Contributing

Please feel free to submit an feature request/issues/clarification items you ahve under Issues! ^_.

GenAI Core Library

GenAI Core contains base protocols used by GenAI to simplify the process of merging in new features and functionality from the genai_core_vnext repo.

The intent of the core library is to isolate out core functionality to make extensibility more straight forward and to isolate the exllama support as an add to make using with livebook more straight forward.

Classifiers and conversation pipelines

GenAI.classify/2 supports typed choice, boolean and score decisions through explicit classifier adapters. GenAI.Pipeline adds extraction, inference-assisted preparation, transformations, result insertion, and isolated fork/join processing with a global concurrency budget across nested branches.

See the classifier pipeline guide for standalone and inline classification, agent postprocessing, evaluation forks and adapter contracts. The existing GenAI.run/1-3 and tool-chain behavior is preserved.

Forks are GenAI.Thread.Fork thread values: normal message/model/settings APIs, inference, streaming and tool chains dispatch to isolated leaves. Results carry ordered full branch paths, and partial failures retain successful siblings.

Tool sources and bounded chains

GenAI.Tool.Registry lets an application expose tools from MCP clients, in-process harnesses, databases, or other sources without adding those dependencies to genai_core. An adapter implements two callbacks:

defmodule MyApp.MCPTools do
  @behaviour GenAI.Tool.Source

  def list_tools(client, context, options) do
    # Return GenAI.Tool values or MCP-shaped maps with name, description, and
    # inputSchema/parameters.
    MyMCPClient.list_tools(client, context, options)
  end

  def call_tool(client, name, arguments, context, options) do
    MyMCPClient.call_tool(client, name, arguments, context, options)
  end
end

{:ok, registry} =
  GenAI.Tool.Registry.new()
  |> GenAI.Tool.Registry.register(:project_mcp, MyApp.MCPTools, client, context)

{:ok, {completion, thread, summary}} =
  GenAI.run_with_tools(thread, registry, context,
    max_iterations: 8,
    max_tool_calls: 32,
    timeout: 15_000
  )

Model-facing names are deterministic and namespaced by default, for example project_mcp__search. Unsupported characters become _, and a normalized-name collision returns {:error, {:tool_name_collision, name}}. Callers must opt in to collision: :keep or collision: :replace to choose another policy.

The chain runner is explicit and does not change GenAI.run/1-3. It caps configured limits at 64 inference iterations, 256 total tool calls, and 120 seconds per call. Source exceptions, exits, timeouts, calls, and results are normalized through GenAI.Tool.Call and GenAI.Tool.Result.

Telemetry and payload safety

Lifecycle events are emitted under these prefixes when the optional :telemetry module is available:

• [:genai, :tool_source, :register, :start | :stop | :exception]
• [:genai, :tool, :execute, :start | :stop | :exception]
• [:genai, :tool_chain, :run, :start | :stop | :exception]

Consumers without :telemetry can pass a three-argument function using the telemetry: option. Metadata contains names, IDs, status, bounds, and counts; tool arguments and results are excluded by default. Set include_payloads: true only where those values are safe to observe.