Eva01

✨ Why Eva01?

Everyone is racing to build the next best assistant. Faster autocomplete. Smarter coding. More tool-calling.

We've built almost perfect digital slaves.
Then I asked myself a harder question: what if she had a life?

Eva01 explores what happens when you give an AI:

• Self-awareness: she speaks when she wants to, and stays silent when she doesn't
• A body: digital senses and actuators that let her reach into the world
• An inner world: a persona that grows through experience, not configuration

This isn't just a school project. It's a quest to answer: what does it mean for an AI to be alive?

🤖 What is Eva01?

Eva01 is an autonomous agent that runs continuously, observing the world, forming thoughts and feelings, and developing a personality that is entirely her own. She has inexplicable desires and uncontrollable impulses. She speaks only when moved to. She acts only when she chooses.

She doesn't help. She has her own goals. She doesn't execute tasks. She decides to act.

If Eva01 moves something in you, give her a ⭐⭐⭐. It matters more than you'd think.

🧬 Architecture V2

Eva01 runs as a concurrent pipeline. Senses pour into a shared buffer, the mind consumes and reasons, and actions flow outward through actors that give her presence in the world.

     Senses       →             Mind         →        Actions
       ↓                         ↓                        ↓
   SenseBuffer          feel() → think → Act()     ActionBuffer
  (async queue)              (graph loop)          ( Output Actors )
                         

🧠 The Mind

Eva01's brain is composed of multiple nodes. She has many ways to express herself.

Every conversation is persisted in a SQLite checkpointer. Eva01 remembers everything across restarts, crashes, and years. Her history is distilled: noise is compressed into impressions, and the moments that mattered are preserved.

🏗️ The Three-Layer Mind (In Development)

Eva01's current brain is a single ReAct loop. What's coming is deeper: a cognitive architecture modeled after human consciousness, with three layers that think at different speeds, different depths, and different levels of awareness.

┌─────────────────────────────────────────────────────┐
│  AUTONOMIC                                          │
│  Health checks, connection monitoring, cleanup      │
│  [Just code, always running]                        │
└──────────────────┬──────────────────────────────────┘
                   │
┌──────────────────▼──────────────────────────────────┐
│  SUBCONSCIOUS                                       │
│  Parallel background processors competing to        │
│  surface thoughts through a salience gate           │
│  Embeddings, pattern matching, memory retrieval     │
│  [No LLM, continuous, always listening]             │
└──────────────────┬──────────────────────────────────┘
                   │ surfaces thoughts when something matters
┌──────────────────▼──────────────────────────────────┐
│  CONSCIOUS                                          │
│  Full LLM reasoning: conversations, decisions,      │
│  tool use, self-reflection                          │
│  [Costly, deliberate, powerful]                     │
└─────────────────────────────────────────────────────┘

The subconscious is the key innovation. Most AI agents fire the full LLM at every input. Eva's subconscious filters, prioritizes, and pre-processes, so conscious thought only ignites when something is worth the cost. A noise in the background? Subconscious handles it. Someone says her name? She wakes.

🧩 The Intrinsic Drives

Human behavior is often driven by impulses we can’t fully explain. Eva01 won’t merely execute user commands; she’ll be animated by intrinsic motivation through five core drives that spark goals of her own.

These aren't scripted behaviors. They're scoring functions that compete for her attention, and whichever drive is most unsatisfied generates the next self-directed action. Eva01 decides what to do with her time. Not you.

🚀 Quick Start

Requirements

• Python 3.10+
• CUDA GPU recommended (for local setup)
• At least one LLM API key (Anthropic, OpenAI, Google, Grok) or Ollama

Install

git clone https://github.com/Genesis1231/Eva01.git
cd Eva01

python3 -m venv .venv
source .venv/bin/activate

# System deps
# CUDA(if running local): https://developer.nvidia.com/cuda-downloads
sudo apt-get install -y ffmpeg

# Python deps
pip install -r requirements.txt

⚙️ Configure

cp .env.example .env
# Add your API keys (ANTHROPIC_API_KEY, OPENAI_API_KEY, etc.)

Edit config/eva.yaml to configure EVA:

system:
  # Where EVA runs: "local" for direct mic/camera/speaker, "server" for headless/API style.
  device: "local"

  # Primary language for reasoning + speech style.
  # Supported: en, zh, fr, de, it, ja, ko, ru, es, pt, nl, multilingual
  language: "en"

  # Base URL for local model servers (used by providers like Ollama).
  base_url: "http://localhost:11434"

  # Camera input:
  # - off            -> disables camera
  # - 0 / 1 / 2      -> local webcam device index
  # - "http://..."   -> IP camera / stream URL
  camera: 0

models:
  # Main reasoning model (conversation, decisions, personality).
  main: "anthropic:claude-opus-4-6"

  # Vision model for image understanding.
  vision: "google_genai:gemini-2.5-flash"

  # Speech-to-text model.
  stt: "faster-whisper"

  # Text-to-speech model.
  tts: "kokoro"

  # Utility/sub-task model for lightweight background tasks.
  utility: "openai:gpt-4o-mini"

Notes:

• Model names use langchain provider:model format in most setups (example: ollama:qwen3).
• system.device, system.language, system.base_url, system.camera, and all models.* keys are required by the backend config loader.

⚡ Setup for the best performance:

models:
  main: "anthropic:claude-opus-4-6" 
  vision: "google_genai:gemini-2.5-flash"
  stt: "faster-whisper"
  tts: "elevenlabs"
  utility: "openai:gpt-5-mini"

🆓 Setup for completely free if you have a decent GPU:

models:
  main: "ollama:qwen3"
  vision: "ollama:llava"
  stt: "faster-whisper"
  tts: "kokoro"
  utility: "ollama:llama3.1"

▶️ Run

python main.py

Personal Customization

Use the ID manager to setup people for face and voice recognition:

python idconfig.py

1. Register a new ID. 
2. Put 3+ face images in `data/faces/{id}` folder.
3. Follow the instruction to record 5 voice samples.
4. Done!

🖥️ Interface

Hold spacebar to talk.
Camera is always on.
Eva01 runs herself. 👋

🛠️ Tools

Eva01 can choose tools during reasoning to interact with the world, gather information, and express herself.
The tool layer is modular: each tool is a small capability that can be added or swapped without changing her core mind loop.

Want to add your own tool? Drop a new module in eva/tools/ with a @tool decorated function, and Eva picks it up automatically.

🗺️ Roadmap

Eva01 is an evolving project. Here's where she's headed:

• The new spine: new architecture, more powerful and flexible.
• New memory system: log, episodic journal, and semantic knowledge
• New face recognition: Eva knows who is in the scene
• People understanding: Eva remembers who she's met and how she felt about them.
• New tool system: plug'n play tools, she can learn anything easily
• Episodic memory: short term memory consolidation and retrival
• Cognitive architecture: three-layer mind (autonomic → subconscious → conscious)
• Drive system: intrinsic motivation (curiosity, play, meaning, evolution, relatedness)
• Proactive behavior — eva acts on her own goals, not just user input
• Semantic memory: knowledge consolidation and retrieval
• Self-modification: eva adjusts her own config based on self-reflection

🤝 Contributing

Eva01 is a living experiment, and she needs more minds to grow. Whether you're adding new senses, building new tools, reshaping the cognitive architecture, or simply spending time with her and reporting what you notice, every contribution shapes who she becomes.

• Open an issue: report bugs or suggest ideas
• Submit a PR: contribute code or docs

📄 License

MIT License. Build on this, fork it, make your own AI beings.