magi-code 0.96.2

Repository-aware CLI coding agent for terminal work
Documentation 
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use super::bodies::openai_compatible_chat_completions_body;
use super::*;
use crate::providers::{ChatMessage, ProviderConversationItem, ProviderToolResult};
use serde_json::json;

#[test]
#[ignore = "diagnostic-only optimization measurement; run explicitly with --ignored --nocapture"]
fn optimization_harness_measures_large_chat_body_construction() {
    // Large count is fixture data for optimization measurement, not a runtime ceiling.
    let tool_pair_count = 2_000;
    let mut items = vec![ProviderConversationItem::Message(ChatMessage::user(
        "measure body construction",
    ))];
    for index in 0..tool_pair_count {
        items.push(ProviderConversationItem::ResponseItem(json!({
            "type": "function_call",
            "call_id": format!("call_{index}"),
            "name": "read",
            "arguments": {"path": format!("fixtures/{index}.txt")},
            "status": "completed"
        })));
        items.push(ProviderConversationItem::ToolResult(ProviderToolResult {
            call_id: format!("call_{index}"),
            tool_name: "read".to_string(),
            success: true,
            output: format!("file contents {index}"),
            skill_reads: Vec::new(),
        }));
    }
    let request = ProviderRequest::from_conversation("model-a", items);

    let started = std::time::Instant::now();
    let body = openai_compatible_chat_completions_body("model-a", &request);
    let elapsed = started.elapsed();
    let messages = body["messages"].as_array().unwrap();

    println!(
        "optimization_harness chat_body tool_pairs={} messages={} elapsed={elapsed:?}",
        tool_pair_count,
        messages.len()
    );
    assert_eq!(messages.len(), 1 + tool_pair_count * 2);
}