LLM model metadata catalog with fast, capability-aware lookups. Use simple "provider:model" or "model@provider" specs, get validated Provider/Model structs, and select models by capabilities. Ships with a packaged snapshot; no network required by default.
The packaged catalog loads lazily on the first query and starts no llm_db
supervisor or worker. Use LLMDB.load/1 when you need explicit control over
loading or want an error tuple; a lazy first-use failure raises
LLMDB.LoadError. Loading never pulls provider metadata or reads dotenv files.
- Primary interface:
model_spec— a string like"openai:gpt-4o-mini"or"gpt-4o-mini@openai"(filename-safe) - Fast O(1) reads via
:persistent_term - Minimal dependencies
LLM model metadata changes constantly. Providers launch new models, rename aliases, retire previews, change pricing, add modalities, and expose new runtime capabilities without waiting for downstream libraries to catch up.
LLM DB gives that moving catalog a refreshable snapshot pattern: pull upstream metadata, validate and normalize it, package it into releases, and let consumers query a stable local database at runtime. The site at llmdb.xyz showcases the live catalog and makes those ongoing changes easier to inspect.
LLMDB now distinguishes between descriptive catalog metadata and typed execution
metadata.
LLMDB.Provider.runtimedeclares provider-wide execution defaults such asbase_url, auth strategy, default headers/query params, config schema, and runtime docsLLMDB.Model.executiondeclares operation-specific support and the canonical API family used to execute that operationcatalog_only: truemarks packaged entries that are intentionally non-executable
Legacy fields like base_url, doc, and extra remain available during
migration, but runtime and execution are the intended source of truth for
downstream runtime consumers.
The packaged snapshot is enriched at build time:
- providers with a stable runtime contract gain typed
runtimemetadata - models with a safe canonical execution lane gain typed
executionmetadata - remaining packaged entries are marked
catalog_only: truerather than forcing downstream consumers to guess
If your project has Igniter available, you can install LLM DB using the command
mix igniter.install llm_dbModel metadata is refreshed regularly, so versions follow CalVer (YYYY.M.Patch with no leading zeros):
def deps do
[
{:llm_db, "~> 2025.11.0"}
]
endA model_spec is a string in one of two formats:
"provider:model"(e.g.,"openai:gpt-4o-mini") — traditional colon format"model@provider"(e.g.,"gpt-4o-mini@openai") — filename-safe format
Both formats are automatically recognized and work interchangeably. Use the @ format when model specs appear in filenames, CI artifact names, or other filesystem contexts where colons are problematic.
Model lookup and parsing also accept tuples such as {:provider_atom, "id"} and {"provider-id", "id"}, but prefer the string spec. String provider IDs are normalized to the canonical provider atom.
{:ok, model} = LLMDB.model("openai:gpt-4o-mini")
#=> %LLMDB.Model{id: "gpt-4o-mini", provider: :openai, ...}
{:ok, model} = LLMDB.model("gpt-4o-mini@openai")
#=> %LLMDB.Model{id: "gpt-4o-mini", provider: :openai, ...}# Get a model and read metadata
{:ok, model} = LLMDB.model("openai:gpt-4o-mini")
model.capabilities.tools.enabled #=> true
model.cost.input #=> 0.15 (per 1M tokens)
model.limits.context #=> 128_000
# Model aliases auto-resolve to canonical IDs
{:ok, model} = LLMDB.model("anthropic:claude-haiku-4.5")
model.id #=> "claude-haiku-4-5-20251001" (canonical ID)
# Select a model by capabilities (returns {provider, id})
{:ok, {provider, id}} = LLMDB.select(
require: [chat: true, tools: true, json_native: true],
prefer: [:openai, :anthropic]
)
{:ok, model} = LLMDB.model({provider, id})
# List providers
LLMDB.providers()
#=> [%LLMDB.Provider{id: :anthropic, ...}, %LLMDB.Provider{id: :openai, ...}]
# Check availability (allow/deny filters)
LLMDB.allowed?("openai:gpt-4o-mini") #=> truemodel/1—"provider:model","model@provider",{:provider, id}, or{"provider", id}→{:ok, %Model{}}|{:error, _}model/2—provideratom +id→{:ok, %Model{}}|{:error, _}models/0— list all models →[%Model{}]models/1— list provider's models →[%Model{}]providers/0— list all providers →[%Provider{}]provider/1— get provider by ID →{:ok, %Provider{}}|:errorselect/1— pick first match by capabilities →{:ok, {provider, id}}|{:error, :no_match}candidates/1— get all matches by capabilities →[{provider, id}]capabilities/1— get capabilities map →map()|nilallowed?/1— check availability →boolean()parse/1,2— parse spec string (both formats) →{:ok, {provider, id}}|{:error, _}parse!/1,2— parse spec string, raising on error →{provider, id}format/1,2— format{provider, id}as string →"provider:model"or"model@provider"build/1,2— build spec string from input, converting between formats →String.t()load/1,load/0— load or reload snapshot with optional runtime overridesload_empty/1— load empty catalog (fallback when no snapshot available)epoch/0,snapshot/0— diagnosticsLLMDB.History.available?/0— history files available in runtimeLLMDB.History.meta/0— history metadata (meta.json)LLMDB.History.timeline/2— lineage-aware events for one modelLLMDB.History.recent/1— most recent events globally (capped)
See the full function docs in hexdocs.
%LLMDB.Provider{
id: :openai,
name: "OpenAI",
base_url: "https://api.openai.com",
env: ["OPENAI_API_KEY"],
doc: "https://platform.openai.com/docs",
runtime: %{
base_url: "https://api.openai.com/v1",
auth: %{type: "bearer", env: ["OPENAI_API_KEY"]},
default_headers: %{},
default_query: %{},
config_schema: [],
doc_url: "https://platform.openai.com/docs/api-reference"
},
catalog_only: false,
extra: %{}
}%LLMDB.Model{
id: "gpt-4o-mini",
provider: :openai,
name: "GPT-4o mini",
family: "gpt-4o",
doc_url: "https://platform.openai.com/docs/models/gpt-4o-mini",
limits: %{context: 128_000, output: 16_384},
cost: %{input: 0.15, output: 0.60},
capabilities: %{
chat: true,
tools: %{enabled: true, streaming: true},
json: %{native: true, schema: true},
streaming: %{text: true, tool_calls: true}
},
execution: %{
text: %{supported: true, family: "openai_chat_compatible"},
object: %{supported: true, family: "openai_chat_compatible"},
embed: nil,
image: nil,
transcription: nil,
speech: nil,
realtime: nil
},
catalog_only: false,
tags: [],
deprecated?: false,
aliases: [],
extra: %{}
}The packaged snapshot loads automatically on the first query. Optional runtime filters, preferences, and custom providers:
# config/runtime.exs
config :llm_db,
filter: %{
allow: :all, # :all or %{provider => [patterns]}
deny: %{openai: ["*-preview"]} # deny patterns override allow
},
prefer: [:openai, :anthropic], # provider preference order
custom: %{
vllm: [
name: "Local vLLM Provider",
base_url: "http://localhost:8000/v1",
models: %{
"llama-3" => %{capabilities: %{chat: true}},
"mistral-7b" => %{capabilities: %{chat: true, tools: %{enabled: true}}}
}
]
}Runtime environment: Starting or querying LLM DB never reads a host .env
file. Applications own their runtime configuration and may use Dotenvy, direnv,
or another mechanism before starting dependencies.
The maintainer-only mix llm_db.pull task loads the repository-local .env
before contacting upstream providers. These settings apply only to that task:
config :llm_db,
load_dotenv: true, # set false to skip .env during metadata pulls
dotenv_override: true # repo credentials override the maintainer shell# Allow all, deny preview/beta models
config :llm_db,
filter: %{
allow: :all,
deny: %{openai: ["*-preview", "*-beta"]}
}
# Allow only specific model families
config :llm_db,
filter: %{
allow: %{
anthropic: ["claude-3-haiku-*", "claude-3.5-sonnet-*"],
openrouter: ["anthropic/claude-*"]
},
deny: %{}
}
# Runtime override (widen/narrow filters without rebuild)
{:ok, _snapshot} = LLMDB.load(
allow: %{openai: ["gpt-4o-*"]},
deny: %{}
)Important: Filters match against canonical model IDs only, not aliases. Use canonical IDs (typically dated versions like claude-haiku-4-5-20251001) in filter patterns. Aliases are resolved during model lookup, after filtering is applied.
Add local or private models to the catalog:
# config/runtime.exs
config :llm_db,
custom: %{
# Provider ID as key
vllm: [
name: "Local vLLM Provider",
base_url: "http://localhost:8000/v1",
env: ["OPENAI_API_KEY"],
doc: "https://docs.vllm.ai",
models: %{
"llama-3-8b" => %{
name: "Llama 3 8B",
family: "llama-3",
capabilities: %{chat: true, tools: %{enabled: true}},
limits: %{context: 8192, output: 2048},
cost: %{input: 0.0, output: 0.0}
},
"mistral-7b" => %{
capabilities: %{chat: true}
}
}
],
myprovider: [
name: "My Custom Provider",
models: %{
"custom-model" => %{capabilities: %{chat: true}}
}
]
}
# Use custom models like any other
{:ok, model} = LLMDB.model("vllm:llama-3-8b")
{:ok, {provider, id}} = LLMDB.select(require: [chat: true], prefer: [:vllm, :openai])If you use LLMDB with ReqLLM, use a provider ID that ReqLLM supports (for local OpenAI-compatible servers, use :vllm) or register your own ReqLLM provider module for custom IDs like :local.
Filter Rules:
- Provider keys: atoms or strings; patterns:
"*"(glob) and~r//(Regex) - Deny wins over allow
- Unknown providers are warned and ignored
- Empty allow map
%{}behaves like:all allow: %{provider: []}blocks provider entirely
See Runtime Filters guide for details and troubleshooting.
Snapshot is shipped with the library. To rebuild with fresh data:
# Fetch upstream data (optional)
mix llm_db.pull
# Build canonical snapshot artifacts
mix llm_db.build
# Install the packaged snapshot for local runtime/package validation
mix llm_db.build --installSnapshot schema v1 remains the packaged and published default. To evaluate the versioned sparse v2 representation side by side without installing it:
mix llm_db.build --schema-version 2See Snapshot Formats and Sparse v2 Rollout for the encoding rules, compatibility contract, measured sizes, and rollout gate.
Migrate legacy Git-tracked metadata history into the snapshot store once:
mix llm_db.history.migrate_git --publishThis writes snapshot-based history artifacts under priv/llm_db/history/ and
materializes immutable historical snapshots under
_build/llm_db/snapshot_store/snapshots/. With --publish, it also seeds the
immutable snapshot releases and publishes the rebuilt history bundle.
After that one-time migration, publish each current snapshot and rebuild history from the published snapshot observation chain:
mix llm_db.snapshot.publish
mix llm_db.history.rebuild --publish
mix llm_db.history.sync
mix llm_db.history.check
mix llm_db.history.check --allow-outdatedmix llm_db.history.backfill and LLMDB.History.Backfill remain functional for
compatibility but are deprecated. They may be removed no earlier than
v2027.0.0, after at least one minor release deprecation window.
For exceptional spec migrations (renames/provider moves that inference cannot match),
add optional lineage overrides in priv/llm_db/history/lineage_overrides.json:
{
"schema_version": 1,
"lineage": {
"openai:gpt-4.1": "openai:gpt-4o"
}
}History artifacts remain optional local/published data.
Hex packages still only ship priv/llm_db/snapshot.json.
See the Sources & Engine guide for details.
Designed to power ReqLLM, but fully standalone. Use model_spec + model/1 to retrieve metadata for API calls.
Important: LLMDB custom provider IDs do not automatically create ReqLLM providers.
- For local OpenAI-compatible servers, use
:vllm. - For arbitrary provider IDs (for example
:local), register a ReqLLM provider module:
defmodule MyApp.ReqLLM.Providers.Local do
use ReqLLM.Provider,
id: :local,
default_base_url: "http://localhost:8080/v1",
default_env_key: "OPENAI_API_KEY"
use ReqLLM.Provider.Defaults
@provider_schema []
end
# config/config.exs
config :req_llm, custom_providers: [MyApp.ReqLLM.Providers.Local]mix setup # Install dependencies and git hooksThis project uses git_hooks to enforce code quality. Hooks install automatically on mix compile in dev:
| Hook | Action |
|---|---|
| commit-msg | Validates conventional commit format |
| pre-commit | Runs mix format --check-formatted |
| pre-push | Runs mix quality (format, compile warnings, dialyzer, credo) |
All commits must follow conventional commit format:
type(scope): description
# Examples:
feat: add new provider support
fix: resolve model lookup edge case
docs: update API documentation
chore: update dependencies
Types: feat, fix, docs, style, refactor, perf, test, build, ci, chore, revert
- API and Support Policy — Stable APIs, extension points, internal modules, and compatibility guarantees
- Using the Data — Runtime API and querying
- Consumer Integration — Best practices for libraries using llm_db
- Runtime Filters — Load-time and runtime filtering
- Sources & Engine — ETL pipeline, data sources, precedence
- Schema System — Zoi validation and data structures
- Model Struct Evolution Proposal — Proposed conditional pricing and richer capability metadata
- Release Process — Snapshot-based releases
Apache-2.0 - see LICENSE file for details.