Crow.Code - Sell Project

CONTACT ME: oroszballazs@gmail.com crow.code — Air-Gapped & Multi-AI Enterprise Coding Agent (Full Source + IP) crow.code is a production-grade, terminal-first AI coding agent engineered for developers, enterprise teams, and organizations that demand absolute data privacy alongside multi-model orchestration. Unlike typical AI coding tools that lock you into a single cloud provider or compromise your source code, crow.code is built to run 100% offline (Air-Gapped) or combine several local and cloud AI models side-by-side in the same project, conversation, and execution pipeline. At its core, crow.code features an advanced Multi-Model Consensus & Orchestration Framework. You can assign different roles to different models simultaneously (e.g., local DeepSeek-R1 for core logic, Claude for refactoring, GPT-4o for security auditing) to run concurrent multi-perspective code reviews and automated self-healing loops. This is not a simple wrapper around an API—it is a comprehensive, provider-agnostic enterprise agent framework built in Python from the ground up. 🛡️ Enterprise & Air-Gapped Core Capabilities 100% Offline / Air-Gapped Mode: Run completely internet-free using local LLMs (via Ollama, vLLM, or custom local endpoints). Zero Data Retention (ZDR) guaranteed—your proprietary source code never leaves your local machine or corporate network. Zero-API-Key Architecture: Out-of-the-box support for local model execution without requiring external API keys, subscription tokens, or third-party cloud verification. Multi-Model Consensus Code Review (/review): Launch an automated "AI panel" where multiple models evaluate the same code simultaneously. For example, Claude writes the code, a local DeepSeek checks the logic, and an audit model scans for vulnerabilities—delivering a consensus-validated, high-quality output. 🧰 What's Included File Management & Context: Read, create, edit, and inspect project files with deep directory awareness. Terminal Execution: Run shell commands and development tools directly, featuring secure confirmation gating by default. Git Integration: Automated status tracking, diff generation, and smart, approved commits. Automated Test Execution: Continuous, pytest-based self-healing testing loops. Skills System (/useskill): Modular, explicitly-loaded instruction sets for highly specialized or domain-specific corporate workflows. Persistent Memory & Personalization (/personalize): The agent builds and updates a local profile over time, curating style preferences and context without cloud dependencies. Session Management (/save, /load): Instantly save, reload, and resume full multi-model conversations. Mid-Conversation Model Switching (/switchto): Configure up to 5 AI modules and switch between them dynamically without losing project context. Multi-Persona Analysis Mode (/gi): Gain several unique AI perspectives on complex algorithmic problems. Safety-First Workflow Tools: Includes /plan (preview without side effects), /diff, /undo, and a /bypassy auto-approve mode for trusted sandbox runs. Security & Auditing (/hackit): Bounded security audit mode with targeted, automated vulnerability fixes. Ultra Mode (/ultramode): Advanced local machine control (open/close Windows apps, approved uninstalls via winget). Higgsfield Integration (/higgsfield): Built-in multimodal support for advanced visual code analysis, UI/UX evaluation, and inline asset generation. GitHub Discovery (/find.repo & /download): Natural-language repository search and direct workspace downloading. Local Network File Transfer (/pydrop): Secure, offline file transferring across your local network. Usage & Token Tracking (/usage): Comprehensive token cost and API usage logging. One-Click Deployment: STARTCROWCODE.bat automatically creates a virtual environment, installs local dependencies, and launches a guided setup wizard. Clean Release Script (preparerelease.ps1): Strips API keys, local configs, sessions, and personal data for secure white-label distribution. 🏗️ Architecture A clean, highly modular Python codebase with strict separation of concerns between the agent loop, CLI, provider integrations, tool registry, and schemas. The architecture is explicitly designed to be extended with new offline models, local specialized tools, or enterprise skills without ever altering the core orchestration engine. 💎 Why It's Highly Valuable Eliminates Vendor Lock-In & Cloud Risk: Solves the two biggest hurdles for enterprise AI adoption—dependence on a single LLM provider and the security risk of leaking source code to external servers. Substantial, Non-Trivial Engineering: Building a stable, local multi-agent system that orchestrates model cross-talk, manages persistent context, handles file-system safety gates, and executes local code is an enterprise-grade engineering feat—not a weekend project. Production-Ready & Fully Documented: This is a fully functional, thoroughly tested asset—not a conceptual prototype. Complete IP & Source Ownership:...