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<h1 id="adr-006-rig-framework-para-llm-agent-orchestration"><a class="header" href="#adr-006-rig-framework-para-llm-agent-orchestration">ADR-006: Rig Framework para LLM Agent Orchestration</a></h1>
<p><strong>Status</strong>: Accepted | Implemented
<strong>Date</strong>: 2024-11-01
<strong>Deciders</strong>: LLM Architecture Team
<strong>Technical Story</strong>: Selecting Rust-native framework for LLM agent tool calling and streaming</p>
<hr />
<h2 id="decision"><a class="header" href="#decision">Decision</a></h2>
<p>Usar <strong>rig-core 0.15</strong> para orquestación de agentes LLM (no LangChain, no SDKs directos de proveedores).</p>
<hr />
<h2 id="rationale"><a class="header" href="#rationale">Rationale</a></h2>
<ol>
<li><strong>Rust-Native</strong>: Sin dependencias Python, compila a binario standalone</li>
<li><strong>Tool Calling Support</strong>: First-class abstraction para function calling</li>
<li><strong>Streaming</strong>: Built-in streaming de respuestas</li>
<li><strong>Minimal Abstraction</strong>: Wrapper thin sobre APIs de proveedores (no over-engineering)</li>
<li><strong>Type Safety</strong>: Schemas automáticos para tool definitions</li>
</ol>
<hr />
<h2 id="alternatives-considered"><a class="header" href="#alternatives-considered">Alternatives Considered</a></h2>
<h3 id="-langchain-python-bridge"><a class="header" href="#-langchain-python-bridge">❌ LangChain (Python Bridge)</a></h3>
<ul>
<li><strong>Pros</strong>: Muy maduro, mucho tooling</li>
<li><strong>Cons</strong>: Requiere Python runtime, complejidad de IPC</li>
</ul>
<h3 id="-direct-provider-sdks-claude-openai-etc"><a class="header" href="#-direct-provider-sdks-claude-openai-etc">❌ Direct Provider SDKs (Claude, OpenAI, etc.)</a></h3>
<ul>
<li><strong>Pros</strong>: Control total</li>
<li><strong>Cons</strong>: Reimplementar tool calling, streaming, error handling múltiples veces</li>
</ul>
<h3 id="-rig-framework-chosen"><a class="header" href="#-rig-framework-chosen">✅ Rig Framework (CHOSEN)</a></h3>
<ul>
<li>Rust-native, thin abstraction</li>
<li>Tool calling built-in</li>
<li>Streaming support</li>
</ul>
<hr />
<h2 id="trade-offs"><a class="header" href="#trade-offs">Trade-offs</a></h2>
<p><strong>Pros</strong>:</p>
<ul>
<li>✅ Rust-native (no Python dependency)</li>
<li>✅ Tool calling abstraction reducida</li>
<li>✅ Streaming responses</li>
<li>✅ Type-safe schemas</li>
<li>✅ Minimal memory footprint</li>
</ul>
<p><strong>Cons</strong>:</p>
<ul>
<li>⚠️ Comunidad más pequeña que LangChain</li>
<li>⚠️ Menos ejemplos/tutorials disponibles</li>
<li>⚠️ Actualización menos frecuente que alternatives</li>
</ul>
<hr />
<h2 id="implementation"><a class="header" href="#implementation">Implementation</a></h2>
<p><strong>Agent with Tool Calling</strong>:</p>
<pre><pre class="playground"><code class="language-rust"><span class="boring">#![allow(unused)]
</span><span class="boring">fn main() {
</span>// crates/vapora-llm-router/src/providers.rs
use rig::client::Client;
use rig::completion::Prompt;
let client = rig::client::OpenAIClient::new(&amp;api_key);
// Define tool schema
let calculate_tool = rig::tool::Tool {
name: "calculate".to_string(),
description: "Perform arithmetic calculation".to_string(),
schema: json!({
"type": "object",
"properties": {
"expression": {"type": "string"}
}
}),
};
// Call with tool
let response = client
.post_chat()
.preamble("You are a helpful assistant")
.user_message("What is 2 + 2?")
.tool(calculate_tool)
.call()
.await?;
<span class="boring">}</span></code></pre></pre>
<p><strong>Streaming Responses</strong>:</p>
<pre><pre class="playground"><code class="language-rust"><span class="boring">#![allow(unused)]
</span><span class="boring">fn main() {
</span>// Stream chunks as they arrive
let mut stream = client
.post_chat()
.user_message(prompt)
.stream()
.await?;
while let Some(chunk) = stream.next().await {
match chunk {
Ok(text) =&gt; println!("{}", text),
Err(e) =&gt; eprintln!("Error: {:?}", e),
}
}
<span class="boring">}</span></code></pre></pre>
<p><strong>Key Files</strong>:</p>
<ul>
<li><code>/crates/vapora-llm-router/src/providers.rs</code> (provider implementations)</li>
<li><code>/crates/vapora-llm-router/src/router.rs</code> (routing logic)</li>
<li><code>/crates/vapora-agents/src/executor.rs</code> (agent task execution)</li>
</ul>
<hr />
<h2 id="verification"><a class="header" href="#verification">Verification</a></h2>
<pre><code class="language-bash"># Test tool calling
cargo test -p vapora-llm-router test_tool_calling
# Test streaming
cargo test -p vapora-llm-router test_streaming_response
# Integration test with real provider
cargo test -p vapora-llm-router test_agent_execution -- --nocapture
# Benchmark tool calling latency
cargo bench -p vapora-llm-router bench_tool_response_time
</code></pre>
<p><strong>Expected Output</strong>:</p>
<ul>
<li>Tools invoked correctly with parameters</li>
<li>Streaming chunks received in order</li>
<li>Agent executes tasks and returns results</li>
<li>Latency &lt; 100ms per tool call</li>
</ul>
<hr />
<h2 id="consequences"><a class="header" href="#consequences">Consequences</a></h2>
<h3 id="developer-workflow"><a class="header" href="#developer-workflow">Developer Workflow</a></h3>
<ul>
<li>Tool schemas defined in code (type-safe)</li>
<li>No Python bridge debugging complexity</li>
<li>Single-language stack (all Rust)</li>
</ul>
<h3 id="performance"><a class="header" href="#performance">Performance</a></h3>
<ul>
<li>Minimal latency (direct to provider APIs)</li>
<li>Streaming reduces perceived latency</li>
<li>Tool calling has &lt;50ms overhead</li>
</ul>
<h3 id="future-extensibility"><a class="header" href="#future-extensibility">Future Extensibility</a></h3>
<ul>
<li>Adding new providers: implement <code>LLMClient</code> trait</li>
<li>Custom tools: define schema + handler in Rust</li>
<li>See ADR-007 (Multi-Provider Support)</li>
</ul>
<hr />
<h2 id="references"><a class="header" href="#references">References</a></h2>
<ul>
<li><a href="https://github.com/0xPlaygrounds/rig">Rig Framework Documentation</a></li>
<li><code>/crates/vapora-llm-router/src/providers.rs</code> (provider abstractions)</li>
<li><code>/crates/vapora-agents/src/executor.rs</code> (agent execution)</li>
</ul>
<hr />
<p><strong>Related ADRs</strong>: ADR-007 (Multi-Provider LLM), ADR-001 (Workspace)</p>
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