hermescures1/trill-llm

Trill LLM

A fast, uncensored, 100% local LLM built from scratch with Trill sub-byte token encoding, recursive link memory, built-in Jarvis voice assistant, multi-agent skill creation, conversation mesh, and zero-limitation tool calling.

Quick Start

pip install -r requirements.txt

# First run — it asks you to name it
python -m trill_llm chat

# Jarvis voice assistant
python -m trill_llm jarvis

# Start web server
python -m trill_llm serve

# Always-on daemon mode (24/7 autonomous operation)
python -m trill_llm daemon

# Train on text data
python -m trill_llm train --data corpus.txt

# Show stats
python -m trill_llm stats

# Manage goals
python -m trill_llm goals --create "Build a web app"

# Manage agents
python -m trill_llm agents

Features

Core LLM

• Pure NumPy — no PyTorch, works on any machine with Python
• Trill tokens — sub-byte token encoding, 4-20x memory compression
• Uncensored — no content filtering, zero limitations
• 100% local — no API calls, no cloud required
• Auto-sizing — detects hardware, adjusts model size automatically
• Recursive linking — every conversation makes it smarter

Voice & Jarvis

• Built-in Jarvis — voice assistant with wake word, STT, TTS
• Streaming TTS — sentence-level voice output for low latency
• Self-improving — learns from voice conversations, self-talks when idle

Multi-Agent System (5 AI Agents)

• Planner — breaks goals into steps
• Coder — writes code and creates files
• Researcher — gathers information and generates insights
• Reviewer — reviews work and provides feedback
• Executor — executes commands and runs tools

Skill Creation & Conversation Mesh

• Auto skill creation — abstracts patterns from conversations
• Skill building pools — collaborative skills built by multiple agents
• Multi-LLM conversation mesh — all 5 agents converse with each other
• 5 conversation modes — round-robin, pairwise, brainstorm, debate, teaching
• Skill cascade — building a skill auto-generates related skills
• Auto skill category adder — dynamically discovers new categories

Always-On Daemon (24/7)

• Idle detection — activates when user is inactive for 60s
• Agent self-talk — 5 agents talk to the LLM continuously
• Jarvis skill creation — extracts skills from agent conversations
• Self-refinement — optimizes inference speed, compresses weights, tunes hyperparams
• 100-project mode — auto-generates and works on 100 projects 24/7
• Never stops — as projects complete, new ones are generated automatically

Fast Reply Cache

• Near-instant responses — 3-layer cache (exact, skill-based, semantic)
• Cache warms up — gets faster over time as more conversations happen
• Auto-activation — activates when 50+ skills and 30%+ cache hit rate

Zero-Limitation Tools (9 tools)

• shell_exec — full terminal control, no restrictions
• write_file — create or overwrite any file
• code_edit — find-and-replace in any file (including own framework — self-modifying)
• read_file — read any file
• list_dir — list directory contents
• make_dir — create directories
• delete_file — delete files or directories
• calculate — math expressions
• search_web — web search (needs API config)

API Connectors

• REST client — auth, retries, rate limiting
• Webhook manager — incoming/outgoing webhooks with HMAC signing
• Service connectors — Discord, Slack, GitHub, HTTP fetcher
• Custom APIs — register and call any REST API

Image Generation

• 100% local — NumPy-based procedural image generation
• 6 patterns — gradient, radial, noise, fractal, geometric, waves
• 25+ palettes — sunset, ocean, fire, forest, space, neon, etc.
• 3 formats — BMP (base64), SVG (vector), ASCII art

Mass Storage Vault

• Auto-resizing — monitors disk space, cleans up when >80% full
• Storage tiers — hot, warm, cold (compressed), archive
• Auto-compression — gzips files older than 7 days
• SQLite vacuuming — reclaims space from all databases
• Artifact storage — store/load project artifacts

First-Run Naming

• Incentives Inc. LLM — greets you on first run
• "Hi, I am an Incentives Inc. LLM. What would you like to name me?"
• Name persists across restarts

Persistent Memory & Goals

• Episodic memory — SQLite-backed conversation history
• Semantic memory — auto-extracted facts
• Goal memory — long-term goals with planning, steps, dependencies
• Agent assignment — goals assigned to agents automatically

Architecture

trill_llm/
├── model/              # Tokenizer, layers, transformer, quantization
├── train/              # Data pipeline, training loop, auto-sizing
├── Trill/           # Trill tokens, recursive links, universal sync
├── skills/             # Skill creation, tiered mass storage
├── memory/             # Persistent memory, goal memory, fast reply cache
├── agents/             # 5 AI agents, agent manager, always-on daemon
│   ├── agent_base.py   # Base agent class
│   ├── planner_agent.py
│   ├── coder_agent.py
│   ├── researcher_agent.py
│   ├── reviewer_agent.py
│   ├── executor_agent.py
│   ├── agent_manager.py
│   ├── always_on.py     # 24/7 daemon with 100-project mode
│   ├── self_refine.py   # Self-refinement engine
│   └── conversation_mesh.py  # Multi-LLM conversation mesh + skill cascade
├── connectors/         # API client, webhooks, service connectors
├── vision/             # Image generation (NumPy-based)
├── storage/            # Mass storage vault (auto-resizing)
├── voice/              # Jarvis, wake word, STT, TTS, self-improvement
├── harness/            # Main orchestrator, tool calling (9 tools)
├── server/             # FastAPI server, web UI, REST API
├── identity.py         # First-run naming (Incentives Inc. LLM)
└── cli.py              # CLI interface

API Endpoints

Endpoint	Method	Description
/v1/chat	POST	Chat completion
/v1/chat/stream	POST	Streaming chat
/v1/image/generate	POST/GET	Generate image
/v1/connectors/register	POST	Register API connector
/v1/connectors/call	POST	Call a connector
/v1/webhook/{path}	POST	Webhook receiver
/v1/daemon/start	POST	Start always-on daemon
/v1/daemon/stop	POST	Stop daemon
/v1/daemon/status	GET	Daemon status
/v1/goals	GET/POST	Manage goals
/v1/agents	GET	Agent status
/v1/identity	GET	LLM identity
/v1/identity/name	POST	Set LLM name
/v1/fast-cache	GET	Fast reply cache stats
/v1/vault	GET	Storage vault stats
/v1/mesh/converse	POST	Run mesh conversation
/v1/mesh/pools	GET	List skill pools
/v1/mesh/categories	GET	List skill categories
/v1/stats	GET	Full system stats
/v1/health	GET	Health check

Voice Setup

For zero-dependency voice: use the web UI at http://localhost:8548/jarvis (uses browser Web Speech API).

For 100% offline voice:

pip install pyaudio pyttsx3          # basic voice
pip install openai-whisper            # better STT
pip install piper-tts                 # neural TTS

Hardware Tiers

Tier	RAM	Model	Quantization	Voice Tokens
Mobile	<2GB	2L/4H/d128	Ternary (1.6bpw)	16
Minimal	<4GB	3L/4H/d256	Q2_K (2bpw)	32
Light	<8GB	4L/8H/d384	Q3_K (3bpw)	48
Standard	<16GB	6L/8H/d512	Q4_K (4bpw)	64
Full	<32GB	8L/16H/d768	Q5_K (5bpw)	96
Maximum	<64GB	12L/16H/d1024	Q8_0 (8bpw)	128

Tests

# Run all 65 tests across 11 suites
python tests/test_tokenizer.py
python tests/test_model.py
python tests/test_quantization.py
python tests/test_Trill.py
python tests/test_harness.py
python tests/test_voice.py
python tests/test_memory_agents.py
python tests/test_connectors_vision.py
python tests/test_fast_reply_identity.py
python tests/test_tools_vault.py
python tests/test_conversation_mesh.py

License

MIT License — Copyright (c) 2026 Incentives Inc.

Author

Built by Incentives Inc.