117 lines
3.4 KiB
YAML
117 lines
3.4 KiB
YAML
# 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
|