ReqLLM and LLMDB

Provider-agnostic LLM HTTP client and model metadata database for the Jido ecosystem.

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req_llm and llmdb are standalone packages maintained alongside Jido. They work independently of the agent framework — you can use them in any Elixir project — but they form the LLM infrastructure layer that jido_ai builds on.

ReqLLM

A Req plugin that provides a unified interface for calling LLM APIs across providers. Instead of writing provider-specific HTTP code, you configure a model string like "anthropic:claude-sonnet-4-20250514" or "openai:gpt-4o" and ReqLLM handles the rest.

What it handles:

  • Provider abstraction — one API for Anthropic, OpenAI, Google, Mistral, Groq, Ollama, and others
  • Automatic retries — configurable retry logic with exponential backoff for transient failures
  • Rate limiting — built-in rate limit handling with provider-specific backoff
  • Streaming — unified streaming interface across providers that support SSE
  • Request/response normalization — consistent message format regardless of provider quirks

Basic usage:

# Add to mix.exs
{:req_llm, "~> 0.3"}

# Make a request
req = Req.new() |> ReqLLM.attach()

{:ok, response} = ReqLLM.chat(req,
  model: "anthropic:claude-sonnet-4-20250514",
  messages: [%{role: "user", content: "Hello"}]
)

In the Jido ecosystem, jido_ai uses ReqLLM under the hood for all LLM communication. Model aliases like :fast and :capable resolve to ReqLLM model strings. See Configuration for alias setup.

→ ReqLLM HexDocs · GitHub

LLMDB

A model metadata database that tracks capabilities, pricing, context window sizes, and feature support across LLM providers. Available as both an Elixir library and a web interface at llmdb.xyz.

What it provides:

  • Model lookup — query models by provider, capability, or feature support
  • Context limits — max input tokens, max output tokens, and context window sizes
  • Pricing data — per-token costs for input and output across providers
  • Feature flags — which models support tool calling, vision, streaming, JSON mode, etc.
  • Regularly updated — model data is maintained as the provider landscape changes

Basic usage:

# Add to mix.exs
{:llmdb, "~> 0.1"}

# Look up a model
model = LLMDB.get("anthropic:claude-sonnet-4-20250514")
model.context_window   #=> 200_000
model.max_output        #=> 64_000

# Find models by capability
LLMDB.list(provider: :anthropic, supports: :tool_calling)

In the Jido ecosystem, LLMDB provides the model metadata that jido_ai uses when resolving aliases and validating token budgets.

→ LLMDB web interface · GitHub

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