Community-maintained TOML catalog for LibreFang. New models can be added via PR without requiring a LibreFang binary release. Includes validation script, bilingual docs, and GitHub templates.
3.4 KiB
3.4 KiB
Contributing to LibreFang Model Catalog
Thank you for helping keep the model catalog up to date! This guide explains how to add or update model entries.
How to Add a New Model
1. Fork & Clone
git clone https://github.com/<your-fork>/model-catalog.git
cd model-catalog
2. Find the Right Provider File
Each provider has its own file in providers/. For example:
- OpenAI models go in
providers/openai.toml - Anthropic models go in
providers/anthropic.toml
If the provider doesn't exist yet, create a new file (e.g. providers/newprovider.toml) with the [provider] section and your [[models]] entries.
3. Add Your Model Entry
Append a [[models]] block to the provider file:
[[models]]
id = "new-model-id" # The exact API model ID
display_name = "New Model Name" # Human-readable name
tier = "smart" # frontier | smart | balanced | fast | local
context_window = 128000
max_output_tokens = 16384
input_cost_per_m = 2.50 # USD per million input tokens
output_cost_per_m = 10.0 # USD per million output tokens
supports_tools = true
supports_vision = false
supports_streaming = true
aliases = [] # Optional short names
4. Validate
python scripts/validate.py
This checks:
- All TOML files parse correctly
- Required fields are present
- Tier values are valid
- Costs are non-negative
- No duplicate model IDs
5. Submit a Pull Request
Push your branch and open a PR. The PR template will guide you through the checklist.
Where to Find Model Information
- OpenAI: https://openai.com/pricing
- Anthropic: https://docs.anthropic.com/en/docs/about-claude/models
- Google Gemini: https://ai.google.dev/pricing
- DeepSeek: https://platform.deepseek.com/api-docs/pricing
- Mistral: https://mistral.ai/technology/#pricing
- Groq: https://wow.groq.com/
- xAI: https://docs.x.ai/docs
- Cohere: https://cohere.com/pricing
- Together: https://www.together.ai/pricing
- Fireworks: https://fireworks.ai/pricing
- Perplexity: https://docs.perplexity.ai/guides/pricing
Tier Definitions
| Tier | Description | Examples |
|---|---|---|
frontier |
Most capable, cutting-edge | Claude Opus, GPT-4.1, Gemini 2.5 Pro |
smart |
Smart and cost-effective | Claude Sonnet, GPT-4o, Gemini 2.5 Flash |
balanced |
Balanced speed and cost | GPT-4.1 Mini, Llama 3.3 70B |
fast |
Fastest, cheapest | GPT-4o Mini, Claude Haiku, Gemma 2 9B |
local |
Local models, zero cost | Ollama, vLLM, LM Studio |
Guidelines
- Pricing must be in USD per million tokens -- convert from other units if needed
- Use the exact model ID that the provider's API expects
- Don't guess -- only add data you can verify from official sources
- One provider per file -- don't mix providers in a single TOML file
- Keep aliases short -- 1-3 word abbreviations that users would naturally type
贡献指南
感谢您帮助维护模型目录!以下是添加或更新模型条目的方法。
如何添加新模型
- Fork 并克隆此仓库
- 在
providers/目录中找到对应的提供商文件 - 添加
[[models]]条目(参考上方英文模板) - 运行
python scripts/validate.py验证 - 提交 Pull Request
定价说明
- 所有价格均以 美元/百万 tokens 为单位
- 免费模型和本地模型的价格为
0.0 - 请从官方定价页面获取准确数据