Multi-Agent LLM Research Demo¶

examples/03_llm_research demonstrates a multi-agent A2A server with two streaming research agents and one evaluator agent. It includes both a CLI client and a Sinatra web client.

What it runs¶

Path	Agent	Model
`http://localhost:9292/anthropic`	`AnthropicResearchAgent`	`claude-sonnet-4-6`
`http://localhost:9292/openai`	`OpenAIResearchAgent`	`gpt-5.4`
`http://localhost:9292/evaluator`	`EvaluatorAgent`	`claude-sonnet-4-6`
`http://localhost:4567`	Sinatra web UI	Streams both responses and the evaluation to the browser

Files¶

File	Purpose
`examples/03_llm_research/server.rb`	Configures RubyLLM, defines three executors, and starts a path-routed multi-agent A2A server
`examples/03_llm_research/client.rb`	CLI client that queries both research agents in parallel and sends both responses to the evaluator
`examples/03_llm_research/web_client.rb`	Sinatra UI that streams both research responses and the evaluator response to the browser
`examples/03_llm_research/run`	Lifecycle script that starts the A2A server and web client together

Setup¶

The demo uses LLM and web UI libraries that are intentionally not runtime dependencies of the simple_a2a gem. Add them to your local bundle before running the demo:

bundle add ruby_llm async-http-faraday sinatra

Set both provider keys:

export ANTHROPIC_API_KEY=your_key_here
export OPENAI_API_KEY=your_key_here

Run the web demo¶

From the repository root:

bundle exec ruby examples/run 03_llm_research

The custom runner starts:

Service	URL
A2A multi-agent server	`http://localhost:9292`
Web client	`http://localhost:4567`

Open http://localhost:4567, enter a topic, and the page streams output from both research agents followed by the evaluator.

Run the CLI client¶

Start the multi-agent server:

bundle exec ruby examples/03_llm_research/server.rb

Then run the CLI client from another terminal:

bundle exec ruby examples/03_llm_research/client.rb "compare the practical tradeoffs of A2A and MCP"

If no topic is supplied, the client uses its built-in default topic.

Server design¶

The server uses A2A.multi_server to mount multiple agents under one Falcon process:

A2A.multi_server(
  agents: {
    "/anthropic" => { agent_card: anthropic_card, executor: AnthropicResearchExecutor.new },
    "/openai"    => { agent_card: openai_card,    executor: OpenAIResearchExecutor.new },
    "/evaluator" => { agent_card: evaluator_card, executor: EvaluatorExecutor.new }
  },
  port: 9292
).run

Each executor includes a shared streaming helper that calls RubyLLM and emits TaskArtifactUpdateEvent chunks while the model response arrives.

Web client design¶

The web client exposes a browser-facing SSE endpoint at /research. Internally it opens A2A SSE subscriptions to the Anthropic and OpenAI agents in parallel, buffers both complete responses, then streams the evaluator response back to the browser.

This is useful as a reference for bridging A2A streaming into another application protocol while keeping the A2A agents independently addressable.