# Experiment 1: LifelongAgent KG with higher max_tokens
# Compare against baseline (max_tokens=1024) where 5/19 samples hit token limit
# Hypothesis: longer output allows complete reasoning chains → higher KG accuracy

[meta]
name = "qwen3.5-122b-kg-hightoken"
description = "LifelongAgent KG with 8192 max_tokens (was 1024)"

[defaults]
temperature = 0.6
max_tokens = 8192          # 8x increase from baseline 1024

[judge]
model = "gpt-5-mini-2025-08-07"
temperature = 0.0
max_tokens = 4096

[run]
max_workers = 1
output_dir = "results/qwen3.5-122b-kg-hightoken/"
seed = 42
telemetry = true
gpu_metrics = true

[[models]]
name = "Qwen/Qwen3.5-122B-A10B-FP8"
engine = "vllm"
param_count_b = 122.0
active_params_b = 10.0
gpu_peak_tflops = 989.5
gpu_peak_bandwidth_gb_s = 3350.0
num_gpus = 4

[[benchmarks]]
name = "lifelong-agent"
backend = "jarvis-direct"
max_samples = 50
subset = "knowledge_graph"
