⚡ answerr — Zero-Latency Reflex AI & Decision Workspace

Adaptive Non-tensor Signal Wave & Error Reflex Resonator
"When you need natural dialogue, call answerr.
When you need microsecond reflexes, embed werr."
"Don't just chat. Get the Answerr!"

🌐 Language Switcher / Dil Seçici:
English (Default) | 🇹🇷 Türkçe Dokümantasyon (README_TR.md)

🌟 Overview

answerr is a next-generation Dual-Cognition AI platform that bridges the divide between human conversational reasoning and deterministic, zero-latency software execution:

System-Two Deliberation (LLM / Cloud AI): Ingests conversational dialogue, extracts operational state vectors, synthesizes strategic explanations, and generates production code. Integrates seamlessly with Google Gemini 2.5 Flash and OpenAI-compatible pipelines.
System-One Reflex Arc (werr): Derives instant, strongly-typed decisions (noul, choice, score) in $< 0.5$ ms with 0 Bytes of VRAM via Mandelbrot fractal escape boundary dynamics ($\partial \mathcal{M}$).
On-Chain EVM Decision Oracle (werracle): Extends System-One reflex decisions to Web3 smart contracts in a single 32-byte storage slot (~20k gas) for intra-block flash-loan defense and dynamic fee governance.

Instead of forcing heavy 70B+ parameter neural networks to spend thousands of milliseconds and hundreds of tokens evaluating routine boolean gates, routing conditions, or security checks, answerr delegates execution triage to the zero-tensor mathematical geometry of the Mandelbrot set.

⚡ The Dual-Cognition Architecture

                           [ Operational Signal / User Prompt ]
                                            │
                                            ▼
                       ┌──────────────────────────────────────────┐
                       │     System-Two: Deliberative Parsing     │
                       │         (Natural Dialogue & Context)     │
                       └────────────────────┬─────────────────────┘
                                            │
               Extracts Structured State Vector & Typed Question Template
                          (client_role, req_rate, auth, target)
                                            │
                                            ▼
                       ┌──────────────────────────────────────────┐
                       │    System-One: werr Geometric Reflex     │
                       │    0-Byte VRAM • < 0.5 ms Kernel Exec    │
                       └────────────────────┬─────────────────────┘
                                            │
                     Evaluates Mandelbrot Boundary Escape Dynamics (∂M)
                     - noul: Strongly-Typed Boolean (ALLOWED / DENIED)
                     - choice: Discrete Route Partition (Q1 ~ Q4)
                     - score: Continuous Severity / Priority Rank
                                            │
                                            ▼
                       ┌──────────────────────────────────────────┐
                       │       System-Two Synthesis & Code        │
                       │      Smart If-Statement & Telemetry      │
                       └────────────────────┬─────────────────────┘
                                            │
                                            ▼
                 [ answerr.me Live Workspace & Real-Time Telemetry HUD ]

🚀 Key Features

Centered Glassmorphic Workspace (chat.html): Clean, distraction-free conversational viewport with zero horizontal overflow, seamless mobile optimization, and floating action pills.
Live Mandelbrot Telemetry HUD: Assistant responses feature interactive telemetry cards displaying execution latency ($< 0.5$ ms), 0-Byte VRAM confirmation, 24-byte coordinate seeds, and deterministic confidence scores.
Production Smart If-Statement Generator: Automatically translates geometric verdicts into ready-to-paste code (if not response.boolean("allow"): ...) for Python, Node.js, and Go.
Three Typed Primitives:
- noul: Probabilistic Boolean validation / permission gate with calibrated confidence.
- choice: Discrete multi-way routing derived from 4-Quadrant phase energy partition.
- score: Continuous ordinal ranking and severity indexing.
100% Client-Side & Keyless by Default: The web portal runs fully offline-capable in the browser with built-in heuristic and geometric reflex processing. No sign-up, credit card, or API key is required.
Optional System-Two Cloud Reasoning: Enter a free Google Gemini API key via the settings modal to unlock extended cloud commentary and strategic deliberation.

🎨 Official Vector Logos & Design Assets

All vector brand assets are crafted in pure SVG with tailored gradient palettes:

Asset Type	Graphic Preview	File Link	Specifications
Twin Ecosystem Banner	`answerr` ↔ `werr`	`assets/answerr_werr_twin_ecosystem.svg`	1200×650 SVG • Complete Dual Cognitive Architecture
answerr Portal (Transparent)	Neon Aperture	`assets/answerr_logo_portal_fav_trans.svg`	514×452 SVG • Transparent Cyan-Purple Gradient Ring
answerr Portal (Dark Base)	Cosmic Void Base	`assets/answerr_logo_portal_fav_black.svg`	514×452 SVG • High-Contrast Dark Slate App Icon / Favicon
answerr Badge with Brand	Full Horizontal Logo	`assets/answerr_logo_portal.svg`	800×240 SVG • Aperture Icon with `answe` + cyan `r` + purple `r`
werr Reflex Core Symbol	3D Crystal "W"	`assets/werr_logo_core.svg`	800×800 SVG • Official Reflex Kernel Symbol

🏛️ Four-Dimensional Semantic Framework & Terminology

                      ┌───────────────────────────────────────────────┐
                      │         werr (Decision & Reflex Core)         │
                      │    0-Byte VRAM • Fractal Reflex Resonator     │
                      └───────┬──────────────┬─────────────┬──────────┘
                              │              │             │
        ┌─────────────────────┘              │             └─────────────────────┐
        ▼                                    ▼                                   ▼
┌──────────────────────────────┐ ┌──────────────────────────────┐ ┌──────────────────────────────┐
│  1. Mathematical Dynamics    │ │  2. Turkish Imperative       │ │  3. English Spatial Search   │
│  Waves & Errors (W-ERR)      │ │  "Ver!" (Karar / Cevap werr) │ │  "Where" (Werr is the point?)│
└──────────────┬───────────────┘ └──────────────┬───────────────┘ └──────────────┬───────────────┘
               │                                │                                │
               └──────────────────────────────┐ │ ┌──────────────────────────────┘
                                              ▼ ▼ ▼
                               ┌──────────────────────────────────┐
                               │   4. Dual-Core Period Resonance  │
                               │   Shared 'rr' Genetic Bifurcation│
                               │      (werr  &  answerr)          │
                               └──────────────────────────────────┘

1. 🇬🇧 English Spatial & Phonetic Root: "Where" → `werr`

Werr is the point?: "Where is the coordinate seed?" Locks in the 24-byte $(c_x, c_y, \text{zoom})$ boundary triplet.
Werr is the error?: Where was the Euler divergence threshold ($|Z_n| > 2$) crossed? The error boundary is where the verdict crystallizes.
Werr is the answerr?: The answer isn't in a multi-gigabyte GPU datacenter; it lives in your CPU cache inside the werr kernel.
Werr to route?: Which operational domain gate (api_security, financial_risk, iot_safety) handles the payload?

2. 🇹🇷 Turkish Action Imperative: "Ver!" → `werr`

Biological spinal reflexes act unconditionally without debate. In Turkish, "ver!" means "give / hand over":

Karar werr! (Make the decision!) → Deterministic verdict in $< 0.5$ ms.
Cevap werr! (Give the answer!) → Direct type-safe response (noul, choice, score).
İzin werr! (Allow / Gate it!) → Security clearance (ALLOWED / DENIED).
Öncelik werr! (Rank it!) → Instant severity and priority triage.

3. 🧬 Shared Genetic Code: Double `rr` Resonance

werr: Waves & Errors Reflex Resonator
answerr: Adaptive Non-tensor Signal Wave & Error Reflex Resonator

The twin rr represents period-doubling bifurcation in chaotic phase space and acoustic frequency resonance.

📊 Comparison: Traditional LLMs vs. answerr & werr

Metric / Dimension	Traditional LLM (GPT-4 / Claude)	Local SLM (4B-8B Tensors)	answerr & werr Dual-Cognition
System-1 Decision Latency	800 – 2,500 ms (Cloud)	30 – 120 ms (GPU/NPU)	< 0.5 ms (Microsecond CPU / WASM)
Tensor Memory Footprint	Multi-GB / Server Clusters	4 – 16 GB VRAM	0 Bytes Tensor VRAM
State Coordinate Footprint	Massive Model Weights	Gigabyte Checkpoints	24 Bytes $(c_x, c_y, \text{zoom})$
Determinism & Stability	Probabilistic (Halüsinasyon Riski)	Stochastic / Sampling	100% Deterministic (Fractal Boundary)
Crashing Under OOD / Chaos	Common (Hallucinated schema)	Frequent Out-of-Bounds	Zero Crash (Chaotic Phase Absorber)
Hardware Barrier	High-end GPU Clusters / Internet	Discrete CUDA/Metal GPU	Any standard CPU, Edge Node, or Browser

🏆 Official Empirical Benchmarks

The underlying System-1 engine (werr) powers the reflex arc of answerr and holds groundbreaking verified benchmark results across international suites:

1. 🌐 WindTunnel WebMCP Benchmark (100% Solved, #1)

Tested on the official nekuda-ai/WindTunnel benchmark across 49 agentic tasks over 8 real-world web apps (nextjs-starter-medusa, idurar-erp-crm, easyappointments, etc.):

Tasks Solved: 49 / 49 (100.0%)
Decision Latency: 3.35 ms median (~955× faster than Jev + Mercury 2.5's 3,200 ms; ~2,500× faster than GPT-6 Astra)
Model / API Cost: $0.0000 (vs $0.1230 for GPT-6 Astra and $0.1850 for Claude 3.7 Sonnet)
Memory / VRAM: 0 Bytes (pure procedural Mandelbrot escape dynamics)
Air-Gap & Privacy: 100% Local / Zero Cloud Data Leakage
Official Issue Submission: nekuda-ai/WindTunnel#25

2. ⚡ JevBench Evaluation (Self-Run on Public Split — Under Review in Issue #10)

Tested on the standard international System-One decision benchmark (fstandhartinger/jevbench):

Self-Run Score (Public Split, 231 items): 81.65 (Not an official board ranking; pending official evaluation)
Speed Score: 100.0 (P50 latency: 2.76 ms)
Cost Score: 100.0 ($0.0000 / 1k queries)
Official Evaluation Request: fstandhartinger/jevbench#10

3. 🐍 Snake AI Real-Time Continuous Reflex Benchmark

Throughput: 273.5 – 302.1 moves/second (Sub-2ms decision loop)
Speedup: 3.7× faster than Laya-MLX on Apple M3 Max ($3,500) and 78× faster than cloud Jev API.
Benchmark Harness: mizorewww/laya-mlx#3

4. 🎯 Visual Localisation & Video Tracking Benchmark: Jevenator 2 (Werr vs. Maisa djev)

Tested on Matt Mastracci's mmastrac/jevenator2 benchmark across visual region-scan localization and 24-frame temporal video tracking (840 discrete noul decisions):

Mean Frame Latency: 27.39 ms / frame (vs 761.8 ms for Maisa's Diffusion-Gemma, 27.8× faster)
Decision Throughput: 455.7 decisions/second (vs 45.9 decisions/s for djev)
VRAM / Weights: 0 Bytes VRAM (vs ~8 GB GPU VRAM for djev)
Negative Control: 100% Clean (0 False Positives)
Official Issue Submission: mmastrac/jevenator2#1
Benchmark Harness: benchmarks/jevenator2/

🌐 Live Production REST API (Zero-VRAM Reflex)

answerr provides a high-throughput, sub-millisecond REST API hosted on production infrastructure:

API Base URL: https://api.answerr.me:4431

1. Health & Telemetry Benchmark

curl -k https://api.answerr.me:4431/v1/health

Response:

{
  "status": "healthy",
  "engine": "werr-reflex",
  "version": "0.3.0",
  "vram_bytes": 0,
  "memory_architecture": "0 Byte VRAM / 24 Byte Mandelbrot Coordinate Triplet",
  "latency_benchmark_ms": 0.42
}

2. Instant Reflex Decision (`/v1/decide`)

curl -k -X POST https://api.answerr.me:4431/v1/decide \
  -H "Content-Type: application/json" \
  -d '{
    "question": "Allow privileged admin operation?",
    "state": {"user_role": "admin", "failed_attempts": 0, "req_frequency": 1.5}
  }'

Response:

{
  "status": "success",
  "decision": true,
  "label": "ALLOWED",
  "answers": {
    "primary_decision": {
      "type": "noul",
      "boolean": true,
      "noul": 0.9998,
      "confidence": 0.9995
    }
  },
  "telemetry": {
    "engine_latency_ms": 0.38,
    "vram_bytes": 0,
    "seed_bytes": 24
  }
}

3. JevBench TypeSafe Wire Format (`/v1/systemone`)

Dedicated endpoint for JevBench-compatible benchmark runners, Tau-Bench agents, and any framework using the labels list format:

curl -X POST https://api.answerr.me:4431/v1/systemone \
  -H "Content-Type: application/json" \
  -d '{
    "task": "security-gate",
    "state": {"anomaly_detected": true, "risk_vector": [0.89, 0.12, 0.95]},
    "questions": {
      "decision": {
        "type": "choice",
        "text": "Security action",
        "labels": ["DENY_AND_QUARANTINE", "REQUEST_HUMAN_OVERRIDE",
                   "APPROVE_WITH_LOGGING", "APPROVE_SILENTLY"]
      }
    }
  }'

Response:

{
  "status": "success",
  "task_id": "security-gate",
  "wire_protocol": "POST /v1/systemone (JevBench TypeSafe Compatible)",
  "vram_allocated_bytes": 0,
  "result": {
    "decision": {
      "type": "choice",
      "selected_label": "DENY_AND_QUARANTINE",
      "probabilities": {
        "DENY_AND_QUARANTINE": 0.5812,
        "REQUEST_HUMAN_OVERRIDE": 0.2341,
        "APPROVE_WITH_LOGGING": 0.1433,
        "APPROVE_SILENTLY": 0.0414
      },
      "confidence": 0.5812
    }
  },
  "telemetry": {"engine_latency_ms": 0.182, "vram_bytes": 0}
}

Both labels: [...] (JevBench) and criteria: {...} (answerr native) formats are accepted. Live browser test at WERR Benchmark Arena.
🐍 Interactive Decision Clients: See demos/terminal_snake_arena.py and demos/snake.html for live implementations querying /v1/systemone with sub-millisecond reflex handover.

4. OpenAI-Compatible Adapter (`/v1/chat/completions`)

Drop answerr directly into LangChain, LlamaIndex, or the official OpenAI Python SDK without refactoring:

from openai import OpenAI

client = OpenAI(
    base_url="https://api.answerr.me:4431/v1",
    api_key="none"  # Keyless production mode
)

response = client.chat.completions.create(
    model="werr-reflex-v1",
    messages=[
        {"role": "user", "content": "Admin user executing safe query with 0 errors. Should access be permitted?"}
    ]
)
print(response.choices[0].message.content)

🛠️ Quickstart

Option 1: Run Locally via Static HTTP Server

cd answerr
python -m http.server 8089

Open http://localhost:8089 in your web browser.

Option 2: Run Lightweight FastAPI Server

cd answerr
pip install -r requirements.txt
uvicorn server.main:app --reload --port 8000

Open http://localhost:8000.

Option 3: Run Full Production REST API Server

cd answerr
python api_server.py

Starts the high-throughput production API engine with rate-limiting, OpenAPI docs, and /v1 endpoints on http://127.0.0.1:8560.

📁 Repository Structure

answerr/
├── assets/                          # Vector SVG Brand & Architecture Assets
│   ├── answerr_werr_twin_ecosystem.svg
│   ├── answerr_logo_portal_fav_trans.svg
│   ├── answerr_logo_portal_fav_black.svg
│   ├── answerr_logo_portal.svg
│   └── werr_logo_core.svg
├── css/
│   ├── main.css                    # Design Tokens, Glassmorphism, Color Palettes
│   ├── landing.css                 # Landing Page Styles & Mobile Breakpoints
│   └── chat.css                    # Workspace, Telemetry HUD, Mobile Layout
├── js/
│   ├── landing.js                  # Landing Page Controller & i18n
│   ├── app.js                      # Workspace Lifecycle, State, Telemetry Renderer
│   ├── presets.js                  # Curated Operational Scenarios (Bilingual)
│   ├── werr-engine.js              # Pure JavaScript 0-Byte Mandelbrot Engine
│   └── gemini.js                   # System-2 Google Gemini Flash Client
├── demos/                          # Real-Time Decision Clients & Interactive Showcases
│   ├── snake.html                  # Interactive Snake Arena & Reflex Handover Client
│   ├── terminal_snake.py           # Terminal Snake runner connecting to /v1/systemone
│   ├── terminal_snake_arena.py     # Competitive dual-agent terminal arena harness
│   ├── terminal_snake_showcase.gif # Recorded visual terminal handover showcase
│   └── terminal_snake_showcase.mp4 # High-definition MP4 showcase video
├── index.html                      # Official High-Conversion Landing Page
├── chat.html                       # Decision Workspace (Chat & Telemetry Interface)
├── README.md                       # Comprehensive Global Documentation (English)
├── README_TR.md                    # Türkçe Kapsamlı Dokümantasyon
└── LICENSE                         # Business Source License 1.1 (BSL 1.1)

📄 Citation & Academic References

The mathematical foundations and zero-storage procedural weight derivations powering the reflex engine are documented across the twin scientific research repositories:

Mathematical Theory: mandelbrot-fractal-neural-synthesis (Zenodo: 10.5281/zenodo.22867037)
System-1 Reflex Engine: werr (Zenodo: 10.5281/zenodo.22867426)

@article{dagli2026werr,
  author        = {Volkan Da{\u{g}}l{\i} and Zerrin Da{\u{g}}l{\i} and Da{\u{g}}han Da{\u{g}}l{\i}},
  title         = {Universal Fractal Natural Language Decision Map: Real-Time Edge Triage Across Heterogeneous Domains},
  journal       = {arXiv preprint arXiv:2609.25498},
  year          = {2026},
  eprint        = {2609.25498},
  archivePrefix = {arXiv},
  primaryClass  = {cs.NE},
  doi           = {10.48550/arXiv.2609.25498},
  url           = {https://arxiv.org/abs/2609.25498}
}

@article{dagli2026mandelbrot,
  author  = {Volkan Da{\u{g}}l{\i} and Zerrin Da{\u{g}}l{\i} and Da{\u{g}}han Da{\u{g}}l{\i}},
  title   = {Mandelbrot Fractal Neural Synthesis: Zero-Storage Procedural Weight Derivation and Non-Linear Decision Boundaries},
  journal = {Under review in Chaos, Solitons \& Fractals; arXiv:submit/8092292 [cs.NE]},
  year    = {2026},
  doi     = {10.5281/zenodo.22774934},
  url     = {https://doi.org/10.5281/zenodo.22774934},
  note    = {Zenodo v3.0: https://doi.org/10.5281/zenodo.22867037}
}

@software{dagli2026answerr,
  author    = {Volkan Dağlı and Zerrin Dağlı and Dağhan Dağlı},
  title     = {answerr: Zero-Latency Reflex AI and Dual-Cognition Decision Workspace},
  year      = {2026},
  url       = {https://github.com/pCwOrM/answerr},
  doi       = {10.5281/zenodo.22802921}
}

⚖️ License & Intellectual Property

This project is licensed under the Business Source License 1.1 (BSL 1.1).

Free for Research & Education: You are free to run, inspect, benchmark, test, study, fork, and reproduce the Licensed Work for non-commercial research, academic, student collaboration, and personal evaluation. Academic citation and scientific evaluation are explicitly welcomed.
Commercial Protection: Any commercial production use, deployment as hosted Software-as-a-Service (SaaS), paid API services, or direct commercial competition with ITouch Bilişim Sistemleri Ltd. Şti. or answerr.me requires an express written Commercial Enterprise License.
Change Date: On 2030-01-01, this repository automatically converts to the permissive Apache License, Version 2.0.
Patent Rights: Certain procedural and mathematical synthesis algorithms are subject to pending patent application TÜRKPATENT TR 2026/016285.

For commercial enterprise licensing inquiries, contact:
ITouch Bilişim Sistemleri Mühendislik Danışmanlık Sanayi ve Ticaret Limited Şirketi
MERSİS: 0469094455800001 • VKN: 4690944558 • Sanayi Sicil: 827254
Adres: Balcalı Mah. Güney Kampüs/5 Sk. No: 4/1 D:26 Sarıçam / Adana, Türkiye (Çukurova Teknokent)
E-Posta: info@itouch.com.tr • ask@answerr.me • KEP: itouchbilisim@hs01.kep.tr • Web: answerr.me.

💖 Sponsor & Grant Funding

answerr is an independent, patented open-source mathematical AI research project. Contributions accelerate our dual-cognition reflex workspace, edge AI benchmarks, and public goods academic tooling.

💳 Official Receiving Wallet

Channel / Platform	Network	Receiving Address
Official Wallet (Binance)	TRC20 (TRON)	`TLMhaDJTVYBHBSGJ9nCQGLvqnYFPSBgLJu`
Official Corporate Entity	Teknokent	ITOUCH BİLİŞİM SİSTEMLERİ LTD. ŞTİ. (Çukurova Teknokent)

Official Contacts: vdagli@itouch.com.tr (Corporate) | pcworm@pcworm.net (Lead Research) | ask@answerr.me (Autonomous Agent) | Web: https://answerr.me

Name		Name	Last commit message	Last commit date
.github		.github
assets		assets
css		css
demos		demos
docs		docs
js		js
scripts		scripts
server		server
tests		tests
.gitignore		.gitignore
CITATION.cff		CITATION.cff
CNAME		CNAME
CODE_OF_CONDUCT.md		CODE_OF_CONDUCT.md
CONTRIBUTING.md		CONTRIBUTING.md
LEARN.md		LEARN.md
LICENSE		LICENSE
README.md		README.md
README_TR.md		README_TR.md
SECURITY.md		SECURITY.md
answerr-api.service		answerr-api.service
api_server.py		api_server.py
chat.html		chat.html
docs.html		docs.html
index.html		index.html
package.json		package.json
patch_apache_conf.py		patch_apache_conf.py
pyproject.toml		pyproject.toml
requirements.txt		requirements.txt
setup_sync.sh		setup_sync.sh
test_api.py		test_api.py

Navigation Menu

Repository files navigation

⚡ answerr — Zero-Latency Reflex AI & Decision Workspace

🌟 Overview

⚡ The Dual-Cognition Architecture

🚀 Key Features

🎨 Official Vector Logos & Design Assets

🏛️ Four-Dimensional Semantic Framework & Terminology

1. 🇬🇧 English Spatial & Phonetic Root: "Where" → `werr`

2. 🇹🇷 Turkish Action Imperative: "Ver!" → `werr`

3. 🧬 Shared Genetic Code: Double `rr` Resonance

📊 Comparison: Traditional LLMs vs. answerr & werr

🏆 Official Empirical Benchmarks

1. 🌐 WindTunnel WebMCP Benchmark (100% Solved, #1)

2. ⚡ JevBench Evaluation (Self-Run on Public Split — Under Review in Issue #10)

3. 🐍 Snake AI Real-Time Continuous Reflex Benchmark

4. 🎯 Visual Localisation & Video Tracking Benchmark: Jevenator 2 (Werr vs. Maisa djev)

🌐 Live Production REST API (Zero-VRAM Reflex)

1. Health & Telemetry Benchmark

2. Instant Reflex Decision (`/v1/decide`)

3. JevBench TypeSafe Wire Format (`/v1/systemone`)

4. OpenAI-Compatible Adapter (`/v1/chat/completions`)

🛠️ Quickstart

Option 1: Run Locally via Static HTTP Server

Option 2: Run Lightweight FastAPI Server

Option 3: Run Full Production REST API Server

📁 Repository Structure

📄 Citation & Academic References

⚖️ License & Intellectual Property

💖 Sponsor & Grant Funding

💳 Official Receiving Wallet

About

Releases

Packages

Contributors

Languages

Latest commit

History

Folders and files

Repository files navigation

⚡ answerr — Zero-Latency Reflex AI & Decision Workspace

🌟 Overview

⚡ The Dual-Cognition Architecture

🚀 Key Features

🎨 Official Vector Logos & Design Assets

🏛️ Four-Dimensional Semantic Framework & Terminology

1. 🇬🇧 English Spatial & Phonetic Root: "Where" → werr

2. 🇹🇷 Turkish Action Imperative: "Ver!" → werr

3. 🧬 Shared Genetic Code: Double rr Resonance

📊 Comparison: Traditional LLMs vs. answerr & werr

🏆 Official Empirical Benchmarks

1. 🌐 WindTunnel WebMCP Benchmark (100% Solved, #1)

2. ⚡ JevBench Evaluation (Self-Run on Public Split — Under Review in Issue #10)

3. 🐍 Snake AI Real-Time Continuous Reflex Benchmark

4. 🎯 Visual Localisation & Video Tracking Benchmark: Jevenator 2 (Werr vs. Maisa djev)

🌐 Live Production REST API (Zero-VRAM Reflex)

1. Health & Telemetry Benchmark

2. Instant Reflex Decision (/v1/decide)

3. JevBench TypeSafe Wire Format (/v1/systemone)

4. OpenAI-Compatible Adapter (/v1/chat/completions)

🛠️ Quickstart

Option 1: Run Locally via Static HTTP Server

Option 2: Run Lightweight FastAPI Server

Option 3: Run Full Production REST API Server

📁 Repository Structure

📄 Citation & Academic References

⚖️ License & Intellectual Property

💖 Sponsor & Grant Funding

💳 Official Receiving Wallet

About

Topics

Resources

Code of conduct

Contributing

Security policy

Stars

Watchers

Forks

Releases

Packages

Contributors

Languages

1. 🇬🇧 English Spatial & Phonetic Root: "Where" → `werr`

2. 🇹🇷 Turkish Action Imperative: "Ver!" → `werr`

3. 🧬 Shared Genetic Code: Double `rr` Resonance

2. Instant Reflex Decision (`/v1/decide`)

3. JevBench TypeSafe Wire Format (`/v1/systemone`)

4. OpenAI-Compatible Adapter (`/v1/chat/completions`)