project-confluence/config.arc.yaml at main · cloudynirvana/project-confluence · GitHub

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# ============================================================
# AutoResearchClaw Config — Project Confluence
# Complexity-Restoring Precision Oncology Research
# ============================================================

project:
  name: "project-confluence"
  mode: "full-auto"

research:
  topic: >-
    Investigate whether the Unified Complexity Profile (UCP) framework,
    using a 5D Phi vector (temporal, spatial, functional, informational,
    coupling), can serve as a universal biomarker for disease severity
    and therapeutic response prediction across cancer types. Specifically,
    test the hypothesis that restoring dynamical complexity (Phi) toward
    healthy attractor states via optimized drug scheduling produces
    superior outcomes compared to traditional maximum-tolerated-dose
    approaches. Use the 15D SAEM ODE system modeling metabolic (10D),
    immune (3D), and microenvironment (2D) dynamics with Michaelis-Menten
    nonlinearities. Validate against pan-cancer profiles: TNBC, PDAC,
    NSCLC, Melanoma, GBM, CRC, HGSOC, mCRPC, AML.
  domains: ["computational-biology", "dynamical-systems", "oncology", "precision-medicine"]
  daily_paper_count: 10
  quality_threshold: 3.5

runtime:
  timezone: "Africa/Lagos"
  max_parallel_tasks: 2
  approval_timeout_hours: 24
  retry_limit: 3

llm:
  provider: "openai-compatible"
  base_url: "https://integrate.api.nvidia.com/v1"
  api_key_env: "NEMOTRON_API_KEY"
  primary_model: "nvidia/llama-3.1-nemotron-70b-instruct"
  fallback_models: ["nvidia/llama-3.1-nemotron-70b-instruct"]
  s2_api_key: ""

experiment:
  mode: "sandbox"
  time_budget_sec: 900
  max_iterations: 10
  metric_key: "phi_distance"
  metric_direction: "minimize"
  sandbox:
    python_path: "python"
    gpu_required: false
    allowed_imports:
      - math
      - random
      - json
      - csv
      - os
      - sys
      - numpy
      - scipy
      - torch
      - sklearn
      - matplotlib
      - pandas
      # Project Confluence modules
      - models.ode_system
      - models.complexity_profiler
      - models.patient_fitter
      - models.drug_optimization_engine
      - models.intervention
      - models.immune_dynamics
      - models.ferroptosis
      - models.coherence
      - models.alphafold_client
      - models.structure_bridge
    max_memory_mb: 4096

export:
  target_conference: "neurips_2025"
  authors: "Ogbonna, Kelechi"
  bib_file: "references"

prompts:
  custom_file: "prompts.confluence.yaml"

security:
  hitl_required_stages: []  # Full auto with --auto-approve
  allow_publish_without_approval: false
  redact_sensitive_logs: true

knowledge_base:
  backend: "markdown"
  root: "docs/kb"

notifications:
  channel: "console"
  target: ""

openclaw_bridge:
  use_cron: false
  use_message: false
  use_memory: true
  use_sessions_spawn: false
  use_web_fetch: true
  use_browser: false