Providers
LLM provider and model metadata for LibreFang. Each provider file defines the provider's API configuration and all available models with pricing, context windows, and capability flags.
Structure
providers/
├── anthropic.toml
├── openai.toml
├── groq.toml
└── ... (46 providers, 220+ models)
Provider TOML Format
[provider]
id = "provider-id" # Unique identifier (lowercase, hyphenated)
display_name = "Provider Name"
api_key_env = "PROVIDER_API_KEY" # Env var for API key
base_url = "https://api.example.com"
key_required = true
[[models]]
id = "model-id" # Exact API model ID
display_name = "Model 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 = ["short-name"]
Tier Definitions
| Tier | Description | Examples |
|---|---|---|
frontier |
Most capable, cutting-edge | Claude Opus, GPT-4.1 |
smart |
Smart, cost-effective | Claude Sonnet, Gemini 2.5 Flash |
balanced |
Balanced speed/cost | GPT-4.1 Mini, Llama 3.3 70B |
fast |
Fastest, cheapest | GPT-4o Mini, Claude Haiku |
local |
Local models, zero cost | Ollama, vLLM, LM Studio |
Validation
python scripts/validate.py
Checks: required fields, valid tiers, non-negative costs, no duplicate model IDs.
Adding or Updating a Model
- Edit or create the provider file in
providers/ - Use exact API model IDs and verify pricing from official sources
- Run
python scripts/validate.py - Submit a PR
See CONTRIBUTING.md for the full guide and pricing source links.