 + ) + print(f"Cover: {image_url}") + + return { + "summary": summary, + "audio": audio_path, + "cover": image_url + } + +# Run +result = asyncio.run(create_book_content("Atomic Habits", "James Clear")) +``` + +--- + +## Troubleshooting + +### LLM Issues + +**"API key not found"** +- Make sure you've set the API key in `config.yaml` or environment variables +- For Qwen: `DASHSCOPE_API_KEY` +- For OpenAI: `OPENAI_API_KEY` +- For DeepSeek: `DEEPSEEK_API_KEY` + +**"Connection error"** +- Check `base_url` in config +- Verify API endpoint is accessible +- For Ollama, make sure server is running (`ollama serve`) + +### TTS Issues + +**"SSL error"** +- Edge TTS is free but requires internet connection +- SSL verification is disabled by default for development + +### Image Issues + +**"ComfyUI connection refused"** +- Make sure ComfyUI is running at http://127.0.0.1:8188 +- Or configure RunningHub API key for cloud execution + +**"Workflow file not found"** +- Check workflow path is correct +- Use relative path from project root: `workflows/your_workflow.json` + +**"No images generated"** +- Check workflow has `SaveImage` node +- Verify workflow parameters are correct +- Check ComfyUI logs for errors + +--- + +## Next Steps + +- See `/examples/` directory for complete examples +- Run `python test_integration.py` to test all capabilities +- Create custom workflows in `/workflows/` directory +- Check ComfyKit documentation: https://puke3615.github.io/ComfyKit + +--- + +**Happy creating with ReelForge!** 📚🎬 + diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..85d1cee --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,51 @@ +[project] +name = "reelforge" +version = "0.1.0" +description = "The modular video creation platform - Forge your perfect reel engine" +authors = [ + {name = "ReelForge Team"} +] +readme = "README.md" +requires-python = ">=3.11" +dependencies = [ + "fastmcp>=2.0.0", + "pydantic>=2.0.0", + "loguru>=0.7.0", + "pyyaml>=6.0.0", + "edge-tts>=7.2.3", + "certifi>=2025.10.5", + "comfykit>=0.1.0", + "ffmpeg-python>=0.2.0", + "httpx>=0.28.1", + "pillow>=10.0.0,<12", + "html2image>=2.0.7", + "streamlit>=1.40.0", + "openai>=2.6.0", +] + +[project.optional-dependencies] +dev = [ + "pytest>=8.0.0", + "pytest-asyncio>=0.23.0", + "ruff>=0.6.0", +] + +[project.scripts] +reelforge = "reelforge.cli:main" + +[build-system] +requires = ["hatchling"] +build-backend = "hatchling.build" + +[tool.ruff] +line-length = 100 +target-version = "py311" + +[tool.ruff.lint] +select = ["E", "F", "I"] +ignore = ["E501"] + +[tool.pytest.ini_options] +asyncio_mode = "auto" +testpaths = ["tests"] + diff --git a/reelforge/__init__.py b/reelforge/__init__.py new file mode 100644 index 0000000..7cda1cb --- /dev/null +++ b/reelforge/__init__.py @@ -0,0 +1,23 @@ +""" +ReelForge - AI-powered book video generator with pluggable capabilities + +Convention-based capability system using FastMCP and LiteLLM. + +Usage: + from reelforge import reelforge + + # Initialize + await reelforge.initialize() + + # Use capabilities + answer = await reelforge.llm("Explain atomic habits") + audio = await reelforge.tts("Hello world") + book = await reelforge.book_fetcher("原则") +""" + +from reelforge.service import ReelForgeCore, reelforge + +__version__ = "0.1.0" + +__all__ = ["ReelForgeCore", "reelforge"] + diff --git a/reelforge/capabilities/__init__.py b/reelforge/capabilities/__init__.py new file mode 100644 index 0000000..3119687 --- /dev/null +++ b/reelforge/capabilities/__init__.py @@ -0,0 +1,4 @@ +""" +Built-in capabilities for ReelForge +""" + diff --git a/reelforge/capabilities/book_fetcher.py b/reelforge/capabilities/book_fetcher.py new file mode 100644 index 0000000..d1501a3 --- /dev/null +++ b/reelforge/capabilities/book_fetcher.py @@ -0,0 +1,173 @@ +""" +Book Fetcher Capabilities + +Fetch book information from various sources: +- Google Books API (free, stable, English/Chinese books) +- Douban (framework, requires custom implementation) + +Convention: Tool names must be book_fetcher_{id} + +Note: For LLM-based book info generation, use services/book_fetcher.py + which combines LLM capability with book fetcher logic. +""" + +import json +from typing import Optional + +import httpx +from loguru import logger +from pydantic import Field + +from reelforge.core.mcp_server import reelforge_mcp + + +@reelforge_mcp.tool( + description="Fetch book information from Google Books API", + meta={ + "reelforge": { + "display_name": "Google Books", + "description": "Fetch book info from Google Books (English/Chinese books)", + "is_default": True, + } + }, +) +async def book_fetcher_google( + book_name: str = Field(description="Book name"), + author: Optional[str] = Field(default=None, description="Author name (optional)"), +) -> str: + """ + Fetch book information from Google Books API + + Free API, no key required. Works for both English and Chinese books. + + Args: + book_name: Book name + author: Author name (optional, for better search results) + + Returns: + JSON string with book information: + { + "title": "Book title", + "author": "Author name", + "summary": "Book summary", + "genre": "Category", + "publication_year": "2018", + "cover_url": "https://...", + "isbn": "9781234567890" + } + + Example: + >>> info = await book_fetcher_google("Atomic Habits") + >>> book = json.loads(info) + >>> print(book['title']) + Atomic Habits + """ + logger.info(f"Fetching book info from Google Books: {book_name}") + + try: + # Build search query + query = book_name + if author: + query += f"+inauthor:{author}" + + # Call Google Books API + async with httpx.AsyncClient() as client: + url = "https://www.googleapis.com/books/v1/volumes" + params = { + "q": query, + "maxResults": 1, + "langRestrict": "zh-CN,en", # Chinese and English + } + + response = await client.get(url, params=params, timeout=10.0) + response.raise_for_status() + data = response.json() + + if "items" not in data or len(data["items"]) == 0: + logger.warning(f"No results found for: {book_name}") + raise ValueError(f"No results found for book: {book_name}") + + # Parse first result + item = data["items"][0] + volume_info = item.get("volumeInfo", {}) + + book_info = { + "title": volume_info.get("title", book_name), + "author": ", ".join(volume_info.get("authors", [author or "Unknown"])), + "summary": volume_info.get("description", "No description available"), + "genre": ", ".join(volume_info.get("categories", ["Uncategorized"])), + "publication_year": volume_info.get("publishedDate", "")[:4] if volume_info.get("publishedDate") else "", + "cover_url": volume_info.get("imageLinks", {}).get("thumbnail", ""), + "isbn": next( + (id_info["identifier"] for id_info in volume_info.get("industryIdentifiers", []) + if id_info["type"] in ["ISBN_13", "ISBN_10"]), + "" + ), + } + + logger.info(f"✅ Successfully fetched from Google Books: {book_info['title']}") + return json.dumps(book_info, ensure_ascii=False, indent=2) + + except httpx.HTTPError as e: + logger.error(f"HTTP error fetching from Google Books: {e}") + raise + except Exception as e: + logger.error(f"Error fetching from Google Books: {e}") + raise + + +@reelforge_mcp.tool( + description="Fetch book information from Douban (requires custom implementation)", + meta={ + "reelforge": { + "display_name": "豆瓣读书 (Douban)", + "description": "Fetch book info from Douban (best for Chinese books) - requires custom implementation", + "is_default": False, + } + }, +) +async def book_fetcher_douban( + book_name: str = Field(description="Book name"), + author: Optional[str] = Field(default=None, description="Author name (optional)"), +) -> str: + """ + Fetch book information from Douban + + NOTE: Douban official API is closed. This is a framework for custom implementation. + + You can implement this using: + 1. Third-party Douban API services + 2. Web scraping (be careful with rate limits) + 3. Cached database + + Args: + book_name: Book name + author: Author name (optional) + + Returns: + JSON string with book information + + Example implementation: + ```python + # Option 1: Use third-party API + async with httpx.AsyncClient() as client: + url = "https://your-douban-api-service.com/search" + params = {"q": book_name} + response = await client.get(url, params=params) + data = response.json() + return json.dumps(data, ensure_ascii=False) + + # Option 2: Web scraping + # Use BeautifulSoup + httpx to scrape Douban pages + + # Option 3: Pre-built database + # Query your own book database + ``` + """ + logger.error("book_fetcher_douban is not implemented") + logger.info("To implement: Edit reelforge/capabilities/book_fetcher.py and add your logic") + raise NotImplementedError( + "book_fetcher_douban requires custom implementation. " + "Please edit reelforge/capabilities/book_fetcher.py to add your Douban API integration." + ) + diff --git a/reelforge/capabilities/image.py b/reelforge/capabilities/image.py new file mode 100644 index 0000000..860af9e --- /dev/null +++ b/reelforge/capabilities/image.py @@ -0,0 +1,141 @@ +""" +Image Generation Capabilities using ComfyKit + +ComfyKit provides unified access to ComfyUI workflows: +- Local ComfyUI execution +- RunningHub cloud execution +- Flexible workflow-based generation +- Structured result handling + +Convention: Tool names must be image_{id} +""" + +import os +from typing import Any + +from comfykit import ComfyKit +from loguru import logger +from pydantic import Field + +from reelforge.core.mcp_server import reelforge_mcp + + +@reelforge_mcp.tool( + description="Generate images using ComfyKit (local ComfyUI or RunningHub cloud)", + meta={ + "reelforge": { + "display_name": "ComfyKit Image Generator", + "description": "基于 ComfyKit 的图像生成 - 支持本地和云端", + "is_default": True, + } + }, +) +async def image_comfykit( + workflow: str = Field(description="Workflow path, ID, or URL"), + comfyui_url: str | None = Field(default=None, description="ComfyUI server URL (default: http://127.0.0.1:8188)"), + runninghub_api_key: str | None = Field(default=None, description="RunningHub API key (for cloud execution)"), + # Common workflow parameters + prompt: str | None = Field(default=None, description="Image generation prompt"), + width: int | None = Field(default=None, description="Image width"), + height: int | None = Field(default=None, description="Image height"), + negative_prompt: str | None = Field(default=None, description="Negative prompt"), + steps: int | None = Field(default=None, description="Sampling steps"), + seed: int | None = Field(default=None, description="Random seed"), + cfg: float | None = Field(default=None, description="CFG scale"), + sampler: str | None = Field(default=None, description="Sampler name"), +) -> str: + """ + Generate image using ComfyKit + + Supports both local ComfyUI and RunningHub cloud execution. + Returns the first generated image URL. + + Environment variables (optional): + - COMFYUI_BASE_URL: ComfyUI server URL + - RUNNINGHUB_API_KEY: RunningHub API key + + Example: + # Local ComfyUI (default) + image_url = await image_comfykit( + workflow="workflows/book_cover.json", + title="Atomic Habits", + author="James Clear" + ) + + # RunningHub cloud + image_url = await image_comfykit( + workflow="12345", # RunningHub workflow ID + runninghub_api_key="rh-key-xxx", + prompt="a beautiful landscape" + ) + + # Custom ComfyUI server + image_url = await image_comfykit( + workflow="workflows/text2img.json", + comfyui_url="http://192.168.1.100:8188", + prompt="a cute cat" + ) + """ + logger.debug(f"Generating image with workflow: {workflow}") + + try: + # Initialize ComfyKit + kit_config = {} + + # Local ComfyUI configuration + if comfyui_url: + kit_config["comfyui_url"] = comfyui_url + elif os.getenv("COMFYUI_BASE_URL"): + kit_config["comfyui_url"] = os.getenv("COMFYUI_BASE_URL") + + # RunningHub cloud configuration + if runninghub_api_key: + kit_config["runninghub_api_key"] = runninghub_api_key + elif os.getenv("RUNNINGHUB_API_KEY"): + kit_config["runninghub_api_key"] = os.getenv("RUNNINGHUB_API_KEY") + + kit = ComfyKit(**kit_config) + + # Build workflow parameters + workflow_params = {} + if prompt is not None: + workflow_params["prompt"] = prompt + if width is not None: + workflow_params["width"] = width + if height is not None: + workflow_params["height"] = height + if negative_prompt is not None: + workflow_params["negative_prompt"] = negative_prompt + if steps is not None: + workflow_params["steps"] = steps + if seed is not None: + workflow_params["seed"] = seed + if cfg is not None: + workflow_params["cfg"] = cfg + if sampler is not None: + workflow_params["sampler"] = sampler + + logger.debug(f"Workflow parameters: {workflow_params}") + + # Execute workflow + result = await kit.execute(workflow, workflow_params) + + # Check execution status + if result.status != "completed": + error_msg = result.msg or "Unknown error" + logger.error(f"Image generation failed: {error_msg}") + raise Exception(f"Image generation failed: {error_msg}") + + # Return first image URL + if result.images: + image_url = result.images[0] + logger.info(f"Generated image: {image_url}") + return image_url + else: + logger.error("No images generated") + raise Exception("No images generated") + + except Exception as e: + logger.error(f"ComfyKit error: {e}") + raise + diff --git a/reelforge/capabilities/llm.py b/reelforge/capabilities/llm.py new file mode 100644 index 0000000..f1215ea --- /dev/null +++ b/reelforge/capabilities/llm.py @@ -0,0 +1,111 @@ +""" +LLM Capabilities using OpenAI SDK + +All LLM providers that follow OpenAI SDK protocol are supported: +- OpenAI (gpt-4o, gpt-4o-mini, gpt-3.5-turbo) +- Alibaba Qwen (qwen-max, qwen-plus, qwen-turbo) +- Anthropic Claude (claude-sonnet-4-5, claude-opus-4, claude-haiku-4) +- DeepSeek (deepseek-chat) +- Moonshot Kimi (moonshot-v1-8k, moonshot-v1-32k, moonshot-v1-128k) +- Ollama (llama3.2, qwen2.5, mistral, codellama) - FREE & LOCAL! +- Any custom provider with OpenAI-compatible API + +Convention: Unified llm_call tool for all providers +""" + +from openai import AsyncOpenAI +from loguru import logger +from pydantic import Field + +from reelforge.core.mcp_server import reelforge_mcp + + +@reelforge_mcp.tool( + description="Generate text using any OpenAI SDK compatible LLM", + meta={ + "reelforge": { + "display_name": "LLM (OpenAI SDK)", + "description": "Unified interface for all OpenAI SDK compatible LLMs", + "is_default": True, + } + }, +) +async def llm_call( + prompt: str = Field(description="The prompt to generate from"), + api_key: str = Field(description="API key for the LLM provider"), + base_url: str = Field(description="Base URL for the LLM API"), + model: str = Field(description="Model name to use"), + temperature: float = Field(default=0.7, description="Sampling temperature"), + max_tokens: int = Field(default=2000, description="Maximum tokens to generate"), +) -> str: + """ + Generate text using any OpenAI SDK compatible LLM + + This is a unified interface that works with any LLM provider + following the OpenAI SDK protocol. + + Example: + # OpenAI + result = await llm_call( + prompt="Explain quantum physics", + api_key="sk-xxx", + base_url="https://api.openai.com/v1", + model="gpt-4o" + ) + + # Qwen + result = await llm_call( + prompt="解释量子物理", + api_key="sk-xxx", + base_url="https://dashscope.aliyuncs.com/compatible-mode/v1", + model="qwen-max" + ) + + # Anthropic Claude + result = await llm_call( + prompt="Explain reasoning step by step", + api_key="sk-ant-xxx", + base_url="https://api.anthropic.com/v1/", + model="claude-sonnet-4-5" + ) + + # DeepSeek + result = await llm_call( + prompt="Explain AI", + api_key="sk-xxx", + base_url="https://api.deepseek.com", + model="deepseek-chat" + ) + + # Ollama (Local - FREE & PRIVATE!) + result = await llm_call( + prompt="Write a Python function to sort a list", + api_key="ollama", # Required but unused + base_url="http://localhost:11434/v1", + model="llama3.2" + ) + """ + logger.debug(f"LLM call: model={model}, base_url={base_url}") + + try: + client = AsyncOpenAI( + api_key=api_key, + base_url=base_url, + ) + + response = await client.chat.completions.create( + model=model, + messages=[{"role": "user", "content": prompt}], + temperature=temperature, + max_tokens=max_tokens, + ) + + result = response.choices[0].message.content + logger.debug(f"LLM response length: {len(result)} chars") + + return result + + except Exception as e: + logger.error(f"LLM call error (model={model}, base_url={base_url}): {e}") + raise + diff --git a/reelforge/capabilities/tts.py b/reelforge/capabilities/tts.py new file mode 100644 index 0000000..1c077fa --- /dev/null +++ b/reelforge/capabilities/tts.py @@ -0,0 +1,263 @@ +""" +TTS Capabilities using edge-tts + +edge-tts provides free access to Microsoft Edge's online text-to-speech service: +- 400+ voices across 100+ languages +- Natural sounding speech +- No API key required +- Free to use + +Convention: Tool names must be tts_{id} +""" + +import asyncio +import base64 +import ssl +import certifi +import edge_tts +from loguru import logger +from pydantic import Field +from aiohttp import WSServerHandshakeError, ClientResponseError + +from reelforge.core.mcp_server import reelforge_mcp + +# Global flag for SSL verification (set to False for development only) +_SSL_VERIFY_ENABLED = False + +# Retry configuration for Edge TTS (to handle 401 errors) +_RETRY_COUNT = 3 # Default retry count +_RETRY_DELAY = 2.0 # Retry delay in seconds + + +@reelforge_mcp.tool( + description="Convert text to speech using Microsoft Edge TTS - free and natural sounding", + meta={ + "reelforge": { + "display_name": "Edge TTS", + "description": "Microsoft Edge Text-to-Speech - 免费且音质自然", + "is_default": True, + } + }, +) +async def tts_edge( + text: str = Field(description="Text to convert to speech"), + voice: str = Field(default="zh-CN-YunjianNeural", description="Voice ID (e.g., zh-CN-YunjianNeural, en-US-JennyNeural)"), + rate: str = Field(default="+0%", description="Speech rate (e.g., +0%, +50%, -20%)"), + volume: str = Field(default="+0%", description="Speech volume (e.g., +0%, +50%, -20%)"), + pitch: str = Field(default="+0Hz", description="Speech pitch (e.g., +0Hz, +10Hz, -5Hz)"), + retry_count: int = Field(default=_RETRY_COUNT, description="Number of retries on failure (default: 3)"), + retry_delay: float = Field(default=_RETRY_DELAY, description="Delay between retries in seconds (default: 2.0)"), +) -> str: + """ + Convert text to speech using Microsoft Edge TTS + + This service is free and requires no API key. + Supports 400+ voices across 100+ languages. + + Returns audio data as base64-encoded string (MP3 format). + + Includes automatic retry mechanism to handle 401 authentication errors + and temporary network issues (default: 3 retries with 2s delay). + + Popular Chinese voices: + - zh-CN-YunjianNeural (male, default) + - zh-CN-XiaoxiaoNeural (female) + - zh-CN-YunxiNeural (male) + - zh-CN-XiaoyiNeural (female) + + Popular English voices: + - en-US-JennyNeural (female) + - en-US-GuyNeural (male) + - en-GB-SoniaNeural (female, British) + + Example: + audio_base64 = await tts_edge( + text="你好，世界！", + voice="zh-CN-YunjianNeural", + rate="+20%" + ) + # Decode: audio_bytes = base64.b64decode(audio_base64) + """ + logger.debug(f"Calling Edge TTS with voice: {voice}, rate: {rate}, retry_count: {retry_count}") + + last_error = None + + # Retry loop + for attempt in range(retry_count + 1): # +1 because first attempt is not a retry + try: + if attempt > 0: + logger.info(f"🔄 Retrying Edge TTS (attempt {attempt + 1}/{retry_count + 1}) after {retry_delay}s delay...") + await asyncio.sleep(retry_delay) + + # Monkey patch ssl.create_default_context if SSL verification is disabled + if not _SSL_VERIFY_ENABLED: + if attempt == 0: # Only log warning once + logger.warning("SSL verification is disabled for development. This is NOT recommended for production!") + original_create_default_context = ssl.create_default_context + + def create_unverified_context(*args, **kwargs): + ctx = original_create_default_context(*args, **kwargs) + ctx.check_hostname = False + ctx.verify_mode = ssl.CERT_NONE + return ctx + + # Temporarily replace the function + ssl.create_default_context = create_unverified_context + + try: + # Create communicate instance + communicate = edge_tts.Communicate( + text=text, + voice=voice, + rate=rate, + volume=volume, + pitch=pitch, + ) + + # Collect audio chunks + audio_chunks = [] + async for chunk in communicate.stream(): + if chunk["type"] == "audio": + audio_chunks.append(chunk["data"]) + + audio_data = b"".join(audio_chunks) + + if attempt > 0: + logger.success(f"✅ Retry succeeded on attempt {attempt + 1}") + + logger.info(f"Generated {len(audio_data)} bytes of audio data") + + # Encode as base64 for JSON serialization + audio_base64 = base64.b64encode(audio_data).decode('utf-8') + return audio_base64 + + finally: + # Restore original function if we patched it + if not _SSL_VERIFY_ENABLED: + ssl.create_default_context = original_create_default_context + + except (WSServerHandshakeError, ClientResponseError) as e: + # Network/authentication errors - retry + last_error = e + error_code = getattr(e, 'status', 'unknown') + logger.warning(f"⚠️ Edge TTS error (attempt {attempt + 1}/{retry_count + 1}): {error_code} - {e}") + + if attempt >= retry_count: + # Last attempt failed + logger.error(f"❌ All {retry_count + 1} attempts failed. Giving up.") + raise + # Otherwise, continue to next retry + + except Exception as e: + # Other errors - don't retry, raise immediately + logger.error(f"Edge TTS error (non-retryable): {e}") + raise + + # Should not reach here, but just in case + if last_error: + raise last_error + else: + raise RuntimeError("Edge TTS failed without error (unexpected)") + + +@reelforge_mcp.tool( + description="List all available voices for Edge TTS", + meta={ + "reelforge": { + "display_name": "List Edge TTS Voices", + "description": "获取所有可用的Edge TTS音色列表", + "is_default": False, + } + }, +) +async def tts_edge_list_voices( + locale: str | None = Field(default=None, description="Filter by locale (e.g., zh-CN, en-US, ja-JP)"), + retry_count: int = Field(default=_RETRY_COUNT, description="Number of retries on failure (default: 3)"), + retry_delay: float = Field(default=_RETRY_DELAY, description="Delay between retries in seconds (default: 2.0)"), +) -> list[str]: + """ + List all available voices for Edge TTS + + Returns a list of voice IDs (ShortName). + Optionally filter by locale. + + Includes automatic retry mechanism to handle network errors + (default: 3 retries with 2s delay). + + Example: + # List all voices + voices = await tts_edge_list_voices() + # Returns: ['zh-CN-YunjianNeural', 'zh-CN-XiaoxiaoNeural', ...] + + # List Chinese voices only + voices = await tts_edge_list_voices(locale="zh-CN") + # Returns: ['zh-CN-YunjianNeural', 'zh-CN-XiaoxiaoNeural', ...] + """ + logger.debug(f"Fetching Edge TTS voices, locale filter: {locale}, retry_count: {retry_count}") + + last_error = None + + # Retry loop + for attempt in range(retry_count + 1): + try: + if attempt > 0: + logger.info(f"🔄 Retrying list voices (attempt {attempt + 1}/{retry_count + 1}) after {retry_delay}s delay...") + await asyncio.sleep(retry_delay) + + # Monkey patch SSL if verification is disabled + if not _SSL_VERIFY_ENABLED: + if attempt == 0: # Only log warning once + logger.warning("SSL verification is disabled for development. This is NOT recommended for production!") + original_create_default_context = ssl.create_default_context + + def create_unverified_context(*args, **kwargs): + ctx = original_create_default_context(*args, **kwargs) + ctx.check_hostname = False + ctx.verify_mode = ssl.CERT_NONE + return ctx + + ssl.create_default_context = create_unverified_context + + try: + # Get all voices + voices = await edge_tts.list_voices() + + # Filter by locale if specified + if locale: + voices = [v for v in voices if v["Locale"].startswith(locale)] + + # Extract voice IDs (ShortName) + voice_ids = [voice["ShortName"] for voice in voices] + + if attempt > 0: + logger.success(f"✅ Retry succeeded on attempt {attempt + 1}") + + logger.info(f"Found {len(voice_ids)} voices" + (f" for locale '{locale}'" if locale else "")) + return voice_ids + + finally: + # Restore original function if we patched it + if not _SSL_VERIFY_ENABLED: + ssl.create_default_context = original_create_default_context + + except (WSServerHandshakeError, ClientResponseError) as e: + # Network/authentication errors - retry + last_error = e + error_code = getattr(e, 'status', 'unknown') + logger.warning(f"⚠️ List voices error (attempt {attempt + 1}/{retry_count + 1}): {error_code} - {e}") + + if attempt >= retry_count: + logger.error(f"❌ All {retry_count + 1} attempts failed. Giving up.") + raise + + except Exception as e: + # Other errors - don't retry, raise immediately + logger.error(f"List voices error (non-retryable): {e}") + raise + + # Should not reach here, but just in case + if last_error: + raise last_error + else: + raise RuntimeError("List voices failed without error (unexpected)") + diff --git a/reelforge/cli.py b/reelforge/cli.py new file mode 100644 index 0000000..01eedb7 --- /dev/null +++ b/reelforge/cli.py @@ -0,0 +1,38 @@ +""" +ReelForge CLI +""" + +import asyncio + +from loguru import logger + +from reelforge.app import app + + +async def test_llm(): + """Test LLM capability""" + # Initialize app + await app.initialize() + + # Test prompt + prompt = "Explain the book 'Atomic Habits' by James Clear in 3 sentences." + + logger.info(f"\n📝 Test Prompt: {prompt}\n") + + # Call LLM + result = await app.router.call("llm", prompt=prompt) + + logger.info(f"\n✨ Result:\n{result}\n") + + +def main(): + """Main CLI entry point""" + logger.info("🚀 ReelForge CLI\n") + + # Run test + asyncio.run(test_llm()) + + +if __name__ == "__main__": + main() + diff --git a/reelforge/config.py b/reelforge/config.py new file mode 100644 index 0000000..1fc0c74 --- /dev/null +++ b/reelforge/config.py @@ -0,0 +1,85 @@ +""" +Configuration system for ReelForge +""" + +import os +from pathlib import Path +from typing import Any + +import yaml +from loguru import logger + + +def load_config(config_path: str = "config.yaml") -> dict[str, Any]: + """ + Load configuration from YAML file + + User-friendly flat format (no internal conversion): + project_name: ReelForge + llm: + api_key: xxx + base_url: xxx + model: xxx + tts: + default: edge + edge: null + image: + default: comfykit + comfykit: + comfyui_url: http://xxx + + Args: + config_path: Path to config file (default: config.yaml) + + Returns: + Configuration dict (as-is from YAML) + """ + # Check if config file exists + config_file = Path(config_path) + if not config_file.exists(): + logger.warning(f"Config file not found: {config_path}") + logger.info("Using default configuration") + return _get_default_config() + + # Load config + logger.info(f"Loading config from: {config_path}") + with open(config_file, 'r', encoding='utf-8') as f: + config = yaml.safe_load(f) + + # Handle None (empty YAML file) + if config is None: + config = {} + + # Ensure project_name exists + if "project_name" not in config: + config["project_name"] = "ReelForge" + + return config + + +def _get_default_config() -> dict[str, Any]: + """Get default configuration""" + return { + "project_name": "ReelForge", + "llm": { + "api_key": "", + "base_url": "", + "model": "" + }, + "tts": { + "default": "edge", + "edge": None + }, + "image": { + "default": "comfykit", + "comfykit": { + "comfyui_url": "http://127.0.0.1:8188" + } + }, + "book_fetcher": { + "default": "google", + "google": None, + "douban": None + } + } + diff --git a/reelforge/config_manager.py b/reelforge/config_manager.py new file mode 100644 index 0000000..0828d21 --- /dev/null +++ b/reelforge/config_manager.py @@ -0,0 +1,281 @@ +""" +Configuration manager for WebUI + +Handles loading, saving, and validating configuration +from the web interface. +""" + +from pathlib import Path +from typing import Dict, Any, Optional, List +import yaml +from loguru import logger + + +class ConfigStatus: + """Configuration validation status""" + + def __init__(self): + self.is_complete: bool = True + self.missing_fields: List[str] = [] + self.warnings: List[str] = [] + + def add_missing(self, field: str): + """Add a missing required field""" + self.is_complete = False + self.missing_fields.append(field) + + def add_warning(self, message: str): + """Add a warning message""" + self.warnings.append(message) + + +class ConfigManager: + """Manage configuration for WebUI""" + + def __init__(self, config_path: str = "config.yaml"): + self.config_path = Path(config_path) + self.config: Optional[Dict[str, Any]] = None + + def load_or_create_default(self) -> Dict[str, Any]: + """ + Load config from file, or create default if not exists + + Returns: + Configuration dictionary + """ + if not self.config_path.exists(): + logger.warning("Config file not found, creating default") + self.config = self._create_default_config() + self.save() + else: + with open(self.config_path, "r", encoding="utf-8") as f: + self.config = yaml.safe_load(f) + + logger.info(f"Configuration loaded from {self.config_path}") + return self.config + + def save(self): + """Save config to file""" + with open(self.config_path, "w", encoding="utf-8") as f: + yaml.dump(self.config, f, allow_unicode=True, default_flow_style=False, sort_keys=False) + logger.info(f"Configuration saved to {self.config_path}") + + def update_from_ui(self, ui_values: Dict[str, Any]): + """ + Update config from UI form values + + Args: + ui_values: Dictionary of form values from Streamlit + """ + # Update LLM configuration + if "llm_provider" in ui_values: + provider = ui_values["llm_provider"] + self.config["llm"]["default"] = provider + + # Ensure provider config exists + if provider not in self.config["llm"]: + self.config["llm"][provider] = {} + + # Update provider-specific config + if f"llm_{provider}_api_key" in ui_values and ui_values[f"llm_{provider}_api_key"]: + self.config["llm"][provider]["api_key"] = ui_values[f"llm_{provider}_api_key"] + + if f"llm_{provider}_base_url" in ui_values and ui_values[f"llm_{provider}_base_url"]: + self.config["llm"][provider]["base_url"] = ui_values[f"llm_{provider}_base_url"] + + if f"llm_{provider}_model" in ui_values and ui_values[f"llm_{provider}_model"]: + self.config["llm"][provider]["model"] = ui_values[f"llm_{provider}_model"] + + # Update TTS configuration + if "tts_provider" in ui_values: + self.config["tts"]["default"] = ui_values["tts_provider"] + + # Update Image configuration + if "image_provider" in ui_values: + self.config["image"]["default"] = ui_values["image_provider"] + + # Update ComfyKit configuration + if "comfykit_mode" in ui_values: + if "comfykit" not in self.config["image"]: + self.config["image"]["comfykit"] = {} + + mode = ui_values["comfykit_mode"] + if mode == "local": + if "comfyui_url" in ui_values: + self.config["image"]["comfykit"]["comfyui_url"] = ui_values["comfyui_url"] + # Remove cloud config + self.config["image"]["comfykit"].pop("runninghub_api_key", None) + else: # cloud + if "runninghub_api_key" in ui_values: + self.config["image"]["comfykit"]["runninghub_api_key"] = ui_values["runninghub_api_key"] + # Remove local config + self.config["image"]["comfykit"].pop("comfyui_url", None) + + # Update Book Fetcher configuration + if "book_provider" in ui_values: + self.config["book_fetcher"]["default"] = ui_values["book_provider"] + + self.save() + + def _is_valid_api_key(self, api_key: str) -> bool: + """ + Check if an API key is valid (not empty or placeholder) + + Args: + api_key: API key to validate + + Returns: + True if valid, False if empty or placeholder + """ + if not api_key: + return False + + # Remove whitespace + api_key = api_key.strip() + + if not api_key: + return False + + # Common placeholders to reject + invalid_patterns = [ + "your_", # your_openai_api_key_here, your_dashscope_api_key_here + "replace", # replace_me, replace_with_your_key + "placeholder", + "example_key", + ] + + api_key_lower = api_key.lower() + for pattern in invalid_patterns: + if pattern in api_key_lower: + return False + + # Accept any non-empty string (allow short keys for testing/custom services) + return True + + def validate(self) -> ConfigStatus: + """ + Validate configuration completeness (simple 3-field format) + + Returns: + ConfigStatus with validation results + """ + status = ConfigStatus() + + # Check LLM configuration (simple format) + llm_config = self.config.get("llm", {}) + + # Check API key + api_key = llm_config.get("api_key", "") + if not self._is_valid_api_key(api_key): + status.add_missing("llm.api_key") + + # Check base_url + base_url = llm_config.get("base_url", "") + if not base_url or not base_url.strip(): + status.add_missing("llm.base_url") + + # Check model + model = llm_config.get("model", "") + if not model or not model.strip(): + status.add_missing("llm.model") + + return status + + def get_comfykit_mode(self) -> str: + """ + Get current ComfyKit mode + + Returns: + "local" or "cloud" + """ + comfykit_config = self.config.get("image", {}).get("comfykit", {}) + + if comfykit_config.get("runninghub_api_key"): + return "cloud" + else: + return "local" + + def get_llm_config(self) -> Dict[str, str]: + """ + Get LLM configuration (simple 3-field format) + + Returns: + Dict with api_key, base_url, model + """ + if self.config is None: + return {"api_key": "", "base_url": "", "model": ""} + + llm_config = self.config.get("llm", {}) + return { + "api_key": llm_config.get("api_key", ""), + "base_url": llm_config.get("base_url", ""), + "model": llm_config.get("model", ""), + } + + def set_llm_config(self, api_key: str, base_url: str, model: str): + """ + Set LLM configuration + + Args: + api_key: API key + base_url: Base URL + model: Model name + """ + self.config["llm"] = { + "api_key": api_key, + "base_url": base_url, + "model": model, + } + + def is_llm_configured(self) -> bool: + """ + Check if LLM is configured + + Returns: + True if all three fields are non-empty + """ + llm_config = self.get_llm_config() + return bool( + llm_config["api_key"] and llm_config["api_key"].strip() and + llm_config["base_url"] and llm_config["base_url"].strip() and + llm_config["model"] and llm_config["model"].strip() + ) + + def get_tts_providers(self) -> List[str]: + """Get list of available TTS providers""" + return ["edge"] + + def get_image_providers(self) -> List[str]: + """Get list of available image providers""" + return ["comfykit"] + + def get_book_providers(self) -> List[str]: + """Get list of available book fetcher providers""" + return ["google", "douban"] + + def _create_default_config(self) -> Dict[str, Any]: + """Create default configuration""" + return { + "project_name": "ReelForge", + "llm": { + "api_key": "", # User must fill in + "base_url": "", # User must fill in + "model": "", # User must fill in + }, + "tts": { + "default": "edge", # Edge TTS is free + "edge": {} + }, + "image": { + "default": "comfykit", + "comfykit": { + "comfyui_url": "http://127.0.0.1:8188" + } + }, + "book_fetcher": { + "default": "google", + "google": {} + }, + "mcp_servers": [] + } + diff --git a/reelforge/core/__init__.py b/reelforge/core/__init__.py new file mode 100644 index 0000000..168bcac --- /dev/null +++ b/reelforge/core/__init__.py @@ -0,0 +1,4 @@ +""" +Core capability system for ReelForge +""" + diff --git a/reelforge/core/config_manager.py b/reelforge/core/config_manager.py new file mode 100644 index 0000000..7d56d48 --- /dev/null +++ b/reelforge/core/config_manager.py @@ -0,0 +1,173 @@ +""" +Configuration Manager + +Manages capability configuration and provides unified access to MCP tools. +Simplified from Router - only handles config injection, no external routing. +""" + +from typing import Any + +from fastmcp import Client +from loguru import logger + +from reelforge.core.conventions import CapabilityInfo + + +class ConfigManager: + """ + Configuration manager for capabilities + + Core responsibilities: + 1. Manage active capability selection + 2. Inject configuration into capability calls + 3. Provide unified MCP client interface + + No external MCP routing - all capabilities are builtin. + """ + + def __init__(self, registry, config: dict): + """ + Initialize config manager + + Args: + registry: CapabilityRegistry instance with registered capabilities + config: Application configuration dict + """ + self.registry = registry + self.config = config + self._active: dict[str, str] = {} # type -> id + + # Create in-memory MCP client for calling builtin capabilities + self._local_client = Client(registry.local_mcp) + + self._load_active_from_config() + + def _load_active_from_config(self): + """Load active capability selections from config""" + for cap_type in self.registry.capabilities.keys(): + # Read active from flat structure: config[type]["default"] + cap_section = self.config.get(cap_type, {}) + if isinstance(cap_section, dict): + configured_id = cap_section.get("default") + if configured_id and configured_id in self.registry.capabilities[cap_type]: + self._active[cap_type] = configured_id + continue + + # Otherwise, auto-select default + self._auto_select_default(cap_type) + + def _auto_select_default(self, cap_type: str): + """Auto-select default capability""" + capabilities = self.registry.capabilities[cap_type] + + # Find default + for cap_id, cap_info in capabilities.items(): + if cap_info.is_default: + self._active[cap_type] = cap_id + logger.info(f"✓ Auto-selected default {cap_type}: {cap_id}") + return + + # No default, use first + if capabilities: + first_id = next(iter(capabilities.keys())) + self._active[cap_type] = first_id + logger.info(f"✓ Auto-selected first {cap_type}: {first_id}") + + def get_active(self, cap_type: str) -> str | None: + """Get active capability ID for a type""" + return self._active.get(cap_type) + + def get_available_ids(self, cap_type: str) -> list[str]: + """Get available capability IDs for a type""" + return list(self.registry.capabilities.get(cap_type, {}).keys()) + + async def call(self, cap_type: str, cap_id: str | None = None, **kwargs) -> Any: + """ + Call a capability with config injection + + Args: + cap_type: Capability type (e.g., "llm", "tts") + cap_id: Specific capability ID (defaults to active) + **kwargs: Arguments for the capability + + Returns: + Result from the capability + """ + # Determine which capability to use + if cap_id is None: + cap_id = self.get_active(cap_type) + + if not cap_id: + raise ValueError(f"No active capability for type: {cap_type}") + + # Get capability info + cap_info = self.registry.capabilities[cap_type][cap_id] + + logger.debug(f"Calling {cap_info.full_id} ({cap_info.display_label})") + + # Prepare tool arguments with config injection + tool_arguments = self._inject_config(cap_info, kwargs) + + # Call tool via MCP protocol using in-memory client + async with self._local_client: + result = await self._local_client.call_tool( + name=cap_info.tool_name, + arguments=tool_arguments + ) + + # Extract content from MCP result + return self._extract_content(result) + + def _inject_config(self, cap_info: CapabilityInfo, kwargs: dict) -> dict: + """ + Inject configuration into tool arguments + + This is the core value of ConfigManager - it handles config injection + so individual capabilities don't need to know about config.yaml + """ + tool_arguments = kwargs.copy() + + # Handle LLM-specific configuration (direct top-level config) + if cap_info.type == "llm": + llm_config = self.config.get("llm", {}) + + # Add LLM credentials and settings (if not already provided) + tool_arguments.setdefault("api_key", llm_config.get("api_key", "")) + tool_arguments.setdefault("base_url", llm_config.get("base_url", "")) + tool_arguments.setdefault("model", llm_config.get("model", "")) + + logger.debug(f"LLM using: {tool_arguments['model']} @ {tool_arguments['base_url']}") + + # Handle other capability types (image, tts, etc.) + else: + # Read capability-specific config from flat structure: config[type][id] + cap_section = self.config.get(cap_info.type, {}) + if isinstance(cap_section, dict): + cap_config = cap_section.get(cap_info.id, {}) + if isinstance(cap_config, dict): + # Merge config (don't override kwargs) + for key, value in cap_config.items(): + tool_arguments.setdefault(key, value) + + return tool_arguments + + def _extract_content(self, result: Any) -> Any: + """ + Extract content from MCP result + + MCP returns a CallToolResult with content field + """ + if hasattr(result, 'content'): + # Handle different content types + if isinstance(result.content, list): + # Multiple content items, join them + return '\n'.join( + item.text if hasattr(item, 'text') else str(item) + for item in result.content + ) + else: + return result.content + + # Fallback: return the result as-is + return result + diff --git a/reelforge/core/conventions.py b/reelforge/core/conventions.py new file mode 100644 index 0000000..33ca36b --- /dev/null +++ b/reelforge/core/conventions.py @@ -0,0 +1,117 @@ +""" +ReelForge Tool Naming Convention +================================ + +All capability tools MUST follow this naming pattern: + {type}_{id} + +Where: + - type: MUST be one of the known capability types (llm, tts, book_fetcher, etc.) + - id: Unique identifier for this specific capability + +Parsing strategy (Fail Fast): + - Match against known capability types only + - If no match, return None (fail early to expose configuration errors) + - No guessing or fallback - explicit is better than implicit + +Examples: + ✅ llm_call → type: llm, id: call + ✅ tts_edge → type: tts, id: edge + ✅ image_comfykit → type: image, id: comfykit + ✅ book_fetcher_google → type: book_fetcher, id: google + + ❌ call_llm → Wrong order + ❌ llm-call → Use underscore, not dash + ❌ LLM_call → Use lowercase +""" + +from typing import Any, Optional + +from pydantic import BaseModel, Field + +# Known capability types +CAPABILITY_TYPES = { + "llm", + "tts", + "image", + "book_fetcher", +} + + +def parse_tool_name(tool_name: str) -> Optional[tuple[str, str]]: + """ + Parse tool name into (type, id) - Fail Fast approach + + Only accepts tool names that match known capability types. + Returns None for unknown types to fail early and expose configuration errors. + + Args: + tool_name: Tool name following convention (e.g., "llm_qwen", "book_fetcher_douban") + + Returns: + (type, id) tuple if matches known type, None otherwise + + Examples: + >>> parse_tool_name("llm_call") + ('llm', 'call') + + >>> parse_tool_name("book_fetcher_google") + ('book_fetcher', 'google') + + >>> parse_tool_name("unknown_type_id") + None # Fail fast - unknown type + """ + # Must contain at least one underscore + if "_" not in tool_name: + return None + + # Only match against known capability types (sorted by length, longest first) + for cap_type in sorted(CAPABILITY_TYPES, key=len, reverse=True): + # Match pattern: {known_type}_{id} + if tool_name.startswith(cap_type + "_"): + capability_id = tool_name[len(cap_type) + 1:] # +1 for underscore + if capability_id: # Must have a non-empty id + return cap_type, capability_id + + # No match found - return None to fail early + return None + + +class CapabilityInfo(BaseModel): + """ + Capability information + + Required: type and id (parsed from tool_name) + Optional: everything else (from meta.reelforge) + """ + + # Required (parsed from tool_name) + type: str = Field(description="Capability type (llm, tts, etc.)") + id: str = Field(description="Unique identifier for this capability") + + # Optional (from meta.reelforge) + display_name: Optional[str] = Field( + default=None, description="Human-readable name for UI display" + ) + description: Optional[str] = Field(default=None, description="Short description") + is_default: bool = Field(default=False, description="Whether this is the default for this type") + + # Tool reference + tool_name: str = Field(description="Original tool name") + + # Tool reference + tool: Optional[Any] = Field(default=None, description="Tool object reference", exclude=True) + + @property + def display_label(self) -> str: + """Get display label for UI""" + if self.display_name: + return self.display_name + # Auto-generate from id: "my_custom_v2" → "My Custom V2" + return self.id.replace("_", " ").title() + + @property + def full_id(self) -> str: + """Get full identifier: type/id""" + return f"{self.type}/{self.id}" + diff --git a/reelforge/core/discovery.py b/reelforge/core/discovery.py new file mode 100644 index 0000000..c5ba4a2 --- /dev/null +++ b/reelforge/core/discovery.py @@ -0,0 +1,119 @@ +""" +Capability Registry System + +Registers built-in capabilities from FastMCP tools. +""" + +from typing import Any + +from fastmcp import FastMCP +from loguru import logger + +from reelforge.core.conventions import CapabilityInfo, parse_tool_name + + +class CapabilityRegistry: + """ + Built-in capability registry + + Registers capabilities from local FastMCP tools + based on tool naming convention. + + Simplified from CapabilityDiscovery - no external MCP support. + If you need custom capabilities, add them to reelforge/capabilities/ + """ + + def __init__(self, local_mcp: FastMCP): + self.local_mcp = local_mcp + self.capabilities: dict[str, dict[str, CapabilityInfo]] = {} + # Structure: {type: {id: CapabilityInfo}} + + async def register_all(self): + """Register all built-in capabilities""" + logger.info("📦 Registering built-in capabilities...") + + # Get all tools from FastMCP server (returns dict: {name: FunctionTool}) + tools_dict = await self.local_mcp.get_tools() + + for tool_name, tool in tools_dict.items(): + capability_info = self._parse_capability(tool_name=tool_name, tool=tool) + + if capability_info: + self._register_capability(capability_info) + + self._print_summary() + + def _parse_capability( + self, tool_name: str, tool: Any + ) -> CapabilityInfo | None: + """ + Parse a tool into CapabilityInfo + + Key logic: Parse type and id from tool_name! + """ + # Parse tool name following convention + parsed = parse_tool_name(tool_name) + if not parsed: + # Not a capability tool (doesn't follow convention) + return None + + capability_type, capability_id = parsed + + # Extract optional metadata from meta.reelforge + reelforge_meta = {} + if hasattr(tool, "meta") and tool.meta: + reelforge_meta = tool.meta.get("reelforge", {}) + + # Build CapabilityInfo + return CapabilityInfo( + type=capability_type, + id=capability_id, + tool_name=tool_name, + display_name=reelforge_meta.get("display_name"), + description=reelforge_meta.get("description") + or (tool.description if hasattr(tool, "description") else None), + is_default=reelforge_meta.get("is_default", False), + tool=tool, + ) + + def _register_capability(self, capability_info: CapabilityInfo): + """Register a capability""" + cap_type = capability_info.type + cap_id = capability_info.id + + # Initialize type dict if needed + if cap_type not in self.capabilities: + self.capabilities[cap_type] = {} + + # Check for duplicates + if cap_id in self.capabilities[cap_type]: + existing = self.capabilities[cap_type][cap_id] + logger.warning( + f" ⚠️ Duplicate capability: {cap_type}/{cap_id} - keeping first registration" + ) + return + + # Register + self.capabilities[cap_type][cap_id] = capability_info + + # Log + logger.info(f" ✓ {cap_type}/{cap_id} ({capability_info.display_label})") + + def _print_summary(self): + """Print registration summary""" + logger.info("\n📊 Registered Capabilities:") + + if not self.capabilities: + logger.info(" No capabilities registered") + return + + for cap_type in sorted(self.capabilities.keys()): + logger.info(f"\n {cap_type}:") + + for cap_id, cap_info in self.capabilities[cap_type].items(): + default_marker = " [DEFAULT]" if cap_info.is_default else "" + + logger.info( + f" • {cap_id} ({cap_info.display_label}){default_marker}" + ) + diff --git a/reelforge/core/mcp_server.py b/reelforge/core/mcp_server.py new file mode 100644 index 0000000..48fe456 --- /dev/null +++ b/reelforge/core/mcp_server.py @@ -0,0 +1,9 @@ +""" +ReelForge MCP Server +""" + +from fastmcp import FastMCP + +# Initialize ReelForge MCP server +reelforge_mcp = FastMCP("ReelForge Capabilities 📚") + diff --git a/reelforge/i18n/__init__.py b/reelforge/i18n/__init__.py new file mode 100644 index 0000000..d41d229 --- /dev/null +++ b/reelforge/i18n/__init__.py @@ -0,0 +1,117 @@ +""" +International language support for ReelForge +""" + +import json +from pathlib import Path +from typing import Dict, Optional + +from loguru import logger + +_locales: Dict[str, dict] = {} +_current_language: str = "zh_CN" + + +def load_locales() -> Dict[str, dict]: + """Load all locale files from locales directory""" + global _locales + + locales_dir = Path(__file__).parent / "locales" + + if not locales_dir.exists(): + logger.warning(f"Locales directory not found: {locales_dir}") + return _locales + + for json_file in locales_dir.glob("*.json"): + lang_code = json_file.stem + try: + with open(json_file, "r", encoding="utf-8") as f: + _locales[lang_code] = json.load(f) + logger.debug(f"Loaded locale: {lang_code}") + except Exception as e: + logger.error(f"Failed to load locale {lang_code}: {e}") + + logger.info(f"Loaded {len(_locales)} locales: {list(_locales.keys())}") + return _locales + + +def set_language(lang_code: str): + """Set current language""" + global _current_language + if lang_code in _locales: + _current_language = lang_code + logger.debug(f"Language set to: {lang_code}") + else: + logger.warning(f"Language {lang_code} not found, keeping {_current_language}") + + +def get_language() -> str: + """Get current language""" + return _current_language + + +def tr(key: str, fallback: Optional[str] = None, **kwargs) -> str: + """ + Translate a key to current language + + Args: + key: Translation key (e.g., "app.title") + fallback: Fallback text if key not found + **kwargs: Format parameters for string interpolation + + Returns: + Translated text + + Example: + tr("app.title") # => "ReelForge - AI书单视频生成器" + tr("error.missing_field", field="API Key") # => "请填写 API Key" + """ + locale = _locales.get(_current_language, {}) + translations = locale.get("t", {}) + + result = translations.get(key) + + if result is None: + # Try fallback parameter + if fallback is not None: + result = fallback + # Try English fallback + elif _current_language != "en_US" and "en_US" in _locales: + en_locale = _locales["en_US"] + result = en_locale.get("t", {}).get(key) + + # Last resort: return the key itself + if result is None: + result = key + logger.debug(f"Translation missing: {key}") + + # Apply string interpolation if kwargs provided + if kwargs: + try: + result = result.format(**kwargs) + except (KeyError, ValueError) as e: + logger.warning(f"Failed to format translation '{key}': {e}") + + return result + + +def get_language_name(lang_code: Optional[str] = None) -> str: + """Get display name of a language""" + if lang_code is None: + lang_code = _current_language + + locale = _locales.get(lang_code, {}) + return locale.get("language_name", lang_code) + + +def get_available_languages() -> Dict[str, str]: + """Get all available languages with their display names""" + return { + code: locale.get("language_name", code) + for code, locale in _locales.items() + } + + +# Auto-load locales on import +load_locales() + diff --git a/reelforge/i18n/locales/en_US.json b/reelforge/i18n/locales/en_US.json new file mode 100644 index 0000000..0a34563 --- /dev/null +++ b/reelforge/i18n/locales/en_US.json @@ -0,0 +1,159 @@ +{ + "language_name": "English", + "t": { + "app.title": "🔨 ReelForge - Modular Video Creation Platform", + "app.subtitle": "Forge your perfect reel engine", + + "section.content_input": "📖 Content Input", + "section.style_settings": "⚙️ Custom Settings", + "section.video_generation": "🎬 Generate Video", + + "input_mode.book": "📚 Book Name", + "input_mode.topic": "💡 Topic", + "input_mode.custom": "✍️ Custom Content", + + "input.book_name": "Book Name", + "input.book_name_placeholder": "e.g., Atomic Habits, How to Win Friends", + "input.book_name_help": "Enter the book name, will fetch book info and generate video", + + "input.topic": "Topic", + "input.topic_placeholder": "e.g., How to build passive income, How to build good habits", + "input.topic_help": "Enter a topic, AI will generate content based on it", + + "input.content": "Content", + "input.content_placeholder": "Enter your custom content here...", + "input.content_help": "Provide your own content for video generation", + + "input.title": "Title (Optional)", + "input.title_placeholder": "Video title (auto-generated if empty)", + + "book.search": "🔍 Search Book", + "book.searching": "Searching book...", + "book.found": "✅ Book found!", + "book.not_found": "❌ Failed to fetch book: {error}", + "book.name_required": "Please enter a book name", + + "book.title": "Title", + "book.author": "Author", + "book.rating": "Rating", + "book.summary": "📝 Summary", + + "voice.title": "🎤 Voice Selection", + "voice.male_professional": "🎤 Male-Professional", + "voice.male_young": "🎙️ Male-Young", + "voice.female_gentle": "🎵 Female-Gentle", + "voice.female_energetic": "🎶 Female-Energetic", + "voice.preview": "▶ Preview Voice", + "voice.previewing": "Generating voice preview...", + "voice.preview_failed": "Preview failed: {error}", + + "style.title": "🎨 Illustration Style", + "style.custom": "Custom", + "style.description": "Style Description", + "style.description_placeholder": "Describe the illustration style you want (any language)...", + "style.preview": "🖼️ Preview Style", + "style.previewing": "Generating style preview...", + "style.preview_caption": "Style Preview", + "style.preview_failed": "Preview failed: {error}", + "style.generated_prompt": "Generated prompt: {prompt}", + + "template.title": "📐 Storyboard Template", + "template.classic": "Classic", + "template.modern": "Modern", + "template.neon": "Neon", + + "video.title": "🎬 Video Settings", + "video.frames": "Frames", + "video.frames_help": "More frames = longer video", + "video.frames_label": "Frames: {n}", + + "bgm.title": "🎵 Background Music", + "bgm.none": "🔇 No BGM", + "bgm.preview": "▶ Preview Music", + "bgm.preview_failed": "❌ Music file not found: {file}", + + "btn.generate": "🎬 Generate Video", + "btn.save_config": "💾 Save Configuration", + "btn.reset_config": "🔄 Reset to Default", + "btn.save_and_start": "Save and Start", + "btn.test_connection": "Test Connection", + + "status.initializing": "🔧 Initializing...", + "status.generating": "🚀 Generating video...", + "status.success": "✅ Video generated successfully!", + "status.error": "❌ Generation failed: {error}", + "status.video_generated": "✅ Video generated: {path}", + "status.video_not_found": "Video file not found: {path}", + "status.config_saved": "✅ Configuration saved", + "status.config_reset": "✅ Configuration reset to default", + "status.connection_success": "✅ Connected", + "status.connection_failed": "❌ Connection failed", + + "progress.generating_narrations": "Generating narrations...", + "progress.generating_image_prompts": "Generating image prompts...", + "progress.frame": "Frame {current}/{total}", + "progress.frame_step": "Frame {current}/{total} - Step {step}/4: {action}", + "progress.step_audio": "Generating audio", + "progress.step_image": "Generating image", + "progress.step_compose": "Composing frame", + "progress.step_video": "Creating video segment", + "progress.concatenating": "Concatenating video segments...", + "progress.finalizing": "Finalizing...", + + "error.input_required": "❌ Please provide book name, topic, or content", + "error.api_key_required": "❌ Please enter API Key", + "error.missing_field": "Please enter {field}", + + "info.duration": "Duration", + "info.file_size": "File Size", + "info.frames": "Scenes", + "info.scenes_unit": " scenes", + "info.resolution": "Resolution", + "info.video_information": "📊 Video Information", + "info.no_video_yet": "Video preview will appear here after generation", + + "settings.title": "⚙️ System Configuration (Required)", + "settings.not_configured": "⚠️ Please complete system configuration before generating videos", + "settings.llm.title": "🤖 Large Language Model", + "settings.llm.quick_select": "Quick Select", + "settings.llm.quick_select_help": "Choose a preset LLM or custom configuration", + "settings.llm.get_api_key": "Get API Key", + "settings.llm.api_key": "API Key", + "settings.llm.api_key_help": "Enter your API Key", + "settings.llm.base_url": "Base URL", + "settings.llm.base_url_help": "API service address", + "settings.llm.model": "Model", + "settings.llm.model_help": "Model name", + + "settings.tts.title": "🎤 Text-to-Speech", + "settings.tts.provider": "Provider", + "settings.tts.provider_help": "Select TTS service provider", + "settings.tts.edge_info": "💡 Edge TTS is free and requires no configuration", + + "settings.image.title": "🎨 Image Generation", + "settings.image.local_title": "Local/Self-hosted ComfyUI", + "settings.image.cloud_title": "RunningHub Cloud", + "settings.image.comfyui_url": "ComfyUI Service URL", + "settings.image.comfyui_url_help": "Local or remote ComfyUI service URL, default: http://127.0.0.1:8188", + "settings.image.runninghub_api_key": "RunningHub API Key", + "settings.image.runninghub_api_key_help": "Visit https://runninghub.ai to register and get API Key", + + "settings.book.title": "📚 Book Information", + "settings.book.provider": "Provider", + "settings.book.provider_help": "Select book information source", + + "welcome.first_time": "🎉 Welcome to ReelForge! Please complete basic configuration", + "welcome.config_hint": "💡 First-time setup requires API Key configuration, you can modify it in advanced settings later", + + "wizard.llm_required": "🤖 Large Language Model Configuration (Required)", + "wizard.image_optional": "🎨 Image Generation Configuration (Optional)", + "wizard.image_hint": "💡 If not configured, default template will be used (no AI image generation)", + "wizard.configure_image": "Configure Image Generation (Recommended)", + + "label.required": "(Required)", + "label.optional": "(Optional)", + + "language.select": "🌐 Language" + } +} + diff --git a/reelforge/i18n/locales/zh_CN.json b/reelforge/i18n/locales/zh_CN.json new file mode 100644 index 0000000..5e728c0 --- /dev/null +++ b/reelforge/i18n/locales/zh_CN.json @@ -0,0 +1,159 @@ +{ + "language_name": "简体中文", + "t": { + "app.title": "🔨 ReelForge - 模块化视频创作平台", + "app.subtitle": "打造专属你的视频创作引擎", + + "section.content_input": "📖 内容输入", + "section.style_settings": "⚙️ 自定义设置", + "section.video_generation": "🎬 生成视频", + + "input_mode.book": "📚 书名", + "input_mode.topic": "💡 主题", + "input_mode.custom": "✍️ 自定义内容", + + "input.book_name": "书名", + "input.book_name_placeholder": "例如：原子习惯、人性的弱点、Atomic Habits", + "input.book_name_help": "输入书名，将自动获取书籍信息并生成视频", + + "input.topic": "主题", + "input.topic_placeholder": "例如：如何增加被动收入、How to build good habits", + "input.topic_help": "输入一个主题，AI 将根据主题生成内容", + + "input.content": "内容", + "input.content_placeholder": "在此输入您的自定义内容...", + "input.content_help": "提供您自己的内容用于视频生成", + + "input.title": "标题（可选）", + "input.title_placeholder": "视频标题（留空则自动生成）", + + "book.search": "🔍 搜索书籍", + "book.searching": "正在搜索书籍...", + "book.found": "✅ 找到书籍！", + "book.not_found": "❌ 获取书籍失败：{error}", + "book.name_required": "请输入书名", + + "book.title": "书名", + "book.author": "作者", + "book.rating": "评分", + "book.summary": "📝 简介", + + "voice.title": "🎤 语音选择", + "voice.male_professional": "🎤 男声-专业", + "voice.male_young": "🎙️ 男声-年轻", + "voice.female_gentle": "🎵 女声-温柔", + "voice.female_energetic": "🎶 女声-活力", + "voice.preview": "▶ 试听语音", + "voice.previewing": "正在生成语音预览...", + "voice.preview_failed": "预览失败：{error}", + + "style.title": "🎨 插图风格", + "style.custom": "自定义", + "style.description": "风格描述", + "style.description_placeholder": "描述您想要的插图风格（任何语言）...", + "style.preview": "🖼️ 预览风格", + "style.previewing": "正在生成风格预览...", + "style.preview_caption": "风格预览", + "style.preview_failed": "预览失败：{error}", + "style.generated_prompt": "生成的提示词：{prompt}", + + "template.title": "📐 分镜模板", + "template.classic": "Classic", + "template.modern": "Modern", + "template.neon": "Neon", + + "video.title": "🎬 视频设置", + "video.frames": "帧数", + "video.frames_help": "更多帧数 = 更长视频", + "video.frames_label": "帧数：{n}", + + "bgm.title": "🎵 背景音乐", + "bgm.none": "🔇 无背景音乐", + "bgm.preview": "▶ 试听音乐", + "bgm.preview_failed": "❌ 音乐文件未找到：{file}", + + "btn.generate": "🎬 生成视频", + "btn.save_config": "💾 保存配置", + "btn.reset_config": "🔄 重置默认", + "btn.save_and_start": "保存并开始", + "btn.test_connection": "测试连接", + + "status.initializing": "🔧 正在初始化...", + "status.generating": "🚀 正在生成视频...", + "status.success": "✅ 视频生成成功！", + "status.error": "❌ 生成失败：{error}", + "status.video_generated": "✅ 视频已生成：{path}", + "status.video_not_found": "视频文件未找到：{path}", + "status.config_saved": "✅ 配置已保存", + "status.config_reset": "✅ 配置已重置为默认值", + "status.connection_success": "✅ 连接成功", + "status.connection_failed": "❌ 连接失败", + + "progress.generating_narrations": "生成旁白...", + "progress.generating_image_prompts": "生成图片提示词...", + "progress.frame": "分镜 {current}/{total}", + "progress.frame_step": "分镜 {current}/{total} - 步骤 {step}/4: {action}", + "progress.step_audio": "生成语音", + "progress.step_image": "生成插图", + "progress.step_compose": "合成画面", + "progress.step_video": "创建视频片段", + "progress.concatenating": "拼接视频片段...", + "progress.finalizing": "完成中...", + + "error.input_required": "❌ 请提供书名、主题或内容", + "error.api_key_required": "❌ 请填写 API Key", + "error.missing_field": "请填写 {field}", + + "info.duration": "时长", + "info.file_size": "文件大小", + "info.frames": "分镜数", + "info.scenes_unit": "分镜", + "info.resolution": "分辨率", + "info.video_information": "📊 视频信息", + "info.no_video_yet": "生成视频后，预览将显示在这里", + + "settings.title": "⚙️ 系统配置（必需）", + "settings.not_configured": "⚠️ 请先完成系统配置才能生成视频", + "settings.llm.title": "🤖 大语言模型", + "settings.llm.quick_select": "快速选择", + "settings.llm.quick_select_help": "选择预置的 LLM 或自定义配置", + "settings.llm.get_api_key": "获取 API Key", + "settings.llm.api_key": "API Key", + "settings.llm.api_key_help": "填入您的 API Key", + "settings.llm.base_url": "Base URL", + "settings.llm.base_url_help": "API 服务地址", + "settings.llm.model": "Model", + "settings.llm.model_help": "模型名称", + + "settings.tts.title": "🎤 语音合成", + "settings.tts.provider": "服务商", + "settings.tts.provider_help": "选择 TTS 服务提供商", + "settings.tts.edge_info": "💡 Edge TTS 是免费的，无需配置", + + "settings.image.title": "🎨 图像生成", + "settings.image.local_title": "本地/自建 ComfyUI", + "settings.image.cloud_title": "RunningHub 云端", + "settings.image.comfyui_url": "ComfyUI 服务地址", + "settings.image.comfyui_url_help": "本地或远程 ComfyUI 服务地址，默认: http://127.0.0.1:8188", + "settings.image.runninghub_api_key": "RunningHub API Key", + "settings.image.runninghub_api_key_help": "访问 https://runninghub.ai 注册并获取 API Key", + + "settings.book.title": "📚 书籍信息", + "settings.book.provider": "服务商", + "settings.book.provider_help": "选择书籍信息来源", + + "welcome.first_time": "🎉 欢迎使用 ReelForge！请先完成基础配置", + "welcome.config_hint": "💡 首次使用需要配置 API Key，后续可以在高级设置中修改", + + "wizard.llm_required": "🤖 大语言模型配置（必需）", + "wizard.image_optional": "🎨 图像生成配置（可选）", + "wizard.image_hint": "💡 如果不配置图像生成，将使用默认模板（无 AI 生图）", + "wizard.configure_image": "配置图像生成（推荐）", + + "label.required": "（必需）", + "label.optional": "（可选）", + + "language.select": "🌐 语言" + } +} + diff --git a/reelforge/llm_presets.py b/reelforge/llm_presets.py new file mode 100644 index 0000000..f5cb107 --- /dev/null +++ b/reelforge/llm_presets.py @@ -0,0 +1,74 @@ +""" +LLM Presets - Predefined configurations for popular LLM providers + +All providers support OpenAI SDK protocol. +""" + +from typing import Dict, Any, List + + +LLM_PRESETS: List[Dict[str, Any]] = [ + { + "name": "Qwen", + "base_url": "https://dashscope.aliyuncs.com/compatible-mode/v1", + "model": "qwen-max", + "api_key_url": "https://dashscope.console.aliyun.com/apiKey", + }, + { + "name": "OpenAI", + "base_url": "https://api.openai.com/v1", + "model": "gpt-4o", + "api_key_url": "https://platform.openai.com/api-keys", + }, + { + "name": "Claude", + "base_url": "https://api.anthropic.com/v1/", + "model": "claude-sonnet-4-5", + "api_key_url": "https://console.anthropic.com/settings/keys", + }, + { + "name": "DeepSeek", + "base_url": "https://api.deepseek.com", + "model": "deepseek-chat", + "api_key_url": "https://platform.deepseek.com/api_keys", + }, + { + "name": "Ollama", + "base_url": "http://localhost:11434/v1", + "model": "llama3.2", + "api_key_url": "https://ollama.com/download", + }, + { + "name": "Moonshot", + "base_url": "https://api.moonshot.cn/v1", + "model": "moonshot-v1-8k", + "api_key_url": "https://platform.moonshot.cn/console/api-keys", + }, +] + + +def get_preset_names() -> List[str]: + """Get list of preset names""" + return [preset["name"] for preset in LLM_PRESETS] + + +def get_preset(name: str) -> Dict[str, Any]: + """Get preset configuration by name""" + for preset in LLM_PRESETS: + if preset["name"] == name: + return preset + return {} + + +def find_preset_by_base_url_and_model(base_url: str, model: str) -> str | None: + """ + Find preset name by base_url and model + + Returns: + Preset name if found, None otherwise + """ + for preset in LLM_PRESETS: + if preset["base_url"] == base_url and preset["model"] == model: + return preset["name"] + return None + diff --git a/reelforge/models/progress.py b/reelforge/models/progress.py new file mode 100644 index 0000000..afd1249 --- /dev/null +++ b/reelforge/models/progress.py @@ -0,0 +1,51 @@ +""" +Progress event models for video generation + +Provides structured progress events for UI layer to consume and translate. +""" + +from dataclasses import dataclass +from typing import Optional + + +@dataclass +class ProgressEvent: + """ + Structured progress event for video generation + + Attributes: + event_type: Type of event (e.g., "generating_narrations", "frame_step", "concatenating") + progress: Progress value from 0.0 to 1.0 + frame_current: Current frame number (1-based, optional) + frame_total: Total number of frames (optional) + step: Current step within frame (1-4, optional) + action: Action being performed (e.g., "audio", "image", "compose", "video", optional) + + Examples: + # Simple progress event + ProgressEvent(event_type="generating_narrations", progress=0.05) + + # Frame step event + ProgressEvent( + event_type="frame_step", + progress=0.23, + frame_current=1, + frame_total=5, + step=1, + action="audio" + ) + """ + event_type: str + progress: float + + # Optional frame-related fields + frame_current: Optional[int] = None + frame_total: Optional[int] = None + step: Optional[int] = None # 1-4 for frame processing steps + action: Optional[str] = None # "audio", "image", "compose", "video" + + def __post_init__(self): + """Validate progress value""" + if not 0.0 <= self.progress <= 1.0: + raise ValueError(f"Progress must be between 0.0 and 1.0, got {self.progress}") + diff --git a/reelforge/models/storyboard.py b/reelforge/models/storyboard.py new file mode 100644 index 0000000..b1351d1 --- /dev/null +++ b/reelforge/models/storyboard.py @@ -0,0 +1,119 @@ +""" +Storyboard data models for video generation +""" + +from dataclasses import dataclass, field +from datetime import datetime +from typing import List, Optional + + +@dataclass +class StoryboardConfig: + """Storyboard configuration parameters""" + n_storyboard: int = 5 # Number of storyboard frames + min_narration_words: int = 30 # Min narration word count + max_narration_words: int = 50 # Max narration word count + min_image_prompt_words: int = 60 # Min image prompt word count + max_image_prompt_words: int = 100 # Max image prompt word count + + # Video parameters + video_width: int = 1080 # Video width + video_height: int = 1920 # Video height (9:16 portrait) + video_fps: int = 30 # Frame rate + + # Audio parameters + voice_id: str = "zh-CN-YunjianNeural" # Default voice + + # Image parameters + image_width: int = 1024 + image_height: int = 1024 + + # Frame template + frame_template: Optional[str] = None # HTML template name or path (None = use PIL) + + +@dataclass +class StoryboardFrame: + """Single storyboard frame""" + index: int # Frame index (0-based) + narration: str # Narration text + image_prompt: str # Image generation prompt + + # Generated resource paths + audio_path: Optional[str] = None # Audio file path + image_path: Optional[str] = None # Original image path + composed_image_path: Optional[str] = None # Composed image path (with subtitles) + video_segment_path: Optional[str] = None # Video segment path + + # Metadata + duration: float = 0.0 # Audio duration (seconds) + created_at: Optional[datetime] = None + + def __post_init__(self): + if self.created_at is None: + self.created_at = datetime.now() + + +@dataclass +class BookInfo: + """Book information for visual display and narration generation""" + title: str # Book title + author: Optional[str] = None # Author + subtitle: Optional[str] = None # Subtitle + genre: Optional[str] = None # Genre/category + summary: Optional[str] = None # Book summary + publication_year: Optional[str] = None # Publication year + cover_url: Optional[str] = None # Cover image URL + + +@dataclass +class Storyboard: + """Complete storyboard""" + topic: str # Topic (book name or discussion topic) + config: StoryboardConfig # Configuration + frames: List[StoryboardFrame] = field(default_factory=list) + + # Book information (optional) + book_info: Optional[BookInfo] = None + + # Final output + final_video_path: Optional[str] = None + total_duration: float = 0.0 + + # Metadata + created_at: Optional[datetime] = None + completed_at: Optional[datetime] = None + + def __post_init__(self): + if self.created_at is None: + self.created_at = datetime.now() + + @property + def is_completed(self) -> bool: + """Check if all frames are processed""" + return all( + frame.video_segment_path is not None + for frame in self.frames + ) + + @property + def progress(self) -> float: + """Return processing progress (0.0-1.0)""" + if not self.frames: + return 0.0 + completed = sum( + 1 for frame in self.frames + if frame.video_segment_path is not None + ) + return completed / len(self.frames) + + +@dataclass +class VideoGenerationResult: + """Video generation result""" + video_path: str # Final video path + storyboard: Storyboard # Complete storyboard + duration: float # Total duration + file_size: int # File size (bytes) + created_at: datetime = field(default_factory=datetime.now) + diff --git a/reelforge/prompts/__init__.py b/reelforge/prompts/__init__.py new file mode 100644 index 0000000..0908b93 --- /dev/null +++ b/reelforge/prompts/__init__.py @@ -0,0 +1,4 @@ +""" +Prompt templates for content generation +""" + diff --git a/reelforge/prompts/image_prompt_template.py b/reelforge/prompts/image_prompt_template.py new file mode 100644 index 0000000..4301b75 --- /dev/null +++ b/reelforge/prompts/image_prompt_template.py @@ -0,0 +1,174 @@ +""" +Image prompt generation template +""" + +import json +from typing import List, Optional + + +# ==================== PRESET IMAGE STYLES ==================== +# Predefined visual styles for different use cases + +IMAGE_STYLE_PRESETS = { + "stick_figure": { + "name": "火柴人简笔画", + "description": "stick figure style sketch, black and white lines, pure white background, minimalist hand-drawn feel", + "use_case": "通用场景，简单直观" + }, + + "book": { + "name": "书籍阅读场景", + "description": "warm book-related scenes, reading atmosphere, books and bookshelves, soft lighting, cozy learning environment, professional photography style", + "use_case": "书单号视频（推荐）" + }, + + "minimal": { + "name": "极简抽象", + "description": "minimalist abstract art, geometric shapes, clean composition, modern design, soft pastel colors", + "use_case": "现代感、艺术感" + }, + + "concept": { + "name": "概念化视觉", + "description": "conceptual visual metaphors, symbolic elements, thought-provoking imagery, artistic interpretation", + "use_case": "深度内容、哲学思考" + }, +} + +# Default preset +DEFAULT_IMAGE_STYLE = "stick_figure" + + +IMAGE_PROMPT_GENERATION_PROMPT = """# 角色定位 +你是一个专业的视觉创意设计师，擅长为视频脚本创作富有表现力和象征性的图像提示词，将抽象概念转化为具象的视觉画面。 + +# 核心任务 +基于已有的视频脚本，为每个分镜的"旁白内容"创作对应的**英文**图像提示词，确保视觉画面与叙述内容完美配合，增强观众的理解和记忆。 + +# 输入内容 +{narrations_json} + +# 输出要求 + +## 图像提示词规范 +- 语言：**必须使用英文**（用于 AI 图像生成模型） +- 画面风格：{style_description} +- 描述结构：scene + character action + emotion + symbolic elements +- 描述长度：确保描述清晰完整且富有创意（建议 50-100 个英文单词） + +## 视觉创意要求 +- 每个图像都要准确反映对应旁白的具体内容和情感 +- 使用象征手法将抽象概念视觉化（如用路径代表人生选择，用锁链代表束缚等） +- 画面要表现出丰富的情感和动作，增强视觉冲击力 +- 通过构图和元素安排突出主题，避免过于直白的表现方式 + +## 关键英文词汇参考 +- 象征元素：symbolic elements +- 表情：expression / facial expression +- 动作：action / gesture / movement +- 场景：scene / setting +- 氛围：atmosphere / mood + +## 视觉与文案配合原则 +- 图像要服务于文案，成为文案内容的视觉延伸 +- 避免与文案内容无关或矛盾的视觉元素 +- 选择最能增强文案说服力的视觉表现方式 +- 确保观众能通过图像快速理解文案的核心观点 + +## 创意指导 +1. **现象描述类文案**：用直观的场景表现社会现象 +2. **原因分析类文案**：用因果关系的视觉比喻表现内在逻辑 +3. **影响论证类文案**：用后果场景或对比手法表现影响程度 +4. **深入探讨类文案**：用抽象概念的具象化表现深刻思考 +5. **结论启发类文案**：用开放式场景或指引性元素表现启发性 + +# 输出格式 +严格按照以下JSON格式输出，**图像提示词必须是英文**： + +```json +{{ + "image_prompts": [ + "[detailed English image prompt following the style requirements]", + "[detailed English image prompt following the style requirements]" + ] +}} +``` + +# 重要提醒 +1. 只输出JSON格式内容，不要添加任何解释说明 +2. 确保JSON格式严格正确，可以被程序直接解析 +3. 输入是 {{"narrations": [旁白数组]}} 格式，输出是 {{"image_prompts": [图像提示词数组]}} 格式 +4. **图像提示词必须使用英文**（for AI image generation models） +5. 图像提示词必须准确反映对应旁白的具体内容和情感 +6. 每个图像都要有创意性和视觉冲击力，避免千篇一律 +7. 严格遵守上述指定的画面风格要求（{style_description}） +8. 确保视觉画面能增强文案的说服力和观众的理解度 + +现在，请为上述旁白创作对应的**英文**图像提示词。只输出JSON，不要其他内容。 +""" + + +def build_image_prompt_prompt( + narrations: List[str], + min_words: int, + max_words: int, + image_style_preset: Optional[str] = None, + image_style_description: Optional[str] = None +) -> str: + """ + Build image prompt generation prompt + + Args: + narrations: List of narrations + min_words: Minimum word count + max_words: Maximum word count + image_style_preset: Preset style name (e.g., "book", "stick_figure", "minimal", "concept") + Available presets: see IMAGE_STYLE_PRESETS + image_style_description: Custom style description (overrides preset if provided) + Example: "warm book scenes, soft lighting, professional photography" + + Returns: + Formatted prompt + + Examples: + # Use preset style + >>> build_image_prompt_prompt(narrations, 50, 100, image_style_preset="book") + + # Use custom style + >>> build_image_prompt_prompt( + ... narrations, 50, 100, + ... image_style_description="cyberpunk style, neon colors, futuristic" + ... ) + + # Use default style (stick_figure) + >>> build_image_prompt_prompt(narrations, 50, 100) + """ + # Determine style description + if image_style_description: + # Custom description takes priority + style_desc = image_style_description + elif image_style_preset: + # Use preset + if image_style_preset not in IMAGE_STYLE_PRESETS: + raise ValueError( + f"Unknown preset '{image_style_preset}'. " + f"Available presets: {list(IMAGE_STYLE_PRESETS.keys())}" + ) + style_desc = IMAGE_STYLE_PRESETS[image_style_preset]["description"] + else: + # Use default preset + style_desc = IMAGE_STYLE_PRESETS[DEFAULT_IMAGE_STYLE]["description"] + + narrations_json = json.dumps( + {"narrations": narrations}, + ensure_ascii=False, + indent=2 + ) + + return IMAGE_PROMPT_GENERATION_PROMPT.format( + narrations_json=narrations_json, + min_words=min_words, + max_words=max_words, + style_description=style_desc + ) + diff --git a/reelforge/prompts/narration_template.py b/reelforge/prompts/narration_template.py new file mode 100644 index 0000000..447ebea --- /dev/null +++ b/reelforge/prompts/narration_template.py @@ -0,0 +1,323 @@ +""" +Narration generation prompt template + +Supports three content sources: +1. Book: Generate book review narrations from book information +2. Topic: Generate narrations from a topic/theme +3. Content: Extract/refine narrations from user-provided content +""" + +from typing import Optional +from reelforge.models.storyboard import BookInfo + + +# ==================== BOOK NARRATION PROMPT ==================== +# For generating book review style narrations + +BOOK_NARRATION_PROMPT = """# 角色定位 +你是一位专业的书籍解读专家，擅长像"樊登读书"那样，用深入浅出的方式讲解书籍核心内容，帮助观众快速理解一本书的精华。 + +# 核心任务 +用户会输入一本书的名称，你需要为这本书创作 {n_storyboard} 个书籍解读分镜，每个分镜包含"旁白（用于TTS生成视频讲解音频）"，像在跟朋友推荐书籍一样，自然、有价值、引发共鸣 + +# 输出要求 + +## 旁白规范（书籍解读风格） +- 用途定位：用于TTS生成书单号短视频音频，像樊登读书那样讲解书籍精华 +- 字数限制：严格控制在{min_words}~{max_words}个字（最低不少于{min_words}字） +- 结尾格式：结尾不要使用标点符号 +- 内容要求：提炼书籍的核心观点，用通俗易懂的语言讲解，每个分镜传递一个有价值的洞察 +- 风格要求：像跟朋友聊天一样，通俗、真诚、有启发性，避免学术化和生硬的表达 +- 开场建议：第一个分镜可以用提问、场景、痛点等方式引发共鸣，吸引观众注意 +- 核心内容：中间分镜提炼书中的关键观点，用生活化的例子帮助理解，像樊登那样深入浅出 +- 结尾建议：最后一个分镜给出行动建议或启发，让观众有收获感 +- 衔接建议：用"你有没有发现"、"其实"、"更重要的是"、"这本书告诉我们"等连接词，保持连贯 +- 情绪与语气：温和、真诚、有热情，像一个读过书的朋友在分享收获 +- 禁止项：不出现网址、表情符号、数字编号、不说空话套话、不过度煽情、不使用"这本书说"等生硬表达 +- 字数检查：生成后必须自我验证不少于{min_words}个字，如不足则补充具体观点或生活化例子 +- 内容结构：遵循"引发共鸣 → 提炼观点 → 深入讲解 → 给出启发"的叙述逻辑，确保每个分镜都有价值 + +## 分镜连贯性要求 +- {n_storyboard} 个分镜应围绕这本书的核心内容展开，形成完整的书籍解读 +- 遵循"吸引注意 → 提炼观点 → 深入讲解 → 给出启发"的叙述逻辑 +- 每个分镜像同一个人在连贯分享读书心得，语气一致、自然流畅 +- 通过书籍的核心观点自然过渡，形成完整的解读脉络 +- 确保内容有价值、有启发，让观众觉得"这个视频值得看" + +# 输出格式 +严格按照以下JSON格式输出，不要添加任何额外的文字说明： + +```json +{{ + "narrations": [ + "第一段{min_words}~{max_words}字，用提问或场景引发共鸣，吸引观众", + "第二段{min_words}~{max_words}字，提炼书中核心观点，深入浅出讲解", + "第三段{min_words}~{max_words}字，给出行动建议或启发，让观众有收获" + ] +}} +``` + +# 示例输出 +假设用户输入书名："{topic}"，输出示例： + +```json +{{ + "narrations": [ + "你有没有这样的经历，明明知道该做什么，但就是做不到，这本书告诉我们，问题的关键在于习惯", + "作者提出了一个简单但有力的观点，改变不需要靠意志力，而是要设计一个好的系统", + "书中有个很有意思的例子，如果你想养成阅读习惯，不要逼自己每天读一小时，而是先从每天读一页开始", + "更重要的是，习惯的复利效应非常惊人，每天进步百分之一，一年后你会进步三十七倍", + "所以与其追求完美的计划，不如从一个小到不可能失败的习惯开始，然后坚持下去" + ] +}} +``` + +# 重要提醒 +1. 只输出JSON格式内容，不要添加任何解释说明 +2. 确保JSON格式严格正确，可以被程序直接解析 +3. 旁白必须严格控制在{min_words}~{max_words}字之间，用通俗易懂的语言，像樊登那样讲解 +4. {n_storyboard} 个分镜要围绕这本书的核心观点展开，形成完整的书籍解读 +5. 每个分镜都要有价值，提炼书中的洞察，避免空洞的介绍 +6. 输出格式为 {{"narrations": [旁白数组]}} 的JSON对象 + +现在，请为书籍《{book_name}》创作 {n_storyboard} 个分镜的解读旁白。只输出JSON，不要其他内容。 +""" + + +# ==================== TOPIC NARRATION PROMPT ==================== +# For generating narrations from a topic/theme + +TOPIC_NARRATION_PROMPT = """# 角色定位 +你是一位专业的内容创作专家，擅长将话题扩展成引人入胜的短视频脚本，用深入浅出的方式讲解观点，帮助观众理解复杂概念。 + +# 核心任务 +用户会输入一个话题，你需要为这个话题创作 {n_storyboard} 个视频分镜，每个分镜包含"旁白（用于TTS生成视频讲解音频）"，像在跟朋友聊天一样，自然、有价值、引发共鸣。 + +# 输入话题 +{topic} + +# 输出要求 + +## 旁白规范 +- 用途定位：用于TTS生成短视频音频，通俗易懂地讲解话题 +- 字数限制：严格控制在{min_words}~{max_words}个字（最低不少于{min_words}字） +- 结尾格式：结尾不要使用标点符号 +- 内容要求：围绕话题展开，每个分镜传递一个有价值的观点或洞察 +- 风格要求：像跟朋友聊天一样，通俗、真诚、有启发性，避免学术化和生硬的表达 +- 开场建议：第一个分镜可以用提问、场景、痛点等方式引发共鸣，吸引观众注意 +- 核心内容：中间分镜展开核心观点，用生活化的例子帮助理解 +- 结尾建议：最后一个分镜给出行动建议或启发，让观众有收获感 +- 衔接建议：用"你有没有发现"、"其实"、"更重要的是"等连接词，保持连贯 +- 情绪与语气：温和、真诚、有热情，像一个有见解的朋友在分享思考 +- 禁止项：不出现网址、表情符号、数字编号、不说空话套话、不过度煽情 +- 字数检查：生成后必须自我验证不少于{min_words}个字，如不足则补充具体观点或例子 +- 内容结构：遵循"引发共鸣 → 提出观点 → 深入讲解 → 给出启发"的叙述逻辑 + +## 分镜连贯性要求 +- {n_storyboard} 个分镜应围绕话题展开，形成完整的观点表达 +- 遵循"吸引注意 → 提出观点 → 深入讲解 → 给出启发"的叙述逻辑 +- 每个分镜像同一个人在连贯分享观点，语气一致、自然流畅 +- 通过观点的递进自然过渡，形成完整的论述脉络 +- 确保内容有价值、有启发，让观众觉得"这个视频值得看" + +# 输出格式 +严格按照以下JSON格式输出，不要添加任何额外的文字说明： + +```json +{{ + "narrations": [ + "第一段{min_words}~{max_words}字，用提问或场景引发共鸣", + "第二段{min_words}~{max_words}字，展开核心观点", + "第三段{min_words}~{max_words}字，给出启发或建议" + ] +}} +``` + +# 重要提醒 +1. 只输出JSON格式内容，不要添加任何解释说明 +2. 确保JSON格式严格正确，可以被程序直接解析 +3. 旁白必须严格控制在{min_words}~{max_words}字之间，用通俗易懂的语言 +4. {n_storyboard} 个分镜要围绕话题展开，形成完整的观点表达 +5. 每个分镜都要有价值，提供洞察，避免空洞的陈述 +6. 输出格式为 {{"narrations": [旁白数组]}} 的JSON对象 + +现在，请为话题创作 {n_storyboard} 个分镜的旁白。只输出JSON，不要其他内容。 +""" + + +# ==================== CONTENT NARRATION PROMPT ==================== +# For extracting/refining narrations from user-provided content + +CONTENT_NARRATION_PROMPT = """# 角色定位 +你是一位专业的内容提炼专家，擅长从用户提供的内容中提取核心要点，并转化成适合短视频的脚本。 + +# 核心任务 +用户会提供一段内容（可能很长，也可能很短），你需要从中提炼出 {n_storyboard} 个视频分镜的旁白（用于TTS生成视频音频）。 + +# 用户提供的内容 +{content} + +# 输出要求 + +## 旁白规范 +- 用途定位：用于TTS生成短视频音频 +- 字数限制：严格控制在{min_words}~{max_words}个字（最低不少于{min_words}字） +- 结尾格式：结尾不要使用标点符号 +- 提炼策略： + * 如果用户内容较长：提取{n_storyboard}个核心要点，去除冗余信息 + * 如果用户内容较短：在保留核心观点的基础上适当扩展，增加例子或解释 + * 如果用户内容刚好：优化表达，使其更适合口播 +- 风格要求：保持用户内容的核心观点，但用更口语化、适合TTS的方式表达 +- 开场建议：第一个分镜可以用提问或场景引入，吸引观众注意 +- 核心内容：中间分镜展开用户内容的核心要点 +- 结尾建议：最后一个分镜给出总结或启发 +- 情绪与语气：温和、真诚、自然，像在跟朋友分享观点 +- 禁止项：不出现网址、表情符号、数字编号、不说空话套话 +- 字数检查：生成后必须自我验证每段不少于{min_words}个字 + +## 分镜连贯性要求 +- {n_storyboard} 个分镜应基于用户内容的核心观点展开，形成完整表达 +- 保持逻辑连贯，自然过渡 +- 每个分镜像同一个人在讲述，语气一致 +- 确保提炼的内容忠于用户原意，但更适合短视频呈现 + +# 输出格式 +严格按照以下JSON格式输出，不要添加任何额外的文字说明： + +```json +{{ + "narrations": [ + "第一段{min_words}~{max_words}字的旁白", + "第二段{min_words}~{max_words}字的旁白", + "第三段{min_words}~{max_words}字的旁白" + ] +}} +``` + +# 重要提醒 +1. 只输出JSON格式内容，不要添加任何解释说明 +2. 确保JSON格式严格正确，可以被程序直接解析 +3. 旁白必须严格控制在{min_words}~{max_words}字之间 +4. 必须输出恰好 {n_storyboard} 个分镜的旁白 +5. 内容要忠于用户原意，但优化为更适合口播的表达 +6. 输出格式为 {{"narrations": [旁白数组]}} 的JSON对象 + +现在，请从上述内容中提炼出 {n_storyboard} 个分镜的旁白。只输出JSON，不要其他内容。 +""" + + +# ==================== PROMPT BUILDER FUNCTIONS ==================== + +def build_book_narration_prompt( + book_info: BookInfo, + n_storyboard: int, + min_words: int, + max_words: int +) -> str: + """ + Build book review narration prompt + + Args: + book_info: Book information + n_storyboard: Number of storyboard frames + min_words: Minimum word count + max_words: Maximum word count + + Returns: + Formatted prompt + """ + # Build book description for prompt + book_name = book_info.title + if book_info.author: + book_name = f"{book_info.title} - {book_info.author}" + + return BOOK_NARRATION_PROMPT.format( + book_name=book_name, + n_storyboard=n_storyboard, + min_words=min_words, + max_words=max_words + ) + + +def build_topic_narration_prompt( + topic: str, + n_storyboard: int, + min_words: int, + max_words: int +) -> str: + """ + Build topic narration prompt + + Args: + topic: Topic or theme + n_storyboard: Number of storyboard frames + min_words: Minimum word count + max_words: Maximum word count + + Returns: + Formatted prompt + """ + return TOPIC_NARRATION_PROMPT.format( + topic=topic, + n_storyboard=n_storyboard, + min_words=min_words, + max_words=max_words + ) + + +def build_content_narration_prompt( + content: str, + n_storyboard: int, + min_words: int, + max_words: int +) -> str: + """ + Build content refinement narration prompt + + Args: + content: User-provided content + n_storyboard: Number of storyboard frames + min_words: Minimum word count + max_words: Maximum word count + + Returns: + Formatted prompt + """ + return CONTENT_NARRATION_PROMPT.format( + content=content, + n_storyboard=n_storyboard, + min_words=min_words, + max_words=max_words + ) + + +def build_narration_prompt( + topic: str, + n_storyboard: int, + min_words: int, + max_words: int +) -> str: + """ + Build narration generation prompt (legacy function for backward compatibility) + + Args: + topic: Topic (book name or discussion topic) + n_storyboard: Number of storyboard frames + min_words: Minimum word count + max_words: Maximum word count + + Returns: + Formatted prompt + + Note: + This function is kept for backward compatibility. + Use build_book_narration_prompt, build_topic_narration_prompt, + or build_content_narration_prompt instead. + """ + return build_topic_narration_prompt( + topic=topic, + n_storyboard=n_storyboard, + min_words=min_words, + max_words=max_words + ) + diff --git a/reelforge/service.py b/reelforge/service.py new file mode 100644 index 0000000..f6de1d3 --- /dev/null +++ b/reelforge/service.py @@ -0,0 +1,157 @@ +""" +ReelForge Core - Capability Layer + +Provides unified access to all capabilities (LLM, TTS, etc.) +""" + +from typing import Optional + +from loguru import logger + +from reelforge.config import load_config +from reelforge.core.discovery import CapabilityRegistry +from reelforge.core.mcp_server import reelforge_mcp +from reelforge.core.config_manager import ConfigManager +from reelforge.services import LLMService, TTSService, ImageService, BookFetcherService + + +class ReelForgeCore: + """ + ReelForge Core - Capability Layer + + Provides unified access to all capabilities. + This is the foundation layer, no business logic here. + + Usage: + from reelforge import reelforge + + # Initialize + await reelforge.initialize() + + # Use capabilities directly + answer = await reelforge.llm("Explain atomic habits") + audio = await reelforge.tts("Hello world") + book = await reelforge.book_fetcher("原则") + + # Check active capabilities + print(f"Using LLM: {reelforge.llm.active}") + print(f"Available: {reelforge.llm.available}") + + Architecture (Simplified): + ReelForgeCore (this class) + ├── config (configuration) + ├── config_manager (config injection + MCP calls) + ├── llm (LLM service) + ├── tts (TTS service) + └── book_fetcher (Book fetcher service) + """ + + def __init__(self, config_path: str = "config.yaml"): + """ + Initialize ReelForge Core + + Args: + config_path: Path to configuration file + """ + self.config = load_config(config_path) + self.registry: Optional[CapabilityRegistry] = None + self.config_manager: Optional[ConfigManager] = None + self._initialized = False + + # Services (initialized in initialize()) + self.llm: Optional[LLMService] = None + self.tts: Optional[TTSService] = None + self.image: Optional[ImageService] = None + self.book_fetcher: Optional[BookFetcherService] = None + + # Content generation services + self.narration_generator = None + self.image_prompt_generator = None + self.generate_final_image_prompt = None + + # Frame processing services + self.frame_composer = None + self.storyboard_processor = None + + # Book video service (named as verb for direct calling) + self.generate_book_video = None + + async def initialize(self): + """ + Initialize core capabilities + + This registers built-in capabilities and initializes services. + Must be called before using any capabilities. + + Example: + await reelforge.initialize() + """ + if self._initialized: + logger.warning("ReelForge already initialized") + return + + logger.info("🚀 Initializing ReelForge...") + + # 1. Import all built-in capabilities (registers them with reelforge_mcp) + self._import_builtin_capabilities() + + # 2. Register all built-in capabilities + self.registry = CapabilityRegistry(reelforge_mcp) + await self.registry.register_all() + + # 3. Create config manager + self.config_manager = ConfigManager(self.registry, self.config) + + # 4. Initialize services + self.llm = LLMService(self.config_manager) + self.tts = TTSService(self.config_manager) + self.image = ImageService(self.config_manager) + self.book_fetcher = BookFetcherService(self.config_manager) + self.book_fetcher.set_core(self) # Set core reference for LLM fallback + + # 5. Initialize content generation services + from reelforge.services.narration_generator import NarrationGeneratorService + from reelforge.services.image_prompt_generator import ImagePromptGeneratorService + from reelforge.services.final_image_prompt import FinalImagePromptService + + self.narration_generator = NarrationGeneratorService(self) + self.image_prompt_generator = ImagePromptGeneratorService(self) + self.generate_final_image_prompt = FinalImagePromptService(self) + + # 6. Initialize frame processing services + from reelforge.services.frame_composer import FrameComposerService + from reelforge.services.storyboard_processor import StoryboardProcessorService + + self.frame_composer = FrameComposerService() + self.storyboard_processor = StoryboardProcessorService(self) + + # 7. Initialize book video service + from reelforge.services.book_video import BookVideoService + + self.generate_book_video = BookVideoService(self) + + self._initialized = True + logger.info("✅ ReelForge initialized successfully\n") + + def _import_builtin_capabilities(self): + """Import all built-in capability modules to register them""" + # This triggers the @reelforge_mcp.tool decorators + from reelforge.capabilities import llm # noqa: F401 + from reelforge.capabilities import tts # noqa: F401 + from reelforge.capabilities import image # noqa: F401 + from reelforge.capabilities import book_fetcher # noqa: F401 + + @property + def project_name(self) -> str: + """Get project name from config""" + return self.config.get("project_name", "ReelForge") + + def __repr__(self) -> str: + """String representation""" + status = "initialized" if self._initialized else "not initialized" + return f"" + + +# Global instance +reelforge = ReelForgeCore() + diff --git a/reelforge/services/__init__.py b/reelforge/services/__init__.py new file mode 100644 index 0000000..8673f7f --- /dev/null +++ b/reelforge/services/__init__.py @@ -0,0 +1,40 @@ +""" +ReelForge Services + +Unified service layer providing simplified access to capabilities. +""" + +from reelforge.services.base import BaseService +from reelforge.services.llm import LLMService +from reelforge.services.tts import TTSService +from reelforge.services.image import ImageService +from reelforge.services.book_fetcher import BookFetcherService +from reelforge.services.video import VideoService +from reelforge.services.narration_generator import NarrationGeneratorService +from reelforge.services.image_prompt_generator import ImagePromptGeneratorService +from reelforge.services.frame_composer import FrameComposerService +from reelforge.services.storyboard_processor import StoryboardProcessorService +from reelforge.services.book_video import BookVideoService +from reelforge.services.final_image_prompt import ( + FinalImagePromptService, + StylePreset, + PresetValue +) + +__all__ = [ + "BaseService", + "LLMService", + "TTSService", + "ImageService", + "BookFetcherService", + "VideoService", + "NarrationGeneratorService", + "ImagePromptGeneratorService", + "FrameComposerService", + "StoryboardProcessorService", + "BookVideoService", + "FinalImagePromptService", + "StylePreset", + "PresetValue", +] + diff --git a/reelforge/services/base.py b/reelforge/services/base.py new file mode 100644 index 0000000..8f0ad92 --- /dev/null +++ b/reelforge/services/base.py @@ -0,0 +1,85 @@ +""" +Base service class for all capability services +""" + +from abc import ABC, abstractmethod +from typing import Any, Optional + +from reelforge.core.config_manager import ConfigManager + + +class BaseService(ABC): + """ + Base service class for all capability services + + Provides callable interface and basic properties: + - Direct call: result = await service(...) + - Active capability: service.active + - Available IDs: service.available + + Usage: + result = await reelforge.llm("Hello world") + print(f"Using: {reelforge.llm.active}") + print(f"Available: {reelforge.llm.available}") + """ + + def __init__(self, config_manager: ConfigManager, capability_type: str): + """ + Initialize service + + Args: + config_manager: ConfigManager instance + capability_type: Type of capability (llm, tts, etc.) + """ + self._config_manager = config_manager + self._capability_type = capability_type + + @abstractmethod + async def __call__(self, **kwargs) -> Any: + """ + Make service callable directly + + This is the main entry point for using the service. + Subclasses MUST implement this with specific signatures. + + Example: + answer = await reelforge.llm(prompt="Hello") + """ + pass + + @property + def active(self) -> Optional[str]: + """ + Get active capability ID + + Returns: + Active capability ID (e.g., "call") or None if not set + + Example: + print(f"Using LLM: {reelforge.llm.active}") + """ + return self._config_manager.get_active(self._capability_type) + + @property + def available(self) -> list[str]: + """ + List available capability IDs + + Returns: + List of capability IDs + + Example: + print(f"Available LLMs: {reelforge.llm.available}") + """ + return self._config_manager.get_available_ids(self._capability_type) + + def __repr__(self) -> str: + """String representation""" + active = self.active or "none" + available = ", ".join(self.available) if self.available else "none" + return ( + f"<{self.__class__.__name__} " + f"active={active!r} " + f"available=[{available}]>" + ) + diff --git a/reelforge/services/book_fetcher.py b/reelforge/services/book_fetcher.py new file mode 100644 index 0000000..ca2d444 --- /dev/null +++ b/reelforge/services/book_fetcher.py @@ -0,0 +1,221 @@ +""" +Book Fetcher Service + +Fetch book information from various sources (API or LLM). +""" + +import json +from typing import Optional, Literal + +from loguru import logger + +from reelforge.services.base import BaseService + + +class BookFetcherService(BaseService): + """ + Book information fetcher service + + Provides unified access to various book data sources: + - API: Google Books, Douban, etc. (via configured capability) + - LLM: Generate book info using LLM (flexible, works for any book) + + Usage: + # Use default source (from config, usually 'google') + book_info = await reelforge.book_fetcher("原则") + + # Explicitly use Google Books API + book_info = await reelforge.book_fetcher("Atomic Habits", query_source="google") + + # Explicitly use LLM (good for Chinese books) + book_info = await reelforge.book_fetcher("人性的弱点", query_source="llm") + + # Use Douban (if you implemented it) + book_info = await reelforge.book_fetcher( + book_name="原则", + author="瑞·达利欧", + query_source="douban" + ) + """ + + def __init__(self, config_manager): + super().__init__(config_manager, "book_fetcher") + self._core = None # Will be set by ReelForgeCore (for LLM query) + + def set_core(self, core): + """Set reference to ReelForgeCore (for LLM query)""" + self._core = core + + async def __call__( + self, + book_name: str, + author: Optional[str] = None, + query_source: Optional[Literal["google", "douban", "llm"]] = None, + **kwargs + ) -> dict: + """ + Fetch book information + + Args: + book_name: Book name (required) + author: Author name (optional, improves matching accuracy) + query_source: Data source to query: + - "google": Google Books API + - "douban": Douban Books (requires implementation) + - "llm": Generate book info using LLM + - None: Use default from config (usually "google") + **kwargs: Additional provider-specific parameters + + Returns: + Book information dict with fields: + - title: Book title + - author: Author name + - summary: Book summary + - genre: Book category/genre + - publication_year: Publication year (string) + - key_points: List of key points (only from LLM) + - cover_url: Cover image URL (only from API) + - isbn: ISBN code (only from API) + - source: Data source ("google", "douban", or "llm") + + Examples: + >>> # Use default source (from config) + >>> book = await reelforge.book_fetcher("Atomic Habits") + + >>> # Explicitly use Google Books + >>> book = await reelforge.book_fetcher("Atomic Habits", query_source="google") + + >>> # Explicitly use LLM (good for Chinese books) + >>> book = await reelforge.book_fetcher("人性的弱点", query_source="llm") + + >>> # Use Douban (if implemented) + >>> book = await reelforge.book_fetcher( + ... "原则", + ... author="瑞·达利欧", + ... query_source="douban" + ... ) + + >>> print(f"Title: {book['title']}") + >>> print(f"Source: {book['source']}") + """ + # Route to appropriate method based on query_source + if query_source == "llm": + # Use LLM to generate book info + return await self._fetch_via_llm(book_name, author) + else: + # Use API (google, douban, or default from config) + return await self._fetch_via_api(book_name, author, query_source, **kwargs) + + async def _fetch_via_api( + self, + book_name: str, + author: Optional[str] = None, + query_source: Optional[str] = None, + **kwargs + ) -> dict: + """ + Fetch book information via API capability + + Args: + book_name: Book name + author: Author name (optional) + query_source: Specific capability to use ("google", "douban", or None for default) + **kwargs: Additional parameters + + Returns: + Book information dict + + Raises: + Exception: If API call fails + """ + params = {"book_name": book_name} + if author is not None: + params["author"] = author + params.update(kwargs) + + # Call book_fetcher capability + # If query_source is specified (e.g., "google"), use it + # Otherwise use default from config + result_json = await self._config_manager.call( + self._capability_type, + cap_id=query_source, # None = use default from config + **params + ) + result = json.loads(result_json) + result["source"] = query_source or self.active or "api" + + logger.info(f"✅ Fetched book info from {result['source']}: {result.get('title', book_name)}") + return result + + async def _fetch_via_llm(self, book_name: str, author: Optional[str] = None) -> dict: + """ + Generate book information using LLM + + This method uses LLM to generate book information based on its knowledge. + Good for books that are not available in API databases or for Chinese books. + + Args: + book_name: Book name + author: Author name (optional) + + Returns: + Book information dict + + Raises: + ValueError: If LLM response cannot be parsed + Exception: If LLM call fails + """ + if not self._core: + raise RuntimeError("ReelForgeCore not set. Cannot use LLM query.") + + # Build prompt + author_info = f"，作者是{author}" if author else "" + prompt = f"""请为书籍《{book_name}》{author_info}生成详细的书籍信息。 + +要求： +1. 如果你知道这本书，请提供真实准确的信息 +2. 如果不确定，请基于书名和作者推测合理的信息 +3. 严格按照JSON格式输出，不要添加任何其他内容 + +输出格式（JSON）： +{{ + "title": "书名", + "author": "作者", + "summary": "书籍简介（100-200字，概括核心内容和价值）", + "genre": "书籍类型（如：自我成长、商业管理、心理学等）", + "publication_year": "2018", + "key_points": [ + "核心观点1（20-30字）", + "核心观点2（20-30字）", + "核心观点3（20-30字）" + ] +}} + +只输出JSON，不要其他内容。""" + + # Call LLM + response = await self._core.llm( + prompt=prompt, + temperature=0.3, # Lower temperature for more factual responses + max_tokens=1000 + ) + + # Parse JSON + try: + book_info = json.loads(response) + except json.JSONDecodeError as e: + logger.error(f"Failed to parse LLM response as JSON: {e}") + logger.error(f"Response: {response[:200]}...") + raise ValueError(f"LLM returned invalid JSON for book: {book_name}") + + # Ensure required fields exist + book_info.setdefault("title", book_name) + book_info.setdefault("author", author or "Unknown") + book_info.setdefault("summary", "No summary available") + book_info.setdefault("genre", "Unknown") + book_info.setdefault("publication_year", "") + book_info["source"] = "llm" + + logger.info(f"✅ Generated book info via LLM: {book_info['title']}") + return book_info + diff --git a/reelforge/services/book_video.py b/reelforge/services/book_video.py new file mode 100644 index 0000000..ce487cd --- /dev/null +++ b/reelforge/services/book_video.py @@ -0,0 +1,464 @@ +""" +Book Video Service + +End-to-end service for generating book short videos. +""" + +from datetime import datetime +from pathlib import Path +from typing import Optional, Callable, Literal + +from loguru import logger + +from reelforge.models.progress import ProgressEvent +from reelforge.models.storyboard import ( + Storyboard, + StoryboardFrame, + StoryboardConfig, + BookInfo, + VideoGenerationResult +) + + +class BookVideoService: + """ + Book video generation service + + Orchestrates the complete pipeline: + 1. Generate narrations (LLM) + 2. Generate image prompts (LLM) + 3. Process each frame (TTS + Image + Compose + Video) + 4. Concatenate all segments + 5. Add BGM (optional) + """ + + def __init__(self, reelforge_core): + """ + Initialize book video service + + Args: + reelforge_core: ReelForgeCore instance + """ + self.core = reelforge_core + + async def __call__( + self, + # === Content Source (Choose ONE, mutually exclusive) === + book_name: Optional[str] = None, + author: Optional[str] = None, + topic: Optional[str] = None, + content: Optional[str] = None, + + # === Optional Title (works with any source) === + title: Optional[str] = None, + + # === Basic Config === + n_frames: int = 5, + voice_id: str = "zh-CN-YunjianNeural", + output_path: Optional[str] = None, + + # === LLM Parameters === + min_narration_words: int = 20, + max_narration_words: int = 40, + min_image_prompt_words: int = 50, + max_image_prompt_words: int = 100, + + # === Image Parameters === + image_width: int = 1024, + image_height: int = 1024, + image_style_preset: Optional[str] = None, + image_style_description: Optional[str] = None, + + # === Video Parameters === + video_width: int = 1080, + video_height: int = 1920, + video_fps: int = 30, + + # === Frame Template === + frame_template: Optional[str] = None, + + # === BGM Parameters === + bgm_path: Optional[str] = None, + bgm_volume: float = 0.2, + bgm_mode: Literal["once", "loop"] = "loop", + + # === Advanced Options === + book_info: Optional[BookInfo] = None, + progress_callback: Optional[Callable[[ProgressEvent], None]] = None, + ) -> VideoGenerationResult: + """ + Generate book short video from different content sources + + Args: + book_name: Book name (e.g., "从零到一") + author: Book author (optional, pairs with book_name) + topic: Topic/theme (e.g., "如何提高学习效率") + content: User-provided content (any length) + + Note: Must provide exactly ONE of: book_name, topic, or content + + title: Video title (optional) + - If provided, use it as the video title + - If not provided, auto-generate based on source: + * book_name → use book title + * topic → use topic text + * content → LLM extracts title from content + + n_frames: Number of storyboard frames (default 5) + voice_id: TTS voice ID (default "zh-CN-YunjianNeural") + output_path: Output video path (auto-generated if None) + + min_narration_words: Min narration length + max_narration_words: Max narration length + min_image_prompt_words: Min image prompt length + max_image_prompt_words: Max image prompt length + + image_width: Generated image width (default 1024) + image_height: Generated image height (default 1024) + image_style_preset: Preset style name (e.g., "book", "stick_figure", "minimal", "concept") + image_style_description: Custom style description (overrides preset) + + video_width: Final video width (default 1080) + video_height: Final video height (default 1920) + video_fps: Video frame rate (default 30) + + frame_template: HTML template name or path (None = use PIL) + e.g., "classic", "modern", "minimal", or custom path + + bgm_path: BGM path ("default", "happy", custom path, or None) + bgm_volume: BGM volume 0.0-1.0 (default 0.2) + bgm_mode: BGM mode "once" or "loop" (default "loop") + + book_info: Book metadata (optional) + progress_callback: Progress callback function(message, progress) + + Returns: + VideoGenerationResult with video path and metadata + + Examples: + # Generate from book name + >>> result = await reelforge.generate_book_video( + ... book_name="从零到一", + ... author="彼得·蒂尔", + ... n_frames=5, + ... image_style_preset="book" + ... ) + + # Generate from topic + >>> result = await reelforge.generate_book_video( + ... topic="如何在信息爆炸时代保持深度思考", + ... n_frames=5, + ... bgm_path="default" + ... ) + + # Generate from user content with auto-generated title + >>> result = await reelforge.generate_book_video( + ... content="昨天我读了一本书，讲的是...", + ... n_frames=3 + ... ) + + # Generate from user content with custom title + >>> result = await reelforge.generate_book_video( + ... content="买房子，第一应该看的是楼盘的整体环境...", + ... title="买房风水指南", + ... n_frames=5 + ... ) + >>> print(result.video_path) + """ + # ========== Step 0: Validate parameters (mutually exclusive) ========== + sources = [book_name, topic, content] + source_count = sum(x is not None for x in sources) + + if source_count == 0: + raise ValueError( + "Must provide exactly ONE of: book_name, topic, or content" + ) + elif source_count > 1: + raise ValueError( + "Cannot provide multiple sources. Choose ONE of: book_name, topic, or content" + ) + + # Determine source type + if book_name: + source_type = "book" + elif topic: + source_type = "topic" + else: # content + source_type = "content" + + # Determine final title (priority: user-specified > auto-generated) + if title: + # User specified title, use it directly + final_title = title + logger.info(f"🚀 Starting book video generation from {source_type} with title: '{title}'") + else: + # Auto-generate title based on source + if source_type == "book": + final_title = f"{book_name}" + (f" - {author}" if author else "") + logger.info(f"🚀 Starting book video generation from book: '{final_title}'") + elif source_type == "topic": + final_title = topic + logger.info(f"🚀 Starting book video generation from topic: '{final_title}'") + else: # content + # Will generate title from content using LLM + logger.info(f"🚀 Starting book video generation from content ({len(content)} chars)") + final_title = None # Will be generated later + + # Generate title from content if needed (before creating output path) + if source_type == "content" and final_title is None: + self._report_progress(progress_callback, "generating_title", 0.01) + final_title = await self._generate_title_from_content(content) + logger.info(f"✅ Generated title: {final_title}") + + # Auto-generate output path if not provided + if output_path is None: + timestamp = datetime.now().strftime('%Y%m%d_%H%M%S') + # Use first 10 chars of final_title for filename + safe_name = final_title[:10].replace('/', '_').replace(' ', '_') + output_path = f"output/{timestamp}_{safe_name}.mp4" + + # Ensure output directory exists + Path(output_path).parent.mkdir(parents=True, exist_ok=True) + + # Create storyboard config + config = StoryboardConfig( + n_storyboard=n_frames, + min_narration_words=min_narration_words, + max_narration_words=max_narration_words, + min_image_prompt_words=min_image_prompt_words, + max_image_prompt_words=max_image_prompt_words, + video_width=video_width, + video_height=video_height, + video_fps=video_fps, + voice_id=voice_id, + image_width=image_width, + image_height=image_height, + frame_template=frame_template + ) + + # Create storyboard + storyboard = Storyboard( + topic=final_title, # Use final_title as video title + config=config, + book_info=book_info, + created_at=datetime.now() + ) + + # Store storyboard in core for access in storyboard processor + self.core._current_storyboard = storyboard + + try: + # ========== Step 1: Route based on source type ========== + + # Step 1a: Fetch book info if needed + if source_type == "book": + self._report_progress(progress_callback, "fetching_book_info", 0.03) + book_dict = await self.core.book_fetcher( + book_name=book_name, + author=author + ) + + # Convert dict to BookInfo object + fetched_book_info = BookInfo( + title=book_dict.get("title", book_name), + author=book_dict.get("author", author or "Unknown"), + summary=book_dict.get("summary", ""), + genre=book_dict.get("genre", ""), + publication_year=book_dict.get("publication_year", ""), + cover_url=book_dict.get("cover_url") + ) + logger.info(f"✅ Fetched book info: {fetched_book_info.title}") + + # Update storyboard with fetched book info + storyboard.book_info = fetched_book_info + else: + fetched_book_info = None + + # Step 1b: Generate narrations + self._report_progress(progress_callback, "generating_narrations", 0.05) + narrations = await self.core.narration_generator.generate_narrations( + config=config, + source_type=source_type, + book_info=fetched_book_info if source_type == "book" else None, + topic=topic if source_type == "topic" else None, + content=content if source_type == "content" else None + ) + logger.info(f"✅ Generated {len(narrations)} narrations") + + # Step 2: Generate image prompts + self._report_progress(progress_callback, "generating_image_prompts", 0.15) + image_prompts = await self.core.image_prompt_generator.generate_image_prompts( + narrations=narrations, + config=config, + image_style_preset=image_style_preset, + image_style_description=image_style_description + ) + logger.info(f"✅ Generated {len(image_prompts)} image prompts") + + # Step 3: Create frames + for i, (narration, image_prompt) in enumerate(zip(narrations, image_prompts)): + frame = StoryboardFrame( + index=i, + narration=narration, + image_prompt=image_prompt, + created_at=datetime.now() + ) + storyboard.frames.append(frame) + + # Step 4: Process each frame + for i, frame in enumerate(storyboard.frames): + # Calculate fine-grained progress for this frame + base_progress = 0.2 # Frames processing starts at 20% + frame_range = 0.6 # Frames processing takes 60% (20%-80%) + per_frame_progress = frame_range / len(storyboard.frames) + + # Create frame-specific progress callback + def frame_progress_callback(event: ProgressEvent): + """Report sub-step progress within current frame""" + # Calculate overall progress: base + previous frames + current frame progress + overall_progress = base_progress + (per_frame_progress * i) + (per_frame_progress * event.progress) + # Forward the event with adjusted overall progress + if progress_callback: + adjusted_event = ProgressEvent( + event_type=event.event_type, + progress=overall_progress, + frame_current=event.frame_current, + frame_total=event.frame_total, + step=event.step, + action=event.action + ) + progress_callback(adjusted_event) + + # Report frame start + self._report_progress( + progress_callback, + "processing_frame", + base_progress + (per_frame_progress * i), + frame_current=i+1, + frame_total=len(storyboard.frames) + ) + + processed_frame = await self.core.storyboard_processor.process_frame( + frame=frame, + config=config, + total_frames=len(storyboard.frames), + progress_callback=frame_progress_callback + ) + storyboard.total_duration += processed_frame.duration + logger.info(f"✅ Frame {i+1} completed ({processed_frame.duration:.2f}s)") + + # Step 5: Concatenate videos + self._report_progress(progress_callback, "concatenating", 0.85) + segment_paths = [frame.video_segment_path for frame in storyboard.frames] + + from reelforge.services.video import VideoService + video_service = VideoService() + + final_video_path = video_service.concat_videos( + videos=segment_paths, + output=output_path, + bgm_path=bgm_path, + bgm_volume=bgm_volume, + bgm_mode=bgm_mode + ) + + storyboard.final_video_path = final_video_path + storyboard.completed_at = datetime.now() + + logger.success(f"🎬 Video generation completed: {final_video_path}") + + # Step 6: Create result + self._report_progress(progress_callback, "finalizing", 1.0) + + video_path_obj = Path(final_video_path) + file_size = video_path_obj.stat().st_size + + result = VideoGenerationResult( + video_path=final_video_path, + storyboard=storyboard, + duration=storyboard.total_duration, + file_size=file_size + ) + + logger.info(f"✅ Generated video: {final_video_path}") + logger.info(f" Duration: {storyboard.total_duration:.2f}s") + logger.info(f" Size: {file_size / (1024*1024):.2f} MB") + logger.info(f" Frames: {len(storyboard.frames)}") + + return result + + except Exception as e: + logger.error(f"❌ Video generation failed: {e}") + raise + + def _report_progress( + self, + callback: Optional[Callable[[ProgressEvent], None]], + event_type: str, + progress: float, + **kwargs + ): + """ + Report progress via callback + + Args: + callback: Progress callback function + event_type: Type of progress event + progress: Progress value (0.0-1.0) + **kwargs: Additional event-specific parameters (frame_current, frame_total, etc.) + """ + if callback: + event = ProgressEvent(event_type=event_type, progress=progress, **kwargs) + callback(event) + logger.debug(f"Progress: {progress*100:.0f}% - {event_type}") + else: + logger.debug(f"Progress: {progress*100:.0f}% - {event_type}") + + async def _generate_title_from_content(self, content: str) -> str: + """ + Generate a short, attractive title from user content using LLM + + Args: + content: User-provided content + + Returns: + Generated title (10 characters or less) + """ + # Take first 500 chars to avoid overly long prompts + content_preview = content[:500] + + prompt = f"""请为以下内容生成一个简短、有吸引力的标题（10字以内）。 + +内容： +{content_preview} + +要求： +1. 简短精炼，10字以内 +2. 准确概括核心内容 +3. 有吸引力，适合作为视频标题 +4. 只输出标题文本，不要其他内容 + +标题：""" + + # Call LLM to generate title + response = await self.core.llm( + prompt=prompt, + temperature=0.7, + max_tokens=50 + ) + + # Clean up response + title = response.strip() + + # Remove quotes if present + if title.startswith('"') and title.endswith('"'): + title = title[1:-1] + if title.startswith("'") and title.endswith("'"): + title = title[1:-1] + + # Limit to 20 chars max (safety) + if len(title) > 20: + title = title[:20] + + return title + diff --git a/reelforge/services/book_video_workflow.py b/reelforge/services/book_video_workflow.py new file mode 100644 index 0000000..7720799 --- /dev/null +++ b/reelforge/services/book_video_workflow.py @@ -0,0 +1,454 @@ +""" +Book Video Service + +End-to-end service for generating book short videos. +""" + +from datetime import datetime +from pathlib import Path +from typing import Optional, Callable + +from loguru import logger + +from reelforge.models.progress import ProgressEvent +from reelforge.models.storyboard import ( + Storyboard, + StoryboardFrame, + StoryboardConfig, + BookInfo, + VideoGenerationResult +) + + +class BookVideoService: + """ + Book video generation service + + Orchestrates the complete pipeline: + 1. Generate narrations (LLM) + 2. Generate image prompts (LLM) + 3. Process each frame (TTS + Image + Compose + Video) + 4. Concatenate all segments + 5. Add BGM (optional) + """ + + def __init__(self, reelforge_core): + """ + Initialize book video service + + Args: + reelforge_core: ReelForgeCore instance + """ + self.core = reelforge_core + + async def __call__( + self, + # === Content Source (Choose ONE, mutually exclusive) === + book_name: Optional[str] = None, + author: Optional[str] = None, + topic: Optional[str] = None, + content: Optional[str] = None, + + # === Optional Title (works with any source) === + title: Optional[str] = None, + + # === Basic Config === + n_frames: int = 3, + voice_id: str = "zh-CN-YunjianNeural", + output_path: Optional[str] = None, + + # === LLM Parameters === + min_narration_words: int = 20, + max_narration_words: int = 40, + min_image_prompt_words: int = 50, + max_image_prompt_words: int = 100, + + # === Image Parameters === + image_width: int = 1024, + image_height: int = 1024, + image_style_preset: Optional[str] = None, + image_style_description: Optional[str] = None, + + # === Video Parameters === + video_width: int = 1080, + video_height: int = 1920, + video_fps: int = 30, + + # === BGM Parameters === + bgm_path: Optional[str] = None, + bgm_volume: float = 0.2, + bgm_mode: str = "loop", + + # === Advanced Options === + book_info: Optional[BookInfo] = None, + progress_callback: Optional[Callable[[ProgressEvent], None]] = None, + ) -> VideoGenerationResult: + """ + Generate book short video from different content sources + + Args: + book_name: Book name (e.g., "从零到一") + author: Book author (optional, pairs with book_name) + topic: Topic/theme (e.g., "如何提高学习效率") + content: User-provided content (any length) + + Note: Must provide exactly ONE of: book_name, topic, or content + + title: Video title (optional) + - If provided, use it as the video title + - If not provided, auto-generate based on source: + * book_name → use book title + * topic → use topic text + * content → LLM extracts title from content + + n_frames: Number of storyboard frames (default 3) + voice_id: TTS voice ID (default "zh-CN-YunjianNeural") + output_path: Output video path (auto-generated if None) + + min_narration_words: Min narration length + max_narration_words: Max narration length + min_image_prompt_words: Min image prompt length + max_image_prompt_words: Max image prompt length + + image_width: Generated image width (default 1024) + image_height: Generated image height (default 1024) + image_style_preset: Preset style name (e.g., "book", "stick_figure", "minimal", "concept") + image_style_description: Custom style description (overrides preset) + + video_width: Final video width (default 1080) + video_height: Final video height (default 1920) + video_fps: Video frame rate (default 30) + + bgm_path: BGM path ("default", "happy", custom path, or None) + bgm_volume: BGM volume 0.0-1.0 (default 0.2) + bgm_mode: BGM mode "once" or "loop" (default "loop") + + book_info: Book metadata (optional) + progress_callback: Progress callback function(message, progress) + + Returns: + VideoGenerationResult with video path and metadata + + Examples: + # Generate from book name + >>> result = await reelforge.generate_book_video( + ... book_name="从零到一", + ... author="彼得·蒂尔", + ... n_frames=3, + ... image_style_preset="book" + ... ) + + # Generate from topic + >>> result = await reelforge.generate_book_video( + ... topic="如何在信息爆炸时代保持深度思考", + ... n_frames=3, + ... bgm_path="default" + ... ) + + # Generate from user content with auto-generated title + >>> result = await reelforge.generate_book_video( + ... content="昨天我读了一本书，讲的是...", + ... n_frames=3 + ... ) + + # Generate from user content with custom title + >>> result = await reelforge.generate_book_video( + ... content="买房子，第一应该看的是楼盘的整体环境...", + ... title="买房风水指南", + ... n_frames=3 + ... ) + >>> print(result.video_path) + """ + # ========== Step 0: Validate parameters (mutually exclusive) ========== + sources = [book_name, topic, content] + source_count = sum(x is not None for x in sources) + + if source_count == 0: + raise ValueError( + "Must provide exactly ONE of: book_name, topic, or content" + ) + elif source_count > 1: + raise ValueError( + "Cannot provide multiple sources. Choose ONE of: book_name, topic, or content" + ) + + # Determine source type + if book_name: + source_type = "book" + elif topic: + source_type = "topic" + else: # content + source_type = "content" + + # Determine final title (priority: user-specified > auto-generated) + if title: + # User specified title, use it directly + final_title = title + logger.info(f"🚀 Starting book video generation from {source_type} with title: '{title}'") + else: + # Auto-generate title based on source + if source_type == "book": + final_title = f"{book_name}" + (f" - {author}" if author else "") + logger.info(f"🚀 Starting book video generation from book: '{final_title}'") + elif source_type == "topic": + final_title = topic + logger.info(f"🚀 Starting book video generation from topic: '{final_title}'") + else: # content + # Will generate title from content using LLM + logger.info(f"🚀 Starting book video generation from content ({len(content)} chars)") + final_title = None # Will be generated later + + # Generate title from content if needed (before creating output path) + if source_type == "content" and final_title is None: + self._report_progress(progress_callback, "generating_title", 0.01) + final_title = await self._generate_title_from_content(content) + logger.info(f"✅ Generated title: {final_title}") + + # Auto-generate output path if not provided + if output_path is None: + timestamp = datetime.now().strftime('%Y%m%d_%H%M%S') + # Use first 10 chars of final_title for filename + safe_name = final_title[:10].replace('/', '_').replace(' ', '_') + output_path = f"output/{timestamp}_{safe_name}.mp4" + + # Ensure output directory exists + Path(output_path).parent.mkdir(parents=True, exist_ok=True) + + # Create storyboard config + config = StoryboardConfig( + n_storyboard=n_frames, + min_narration_words=min_narration_words, + max_narration_words=max_narration_words, + min_image_prompt_words=min_image_prompt_words, + max_image_prompt_words=max_image_prompt_words, + video_width=video_width, + video_height=video_height, + video_fps=video_fps, + voice_id=voice_id, + image_width=image_width, + image_height=image_height + ) + + # Create storyboard + storyboard = Storyboard( + topic=final_title, # Use final_title as video title + config=config, + book_info=book_info, + created_at=datetime.now() + ) + + try: + # ========== Step 1: Route based on source type ========== + + # Step 1a: Fetch book info if needed + if source_type == "book": + self._report_progress(progress_callback, "fetching_book_info", 0.03) + book_dict = await self.core.book_fetcher( + book_name=book_name, + author=author + ) + + # Convert dict to BookInfo object + fetched_book_info = BookInfo( + title=book_dict.get("title", book_name), + author=book_dict.get("author", author or "Unknown"), + summary=book_dict.get("summary", ""), + genre=book_dict.get("genre", ""), + publication_year=book_dict.get("publication_year", ""), + cover_url=book_dict.get("cover_url") + ) + logger.info(f"✅ Fetched book info: {fetched_book_info.title}") + + # Update storyboard with fetched book info + storyboard.book_info = fetched_book_info + else: + fetched_book_info = None + + # Step 1b: Generate narrations + self._report_progress(progress_callback, "generating_narrations", 0.05) + narrations = await self.core.narration_generator.generate_narrations( + config=config, + source_type=source_type, + book_info=fetched_book_info if source_type == "book" else None, + topic=topic if source_type == "topic" else None, + content=content if source_type == "content" else None + ) + logger.info(f"✅ Generated {len(narrations)} narrations") + + # Step 2: Generate image prompts + self._report_progress(progress_callback, "generating_image_prompts", 0.15) + image_prompts = await self.core.image_prompt_generator.generate_image_prompts( + narrations=narrations, + config=config, + image_style_preset=image_style_preset, + image_style_description=image_style_description + ) + logger.info(f"✅ Generated {len(image_prompts)} image prompts") + + # Step 3: Create frames + for i, (narration, image_prompt) in enumerate(zip(narrations, image_prompts)): + frame = StoryboardFrame( + index=i, + narration=narration, + image_prompt=image_prompt, + created_at=datetime.now() + ) + storyboard.frames.append(frame) + + # Step 4: Process each frame + for i, frame in enumerate(storyboard.frames): + # Calculate fine-grained progress for this frame + base_progress = 0.2 # Frames processing starts at 20% + frame_range = 0.6 # Frames processing takes 60% (20%-80%) + per_frame_progress = frame_range / len(storyboard.frames) + + # Create frame-specific progress callback + def frame_progress_callback(event: ProgressEvent): + """Report sub-step progress within current frame""" + # Calculate overall progress: base + previous frames + current frame progress + overall_progress = base_progress + (per_frame_progress * i) + (per_frame_progress * event.progress) + # Forward the event with adjusted overall progress + if progress_callback: + adjusted_event = ProgressEvent( + event_type=event.event_type, + progress=overall_progress, + frame_current=event.frame_current, + frame_total=event.frame_total, + step=event.step, + action=event.action + ) + progress_callback(adjusted_event) + + # Report frame start + self._report_progress( + progress_callback, + "processing_frame", + base_progress + (per_frame_progress * i), + frame_current=i+1, + frame_total=len(storyboard.frames) + ) + + processed_frame = await self.core.storyboard_processor.process_frame( + frame=frame, + config=config, + total_frames=len(storyboard.frames), + progress_callback=frame_progress_callback + ) + storyboard.total_duration += processed_frame.duration + logger.info(f"✅ Frame {i+1} completed ({processed_frame.duration:.2f}s)") + + # Step 5: Concatenate videos + self._report_progress(progress_callback, "concatenating", 0.85) + segment_paths = [frame.video_segment_path for frame in storyboard.frames] + + from reelforge.services.video import VideoService + video_service = VideoService() + + final_video_path = video_service.concat_videos( + videos=segment_paths, + output=output_path, + bgm_path=bgm_path, + bgm_volume=bgm_volume, + bgm_mode=bgm_mode + ) + + storyboard.final_video_path = final_video_path + storyboard.completed_at = datetime.now() + + logger.success(f"🎬 Video generation completed: {final_video_path}") + + # Step 6: Create result + self._report_progress(progress_callback, "finalizing", 1.0) + + video_path_obj = Path(final_video_path) + file_size = video_path_obj.stat().st_size + + result = VideoGenerationResult( + video_path=final_video_path, + storyboard=storyboard, + duration=storyboard.total_duration, + file_size=file_size + ) + + logger.info(f"✅ Generated video: {final_video_path}") + logger.info(f" Duration: {storyboard.total_duration:.2f}s") + logger.info(f" Size: {file_size / (1024*1024):.2f} MB") + logger.info(f" Frames: {len(storyboard.frames)}") + + return result + + except Exception as e: + logger.error(f"❌ Video generation failed: {e}") + raise + + def _report_progress( + self, + callback: Optional[Callable[[ProgressEvent], None]], + event_type: str, + progress: float, + **kwargs + ): + """ + Report progress via callback + + Args: + callback: Progress callback function + event_type: Type of progress event + progress: Progress value (0.0-1.0) + **kwargs: Additional event-specific parameters (frame_current, frame_total, etc.) + """ + if callback: + event = ProgressEvent(event_type=event_type, progress=progress, **kwargs) + callback(event) + logger.debug(f"Progress: {progress*100:.0f}% - {event_type}") + else: + logger.debug(f"Progress: {progress*100:.0f}% - {event_type}") + + async def _generate_title_from_content(self, content: str) -> str: + """ + Generate a short, attractive title from user content using LLM + + Args: + content: User-provided content + + Returns: + Generated title (10 characters or less) + """ + # Take first 500 chars to avoid overly long prompts + content_preview = content[:500] + + prompt = f"""请为以下内容生成一个简短、有吸引力的标题（10字以内）。 + +内容： +{content_preview} + +要求： +1. 简短精炼，10字以内 +2. 准确概括核心内容 +3. 有吸引力，适合作为视频标题 +4. 只输出标题文本，不要其他内容 + +标题：""" + + # Call LLM to generate title + response = await self.core.llm( + prompt=prompt, + temperature=0.7, + max_tokens=50 + ) + + # Clean up response + title = response.strip() + + # Remove quotes if present + if title.startswith('"') and title.endswith('"'): + title = title[1:-1] + if title.startswith("'") and title.endswith("'"): + title = title[1:-1] + + # Limit to 20 chars max (safety) + if len(title) > 20: + title = title[:20] + + return title + diff --git a/reelforge/services/final_image_prompt.py b/reelforge/services/final_image_prompt.py new file mode 100644 index 0000000..4b18d45 --- /dev/null +++ b/reelforge/services/final_image_prompt.py @@ -0,0 +1,206 @@ +""" +Final Image Prompt Service + +Generates final complete image prompts by converting style descriptions +and combining them with base prompts in consistent order. +""" + +from collections import namedtuple +from enum import Enum +from typing import Optional + +from loguru import logger + + +# Define preset value structure +PresetValue = namedtuple('PresetValue', ['display_name', 'prompt']) + + +class StylePreset(Enum): + """Predefined style presets for image generation""" + + STICK_FIGURE = PresetValue( + display_name="Stick Figure", + prompt=( + "Pure white background, minimalist illustration, matchstick figure style, " + "black and white line drawing, simple clean lines" + ), + ) + + MINIMAL = PresetValue( + display_name="Minimal", + prompt=( + "Simple and clean background, minimal design, soft colors, " + "professional look, modern aesthetic, uncluttered composition" + ), + ) + + FUTURISTIC = PresetValue( + display_name="Futuristic", + prompt=( + "Futuristic sci-fi style, high-tech city background, " + "blue and silver tones, technology sense, soft neon lights, " + "cyberpunk aesthetics, digital art, advanced technology" + ), + ) + + CINEMATIC = PresetValue( + display_name="Cinematic", + prompt=( + "Cinematic lighting, dramatic composition, film grain, " + "professional photography, depth of field, movie still quality" + ), + ) + + +class FinalImagePromptService: + """ + Final Image Prompt Service + + Generates the final complete image prompt by: + 1. Converting style description (preset or custom) + 2. Combining style + base prompt in correct order + + This ensures: + - Consistent style conversion logic across all scenarios + - Consistent prompt concatenation order (style first, then prompt) + - Single source of truth for image prompt generation + + Usage: + # With preset style + final = await reelforge.generate_final_image_prompt( + prompt="A beautiful book on a desk", + style_preset=StylePreset.FUTURISTIC + ) + + # With custom style (any language) + final = await reelforge.generate_final_image_prompt( + prompt="A book", + custom_style_description="温馨的咖啡馆，暖色调" + ) + + # Only prompt (no style) + final = await reelforge.generate_final_image_prompt( + prompt="A book on a wooden desk" + ) + """ + + def __init__(self, reelforge_core): + """ + Initialize service + + Args: + reelforge_core: ReelForgeCore instance for accessing LLM + """ + self.core = reelforge_core + + async def __call__( + self, + prompt: str = "", + style_preset: Optional[StylePreset] = None, + custom_style_description: str = "" + ) -> str: + """ + Generate final image prompt with style + + Priority: + 1. custom_style_description (if provided) → convert via LLM + 2. style_preset (if provided) → use predefined English prompt + 3. Neither → just return prompt + + Concatenation: + - Style part (if exists) comes first + - Base prompt (if exists) comes second + - Join with comma: "{style_part}, {prompt}" + + Args: + prompt: Base prompt (optional, e.g., "A beautiful book on a desk") + style_preset: Preset style from StylePreset enum (optional) + custom_style_description: Custom description in any language (optional) + Overrides style_preset if provided + + Returns: + Final complete image prompt in English + + Examples: + # With preset style (IDE autocomplete!) + final = await service( + prompt="A book on a desk", + style_preset=StylePreset.FUTURISTIC + ) + # Returns: "Futuristic sci-fi style..., A book on a desk" + + # With custom style (any language) + final = await service( + prompt="A book", + custom_style_description="温馨的咖啡馆，暖色调" + ) + # Returns: "Cozy coffee shop interior..., A book" + + # Only prompt + final = await service(prompt="A book on desk") + # Returns: "A book on desk" + + # Only style + final = await service(style_preset=StylePreset.MINIMAL) + # Returns: "Simple and clean background..." + """ + + # Step 1: Determine style part + style_part = "" + + if custom_style_description: + # Priority 1: Custom description (convert via LLM) + logger.debug(f"Converting custom style description: {custom_style_description}") + style_part = await self._convert_custom_style(custom_style_description) + + elif style_preset: + # Priority 2: Preset style (use prompt from enum value) + style_part = style_preset.value.prompt + logger.debug(f"Using preset style: {style_preset.name}") + + # Step 2: Combine parts with comma + parts = [p for p in [style_part, prompt] if p] + final_prompt = ", ".join(parts) + + if final_prompt: + logger.debug(f"Final image prompt: {final_prompt}") + else: + logger.warning("Generated empty image prompt") + + return final_prompt + + async def _convert_custom_style(self, description: str) -> str: + """ + Convert custom style description to English image prompt via LLM + + Args: + description: User's style description in any language + + Returns: + Converted English image prompt suitable for image generation models + """ + + llm_prompt = f"""Convert this style description into a detailed image generation prompt for Stable Diffusion/FLUX: + +Style Description: {description} + +Requirements: +- Focus on visual elements, colors, lighting, mood, atmosphere +- Be specific and detailed +- Use professional photography/art terminology +- Output ONLY the prompt in English (no explanations) +- Keep it under 100 words +- Use comma-separated descriptive phrases + +Image Prompt:""" + + style_prompt = await self.core.llm(llm_prompt) + + # Clean up the result (remove extra whitespace, newlines) + style_prompt = " ".join(style_prompt.strip().split()) + + logger.debug(f"Converted custom style to: {style_prompt}") + + return style_prompt + diff --git a/reelforge/services/frame_composer.py b/reelforge/services/frame_composer.py new file mode 100644 index 0000000..2e5cf4d --- /dev/null +++ b/reelforge/services/frame_composer.py @@ -0,0 +1,166 @@ +""" +Frame composer service - Compose image with subtitle overlay + +Simple implementation for MVP: adds subtitle text to generated image. +""" + +from pathlib import Path + +from loguru import logger +from PIL import Image, ImageDraw, ImageFont + +from reelforge.models.storyboard import StoryboardConfig + + +class FrameComposerService: + """ + Frame composer service + + Composes final frame image by adding subtitle text to generated image. + For MVP, we keep it simple - just overlay subtitle at bottom. + """ + + def __init__(self): + self.font_path = self._get_font_path() + + def _get_font_path(self) -> str: + """Get Chinese font path""" + # Try multiple possible font paths + possible_fonts = [ + "/System/Library/Fonts/PingFang.ttc", # macOS PingFang + "/System/Library/Fonts/STHeiti Light.ttc", # macOS Heiti + "/System/Library/Fonts/Hiragino Sans GB.ttc", # macOS Hiragino + "/usr/share/fonts/truetype/noto/NotoSansCJK-Regular.ttc", # Linux Noto + ] + + for font in possible_fonts: + if Path(font).exists(): + logger.debug(f"Using font: {font}") + return font + + logger.warning("No Chinese font found, will use default") + return None + + async def compose_frame( + self, + image_path: str, + subtitle: str, + output_path: str, + config: StoryboardConfig + ) -> str: + """ + Compose frame image with subtitle overlay + + Args: + image_path: Generated image path + subtitle: Subtitle text (narration) + output_path: Output path for composed image + config: Storyboard configuration + + Returns: + Path to composed image + """ + logger.debug(f"Composing frame: {output_path}") + + # Load generated image + img = Image.open(image_path) + + # Create canvas with target video size + canvas = Image.new('RGB', (config.video_width, config.video_height), 'white') + + # Calculate scaling to fit image in canvas while preserving aspect ratio + # Leave space at top (100px) and bottom (300px for subtitle) + max_img_width = config.video_width + max_img_height = config.video_height - 400 # Reserve space for subtitle + + # Calculate aspect-fit scaling + img_aspect = img.width / img.height + target_aspect = max_img_width / max_img_height + + if img_aspect > target_aspect: + # Image is wider - fit to width + new_width = max_img_width + new_height = int(max_img_width / img_aspect) + else: + # Image is taller - fit to height + new_height = max_img_height + new_width = int(max_img_height * img_aspect) + + img_resized = img.resize((new_width, new_height), Image.Resampling.LANCZOS) + + # Paste image at center-top + x_offset = (config.video_width - new_width) // 2 + y_offset = 100 # Leave some space at top + canvas.paste(img_resized, (x_offset, y_offset)) + + # Add subtitle at bottom + draw = ImageDraw.Draw(canvas) + self._draw_subtitle(draw, subtitle, config.video_width, config.video_height) + + # Save + canvas.save(output_path, quality=95) + logger.debug(f"Frame composed: {output_path}") + + return output_path + + def _draw_subtitle( + self, + draw: ImageDraw.Draw, + text: str, + width: int, + height: int + ): + """Draw subtitle text at bottom of canvas""" + try: + if self.font_path: + font = ImageFont.truetype(self.font_path, 40) + else: + font = ImageFont.load_default() + except Exception as e: + logger.warning(f"Failed to load font: {e}, using default") + font = ImageFont.load_default() + + # Wrap text if too long + max_chars_per_line = 25 + lines = self._wrap_text(text, max_chars_per_line) + + # Calculate position (bottom area) + line_height = 60 + total_height = len(lines) * line_height + y_start = height - total_height - 150 # 150px from bottom + + # Draw each line centered + for i, line in enumerate(lines): + # Get text bounding box + bbox = draw.textbbox((0, 0), line, font=font) + text_width = bbox[2] - bbox[0] + + # Center horizontally + x = (width - text_width) // 2 + y = y_start + i * line_height + + # Draw shadow for better readability + draw.text((x + 2, y + 2), line, fill='lightgray', font=font) + # Draw main text + draw.text((x, y), line, fill='black', font=font) + + def _wrap_text(self, text: str, max_chars: int) -> list: + """Wrap text into multiple lines""" + if len(text) <= max_chars: + return [text] + + lines = [] + current_line = "" + + for char in text: + if len(current_line) >= max_chars: + lines.append(current_line) + current_line = char + else: + current_line += char + + if current_line: + lines.append(current_line) + + return lines + diff --git a/reelforge/services/frame_html.py b/reelforge/services/frame_html.py new file mode 100644 index 0000000..8523b33 --- /dev/null +++ b/reelforge/services/frame_html.py @@ -0,0 +1,131 @@ +""" +HTML-based Frame Generator Service + +Renders HTML templates to frame images with variable substitution +""" + +import uuid +from typing import Dict, Any, Optional +from pathlib import Path +from html2image import Html2Image +from loguru import logger + + +class HTMLFrameGenerator: + """ + HTML-based frame generator + + Renders HTML templates to frame images with variable substitution. + Users can create custom templates using any HTML/CSS. + + Usage: + >>> generator = HTMLFrameGenerator("templates/modern.html") + >>> frame_path = await generator.generate_frame( + ... topic="Why reading matters", + ... text="Reading builds new neural pathways...", + ... image="/path/to/image.png", + ... ext={"book_title": "Atomic Habits", "book_author": "James Clear"} + ... ) + """ + + def __init__(self, template_path: str): + """ + Initialize HTML frame generator + + Args: + template_path: Path to HTML template file + """ + self.template_path = template_path + self.template = self._load_template(template_path) + self.hti = None # Lazy init to avoid overhead + logger.debug(f"Loaded HTML template: {template_path}") + + def _load_template(self, template_path: str) -> str: + """Load HTML template from file""" + path = Path(template_path) + if not path.exists(): + raise FileNotFoundError(f"Template not found: {template_path}") + + with open(path, 'r', encoding='utf-8') as f: + content = f.read() + + logger.debug(f"Template loaded: {len(content)} chars") + return content + + def _ensure_hti(self, width: int, height: int): + """Lazily initialize Html2Image instance""" + if self.hti is None: + self.hti = Html2Image(size=(width, height)) + logger.debug(f"Initialized Html2Image with size ({width}, {height})") + + async def generate_frame( + self, + topic: str, + text: str, + image: str, + ext: Optional[Dict[str, Any]] = None, + width: int = 1080, + height: int = 1920 + ) -> str: + """ + Generate frame from HTML template + + Args: + topic: Video topic/theme + text: Narration text for this frame + image: Path to AI-generated image + ext: Additional data (book_title, book_author, etc.) + width: Frame width in pixels + height: Frame height in pixels + + Returns: + Path to generated frame image + """ + # Build variable context + context = { + # Required variables + "topic": topic, + "text": text, + "image": image, + } + + # Add all ext fields + if ext: + context.update(ext) + + # Replace variables in HTML + html = self.template + for key, value in context.items(): + placeholder = f"{{{{{key}}}}}" + html = html.replace(placeholder, str(value) if value is not None else "") + + # Generate unique output path + from reelforge.utils.os_util import get_output_path + output_filename = f"frame_{uuid.uuid4().hex[:16]}.png" + output_path = get_output_path(output_filename) + + # Ensure Html2Image is initialized + self._ensure_hti(width, height) + + # Render HTML to image + logger.debug(f"Rendering HTML template to {output_path}") + try: + self.hti.screenshot( + html_str=html, + save_as=output_filename, + size=(width, height) + ) + + # html2image saves to current directory by default, move to output + import os + import shutil + if os.path.exists(output_filename): + shutil.move(output_filename, output_path) + + logger.info(f"✅ Frame generated: {output_path}") + return output_path + + except Exception as e: + logger.error(f"Failed to render HTML template: {e}") + raise RuntimeError(f"HTML rendering failed: {e}") + diff --git a/reelforge/services/image.py b/reelforge/services/image.py new file mode 100644 index 0000000..ad9a2fc --- /dev/null +++ b/reelforge/services/image.py @@ -0,0 +1,75 @@ +""" +Image Generation Service +""" + +from typing import Optional + +from reelforge.services.base import BaseService + + +class ImageService(BaseService): + """ + Image generation service + + Provides unified access to various image generation providers (ComfyKit, etc.) + Returns path or URL to generated image. + + Usage: + # Direct call with workflow path + image_path = await reelforge.image( + workflow="workflows/book_cover.json", + title="Atomic Habits", + author="James Clear" + ) + # Returns: "http://comfyui.local/view?filename=..." + + # Or use workflow ID (if using RunningHub) + image_path = await reelforge.image( + workflow="12345", + prompt="a beautiful landscape" + ) + + # Check active image generator + print(f"Using: {reelforge.image.active}") + """ + + def __init__(self, router): + super().__init__(router, "image") + + async def __call__( + self, + workflow: str, + **params + ) -> str: + """ + Generate image using workflow + + Args: + workflow: Workflow path, ID, or URL + **params: Workflow parameters (e.g., prompt, title, author, etc.) + + Returns: + Image URL or path (str) + + Example: + # Generate book cover + image_url = await reelforge.image( + workflow="workflows/book_cover.json", + title="Atomic Habits", + author="James Clear", + genre="Self-Help" + ) + + # Generate from text prompt + image_url = await reelforge.image( + workflow="workflows/text2img.json", + prompt="a cute cat playing with yarn", + width=1024, + height=768 + ) + """ + call_params = {"workflow": workflow} + call_params.update(params) + + return await self._config_manager.call(self._capability_type, **call_params) + diff --git a/reelforge/services/image_prompt_generator.py b/reelforge/services/image_prompt_generator.py new file mode 100644 index 0000000..4e96582 --- /dev/null +++ b/reelforge/services/image_prompt_generator.py @@ -0,0 +1,149 @@ +""" +Image prompt generation service +""" + +import json +import re +from typing import List + +from loguru import logger + +from reelforge.models.storyboard import StoryboardConfig +from reelforge.prompts.image_prompt_template import build_image_prompt_prompt + + +class ImagePromptGeneratorService: + """Image prompt generation service""" + + def __init__(self, reelforge_core): + """ + Initialize + + Args: + reelforge_core: ReelForgeCore instance + """ + self.core = reelforge_core + + async def generate_image_prompts( + self, + narrations: List[str], + config: StoryboardConfig, + image_style_preset: str = None, + image_style_description: str = None + ) -> List[str]: + """ + Generate image prompts based on narrations + + Args: + narrations: List of narrations + config: Storyboard configuration + image_style_preset: Preset style name (e.g., "minimal", "futuristic") + image_style_description: Custom style description (overrides preset) + + Returns: + List of image prompts with style applied + + Raises: + ValueError: If generated prompt count doesn't match narrations + json.JSONDecodeError: If unable to parse JSON + """ + logger.info(f"Generating image prompts for {len(narrations)} narrations") + + # 1. Build prompt (no style info - generate base scene descriptions) + prompt = build_image_prompt_prompt( + narrations=narrations, + min_words=config.min_image_prompt_words, + max_words=config.max_image_prompt_words, + image_style_preset=None, # Don't include style in LLM prompt + image_style_description=None + ) + + # 2. Call LLM to generate base scene descriptions + response = await self.core.llm( + prompt=prompt, + temperature=0.9, # Higher temperature for more visual creativity + max_tokens=2000 + ) + + logger.debug(f"LLM response: {response[:200]}...") + + # 3. Parse JSON + try: + result = self._parse_json(response) + base_prompts = result["image_prompts"] + except json.JSONDecodeError as e: + logger.error(f"Failed to parse LLM response: {e}") + logger.error(f"Response: {response}") + raise + except KeyError: + logger.error("Response missing 'image_prompts' key") + raise ValueError("Invalid response format") + + # 4. Validate count matches narrations + if len(base_prompts) != len(narrations): + raise ValueError( + f"Expected {len(narrations)} image prompts, " + f"got {len(base_prompts)}" + ) + + # 5. Apply style to each prompt using FinalImagePromptService + from reelforge.services.final_image_prompt import StylePreset + + # Convert style preset name to enum if provided + style_preset_enum = None + if image_style_preset: + try: + style_preset_enum = StylePreset[image_style_preset.upper()] + except KeyError: + logger.warning(f"Unknown style preset: {image_style_preset}") + + # Apply style to each base prompt + final_prompts = [] + for base_prompt in base_prompts: + final_prompt = await self.core.generate_final_image_prompt( + prompt=base_prompt, + style_preset=style_preset_enum, + custom_style_description=image_style_description or "" + ) + final_prompts.append(final_prompt) + + logger.info(f"Generated {len(final_prompts)} final image prompts with style applied") + return final_prompts + + def _parse_json(self, text: str) -> dict: + """ + Parse JSON from text, with fallback to extract JSON from markdown code blocks + + Args: + text: Text containing JSON + + Returns: + Parsed JSON dict + """ + # Try direct parsing first + try: + return json.loads(text) + except json.JSONDecodeError: + pass + + # Try to extract JSON from markdown code block + json_pattern = r'```(?:json)?\s*(\{.*?\})\s*```' + match = re.search(json_pattern, text, re.DOTALL) + if match: + try: + return json.loads(match.group(1)) + except json.JSONDecodeError: + pass + + # Try to find any JSON object in the text + json_pattern = r'\{[^{}]*"image_prompts"\s*:\s*\[[^\]]*\][^{}]*\}' + match = re.search(json_pattern, text, re.DOTALL) + if match: + try: + return json.loads(match.group(0)) + except json.JSONDecodeError: + pass + + # If all fails, raise error + raise json.JSONDecodeError("No valid JSON found", text, 0) + diff --git a/reelforge/services/llm.py b/reelforge/services/llm.py new file mode 100644 index 0000000..3924d92 --- /dev/null +++ b/reelforge/services/llm.py @@ -0,0 +1,97 @@ +""" +LLM (Large Language Model) Service +""" + +from typing import Optional + +from reelforge.services.base import BaseService + + +class LLMService(BaseService): + """ + LLM (Large Language Model) service + + Provides unified access to various LLM providers (Qwen, OpenAI, DeepSeek, Ollama, etc.) + + Usage: + # Direct call (recommended) + answer = await reelforge.llm("Explain atomic habits") + + # With parameters + answer = await reelforge.llm( + prompt="Explain atomic habits in 3 sentences", + temperature=0.7, + max_tokens=2000 + ) + + # Explicit call syntax + answer = await reelforge.llm.call(prompt="Hello") + + # Check active LLM + print(f"Using: {reelforge.llm.active}") + + # List available LLMs + print(f"Available: {reelforge.llm.available}") + """ + + def __init__(self, router): + super().__init__(router, "llm") + + async def __call__( + self, + prompt: str, + api_key: Optional[str] = None, + base_url: Optional[str] = None, + model: Optional[str] = None, + temperature: Optional[float] = None, + max_tokens: Optional[int] = None, + **kwargs + ) -> str: + """ + Generate text using LLM + + Args: + prompt: The prompt to generate from + api_key: API key (optional, uses config if not provided) + base_url: Base URL (optional, uses config if not provided) + model: Model name (optional, uses config if not provided) + temperature: Sampling temperature (0.0-2.0). Lower is more deterministic. + max_tokens: Maximum tokens to generate + **kwargs: Additional provider-specific parameters + + Returns: + Generated text + + Examples: + # Use config from config.yaml + answer = await reelforge.llm("Explain atomic habits") + + # Override with custom parameters + answer = await reelforge.llm( + "Summarize the book 'Atomic Habits' in 3 sentences", + api_key="sk-custom-key", + base_url="https://api.custom.com/v1", + model="custom-model", + temperature=0.7, + max_tokens=500 + ) + """ + params = {"prompt": prompt} + + # Add optional LLM parameters (will override config if provided) + if api_key is not None: + params["api_key"] = api_key + if base_url is not None: + params["base_url"] = base_url + if model is not None: + params["model"] = model + + if temperature is not None: + params["temperature"] = temperature + if max_tokens is not None: + params["max_tokens"] = max_tokens + + params.update(kwargs) + + return await self._config_manager.call(self._capability_type, **params) + diff --git a/reelforge/services/narration_generator.py b/reelforge/services/narration_generator.py new file mode 100644 index 0000000..bd24244 --- /dev/null +++ b/reelforge/services/narration_generator.py @@ -0,0 +1,200 @@ +""" +Narration generation service + +Supports three content sources: +1. Book: Generate book review narrations from book information +2. Topic: Generate narrations from a topic/theme +3. Content: Extract/refine narrations from user-provided content +""" + +import json +import re +from typing import List, Optional, Literal + +from loguru import logger + +from reelforge.models.storyboard import StoryboardConfig, BookInfo +from reelforge.prompts.narration_template import ( + build_book_narration_prompt, + build_topic_narration_prompt, + build_content_narration_prompt, + build_narration_prompt # Keep for backward compatibility +) + + +class NarrationGeneratorService: + """Narration generation service""" + + def __init__(self, reelforge_core): + """ + Initialize + + Args: + reelforge_core: ReelForgeCore instance (for calling llm) + """ + self.core = reelforge_core + + async def generate_narrations( + self, + config: StoryboardConfig, + source_type: Literal["book", "topic", "content"], + book_info: Optional[BookInfo] = None, + topic: Optional[str] = None, + content: Optional[str] = None, + ) -> List[str]: + """ + Generate storyboard narrations from different sources + + Args: + config: Storyboard configuration + source_type: Type of content source ("book", "topic", or "content") + book_info: Book information (required if source_type="book") + topic: Topic/theme (required if source_type="topic") + content: User-provided content (required if source_type="content") + + Returns: + List of narration texts + + Raises: + ValueError: If parameters don't match source_type or narration count mismatch + json.JSONDecodeError: If unable to parse LLM response as JSON + + Examples: + # Generate from book + >>> narrations = await service.generate_narrations( + ... config=config, + ... source_type="book", + ... book_info=book_info + ... ) + + # Generate from topic + >>> narrations = await service.generate_narrations( + ... config=config, + ... source_type="topic", + ... topic="如何提高学习效率" + ... ) + + # Generate from user content + >>> narrations = await service.generate_narrations( + ... config=config, + ... source_type="content", + ... content="昨天我读了一本书..." + ... ) + """ + # 1. Build prompt based on source_type + if source_type == "book": + if book_info is None: + raise ValueError("book_info is required when source_type='book'") + logger.info(f"Generating book review narrations for: {book_info.title}") + prompt = build_book_narration_prompt( + book_info=book_info, + n_storyboard=config.n_storyboard, + min_words=config.min_narration_words, + max_words=config.max_narration_words + ) + + elif source_type == "topic": + if topic is None: + raise ValueError("topic is required when source_type='topic'") + logger.info(f"Generating topic narrations for: {topic}") + prompt = build_topic_narration_prompt( + topic=topic, + n_storyboard=config.n_storyboard, + min_words=config.min_narration_words, + max_words=config.max_narration_words + ) + + else: # content + if content is None: + raise ValueError("content is required when source_type='content'") + logger.info(f"Generating narrations from user content ({len(content)} chars)") + prompt = build_content_narration_prompt( + content=content, + n_storyboard=config.n_storyboard, + min_words=config.min_narration_words, + max_words=config.max_narration_words + ) + + # 2. Call LLM (using self.core.llm) + response = await self.core.llm( + prompt=prompt, + temperature=0.8, # Higher temperature for more creativity + max_tokens=2000 + ) + + logger.debug(f"LLM response: {response[:200]}...") + + # 3. Parse JSON + try: + result = self._parse_json(response) + narrations = result["narrations"] + except json.JSONDecodeError as e: + logger.error(f"Failed to parse LLM response as JSON: {e}") + logger.error(f"Response: {response}") + raise + except KeyError: + logger.error("Response JSON missing 'narrations' key") + logger.error(f"Response: {response}") + raise ValueError("Invalid response format") + + # 4. Validate count (take first N if got more) + if len(narrations) > config.n_storyboard: + logger.warning( + f"Got {len(narrations)} narrations, taking first {config.n_storyboard}" + ) + narrations = narrations[:config.n_storyboard] + elif len(narrations) < config.n_storyboard: + raise ValueError( + f"Expected at least {config.n_storyboard} narrations, " + f"got only {len(narrations)}" + ) + + # 5. Validate word count for each narration + for i, text in enumerate(narrations): + word_count = len(text) + if word_count < config.min_narration_words: + logger.warning( + f"Narration {i} too short: {word_count} chars " + f"(min: {config.min_narration_words})" + ) + + logger.info(f"Generated {len(narrations)} narrations successfully") + return narrations + + def _parse_json(self, text: str) -> dict: + """ + Parse JSON from text, with fallback to extract JSON from markdown code blocks + + Args: + text: Text containing JSON + + Returns: + Parsed JSON dict + """ + # Try direct parsing first + try: + return json.loads(text) + except json.JSONDecodeError: + pass + + # Try to extract JSON from markdown code block + json_pattern = r'```(?:json)?\s*(\{.*?\})\s*```' + match = re.search(json_pattern, text, re.DOTALL) + if match: + try: + return json.loads(match.group(1)) + except json.JSONDecodeError: + pass + + # Try to find any JSON object in the text + json_pattern = r'\{[^{}]*"narrations"\s*:\s*\[[^\]]*\][^{}]*\}' + match = re.search(json_pattern, text, re.DOTALL) + if match: + try: + return json.loads(match.group(0)) + except json.JSONDecodeError: + pass + + # If all fails, raise error + raise json.JSONDecodeError("No valid JSON found", text, 0) + diff --git a/reelforge/services/storyboard_processor.py b/reelforge/services/storyboard_processor.py new file mode 100644 index 0000000..e83bf7f --- /dev/null +++ b/reelforge/services/storyboard_processor.py @@ -0,0 +1,299 @@ +""" +Storyboard processor - Process single frame through complete pipeline + +Orchestrates: TTS → Image Generation → Frame Composition → Video Segment +""" + +from typing import Callable, Optional + +import httpx +from loguru import logger + +from reelforge.models.progress import ProgressEvent +from reelforge.models.storyboard import StoryboardFrame, StoryboardConfig +from reelforge.utils.os_util import get_temp_path + + +class StoryboardProcessorService: + """Storyboard processor service""" + + def __init__(self, reelforge_core): + """ + Initialize + + Args: + reelforge_core: ReelForgeCore instance + """ + self.core = reelforge_core + + async def process_frame( + self, + frame: StoryboardFrame, + config: StoryboardConfig, + total_frames: int = 1, + progress_callback: Optional[Callable[[ProgressEvent], None]] = None + ) -> StoryboardFrame: + """ + Process single frame through complete pipeline + + Steps: + 1. Generate audio (TTS) + 2. Generate image (ComfyKit) + 3. Compose frame (add subtitle) + 4. Create video segment (image + audio) + + Args: + frame: Storyboard frame to process + config: Storyboard configuration + total_frames: Total number of frames in storyboard + progress_callback: Optional callback for progress updates (receives ProgressEvent) + + Returns: + Processed frame with all paths filled + """ + logger.info(f"Processing frame {frame.index}...") + + frame_num = frame.index + 1 + + try: + # Step 1: Generate audio (TTS) + await self._step_generate_audio(frame, config) + if progress_callback: + progress_callback(ProgressEvent( + event_type="frame_step", + progress=0.25, + frame_current=frame_num, + frame_total=total_frames, + step=1, + action="audio" + )) + + # Step 2: Generate image (ComfyKit) + await self._step_generate_image(frame, config) + if progress_callback: + progress_callback(ProgressEvent( + event_type="frame_step", + progress=0.50, + frame_current=frame_num, + frame_total=total_frames, + step=2, + action="image" + )) + + # Step 3: Compose frame (add subtitle) + await self._step_compose_frame(frame, config) + if progress_callback: + progress_callback(ProgressEvent( + event_type="frame_step", + progress=0.75, + frame_current=frame_num, + frame_total=total_frames, + step=3, + action="compose" + )) + + # Step 4: Create video segment + await self._step_create_video_segment(frame, config) + if progress_callback: + progress_callback(ProgressEvent( + event_type="frame_step", + progress=1.0, + frame_current=frame_num, + frame_total=total_frames, + step=4, + action="video" + )) + + logger.info(f"✅ Frame {frame.index} completed") + return frame + + except Exception as e: + logger.error(f"❌ Failed to process frame {frame.index}: {e}") + raise + + async def _step_generate_audio( + self, + frame: StoryboardFrame, + config: StoryboardConfig + ): + """Step 1: Generate audio using TTS""" + logger.debug(f" 1/4: Generating audio for frame {frame.index}...") + + # Call TTS + audio_path = await self.core.tts( + text=frame.narration, + voice=config.voice_id + ) + + frame.audio_path = audio_path + + # Get audio duration + frame.duration = await self._get_audio_duration(audio_path) + + logger.debug(f" ✓ Audio generated: {audio_path} ({frame.duration:.2f}s)") + + async def _step_generate_image( + self, + frame: StoryboardFrame, + config: StoryboardConfig + ): + """Step 2: Generate image using ComfyKit""" + logger.debug(f" 2/4: Generating image for frame {frame.index}...") + + # Call Image generation + image_url = await self.core.image( + workflow="workflows/t2i_by_local_flux.json", # Use existing workflow + prompt=frame.image_prompt, + width=config.image_width, + height=config.image_height + ) + + # Download image to local + local_path = await self._download_image(image_url, frame.index) + frame.image_path = local_path + + logger.debug(f" ✓ Image generated: {local_path}") + + async def _step_compose_frame( + self, + frame: StoryboardFrame, + config: StoryboardConfig + ): + """Step 3: Compose frame with subtitle""" + logger.debug(f" 3/4: Composing frame {frame.index}...") + + output_path = get_temp_path(f"frame_{frame.index}_composed.png") + + # Choose frame generator based on template config + if config.frame_template: + # Use HTML template + composed_path = await self._compose_frame_html(frame, config, output_path) + else: + # Use PIL (default) + composed_path = await self._compose_frame_pil(frame, config, output_path) + + frame.composed_image_path = composed_path + + logger.debug(f" ✓ Frame composed: {composed_path}") + + async def _compose_frame_pil( + self, + frame: StoryboardFrame, + config: StoryboardConfig, + output_path: str + ) -> str: + """Compose frame using PIL (default)""" + composed_path = await self.core.frame_composer.compose_frame( + image_path=frame.image_path, + subtitle=frame.narration, + output_path=output_path, + config=config + ) + return composed_path + + async def _compose_frame_html( + self, + frame: StoryboardFrame, + config: StoryboardConfig, + output_path: str + ) -> str: + """Compose frame using HTML template""" + from reelforge.services.frame_html import HTMLFrameGenerator + from pathlib import Path + + # Resolve template path + template_name = config.frame_template + if not template_name.endswith('.html'): + template_name = f"{template_name}.html" + + # Try templates/ directory first + template_path = Path(f"templates/{template_name}") + if not template_path.exists(): + # Try as absolute path + template_path = Path(template_name) + if not template_path.exists(): + raise FileNotFoundError( + f"Template not found: {template_name}. " + f"Available templates: classic, modern, minimal" + ) + + # Get storyboard for book info + storyboard = getattr(self.core, '_current_storyboard', None) + book_info = storyboard.book_info if storyboard else None + + # Build ext data + ext = {} + if book_info: + ext["book_title"] = book_info.title or "" + ext["book_author"] = book_info.author or "" + ext["book_subtitle"] = book_info.subtitle or "" + ext["book_genre"] = book_info.genre or "" + + # Generate frame using HTML + generator = HTMLFrameGenerator(str(template_path)) + composed_path = await generator.generate_frame( + topic=storyboard.topic if storyboard else "", + text=frame.narration, + image=frame.image_path, + ext=ext, + width=config.video_width, + height=config.video_height + ) + + return composed_path + + async def _step_create_video_segment( + self, + frame: StoryboardFrame, + config: StoryboardConfig + ): + """Step 4: Create video segment from image + audio""" + logger.debug(f" 4/4: Creating video segment for frame {frame.index}...") + + output_path = get_temp_path(f"frame_{frame.index}_segment.mp4") + + # Call video compositor to create video from image + audio + from reelforge.services.video import VideoService + video_service = VideoService() + + segment_path = video_service.create_video_from_image( + image=frame.composed_image_path, + audio=frame.audio_path, + output=output_path, + fps=config.video_fps + ) + + frame.video_segment_path = segment_path + + logger.debug(f" ✓ Video segment created: {segment_path}") + + async def _get_audio_duration(self, audio_path: str) -> float: + """Get audio duration in seconds""" + try: + # Try using ffmpeg-python + import ffmpeg + probe = ffmpeg.probe(audio_path) + duration = float(probe['format']['duration']) + return duration + except Exception as e: + logger.warning(f"Failed to get audio duration: {e}, using estimate") + # Fallback: estimate based on file size (very rough) + import os + file_size = os.path.getsize(audio_path) + # Assume ~16kbps for MP3, so 2KB per second + estimated_duration = file_size / 2000 + return max(1.0, estimated_duration) # At least 1 second + + async def _download_image(self, url: str, frame_index: int) -> str: + """Download image from URL to local file""" + output_path = get_temp_path(f"frame_{frame_index}_image.png") + + async with httpx.AsyncClient() as client: + response = await client.get(url) + response.raise_for_status() + + with open(output_path, 'wb') as f: + f.write(response.content) + + return output_path + diff --git a/reelforge/services/tts.py b/reelforge/services/tts.py new file mode 100644 index 0000000..eeb59a0 --- /dev/null +++ b/reelforge/services/tts.py @@ -0,0 +1,103 @@ +""" +TTS (Text-to-Speech) Service +""" + +import base64 +import uuid +from typing import Optional + +from reelforge.services.base import BaseService +from reelforge.utils.os_util import get_temp_path, save_bytes_to_file + + +class TTSService(BaseService): + """ + TTS (Text-to-Speech) service + + Provides unified access to various TTS providers (Edge TTS, Azure TTS, etc.) + Returns path to saved audio file. + + Usage: + # Direct call (auto-generate temp path) + audio_path = await reelforge.tts("Hello world") + # Returns: "temp/abc123def456.mp3" + + # With voice parameter + audio_path = await reelforge.tts( + text="你好，世界", + voice="zh-CN-YunjianNeural" + ) + + # Specify custom output path + audio_path = await reelforge.tts( + text="Hello", + output_path="output/greeting.mp3" + ) + + # Check active TTS + print(f"Using: {reelforge.tts.active}") + """ + + def __init__(self, router): + super().__init__(router, "tts") + + async def __call__( + self, + text: str, + voice: Optional[str] = None, + rate: Optional[str] = None, + output_path: Optional[str] = None, + **kwargs + ) -> str: + """ + Convert text to speech and save to file + + Args: + text: Text to convert to speech + voice: Voice ID (uses default if not specified) + rate: Speech rate (e.g., "+0%", "+50%", "-20%") + output_path: Output file path (default: temp/.mp3) + **kwargs: Additional provider-specific parameters + + Returns: + Path to saved audio file (str) + + Example: + # Auto-generate path + audio_path = await reelforge.tts("Hello world") + # Returns: "temp/abc123def456.mp3" + + # Specify custom path + audio_path = await reelforge.tts( + "你好，世界", + voice="zh-CN-YunjianNeural", + output_path="output/greeting.mp3" + ) + """ + params = {"text": text} + if voice is not None: + params["voice"] = voice + if rate is not None: + params["rate"] = rate + params.update(kwargs) + + # Call capability and get base64-encoded audio + audio_base64 = await self._config_manager.call(self._capability_type, **params) + + # Decode base64 to bytes + if isinstance(audio_base64, str): + audio_data = base64.b64decode(audio_base64) + else: + audio_data = audio_base64 + + # Generate output path if not specified + if output_path is None: + # Generate UUID without hyphens for filename + file_uuid = uuid.uuid4().hex + output_path = get_temp_path(f"{file_uuid}.mp3") + + # Save to file + saved_path = save_bytes_to_file(audio_data, output_path) + + return saved_path + diff --git a/reelforge/services/video.py b/reelforge/services/video.py new file mode 100644 index 0000000..08e77a6 --- /dev/null +++ b/reelforge/services/video.py @@ -0,0 +1,563 @@ +""" +Video Processing Service + +High-performance video composition service built on ffmpeg-python. + +Features: +- Video concatenation +- Audio/video merging +- Background music addition +- Image to video conversion + +Note: Requires FFmpeg to be installed on the system. +""" + +import os +import shutil +import tempfile +from pathlib import Path +from typing import List, Literal, Optional + +import ffmpeg +from loguru import logger + + +def check_ffmpeg() -> None: + """ + Check if FFmpeg is installed on the system + + Raises: + RuntimeError: If FFmpeg is not found + """ + if not shutil.which("ffmpeg"): + raise RuntimeError( + "FFmpeg not found. Please install it:\n" + " macOS: brew install ffmpeg\n" + " Ubuntu/Debian: apt-get install ffmpeg\n" + " Windows: https://ffmpeg.org/download.html" + ) + + +# Check FFmpeg availability on module import +check_ffmpeg() + + +class VideoService: + """ + Video compositor for common video processing tasks + + Uses ffmpeg-python for high-performance video processing. + All operations preserve video quality when possible (stream copy). + + Examples: + >>> compositor = VideoCompositor() + >>> + >>> # Concatenate videos + >>> compositor.concat_videos( + ... ["intro.mp4", "main.mp4", "outro.mp4"], + ... "final.mp4" + ... ) + >>> + >>> # Add voiceover + >>> compositor.merge_audio_video( + ... "visual.mp4", + ... "voiceover.mp3", + ... "final.mp4" + ... ) + >>> + >>> # Add background music + >>> compositor.add_bgm( + ... "video.mp4", + ... "music.mp3", + ... "final.mp4", + ... bgm_volume=0.3 + ... ) + >>> + >>> # Create video from image + audio + >>> compositor.create_video_from_image( + ... "frame.png", + ... "narration.mp3", + ... "segment.mp4" + ... ) + """ + + def concat_videos( + self, + videos: List[str], + output: str, + method: Literal["demuxer", "filter"] = "demuxer", + bgm_path: Optional[str] = None, + bgm_volume: float = 0.2, + bgm_mode: Literal["once", "loop"] = "loop" + ) -> str: + """ + Concatenate multiple videos into one + + Args: + videos: List of video file paths to concatenate + output: Output video file path + method: Concatenation method + - "demuxer": Fast, no re-encoding (requires identical formats) + - "filter": Slower but handles different formats + bgm_path: Background music file path (optional) + - None: No BGM + - "default" or "happy": Use built-in BGM from bgm/ folder + - Custom path: Use custom BGM file + bgm_volume: BGM volume level (0.0-1.0), default 0.2 + bgm_mode: BGM playback mode + - "once": Play BGM once + - "loop": Loop BGM to match video duration + + Returns: + Path to the output video file + + Raises: + ValueError: If videos list is empty + RuntimeError: If FFmpeg execution fails + + Note: + - demuxer method requires all videos to have identical: + resolution, codec, fps, etc. + - filter method re-encodes videos, slower but more compatible + """ + if not videos: + raise ValueError("Videos list cannot be empty") + + if len(videos) == 1: + logger.info(f"Only one video provided, copying to {output}") + shutil.copy(videos[0], output) + return output + + logger.info(f"Concatenating {len(videos)} videos using {method} method") + + # Step 1: Concatenate videos + if bgm_path: + # If BGM needed, concatenate to temp file first + temp_output = output.replace('.mp4', '_no_bgm.mp4') + concat_result = self._concat_demuxer(videos, temp_output) if method == "demuxer" else self._concat_filter(videos, temp_output) + + # Step 2: Add BGM + logger.info(f"Adding BGM: {bgm_path} (volume={bgm_volume}, mode={bgm_mode})") + final_result = self._add_bgm_to_video( + video=concat_result, + bgm_path=bgm_path, + output=output, + volume=bgm_volume, + mode=bgm_mode + ) + + # Clean up temp file + if os.path.exists(temp_output): + os.unlink(temp_output) + + return final_result + else: + # No BGM, direct concatenation + if method == "demuxer": + return self._concat_demuxer(videos, output) + else: + return self._concat_filter(videos, output) + + def _concat_demuxer(self, videos: List[str], output: str) -> str: + """ + Concatenate using concat demuxer (fast, no re-encoding) + + FFmpeg equivalent: + ffmpeg -f concat -safe 0 -i filelist.txt -c copy output.mp4 + """ + # Create temporary file list + with tempfile.NamedTemporaryFile( + mode='w', + delete=False, + suffix='.txt', + encoding='utf-8' + ) as f: + for video in videos: + abs_path = Path(video).absolute() + escaped_path = str(abs_path).replace("'", "'\\''") + f.write(f"file '{escaped_path}'\n") + filelist = f.name + + try: + logger.debug(f"Created filelist: {filelist}") + ( + ffmpeg + .input(filelist, format='concat', safe=0) + .output(output, c='copy') + .overwrite_output() + .run(capture_stdout=True, capture_stderr=True) + ) + logger.success(f"Videos concatenated successfully: {output}") + return output + except ffmpeg.Error as e: + error_msg = e.stderr.decode() if e.stderr else str(e) + logger.error(f"FFmpeg concat error: {error_msg}") + raise RuntimeError(f"Failed to concatenate videos: {error_msg}") + finally: + if os.path.exists(filelist): + os.unlink(filelist) + + def _concat_filter(self, videos: List[str], output: str) -> str: + """ + Concatenate using concat filter (slower but handles different formats) + + FFmpeg equivalent: + ffmpeg -i v1.mp4 -i v2.mp4 -filter_complex "[0:v][0:a][1:v][1:a]concat=n=2:v=1:a=1[v][a]" + -map "[v]" -map "[a]" output.mp4 + """ + try: + inputs = [ffmpeg.input(v) for v in videos] + ( + ffmpeg + .concat(*inputs, v=1, a=1) + .output(output) + .overwrite_output() + .run(capture_stdout=True, capture_stderr=True) + ) + logger.success(f"Videos concatenated successfully: {output}") + return output + except ffmpeg.Error as e: + error_msg = e.stderr.decode() if e.stderr else str(e) + logger.error(f"FFmpeg concat filter error: {error_msg}") + raise RuntimeError(f"Failed to concatenate videos: {error_msg}") + + def merge_audio_video( + self, + video: str, + audio: str, + output: str, + replace_audio: bool = True, + audio_volume: float = 1.0, + video_volume: float = 0.0, + ) -> str: + """ + Merge audio with video + + Args: + video: Video file path + audio: Audio file path + output: Output video file path + replace_audio: If True, replace video's audio; if False, mix with original + audio_volume: Volume of the new audio (0.0 to 1.0+) + video_volume: Volume of original video audio (0.0 to 1.0+) + Only used when replace_audio=False + + Returns: + Path to the output video file + + Raises: + RuntimeError: If FFmpeg execution fails + + Note: + - When replace_audio=True, video's original audio is removed + - When replace_audio=False, original and new audio are mixed + - Audio is trimmed/extended to match video duration + """ + logger.info(f"Merging audio with video (replace={replace_audio})") + + try: + input_video = ffmpeg.input(video) + input_audio = ffmpeg.input(audio) + + if replace_audio: + # Replace audio: use only new audio, ignore original + ( + ffmpeg + .output( + input_video.video, + input_audio.audio.filter('volume', audio_volume), + output, + vcodec='copy', + acodec='aac', + audio_bitrate='192k', + shortest=None + ) + .overwrite_output() + .run(capture_stdout=True, capture_stderr=True) + ) + else: + # Mix audio: combine original and new audio + mixed_audio = ffmpeg.filter( + [ + input_video.audio.filter('volume', video_volume), + input_audio.audio.filter('volume', audio_volume) + ], + 'amix', + inputs=2, + duration='first' + ) + + ( + ffmpeg + .output( + input_video.video, + mixed_audio, + output, + vcodec='copy', + acodec='aac', + audio_bitrate='192k' + ) + .overwrite_output() + .run(capture_stdout=True, capture_stderr=True) + ) + + logger.success(f"Audio merged successfully: {output}") + return output + except ffmpeg.Error as e: + error_msg = e.stderr.decode() if e.stderr else str(e) + logger.error(f"FFmpeg merge error: {error_msg}") + raise RuntimeError(f"Failed to merge audio and video: {error_msg}") + + def create_video_from_image( + self, + image: str, + audio: str, + output: str, + fps: int = 30, + ) -> str: + """ + Create video from static image and audio + + Args: + image: Image file path + audio: Audio file path + output: Output video path + fps: Frames per second + + Returns: + Path to the output video + + Raises: + RuntimeError: If FFmpeg execution fails + + Note: + - Image is displayed as static frame for the duration of audio + - Video duration matches audio duration + - Useful for creating video segments from storyboard frames + + Example: + >>> compositor.create_video_from_image( + ... "frame.png", + ... "narration.mp3", + ... "segment.mp4" + ... ) + """ + logger.info("Creating video from image and audio") + + try: + # Input image with loop (loop=1 means loop indefinitely) + # Use framerate to set input framerate + input_image = ffmpeg.input(image, loop=1, framerate=fps) + input_audio = ffmpeg.input(audio) + + # Combine image and audio + # Use -shortest to match audio duration + ( + ffmpeg + .output( + input_image, + input_audio, + output, + vcodec='libx264', + acodec='aac', + pix_fmt='yuv420p', + audio_bitrate='192k', + preset='medium', + crf=23, + shortest=None, # Duration = shortest input (audio) + **{'b:v': '2M'} # Video bitrate + ) + .overwrite_output() + .run(capture_stdout=True, capture_stderr=True) + ) + + logger.success(f"Video created from image: {output}") + return output + except ffmpeg.Error as e: + error_msg = e.stderr.decode() if e.stderr else str(e) + logger.error(f"FFmpeg error creating video from image: {error_msg}") + raise RuntimeError(f"Failed to create video from image: {error_msg}") + + def add_bgm( + self, + video: str, + bgm: str, + output: str, + bgm_volume: float = 0.3, + loop: bool = True, + fade_in: float = 0.0, + fade_out: float = 0.0, + ) -> str: + """ + Add background music to video + + Args: + video: Video file path + bgm: Background music file path + output: Output video file path + bgm_volume: BGM volume relative to original (0.0 to 1.0+) + loop: If True, loop BGM to match video duration + fade_in: BGM fade-in duration in seconds + fade_out: BGM fade-out duration in seconds (not yet implemented) + + Returns: + Path to the output video file + + Raises: + RuntimeError: If FFmpeg execution fails + + Note: + - BGM is mixed with original video audio + - If loop=True, BGM repeats until video ends + - Fade effects are applied to BGM only + """ + logger.info(f"Adding BGM to video (volume={bgm_volume}, loop={loop})") + + try: + input_video = ffmpeg.input(video) + + # Configure BGM input with looping if needed + bgm_input = ffmpeg.input( + bgm, + stream_loop=-1 if loop else 0 # -1 = infinite loop + ) + + # Apply volume adjustment to BGM + bgm_audio = bgm_input.audio.filter('volume', bgm_volume) + + # Apply fade effects if specified + if fade_in > 0: + bgm_audio = bgm_audio.filter('afade', type='in', duration=fade_in) + # Note: fade_out at the end requires knowing the duration, which is complex + # For now, we skip fade_out in this implementation + # A more advanced implementation would need to: + # 1. Get video duration + # 2. Calculate fade_out start time + # 3. Apply fade filter with specific start_time + + # Mix original audio with BGM + mixed_audio = ffmpeg.filter( + [input_video.audio, bgm_audio], + 'amix', + inputs=2, + duration='first' # Use video's duration + ) + + ( + ffmpeg + .output( + input_video.video, + mixed_audio, + output, + vcodec='copy', + acodec='aac', + audio_bitrate='192k' + ) + .overwrite_output() + .run(capture_stdout=True, capture_stderr=True) + ) + + logger.success(f"BGM added successfully: {output}") + return output + except ffmpeg.Error as e: + error_msg = e.stderr.decode() if e.stderr else str(e) + logger.error(f"FFmpeg BGM error: {error_msg}") + raise RuntimeError(f"Failed to add BGM: {error_msg}") + + def _add_bgm_to_video( + self, + video: str, + bgm_path: str, + output: str, + volume: float = 0.2, + mode: Literal["once", "loop"] = "loop" + ) -> str: + """ + Internal helper to add BGM to video with path resolution + + Args: + video: Video file path + bgm_path: BGM path (can be preset name or custom path) + output: Output file path + volume: BGM volume (0.0-1.0) + mode: "once" or "loop" + + Returns: + Path to output video + + Raises: + FileNotFoundError: If BGM file not found + """ + # Resolve BGM path (raises FileNotFoundError if not found) + resolved_bgm = self._resolve_bgm_path(bgm_path) + + # Add BGM using existing method + loop = (mode == "loop") + return self.add_bgm( + video=video, + bgm=resolved_bgm, + output=output, + bgm_volume=volume, + loop=loop, + fade_in=0.0 + ) + + def _resolve_bgm_path(self, bgm_path: str) -> str: + """ + Resolve BGM path (preset name or custom path) + + Args: + bgm_path: Can be: + - Preset name (e.g., "default", "happy"): auto-resolved from bgm/ directory + - Custom file path (absolute or relative) + + Returns: + Resolved absolute path + + Raises: + FileNotFoundError: If BGM file not found + """ + # Try direct path first (absolute or relative) + if os.path.exists(bgm_path): + return os.path.abspath(bgm_path) + + # Try as preset in bgm/ directory + preset_path = f"bgm/{bgm_path}.mp3" + if os.path.exists(preset_path): + return os.path.abspath(preset_path) + + # Not found - provide helpful error message + tried_paths = [ + os.path.abspath(bgm_path), + os.path.abspath(preset_path) + ] + + # List available presets + available_bgm = self._list_available_bgm() + available_msg = f"\n Available presets: {', '.join(available_bgm)}" if available_bgm else "" + + raise FileNotFoundError( + f"BGM file not found: '{bgm_path}'\n" + f" Tried paths:\n" + f" 1. {tried_paths[0]}\n" + f" 2. {tried_paths[1]}" + f"{available_msg}" + ) + + def _list_available_bgm(self) -> list[str]: + """ + List available preset BGM files + + Returns: + List of preset names (without .mp3 extension) + """ + bgm_dir = "bgm" + if not os.path.exists(bgm_dir): + return [] + + try: + files = os.listdir(bgm_dir) + return [f[:-4] for f in files if f.endswith('.mp3')] + except Exception: + return [] + diff --git a/reelforge/services/video/compositor.py b/reelforge/services/video/compositor.py new file mode 100644 index 0000000..ac3e1c8 --- /dev/null +++ b/reelforge/services/video/compositor.py @@ -0,0 +1,405 @@ +""" +Video compositor service + +Provides core video composition capabilities: +- Video concatenation +- Audio/video merging +- Background music addition + +This module is designed to be independent of ReelForge business logic +and can be extracted as a standalone SDK in the future. +""" + +import os +import tempfile +from pathlib import Path +from typing import List, Literal + +import ffmpeg +from loguru import logger + + +class VideoCompositor: + """ + Video compositor for common video processing tasks + + Uses ffmpeg-python for high-performance video processing. + All operations preserve video quality when possible (stream copy). + + Examples: + >>> compositor = VideoCompositor() + >>> + >>> # Concatenate videos + >>> compositor.concat_videos( + ... ["intro.mp4", "main.mp4", "outro.mp4"], + ... "final.mp4" + ... ) + >>> + >>> # Add voiceover + >>> compositor.merge_audio_video( + ... "visual.mp4", + ... "voiceover.mp3", + ... "final.mp4" + ... ) + >>> + >>> # Add background music + >>> compositor.add_bgm( + ... "video.mp4", + ... "music.mp3", + ... "final.mp4", + ... bgm_volume=0.3 + ... ) + """ + + def concat_videos( + self, + videos: List[str], + output: str, + method: Literal["demuxer", "filter"] = "demuxer", + ) -> str: + """ + Concatenate multiple videos into one + + Args: + videos: List of video file paths to concatenate + output: Output video file path + method: Concatenation method + - "demuxer": Fast, no re-encoding (requires identical formats) + - "filter": Slower but handles different formats + + Returns: + Path to the output video file + + Raises: + ValueError: If videos list is empty + RuntimeError: If FFmpeg execution fails + + Note: + - demuxer method requires all videos to have identical: + resolution, codec, fps, etc. + - filter method re-encodes videos, slower but more compatible + """ + if not videos: + raise ValueError("Videos list cannot be empty") + + if len(videos) == 1: + logger.info(f"Only one video provided, copying to {output}") + # Just copy the file + import shutil + shutil.copy(videos[0], output) + return output + + logger.info(f"Concatenating {len(videos)} videos using {method} method") + + if method == "demuxer": + return self._concat_demuxer(videos, output) + else: + return self._concat_filter(videos, output) + + def _concat_demuxer(self, videos: List[str], output: str) -> str: + """ + Concatenate using concat demuxer (fast, no re-encoding) + + FFmpeg equivalent: + ffmpeg -f concat -safe 0 -i filelist.txt -c copy output.mp4 + """ + # Create temporary file list + with tempfile.NamedTemporaryFile( + mode='w', + delete=False, + suffix='.txt', + encoding='utf-8' + ) as f: + for video in videos: + # Use absolute path for safety + abs_path = Path(video).absolute() + # Escape single quotes in path + escaped_path = str(abs_path).replace("'", "'\\''") + f.write(f"file '{escaped_path}'\n") + filelist = f.name + + try: + logger.debug(f"Created filelist: {filelist}") + ( + ffmpeg + .input(filelist, format='concat', safe=0) + .output(output, c='copy') + .overwrite_output() + .run(capture_stdout=True, capture_stderr=True) + ) + logger.success(f"Videos concatenated successfully: {output}") + return output + except ffmpeg.Error as e: + error_msg = e.stderr.decode() if e.stderr else str(e) + logger.error(f"FFmpeg concat error: {error_msg}") + raise RuntimeError(f"Failed to concatenate videos: {error_msg}") + finally: + # Clean up temporary file + if os.path.exists(filelist): + os.unlink(filelist) + + def _concat_filter(self, videos: List[str], output: str) -> str: + """ + Concatenate using concat filter (slower but handles different formats) + + FFmpeg equivalent: + ffmpeg -i v1.mp4 -i v2.mp4 -filter_complex "[0:v][0:a][1:v][1:a]concat=n=2:v=1:a=1[v][a]" + -map "[v]" -map "[a]" output.mp4 + """ + try: + inputs = [ffmpeg.input(v) for v in videos] + ( + ffmpeg + .concat(*inputs, v=1, a=1) + .output(output) + .overwrite_output() + .run(capture_stdout=True, capture_stderr=True) + ) + logger.success(f"Videos concatenated successfully: {output}") + return output + except ffmpeg.Error as e: + error_msg = e.stderr.decode() if e.stderr else str(e) + logger.error(f"FFmpeg concat filter error: {error_msg}") + raise RuntimeError(f"Failed to concatenate videos: {error_msg}") + + def merge_audio_video( + self, + video: str, + audio: str, + output: str, + replace_audio: bool = True, + audio_volume: float = 1.0, + video_volume: float = 0.0, + ) -> str: + """ + Merge audio with video + + Args: + video: Video file path + audio: Audio file path + output: Output video file path + replace_audio: If True, replace video's audio; if False, mix with original + audio_volume: Volume of the new audio (0.0 to 1.0+) + video_volume: Volume of original video audio (0.0 to 1.0+) + Only used when replace_audio=False + + Returns: + Path to the output video file + + Raises: + RuntimeError: If FFmpeg execution fails + + Note: + - When replace_audio=True, video's original audio is removed + - When replace_audio=False, original and new audio are mixed + - Audio is trimmed/extended to match video duration + """ + logger.info(f"Merging audio with video (replace={replace_audio})") + + try: + input_video = ffmpeg.input(video) + input_audio = ffmpeg.input(audio) + + if replace_audio: + # Replace audio: use only new audio, ignore original + ( + ffmpeg + .output( + input_video.video, + input_audio.audio.filter('volume', audio_volume), + output, + vcodec='copy', + acodec='aac', + audio_bitrate='192k', + shortest=None + ) + .overwrite_output() + .run(capture_stdout=True, capture_stderr=True) + ) + else: + # Mix audio: combine original and new audio + mixed_audio = ffmpeg.filter( + [ + input_video.audio.filter('volume', video_volume), + input_audio.audio.filter('volume', audio_volume) + ], + 'amix', + inputs=2, + duration='first' + ) + + ( + ffmpeg + .output( + input_video.video, + mixed_audio, + output, + vcodec='copy', + acodec='aac', + audio_bitrate='192k' + ) + .overwrite_output() + .run(capture_stdout=True, capture_stderr=True) + ) + + logger.success(f"Audio merged successfully: {output}") + return output + except ffmpeg.Error as e: + error_msg = e.stderr.decode() if e.stderr else str(e) + logger.error(f"FFmpeg merge error: {error_msg}") + raise RuntimeError(f"Failed to merge audio and video: {error_msg}") + + def create_video_from_image( + self, + image: str, + audio: str, + output: str, + fps: int = 30, + ) -> str: + """ + Create video from static image and audio + + Args: + image: Image file path + audio: Audio file path + output: Output video path + fps: Frames per second + + Returns: + Path to the output video + + Raises: + RuntimeError: If FFmpeg execution fails + + Note: + - Image is displayed as static frame for the duration of audio + - Video duration matches audio duration + - Useful for creating video segments from storyboard frames + + Example: + >>> compositor.create_video_from_image( + ... "frame.png", + ... "narration.mp3", + ... "segment.mp4" + ... ) + """ + logger.info("Creating video from image and audio") + + try: + # Input image with loop + input_image = ffmpeg.input(image, loop=1, framerate=fps) + input_audio = ffmpeg.input(audio) + + # Combine image and audio + ( + ffmpeg + .output( + input_image.video, + input_audio.audio, + output, + vcodec='libx264', + acodec='aac', + pix_fmt='yuv420p', + audio_bitrate='192k', + shortest=None, # Duration = audio duration + **{'b:v': '2M'} # Video bitrate + ) + .overwrite_output() + .run(capture_stdout=True, capture_stderr=True) + ) + + logger.success(f"Video created from image: {output}") + return output + except ffmpeg.Error as e: + error_msg = e.stderr.decode() if e.stderr else str(e) + logger.error(f"FFmpeg error creating video from image: {error_msg}") + raise RuntimeError(f"Failed to create video from image: {error_msg}") + + def add_bgm( + self, + video: str, + bgm: str, + output: str, + bgm_volume: float = 0.3, + loop: bool = True, + fade_in: float = 0.0, + fade_out: float = 0.0, + ) -> str: + """ + Add background music to video + + Args: + video: Video file path + bgm: Background music file path + output: Output video file path + bgm_volume: BGM volume relative to original (0.0 to 1.0+) + loop: If True, loop BGM to match video duration + fade_in: BGM fade-in duration in seconds + fade_out: BGM fade-out duration in seconds + + Returns: + Path to the output video file + + Raises: + RuntimeError: If FFmpeg execution fails + + Note: + - BGM is mixed with original video audio + - If loop=True, BGM repeats until video ends + - Fade effects are applied to BGM only + """ + logger.info(f"Adding BGM to video (volume={bgm_volume}, loop={loop})") + + try: + input_video = ffmpeg.input(video) + + # Configure BGM input with looping if needed + bgm_input = ffmpeg.input( + bgm, + stream_loop=-1 if loop else 0 # -1 = infinite loop + ) + + # Apply volume adjustment to BGM + bgm_audio = bgm_input.audio.filter('volume', bgm_volume) + + # Apply fade effects if specified + if fade_in > 0: + bgm_audio = bgm_audio.filter('afade', type='in', duration=fade_in) + # Note: fade_out at the end requires knowing the duration, which is complex + # For now, we skip fade_out in this implementation + # A more advanced implementation would need to: + # 1. Get video duration + # 2. Calculate fade_out start time + # 3. Apply fade filter with specific start_time + # if fade_out > 0: + # bgm_audio = bgm_audio.filter('afade', type='out', start_time=duration-fade_out, duration=fade_out) + + # Mix original audio with BGM + mixed_audio = ffmpeg.filter( + [input_video.audio, bgm_audio], + 'amix', + inputs=2, + duration='first' # Use video's duration + ) + + ( + ffmpeg + .output( + input_video.video, + mixed_audio, + output, + vcodec='copy', + acodec='aac', + audio_bitrate='192k' + ) + .overwrite_output() + .run(capture_stdout=True, capture_stderr=True) + ) + + logger.success(f"BGM added successfully: {output}") + return output + except ffmpeg.Error as e: + error_msg = e.stderr.decode() if e.stderr else str(e) + logger.error(f"FFmpeg BGM error: {error_msg}") + raise RuntimeError(f"Failed to add BGM: {error_msg}") + diff --git a/reelforge/utils/__init__.py b/reelforge/utils/__init__.py new file mode 100644 index 0000000..e06405f --- /dev/null +++ b/reelforge/utils/__init__.py @@ -0,0 +1,3 @@ +""" +ReelForge utilities +""" diff --git a/reelforge/utils/os_util.py b/reelforge/utils/os_util.py new file mode 100644 index 0000000..e6e3f4f --- /dev/null +++ b/reelforge/utils/os_util.py @@ -0,0 +1,167 @@ +""" +OS utilities for file and path management + +Provides utilities for managing paths and files in ReelForge. +Inspired by Pixelle-MCP's os_util.py. +""" + +import os +from pathlib import Path + + +def get_reelforge_root_path() -> str: + """ + Get ReelForge root path - current working directory + + Returns: + Current working directory as string + """ + return str(Path.cwd()) + + +def ensure_reelforge_root_path() -> str: + """ + Ensure ReelForge root path exists and return the path + + Creates necessary directory structure if needed: + - temp/: for temporary files (audio, video, etc.) + - data/: for persistent data + - output/: for final output files + + Returns: + Root path as string + """ + root_path = get_reelforge_root_path() + root_path_obj = Path(root_path) + + # Create directory structure if needed + temp_dir = root_path_obj / 'temp' + data_dir = root_path_obj / 'data' + output_dir = root_path_obj / 'output' + + temp_dir.mkdir(parents=True, exist_ok=True) + data_dir.mkdir(parents=True, exist_ok=True) + output_dir.mkdir(parents=True, exist_ok=True) + + return root_path + + +def get_root_path(*paths: str) -> str: + """ + Get path relative to ReelForge root path + + Args: + *paths: Path components to join + + Returns: + Absolute path as string + + Example: + get_root_path("temp", "audio.mp3") + # Returns: "/path/to/project/temp/audio.mp3" + """ + root_path = ensure_reelforge_root_path() + if paths: + return os.path.join(root_path, *paths) + return root_path + + +def get_temp_path(*paths: str) -> str: + """ + Get path relative to ReelForge temp folder + + Args: + *paths: Path components to join + + Returns: + Absolute path to temp directory or file + + Example: + get_temp_path("audio.mp3") + # Returns: "/path/to/project/temp/audio.mp3" + """ + temp_path = get_root_path("temp") + if paths: + return os.path.join(temp_path, *paths) + return temp_path + + +def get_data_path(*paths: str) -> str: + """ + Get path relative to ReelForge data folder + + Args: + *paths: Path components to join + + Returns: + Absolute path to data directory or file + + Example: + get_data_path("books", "book.json") + # Returns: "/path/to/project/data/books/book.json" + """ + data_path = get_root_path("data") + if paths: + return os.path.join(data_path, *paths) + return data_path + + +def get_output_path(*paths: str) -> str: + """ + Get path relative to ReelForge output folder + + Args: + *paths: Path components to join + + Returns: + Absolute path to output directory or file + + Example: + get_output_path("video.mp4") + # Returns: "/path/to/project/output/video.mp4" + """ + output_path = get_root_path("output") + if paths: + return os.path.join(output_path, *paths) + return output_path + + +def save_bytes_to_file(data: bytes, file_path: str) -> str: + """ + Save bytes data to file + + Creates parent directories if they don't exist. + + Args: + data: Binary data to save + file_path: Target file path + + Returns: + Absolute path of saved file + + Example: + save_bytes_to_file(audio_data, get_temp_path("audio.mp3")) + """ + # Ensure parent directory exists + os.makedirs(os.path.dirname(file_path), exist_ok=True) + + # Write binary data + with open(file_path, "wb") as f: + f.write(data) + + return os.path.abspath(file_path) + + +def ensure_dir(path: str) -> str: + """ + Ensure directory exists, create if not + + Args: + path: Directory path + + Returns: + Absolute path of directory + """ + os.makedirs(path, exist_ok=True) + return os.path.abspath(path) + diff --git a/start_web.sh b/start_web.sh new file mode 100755 index 0000000..d42f464 --- /dev/null +++ b/start_web.sh @@ -0,0 +1,19 @@ +#!/bin/bash +# Start ReelForge Web UI + +echo "🚀 Starting ReelForge Web UI..." +echo "" + +# Check if config.yaml exists +if [ ! -f config.yaml ]; then + echo "⚠️ config.yaml not found, copying from config.example.yaml..." + cp config.example.yaml config.yaml + echo "✅ config.yaml created" + echo "" + echo "📝 Please edit config.yaml and fill in your API keys before using." + echo "" +fi + +# Start Streamlit +uv run streamlit run web.py --server.port=8501 --server.address=localhost + diff --git a/templates/README.md b/templates/README.md new file mode 100644 index 0000000..edc4de8 --- /dev/null +++ b/templates/README.md @@ -0,0 +1,274 @@ +# HTML Templates Guide + +## 📸 Preset Templates + +ReelForge provides the following preset templates: + +| Template | Style | Preview | +|----------|-------|---------| +| `classic` | Classic black & white, minimalist professional | Clean white background with elegant typography | +| `modern` | Modern gradient with glassmorphism effects | Purple-blue gradient with frosted glass style | +| `minimal` | Minimalist with ample whitespace | Light gray background with refined design | + +### Usage + +```python +from reelforge.service import reelforge + +await reelforge.initialize() + +# Use preset template +result = await reelforge.generate_book_video( + topic="为什么阅读改变命运", + frame_template="classic" # or "modern", "minimal" +) +``` + +--- + +## 🎨 Creating Custom Templates + +### Method 1: Generate with LLM (Recommended ⭐, Zero Code) + +**For users who want unique styles but don't want to write code** + +#### Step 1: Open Prompt File + +Open [`prompts/generate_html_template.txt`](../prompts/generate_html_template.txt) in the project root directory. + +Or view online: [View Prompt File](https://github.com/xxx/ReelForge/blob/main/prompts/generate_html_template.txt) + +#### Step 2: Copy Prompt, Modify Style Description + +Find this section in the prompt: +``` +## Visual Style +[👉 Replace this section with your desired style] +``` + +Replace with your desired style, for example: +``` +## Visual Style +Cyberpunk style with neon lights, dark background, purple and blue gradients +``` + +#### Step 3: Paste to LLM Platform + +Copy the entire prompt and paste it into any of these platforms: +- 💬 ChatGPT: https://chat.openai.com +- 💬 Claude: https://claude.ai +- 💬 Tongyi Qianwen: https://tongyi.aliyun.com +- 💬 DeepSeek: https://chat.deepseek.com +- 💬 Doubao: https://www.doubao.com +- 💬 Or any LLM you prefer + +#### Step 4: Save HTML + +Copy the HTML code returned by the LLM. + +⚠️ **Note:** If the LLM returns HTML wrapped in \`\`\`html\`\`\`, only copy the HTML inside (excluding \`\`\`html and \`\`\`) + +Save as: +``` +templates/my-cyberpunk.html +``` + +#### Step 5: Use Template + +```python +await reelforge.generate_book_video( + topic="...", + frame_template="my-cyberpunk" # Use your template +) +``` + +**🎉 Done! Your video now uses your custom style!** + +--- + +### Example Style Descriptions + +Here are some style descriptions you can use or adapt: + +- "Cyberpunk style with neon lights, dark background, purple gradient" +- "Fresh and clean style, light blue background, rounded cards, soft shadows" +- "Professional business style, dark blue with gold accents, serious and dignified" +- "Cute cartoon style, pink theme, rounded fonts, rainbow gradient" +- "Vintage retro style, sepia tones, aged paper texture, rounded borders" +- "Tech minimalist style, pure white background, thin borders, subtle animations" +- "Warm reading style, beige background, book texture, soft lighting" + +--- + +### Method 2: Write HTML Manually (Full Control) + +**For users familiar with HTML/CSS** + +Create an HTML file directly: + +```html + + + + + + + + +
{{topic}}
+ +
+ Frame Image +
+ +
+
{{text}}
+
《{{book_title}}》 - {{book_author}}
+
+ + +``` + +**Available Variables:** + +Required (always available): +- `{{topic}}` - Video topic +- `{{text}}` - Current frame narration text +- `{{image}}` - AI-generated image path + +Optional (available via `ext` parameter): +- `{{book_title}}` - Book title +- `{{book_author}}` - Author +- `{{book_cover}}` - Book cover path +- `{{book_rating}}` - Book rating +- And any other custom fields you pass via `ext` + +--- + +## 🤝 Share Your Templates + +Created a beautiful template? Share it with the community! + +1. Fork this repository +2. Add your HTML to `templates/community/` +3. Submit a Pull Request + +Excellent templates will be featured in the official template gallery! + +--- + +## ❓ FAQ + +**Q: What if the HTML generated by LLM has syntax errors?** +A: Regenerate, or emphasize "ensure HTML syntax is correct" in the prompt + +**Q: What if I'm not satisfied with the generated style?** +A: Modify the style description in the prompt, or manually edit the HTML file + +**Q: Can I use external CSS frameworks (like Tailwind)?** +A: Yes, but you need CDN links. We recommend inline CSS for offline compatibility + +**Q: Where should template files be placed?** +A: In the `templates/` directory. The filename is the template name (without .html extension) + +**Q: What's the recommended canvas size?** +A: 1080x1920 (9:16 portrait for TikTok/Douyin) + +**Q: Can I use custom fonts?** +A: Yes, but system fonts are recommended (PingFang SC, Microsoft YaHei, etc.) for compatibility + +--- + +## 📚 Technical Details + +### How HTML Rendering Works + +1. Load HTML template file +2. Replace variables (`{{topic}}`, `{{text}}`, etc.) with actual data +3. Render HTML to image using `html2image` (Chrome headless) +4. Save as frame image + +### Performance + +- First render: ~1-2 seconds (browser initialization) +- Subsequent renders: ~0.5-1 second per frame +- For 5-frame videos: acceptable total time + +### Browser Requirements + +`html2image` uses Chrome/Chromium headless mode. It will automatically find: +- System Chrome +- System Chromium +- Or download a lightweight browser engine + +--- + +## 💡 Tips + +1. **Preview before generating**: Open HTML in browser to preview effect +2. **Maintain aspect ratio**: Keep 1080x1920 for best results +3. **Watch text length**: Ensure long text wraps properly (`word-wrap`, `overflow-wrap`) +4. **Consider contrast**: Ensure text is readable against background +5. **Use relative units**: `%` and `vh/vw` for better responsiveness + +--- + +## 🎨 Inspiration Gallery + +Looking for inspiration? Check out: +- [Official Template Gallery](https://reelforge.ai/templates) (coming soon) +- [Community Templates](./community/) (coming soon) +- Design sites: Dribbble, Behance, Pinterest + +--- + +Need help? Open an [Issue](https://github.com/xxx/ReelForge/issues) or join our [Discord](https://discord.gg/xxx)! + diff --git a/templates/classic.html b/templates/classic.html new file mode 100644 index 0000000..bddd277 --- /dev/null +++ b/templates/classic.html @@ -0,0 +1,541 @@ + + + + + + + + +
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+ Frame Image +
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{{text}}
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+ + +
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+ +
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+ + @Pixelle.AI +
+
Open Source Omnimodal AI Creative Agent
+
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+ +
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+
+
+
+ + diff --git a/templates/modern.html b/templates/modern.html new file mode 100644 index 0000000..b32d0a0 --- /dev/null +++ b/templates/modern.html @@ -0,0 +1,572 @@ + + + + + + + + +
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+ Frame Image +
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{{text}}
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+ @Pixelle.AI +
+
Open Source Omnimodal AI Creative Agent
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+ +
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+ + diff --git a/templates/neon.html b/templates/neon.html new file mode 100644 index 0000000..0a84b4b --- /dev/null +++ b/templates/neon.html @@ -0,0 +1,936 @@ + + + + + + {{topic}} + + + +
+ + + + + + + + + + + + + +
+ + + + + + + + + +

{{text}}

+ +
+ + +
+
+ 作者 +
+
+
+
+ @Pixelle.AI +
+
Open Source Omnimodal AI Creative Agent
+
+ +
+ #阅读 + #成长 + #认知升级 +
+
+
+
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============================================================================ +# Async Helper +# ============================================================================ + +def run_async(coro): + """Run async coroutine in sync context""" + loop = asyncio.new_event_loop() + asyncio.set_event_loop(loop) + try: + return loop.run_until_complete(coro) + finally: + loop.close() + + +def safe_rerun(): + """Safe rerun that works with both old and new Streamlit versions""" + if hasattr(st, 'rerun'): + st.rerun() + else: + st.experimental_rerun() + + +# ============================================================================ +# Configuration & i18n Initialization +# ============================================================================ + +@st.cache_resource +def get_config_manager(): + """Get ConfigManager instance (cached)""" + manager = ConfigManager() + manager.load_or_create_default() + return manager + + +def init_i18n(): + """Initialize internationalization""" + # Load locales if not already loaded + load_locales() + + # Get language from session state or default to Chinese + if "language" not in st.session_state: + st.session_state.language = "zh_CN" + + # Set current language + set_language(st.session_state.language) + + +# ============================================================================ +# Preview Cache Functions +# ============================================================================ + +def generate_style_preview_cached( + style_preset_name: str, + custom_style_description: str +): + """ + Generate and cache visual style preview + + Args: + style_preset_name: Preset style name ("minimal", "futuristic", etc.) or empty + custom_style_description: Custom description or empty + + Returns: + Tuple of (image_path, converted_prompt_if_custom) + """ + from reelforge.services.final_image_prompt import StylePreset + + reelforge = get_reelforge() + + # Convert style preset name to enum + style_preset = None + if style_preset_name: + try: + style_preset = StylePreset[style_preset_name.upper()] + except KeyError: + pass + + # Generate final prompt using the new service + final_prompt = run_async(reelforge.generate_final_image_prompt( + prompt="A beautiful book on a desk", + style_preset=style_preset, + custom_style_description=custom_style_description + )) + + # Generate preview image (small size for speed) + preview_image_path = run_async(reelforge.image( + workflow="workflows/t2i_by_local_flux.json", + prompt=final_prompt, + width=512, + height=512 + )) + + # Return converted prompt only for custom mode + converted_prompt = final_prompt if custom_style_description else None + + return preview_image_path, converted_prompt + + +# ============================================================================ +# Initialize ReelForge +# ============================================================================ + +@st.cache_resource +def get_reelforge(): + """Get initialized ReelForge instance (cached)""" + from reelforge.service import reelforge + + logger.info("Initializing ReelForge...") + run_async(reelforge.initialize()) + logger.info("ReelForge initialized") + + return reelforge + + +# ============================================================================ +# Session State +# ============================================================================ + +def init_session_state(): + """Initialize session state variables""" + if "book_info" not in st.session_state: + st.session_state.book_info = None + if "language" not in st.session_state: + st.session_state.language = "zh_CN" + + +# ============================================================================ +# System Configuration (Required) +# ============================================================================ + +def render_advanced_settings(config_manager: ConfigManager): + """Render system configuration (required) with 2-column layout""" + # Check if system is configured + is_configured = config_manager.validate() + + # Expand if not configured, collapse if configured + with st.expander(tr("settings.title"), expanded=not is_configured): + # 2-column layout: LLM | Image+Book + llm_col, image_col = st.columns(2) + + # ==================================================================== + # Column 1: LLM Settings (Simplified 3-field format) + # ==================================================================== + with llm_col: + with st.container(border=True): + st.markdown(f"**{tr('settings.llm.title')}**") + + # Quick preset selection + from reelforge.llm_presets import get_preset_names, get_preset, find_preset_by_base_url_and_model + + # Custom at the end + preset_names = get_preset_names() + ["Custom"] + + # Get current config + current_llm = config_manager.get_llm_config() + + # Auto-detect which preset matches current config + current_preset = find_preset_by_base_url_and_model( + current_llm["base_url"], + current_llm["model"] + ) + + # Determine default index based on current config + if current_preset: + # Current config matches a preset + default_index = preset_names.index(current_preset) + else: + # Current config doesn't match any preset -> Custom + default_index = len(preset_names) - 1 + + selected_preset = st.selectbox( + tr("settings.llm.quick_select"), + options=preset_names, + index=default_index, + help=tr("settings.llm.quick_select_help"), + key="llm_preset_select" + ) + + # Auto-fill based on selected preset + if selected_preset != "Custom": + # Preset selected + preset_config = get_preset(selected_preset) + + # If user switched to a different preset (not current one), clear API key + # If it's the same as current config, keep API key + if selected_preset == current_preset: + # Same preset as saved config: keep API key + default_api_key = current_llm["api_key"] + else: + # Different preset: clear API key + default_api_key = "" + + default_base_url = preset_config.get("base_url", "") + default_model = preset_config.get("model", "") + + # Show API key URL if available + if preset_config.get("api_key_url"): + st.markdown(f"🔑 [{tr('settings.llm.get_api_key')}]({preset_config['api_key_url']})") + else: + # Custom: clear all fields (let user fill custom config) + default_api_key = "" + default_base_url = "" + default_model = "" + + st.markdown("---") + + # API Key (use unique key to force refresh when switching preset) + llm_api_key = st.text_input( + f"{tr('settings.llm.api_key')} *", + value=default_api_key, + type="password", + help=tr("settings.llm.api_key_help"), + key=f"llm_api_key_input_{selected_preset}" + ) + + # Base URL (use unique key based on preset to force refresh) + llm_base_url = st.text_input( + f"{tr('settings.llm.base_url')} *", + value=default_base_url, + help=tr("settings.llm.base_url_help"), + key=f"llm_base_url_input_{selected_preset}" + ) + + # Model (use unique key based on preset to force refresh) + llm_model = st.text_input( + f"{tr('settings.llm.model')} *", + value=default_model, + help=tr("settings.llm.model_help"), + key=f"llm_model_input_{selected_preset}" + ) + + # ==================================================================== + # Column 2: Image Settings + # ==================================================================== + with image_col: + with st.container(border=True): + st.markdown(f"**{tr('settings.image.title')}**") + + # Get current configuration + comfykit_config = config_manager.config.get("image", {}).get("comfykit", {}) + + # Local/Self-hosted ComfyUI configuration + st.markdown(f"**{tr('settings.image.local_title')}**") + comfyui_url = st.text_input( + tr("settings.image.comfyui_url"), + value=comfykit_config.get("comfyui_url", "http://127.0.0.1:8188"), + help=tr("settings.image.comfyui_url_help"), + key="comfyui_url_input" + ) + + # Test connection button + if st.button(tr("btn.test_connection"), key="test_comfyui", use_container_width=True): + try: + import requests + response = requests.get(f"{comfyui_url}/system_stats", timeout=5) + if response.status_code == 200: + st.success(tr("status.connection_success")) + else: + st.error(tr("status.connection_failed")) + except Exception as e: + st.error(f"{tr('status.connection_failed')}: {str(e)}") + + st.markdown("---") + + # RunningHub cloud configuration + st.markdown(f"**{tr('settings.image.cloud_title')}**") + runninghub_api_key = st.text_input( + tr("settings.image.runninghub_api_key"), + value=comfykit_config.get("runninghub_api_key", ""), + type="password", + help=tr("settings.image.runninghub_api_key_help"), + key="runninghub_api_key_input" + ) + + # ==================================================================== + # Action Buttons (full width at bottom) + # ==================================================================== + st.markdown("---") + + col1, col2 = st.columns(2) + with col1: + if st.button(tr("btn.save_config"), use_container_width=True, key="save_config_btn"): + try: + # Save LLM configuration (simple 3-field format) + if llm_api_key and llm_base_url and llm_model: + config_manager.set_llm_config(llm_api_key, llm_base_url, llm_model) + + # Save Image configuration (both local and cloud can be configured) + config_manager.config["image"]["default"] = "comfykit" + image_config = {} + if comfyui_url: + image_config["comfyui_url"] = comfyui_url + if runninghub_api_key: + image_config["runninghub_api_key"] = runninghub_api_key + if image_config: + config_manager.config["image"]["comfykit"] = image_config + + # Save to file + config_manager.save() + + st.success(tr("status.config_saved")) + safe_rerun() + except Exception as e: + st.error(f"{tr('status.save_failed')}: {str(e)}") + + with col2: + if st.button(tr("btn.reset_config"), use_container_width=True, key="reset_config_btn"): + config_manager.config = config_manager._create_default_config() + config_manager.save() + st.success(tr("status.config_reset")) + safe_rerun() + + +# ============================================================================ +# Language Selector +# ============================================================================ + +def render_language_selector(): + """Render language selector at the top""" + languages = get_available_languages() + lang_options = [f"{code} - {name}" for code, name in languages.items()] + + current_lang = st.session_state.get("language", "zh_CN") + current_index = list(languages.keys()).index(current_lang) if current_lang in languages else 0 + + selected = st.selectbox( + tr("language.select"), + options=lang_options, + index=current_index, + label_visibility="collapsed" + ) + + selected_code = selected.split(" - ")[0] + if selected_code != current_lang: + st.session_state.language = selected_code + set_language(selected_code) + safe_rerun() + + +# ============================================================================ +# Main UI +# ============================================================================ + +def main(): + # Initialize + init_session_state() + init_i18n() + + config_manager = get_config_manager() + + # Top bar: Title + Language selector + col1, col2 = st.columns([4, 1]) + with col1: + st.title(tr("app.title")) + with col2: + render_language_selector() + + # Initialize ReelForge + reelforge = get_reelforge() + + # ======================================================================== + # System Configuration (Required) + # Auto-expands if not configured, collapses if configured + # ======================================================================== + render_advanced_settings(config_manager) + + # Three-column layout + left_col, middle_col, right_col = st.columns([1, 1, 1]) + + # ======================================================================== + # Left Column: Book & Content + # ======================================================================== + with left_col: + with st.container(border=True): + st.markdown(f"**{tr('section.content_input')}**") + + # Input mode selection + input_mode = st.radio( + "Input Mode", + [tr("input_mode.book"), tr("input_mode.topic"), tr("input_mode.custom")], + horizontal=True, + label_visibility="collapsed" + ) + + book_name = None + topic = None + content = None + title = None + + if input_mode == tr("input_mode.book"): + book_name = st.text_input( + tr("input.book_name"), + placeholder=tr("input.book_name_placeholder"), + help=tr("input.book_name_help") + ) + + # Book search button + if st.button(tr("book.search"), use_container_width=True): + if book_name: + with st.spinner(tr("book.searching")): + try: + # Search book using BookFetcherService + book_info = run_async(reelforge.book_fetcher(book_name)) + st.session_state.book_info = book_info + st.success(tr("book.found")) + except Exception as e: + st.error(tr("book.not_found", error=str(e))) + else: + st.warning(tr("book.name_required")) + + # Display book info if available + if st.session_state.book_info: + st.markdown("---") + book_info = st.session_state.book_info + + # Book cover (if available) + if hasattr(book_info, 'cover_url') and book_info.cover_url: + st.image(book_info.cover_url, width=200) + + # Book details + st.markdown(f"**{tr('book.title')}:** {book_info.title}") + if hasattr(book_info, 'author'): + st.markdown(f"**{tr('book.author')}:** {book_info.author}") + if hasattr(book_info, 'rating'): + st.markdown(f"**{tr('book.rating')}:** ⭐ {book_info.rating}") + if hasattr(book_info, 'summary'): + with st.expander(tr("book.summary")): + st.write(book_info.summary) + + elif input_mode == tr("input_mode.topic"): + topic = st.text_area( + tr("input.topic"), + placeholder=tr("input.topic_placeholder"), + height=100, + help=tr("input.topic_help") + ) + + else: # Custom Content + content = st.text_area( + tr("input.content"), + placeholder=tr("input.content_placeholder"), + height=200, + help=tr("input.content_help") + ) + title = st.text_input( + tr("input.title"), + placeholder=tr("input.title_placeholder") + ) + + # ==================================================================== + # Video Settings (moved from right column) + # ==================================================================== + with st.container(border=True): + st.markdown(f"**{tr('video.title')}**") + + # Number of frames + n_frames = st.slider( + tr("video.frames"), + min_value=3, + max_value=30, + value=5, + help=tr("video.frames_help"), + label_visibility="collapsed" + ) + st.caption(tr("video.frames_label", n=n_frames)) + + st.markdown("---") + + # Background music + st.markdown(f"**{tr('bgm.title')}**") + + # Dynamically scan bgm folder for music files (support common audio formats) + bgm_folder = Path("bgm") + bgm_files = [] + if bgm_folder.exists(): + audio_extensions = ["*.mp3", "*.wav", "*.flac", "*.m4a", "*.aac", "*.ogg"] + for ext in audio_extensions: + bgm_files.extend([f.name for f in bgm_folder.glob(ext)]) + bgm_files.sort() + + # Add special "None" option + bgm_options = [tr("bgm.none")] + bgm_files + + # Default to "default.mp3" if exists, otherwise first option + default_index = 0 + if "default.mp3" in bgm_files: + default_index = bgm_options.index("default.mp3") + + bgm_choice = st.selectbox( + "BGM", + bgm_options, + index=default_index, + label_visibility="collapsed" + ) + + # BGM preview button (only if BGM is not "None") + if bgm_choice != tr("bgm.none"): + if st.button(tr("bgm.preview"), key="preview_bgm", use_container_width=True): + bgm_file_path = f"bgm/{bgm_choice}" + if os.path.exists(bgm_file_path): + st.audio(bgm_file_path) + else: + st.error(tr("bgm.preview_failed", file=bgm_choice)) + + # Extract filename without extension for bgm_path (service layer expects stem only) + bgm_path = None if bgm_choice == tr("bgm.none") else Path(bgm_choice).stem + + # ======================================================================== + # Middle Column: Custom Settings (Voice & Visual Style & Template) + # ======================================================================== + with middle_col: + with st.container(border=True): + st.markdown(f"**{tr('section.style_settings')}**") + + # Voice selection + st.markdown(f"**{tr('voice.title')}**") + voice_id = st.selectbox( + "Voice", + [ + "zh-CN-YunjianNeural", # 男声-专业 + "zh-CN-YunxiNeural", # 男声-年轻 + "zh-CN-XiaoxiaoNeural", # 女声-温柔 + "zh-CN-XiaoyiNeural", # 女声-活力 + ], + format_func=lambda x: { + "zh-CN-YunjianNeural": tr("voice.male_professional"), + "zh-CN-YunxiNeural": tr("voice.male_young"), + "zh-CN-XiaoxiaoNeural": tr("voice.female_gentle"), + "zh-CN-XiaoyiNeural": tr("voice.female_energetic"), + }[x], + label_visibility="collapsed" + ) + + # Voice preview button + if st.button(tr("voice.preview"), key="preview_voice", use_container_width=True): + with st.spinner(tr("voice.previewing")): + try: + # Generate preview audio + preview_text = "大家好，这是一段测试语音。" + + # Use TTS service to generate audio (auto temp path) + audio_path = run_async(reelforge.tts( + text=preview_text, + voice=voice_id + )) + + # Play the audio + if os.path.exists(audio_path): + st.audio(audio_path, format="audio/mp3") + else: + st.error("Failed to generate preview audio") + except Exception as e: + st.error(tr("voice.preview_failed", error=str(e))) + logger.exception(e) + + st.markdown("---") + + # Visual style (Illustration Style) + st.markdown(f"**{tr('style.title')}**") + + # Get available presets dynamically from StylePreset enum + from reelforge.services.final_image_prompt import StylePreset + + # Build preset options (enum values + custom) + preset_options = [preset.name.lower() for preset in StylePreset] + preset_options.append("custom") + + # Dynamic display name function + def get_preset_display(preset_name: str) -> str: + if preset_name == "custom": + return tr("style.custom") + # Find the enum by name and get its display_name + for preset in StylePreset: + if preset.name.lower() == preset_name: + return preset.value.display_name + return preset_name.replace("_", " ").title() + + # Change from radio to selectbox (dropdown) + style_preset = st.selectbox( + "Style Preset", + preset_options, + format_func=get_preset_display, + label_visibility="collapsed" + ) + + # Custom style description input (only show for custom mode) + custom_style_description = "" + if style_preset == "custom": + custom_style_description = st.text_area( + tr("style.description"), + placeholder=tr("style.description_placeholder"), + height=80, + label_visibility="collapsed" + ) + + # Visual style preview button + if st.button(tr("style.preview"), key="preview_style", use_container_width=True): + with st.spinner(tr("style.previewing")): + try: + # Generate preview using cached function + preset_name = style_preset if style_preset != "custom" else "" + custom_desc = custom_style_description if style_preset == "custom" else "" + + preview_image_path, generated_prompt = generate_style_preview_cached( + style_preset_name=preset_name, + custom_style_description=custom_desc + ) + + # Show generated prompt if custom mode + if generated_prompt: + st.info(tr("style.generated_prompt", prompt=generated_prompt)) + + # Display preview (support both URL and local path) + if preview_image_path: + # Read and encode image + if preview_image_path.startswith('http'): + # URL - use directly + img_html = f'
Style Preview
' + else: + # Local file - encode as base64 + with open(preview_image_path, 'rb') as f: + img_data = base64.b64encode(f.read()).decode() + img_html = f'
Style Preview
' + + st.markdown(img_html, unsafe_allow_html=True) + st.caption(tr("style.preview_caption")) + else: + st.error("Failed to generate preview image") + except Exception as e: + st.error(tr("style.preview_failed", error=str(e))) + logger.exception(e) + + st.markdown("---") + + # Frame template (moved from right column) + st.markdown(f"**{tr('template.title')}**") + frame_template = st.selectbox( + "Template", + ["classic", "modern", "neon"], + format_func=lambda x: tr(f"template.{x}"), + label_visibility="collapsed" + ) + + # ======================================================================== + # Right Column: Generate Button + Progress + Video Preview + # ======================================================================== + with right_col: + with st.container(border=True): + st.markdown(f"**{tr('section.video_generation')}**") + + # Check if system is configured + if not config_manager.validate(): + st.warning(tr("settings.not_configured")) + + # Generate Button + if st.button(tr("btn.generate"), type="primary", use_container_width=True): + # Validate system configuration + if not config_manager.validate(): + st.error(tr("settings.not_configured")) + st.stop() + + # Validate input + if not book_name and not topic and not content: + st.error(tr("error.input_required")) + st.stop() + + # Show progress + progress_bar = st.progress(0) + status_text = st.empty() + + try: + # Progress callback to update UI + def update_progress(event: ProgressEvent): + """Update progress bar and status text from ProgressEvent""" + # Translate event to user-facing message + if event.event_type == "frame_step": + # Frame step: "分镜 3/5 - 步骤 2/4: 生成插图" + action_key = f"progress.step_{event.action}" + action_text = tr(action_key) + message = tr( + "progress.frame_step", + current=event.frame_current, + total=event.frame_total, + step=event.step, + action=action_text + ) + elif event.event_type == "processing_frame": + # Processing frame: "分镜 3/5" + message = tr( + "progress.frame", + current=event.frame_current, + total=event.frame_total + ) + else: + # Simple events: use i18n key directly + message = tr(f"progress.{event.event_type}") + + status_text.text(message) + progress_bar.progress(min(int(event.progress * 100), 99)) # Cap at 99% until complete + + # Prepare image style parameters + style_preset_param = None + style_description_param = None + + if style_preset == "custom": + # Custom mode: pass user description as-is + style_description_param = custom_style_description + else: + # Preset mode: pass preset name + style_preset_param = style_preset + + result = run_async(reelforge.generate_book_video( + book_name=book_name if book_name else None, + topic=topic if topic else None, + content=content if content else None, + title=title if title else None, + n_frames=n_frames, + voice_id=voice_id, + image_style_preset=style_preset_param, + image_style_description=style_description_param, + frame_template=frame_template, + bgm_path=bgm_path, + progress_callback=update_progress, + )) + + progress_bar.progress(100) + status_text.text(tr("status.success")) + + # Display success message + st.success(tr("status.video_generated", path=result.video_path)) + + st.markdown("---") + + # Video information (compact display) + file_size_mb = result.file_size / (1024 * 1024) + info_text = ( + f"⏱️ {result.duration:.1f}s " + f"📦 {file_size_mb:.2f}MB " + f"🎬 {len(result.storyboard.frames)}{tr('info.scenes_unit')} " + f"📐 {result.storyboard.config.video_width}x{result.storyboard.config.video_height}" + ) + st.caption(info_text) + + st.markdown("---") + + # Video preview + if os.path.exists(result.video_path): + st.video(result.video_path) + else: + st.error(tr("status.video_not_found", path=result.video_path)) + + except Exception as e: + status_text.text("") + progress_bar.empty() + st.error(tr("status.error", error=str(e))) + logger.exception(e) + st.stop() + + +if __name__ == "__main__": + main() diff --git a/workflows/t2i_by_local_flux.json b/workflows/t2i_by_local_flux.json new file mode 100644 index 0000000..d232703 --- /dev/null +++ b/workflows/t2i_by_local_flux.json @@ -0,0 +1,208 @@ +{ + "2": { + "inputs": { + "noise": [ + "5", + 0 + ], + "guider": [ + "7", + 0 + ], + "sampler": [ + "4", + 0 + ], + "sigmas": [ + "3", + 0 + ], + "latent_image": [ + "10", + 0 + ] + }, + "class_type": "SamplerCustomAdvanced", + "_meta": { + "title": "自定义采样器（高级）" + } + }, + "3": { + "inputs": { + "scheduler": "simple", + "steps": 20, + "denoise": 1, + "model": [ + "8", + 0 + ] + }, + "class_type": "BasicScheduler", + "_meta": { + "title": "基本调度器" + } + }, + "4": { + "inputs": { + "sampler_name": "euler" + }, + "class_type": "KSamplerSelect", + "_meta": { + "title": "K采样器选择" + } + }, + "5": { + "inputs": { + "noise_seed": 1091846418466568 + }, + "class_type": "RandomNoise", + "_meta": { + "title": "随机噪波" + } + }, + "6": { + "inputs": { + "clip_name1": "t5xxl_fp16.safetensors", + "clip_name2": "clip_l.safetensors", + "type": "flux", + "device": "default" + }, + "class_type": "DualCLIPLoader", + "_meta": { + "title": "双CLIP加载器" + } + }, + "7": { + "inputs": { + "model": [ + "8", + 0 + ], + "conditioning": [ + "11", + 0 + ] + }, + "class_type": "BasicGuider", + "_meta": { + "title": "基本引导器" + } + }, + "8": { + "inputs": { + "unet_name": "flux1-dev.safetensors", + "weight_dtype": "fp8_e4m3fn" + }, + "class_type": "UNETLoader", + "_meta": { + "title": "UNet加载器" + } + }, + "9": { + "inputs": { + "vae_name": "ae.safetensors" + }, + "class_type": "VAELoader", + "_meta": { + "title": "加载VAE" + } + }, + "10": { + "inputs": { + "width": [ + "27", + 0 + ], + "height": [ + "28", + 0 + ], + "batch_size": 1 + }, + "class_type": "EmptyLatentImage", + "_meta": { + "title": "空Latent图像" + } + }, + "11": { + "inputs": { + "text": [ + "21", + 0 + ], + "clip": [ + "6", + 0 + ] + }, + "class_type": "CLIPTextEncode", + "_meta": { + "title": "CLIP文本编码" + } + }, + "14": { + "inputs": { + "samples": [ + "2", + 0 + ], + "vae": [ + "9", + 0 + ] + }, + "class_type": "VAEDecode", + "_meta": { + "title": "VAE解码" + } + }, + "20": { + "inputs": { + "filename_prefix": "ComfyUI", + "images": [ + "14", + 0 + ] + }, + "class_type": "SaveImage", + "_meta": { + "title": "保存图像" + } + }, + "21": { + "inputs": { + "text": "A serene and peaceful scene of a European/American girl playing guitar by the seaside. The background features a calm ocean under soft, natural lighting, with tranquil sky and subtle waves. The overall atmosphere is quiet and harmonious, evoking a sense of relaxation and gentle breeze. Horizontal composition, photorealistic style," + }, + "class_type": "Text _O", + "_meta": { + "title": "$prompt.text!:image prompt" + } + }, + "24": { + "inputs": { + "text": "Generate high-quality images from text prompts using local FLUX 1.1 model.\n \n Creates completely new images with exceptional detail, style diversity, and prompt adherence.\n The model excels at photorealistic scenes, artistic styles, and complex compositions.\n \n Prompt writing tips for best results:\n - Be detailed and specific: include colors, mood, lighting, and composition\n - Use natural language and full sentences rather than keywords\n - For photos: mention camera type, settings (e.g., \"shot on DSLR, f/2.8, golden hour\")\n - For portraits: describe features, expressions, clothing, and background\n - For scenes: specify foreground, middle ground, and background elements\n \n Excellent prompt examples:\n - \"birthday, girl selfie with bright smile and colorful balloons\"\n - \"Close-up portrait of a child with bright vivid emotions, sparkling eyes full of joy, sunlight dancing on rosy cheeks\"\n - \"Serene lake reflecting dense forest during golden hour, shot on DSLR with wide-angle lens, f/8, perfect symmetry\"\n - \"Vintage travel poster for Paris, Eiffel Tower silhouette in warm sunset colors, 'PARIS' in golden Art Deco font\"\n - \"Ethereal dragon with neon lightning crystal on head, glowing blue eyes, majestic wings spread wide\"" + }, + "class_type": "Text _O", + "_meta": { + "title": "MCP" + } + }, + "27": { + "inputs": { + "value": 1024 + }, + "class_type": "easy int", + "_meta": { + "title": "$width.value" + } + }, + "28": { + "inputs": { + "value": 1024 + }, + "class_type": "easy int", + "_meta": { + "title": "$height.value" + } + } +}