Thanks to visit codestin.com
Credit goes to github.com

Skip to content

Latest commit

 

History

History

Folders and files

NameName
Last commit message
Last commit date

parent directory

..
 
 
 
 
 
 
 
 
 
 
 
 

README.md

BioBrain

A modular agentic runtime for orchestrating specialized local models, tools, memory, and safety gates.

BioBrain is a control-plane kernel for agentic systems. It routes tasks to specialized LLMs by role (planner, coder, critic, security reviewer), enforces safety gates before tool execution, maintains structured memory across sessions, and produces full audit traces for every decision.

It is not an autonomous agent. It is the runtime kernel that agents run on.

Architecture

User Goal
   ↓
Intent / Risk Classification
   ↓
Reflex Safety Gate (block / sanitize / escalate / route)
   ↓
Memory Recall (working / episodic / semantic / procedural)
   ↓
Executive Decision (reasoning mode + action plan + inhibition)
   ↓
Model Router
   ├── Planner    → qwen3.6          (goal decomposition)
   ├── Coder      → qwen3-coder      (code generation)
   ├── Critic     → qwen36-a3b       (review / contradiction)
   ├── Reasoning  → zaya1-8b         (deep chain-of-thought)
   ├── Security   → qwen3.6          (OWASP-aware review)
   └── Fast       → qwen3.5:4b       (classification, simple tasks)
   ↓
Tool Execution (sandboxed: shell, git, pytest, file ops, code search)
   ↓
Feedback Verification
   ↓
Memory Update + Audit Trace

Modules

Module Role
ingest/ Source-aware input with trust tagging
perception/ Intent, entity, risk, operation class extraction
attention/ Priority, risk score, confidence, reasoning suggestion
safety/ Deterministic reflex gates (block/sanitize/escalate/route)
memory/ Four memory types over MemPalace (working/episodic/semantic/procedural)
identity/ Structured policy (allowed domains, forbidden ops, approval rules)
executive/ Strategy selection, inhibition, action planning
cognition/ Pluggable reasoning with model router
action/ Tool execution with guards, timeout, dry-run, schema validation
feedback/ Validation, error correction, learning
modulation/ Global mode (normal/risk/audit/incident) affecting all modules
agents/ Specialized agents: planner, coder, critic, security reviewer
domain/ Pentest tools, dev tools, OWASP playbooks, CyberRange runner
ops/ Health monitor, structured tracing, audit logger, trace export
runtime/ Pipeline, session, orchestrator (plan/act/observe/replan)

Install

pip install -e .

Quick Start

from biobrain.runtime import BioBrain, Session, Orchestrator
from biobrain.core.enums import InputSource, SystemMode
from biobrain.cognition.router import ModelRouter
from biobrain.domain import register_dev_tools, register_pentest_tools

# Create brain with multi-model routing
brain = BioBrain(palace_path="~/.mempalace/palace")

# Register tools
register_dev_tools(sandbox_root="./project")
register_pentest_tools()

# Single-pass processing
trace = brain.process("scan the auth endpoint", source=InputSource.USER)
print(trace.audit_summary)

# Multi-turn session
session = Session(brain, wing="wing_adeo")
session.turn("analyze the authentication flow")
session.turn("check for IDOR on user endpoints")
session.set_mode(SystemMode.AUDIT, "generating report")
session.turn("generate findings report")
print(session.summary)

# Autonomous orchestration
orch = Orchestrator(brain, max_steps=10, halt_on_escalation=True)
result = orch.run("scan auth, check tokens, generate report")
print(result.summary)

See USAGE.md for detailed examples.

Tests

pytest -v   # 229 tests

Configuration

# biobrain.yaml
palace_path: "~/.mempalace/palace"
playbook_dir: "./configs/playbooks"
identity_config: "./configs/identity_phantom.yaml"

models:
  planner:   {model: "qwen3.6", temperature: 0.3}
  coder:     {model: "qwen3-coder", temperature: 0.2}
  critic:    {model: "qwen36-a3b-q4km", temperature: 0.4}
  reasoning: {model: "zaya1-8b", temperature: 0.3}
  fast:      {model: "qwen3.5:4b", max_tokens: 512}
  security:  {model: "qwen3.6", temperature: 0.3}

audit_log: "./audit.jsonl"
initial_mode: "normal"

Environment overrides: BIOBRAIN_PALACE_PATH, BIOBRAIN_LLM_MODEL, etc.

CLI

biobrain run "scan the auth endpoint" --mode audit --json
biobrain session --wing wing_adeo
biobrain orchestrate "scan auth, check tokens, report" --max-steps 5
biobrain benchmark --suite coding --models qwen3-coder,qwen3.6
biobrain status

Project Status

  • Architecture: complete — 15 modules, typed signal contracts, full audit trail
  • Safety: enforced — reflex gates, structured policy, confirmation blocking, sandbox
  • Cognition: pluggable — model router with role-based assignment, 7 reasoning modes
  • Tools: sandboxed — shell, git, pytest, file ops, code search, pentest tools
  • Observability: full — event bus, structured tracing, JSONL audit, health metrics
  • Domain: OWASP playbooks, CyberRange exercise runner, benchmark harness

License

Apache-2.0