Files
librefang-registry/providers
Evan 396c88dc49 feat(openai): add GPT-5.4 and GPT-5.4-mini (#67)
Add the two GPT-5.4 variants exposed by OpenAI's API (source:
https://developers.openai.com/api/docs/models/gpt-5.4 and
https://developers.openai.com/api/docs/models/gpt-5.4-mini):

- **gpt-5.4** — frontier tier, 1,050,000 context window, 128k max output,
  $2.50 / input MTok, $15.00 / output MTok.
- **gpt-5.4-mini** — balanced tier (matching the naming convention used
  by `gpt-5-mini`, `gpt-4.1-mini`, etc.), 400,000 context window,
  128k max output, $0.75 / input MTok, $4.50 / output MTok.

Ordered right after the GPT-5.2 family and before the Codex variants
section to keep the frontier-GPT chain in release order.

Addresses librefang/librefang-registry#65 — the original request filed
these under the `codex-cli` provider, but Codex CLI's upstream
`models.json` doesn't list `gpt-5.4-mini` (only the full `gpt-5.4`
slug is list-visible there, and it's already tracked in
`providers/codex-cli.toml`). The correct home for OpenAI-API-direct
access is this file; users who want `gpt-5.4-mini` should configure
`provider = "openai"` rather than `provider = "codex-cli"`.
2026-04-20 14:15:20 +09:00
..

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

  1. Edit or create the provider file in providers/
  2. Use exact API model IDs and verify pricing from official sources
  3. Run python scripts/validate.py
  4. Submit a PR

See CONTRIBUTING.md for the full guide and pricing source links.