Skip to main content

AI-powered CLI development assistant

Project description

Cognix Logo

Cognix


๐Ÿš€ v0.1.1 released!

Provider auto-detection and model fallback fixes included. Now works seamlessly with OpenAI-only or Anthropic-only setups.

If you find Cognix useful, please give it a star โญ โ€” it helps us reach more developers and build a stronger community.

โ–ˆโ–€โ–€ โ–ˆโ–€โ–ˆ โ–ˆโ–€โ–€ โ–ˆโ–„โ–‘โ–ˆ โ–ˆ โ–€โ–„โ–€
โ–ˆโ–„โ–„ โ–ˆโ–„โ–ˆ โ–ˆโ–„โ–ˆ โ–ˆโ–‘โ–€โ–ˆ โ–ˆ โ–ˆโ–‘โ–ˆ

Cognix โ€” Augmented AI Development Partner for CLI
Persistent Sessions, Long-Term Memory, Multi-Model Support, and Full-Pipeline Development.
Build smarter, faster, and without context loss.

Version License Python Demo

Quick Start โ€ข Demo โ€ข Features โ€ข Commands


๐ŸŽฏ 12-Second Magic

Cognix is the only AI coding Partner that:

  • ๐Ÿ’พ Session Restoration: Resume interrupted work completely
  • โšก Structured Workflow: Think โ†’ Plan โ†’ Write
  • ๐ŸŽจ Practical Results: Generate beautiful GUI apps instantly
  • ๐Ÿง  Persistent Memory: Remember entire projects across sessions

"Once you have an idea, it's already complete."


๐ŸŽฌ See It In Action

https://github.com/cognix-dev/cognix/assets/226239127/478856788-94577806-5a80-4deb-ae58-c699c43efd3c

12-second demo: Session restoration โ†’ /write โ†’ Beautiful neon green clock app

Quick Demo (12 seconds)

# 0-1 seconds: Start Cognix
cognix

# 1-3 seconds: Session restoration
Would you like to restore the previous session? [y/N]: y
โœ… Session restored successfully!
๐Ÿ”„ Workflow state restored!
   Goal: Brief: big bright green clock popup window bold digits
   Progress: โœ… Think โ†’ โœ… Plan โ†’ โณ Write

# 3-8 seconds: Code generation
cognix> /write --file clock.py
โœจ Writing implementation for: Brief: big bright green clock popup window bold digits
   Target file: clock.py
   Target language: python (from .py)

# 8-10 seconds: Beautiful neon green clock appears
Save generated code to clock.py? [y/N] y
โœ… Code saved to: clock.py

What you just saw:

  1. ๐Ÿ’พ Workflow Restoration: AI remembers your thinking process across sessions
  2. โšก Instant Code Generation: From plan to working GUI in seconds
  3. ๐ŸŽจ Beautiful Results: Functional neon green digital clock with #00FF00 perfection
  4. ๐Ÿš€ Complete Pipeline: Think โ†’ Plan โ†’ Write โ†’ Deploy in one session

Try It Yourself

# Step 1: Start your thinking
cognix> /think "Brief: bright green digital clock GUI"

# Step 2: Plan implementation  
cognix> /plan

# Step 3: Generate code
cognix> /write --file my_clock.py

# Step 4: Exit and run
cognix> exit
python my_clock.py  # โ†’ Beautiful clock appears!

๐Ÿš€ Quick Start

Installation

Recommended (isolated):

pipx install cognix

Alternative:

pip install cognix

Setup (2 minutes)

# 1. Get your API key from Anthropic or OpenAI
# https://console.anthropic.com/ or https://platform.openai.com/

# 2. Create .env file
echo "ANTHROPIC_API_KEY=your_api_key_here" > .env
echo "OPENAI_API_KEY=your_api_key_here" >> .env

# 3. Start Cognix
cognix

Your First Workflow (30 seconds)

cognix> /think "Create a REST API for user authentication"
# ๐Ÿค” AI analyzes your requirements...

cognix> /plan
# ๐Ÿ“‹ AI creates detailed implementation plan...

cognix> /write --file auth_api.py
# โœ๏ธ AI generates production-ready code...

That's it! Your API is ready to use.


๐Ÿ“‹ Commands

Core Workflow

Command Description Example
/think "<goal>" AI analyzes your problem /think "API rate limiting"
/plan Creates implementation strategy /plan
/write [--file path] Generates production code /write --file api.py

Help & Information

Command Description Example
/help Show all commands /help
/model Show current model & options /model
/workflow-status Check current progress /workflow-status
/status Show current config/model /status
/memory Inspect or export memory /memory export

AI Model Management

Command Description Example
/model <name> Switch AI models instantly /model gpt-4o

File Operations

Command Description Example
/edit <file> AI-assisted editing /edit src/main.py
/fix <file> Auto-fix bugs /fix api.py --function auth
/review [dir] Code analysis /review src/
/diff Show changes before applying /diff
/apply Apply generated patch safely /apply
/backup Manage backups/restore /backup restore

Session Management

Command Description Example
/save-session <name> Save your work /save-session "auth-system"
/resume <name> Resume previous work /resume "auth-system"
/list_sessions List saved sessions /list_sessions
/session_info Show current session meta /session_info
/save_session <name> Save current session /save_session mywork
/resume <name> Restore a saved session /resume mywork

Workflow Control

Command Description Example
/clear-workflow Start fresh /clear-workflow

๐ŸŒŸ Key Features

๐Ÿ”„ Multi-AI Powerhouse

cognix> /think "Build a todo app"
# Using Claude-4: Detailed, enterprise-focused analysis

cognix> /model gpt-4o
โœ… Switched to: gpt-4o

cognix> /think "Build a todo app"  
# Using GPT-4o: Creative, modern, action-oriented approach

Compare results instantly. Choose the best AI for each task.

๐Ÿง  True Session Persistence

# Yesterday
cognix> /think "E-commerce platform architecture"
cognix> /plan
# Work interrupted...

# Today
cognix
๐Ÿ”„ Workflow state restored!
Goal: E-commerce platform architecture  
Progress: โœ… Think โ†’ โœ… Plan โ†’ โณ Write

cognix> /write --file platform.py
# Continue exactly where you left off!

โšก Lightning-Fast Development

# Generate production-ready GUI apps in seconds
cognix> /think "Brief: neon green clock GUI"
cognix> /plan  
cognix> /write --file clock.py
# โ†’ Beautiful tkinter app with #00FF00 fluorescent green digits!

Perfect for rapid prototyping and instant visual results.

โšก Intelligent Context Awareness

  • ๐Ÿ“ Auto-scans your project structure
  • ๐Ÿง  Remembers all previous conversations
  • ๐ŸŽฏ Adapts suggestions to your codebase
  • ๐Ÿ”„ Maintains context across sessions

๐Ÿ’ก Real Usage Examples

Scenario 1: Feature Development

cognix> /think "Add OAuth2 authentication to my Express.js API"

๐Ÿ’ญ Analysis Result:
**1) What needs to be built:** OAuth2 flow with JWT tokens, middleware for route protection, 
and integration with popular providers (Google, GitHub, etc.)
**2) Key challenges:** Token validation, refresh logic, and secure session management
**3) Success approach:** Use passport.js ecosystem, implement proper error handling, 
and add comprehensive testing for auth flows

cognix> /plan

๐Ÿ“‹ Implementation Plan:
- Setup & core logic: Install passport, passport-jwt, configure strategies for Google/GitHub OAuth2...
- Security implementation: JWT signing/validation, refresh token rotation, rate limiting...
- Testing & deployment: Unit tests for auth middleware, integration tests for OAuth flows...

cognix> /write --file auth/oauth.js
# Generates complete OAuth2 implementation

Scenario 2: AI Model Comparison

# Claude-4 approach (detailed, enterprise-focused)
cognix> /think "Database caching strategy"
โ†’ Comprehensive analysis with Redis, Memcached comparison, 
  enterprise concerns, compliance considerations

# Switch to GPT-4o for creative alternatives  
cognix> /model gpt-4o
cognix> /think "Database caching strategy"  
โ†’ Modern approach with edge caching, CDN integration,
  serverless caching solutions

# Choose the best elements from both!

Scenario 3: Session Restoration

# After weekend break
cognix
๐Ÿ“‹ Previous session found!
   Last updated: 2025-08-09T18:42:57
   Entries: 15
   Model: claude-sonnet-4-20250514

Would you like to restore the previous session? [y/N]: y
โœ… Session restored successfully!
๐Ÿ”„ Workflow state restored!
   Goal: Microservices architecture design
   Progress: โœ… Think โ†’ โœ… Plan โ†’ โณ Write

# Continue immediately where you left off
cognix> /write --file services/user-service.py

Scenario 4: Rapid GUI Prototyping

# 12-second workflow for visual applications
cognix> /think "Brief: desktop calculator with dark theme"
cognix> /plan
cognix> /write --file calculator.py

# Result: Complete GUI calculator ready to use
python calculator.py  # โ†’ Professional calculator app launches

๐ŸŽฏ Supported AI Models

Claude 4 Series (Anthropic)

  • claude-opus-4-20250514 - Most capable, complex reasoning
  • claude-sonnet-4-20250514 - Balanced performance & speed

GPT-4o Series (OpenAI)

  • gpt-4o - Latest model, highly creative
  • gpt-4o-mini - Fast responses, cost-effective

Legacy Support

  • claude-3-5-sonnet-20241022
  • claude-3-7-sonnet-20250219

Switch between any model instantly: /model gpt-4o


โš™๏ธ Configuration & Customization

Troubleshooting

API Key Configuration Issues

Problem: Provider anthropic not available or No LLM providers available

Solution: Cognix automatically detects available API providers. Configure at least one:

# Option 1: Environment variables
export OPENAI_API_KEY=your_key_here
export ANTHROPIC_API_KEY=your_key_here

# Option 2: .env file
echo "OPENAI_API_KEY=your_key_here" > .env
echo "ANTHROPIC_API_KEY=your_key_here" >> .env
Provider-Specific Setup
OpenAI Only:
bashOPENAI_API_KEY=sk-proj-your_key_here
โ†’ Cognix automatically defaults to gpt-4o
Anthropic Only:
bashANTHROPIC_API_KEY=sk-ant-your_key_here
โ†’ Cognix automatically defaults to claude-sonnet-4-20250514
Manual Model Switching
bashcognix> /model gpt-4o          # Switch to OpenAI
cognix> /model claude-sonnet-4  # Switch to Claude
cognix> /model                  # Show all available models
Environment Detection Order
Cognix checks for API keys in this priority:

Environment variables (OPENAI_API_KEY, ANTHROPIC_API_KEY)
.env file in current directory
.env file in ~/.cognix/ directory

Common Issues

No LLM providers available โ†’ Set at least one API key
Model switching fails โ†’ Use /model to see available options
Session restore errors โ†’ Check ~/.cognix/sessions/ directory permissions

## ๐Ÿ“ Data Storage & Privacy

Cognix stores local data under your home directory:

- `~/.cognix/config.json` โ€” user configuration
- `~/.cognix/sessions/` โ€” saved sessions & autosave
- `~/.cognix/memory/memory.json` โ€” longโ€‘term memory

> All files are local to your machine. You can delete them anytime.

### Default Config (`~/.cognix/config.json`)
```json
{
  "model": "claude-sonnet-4-20250514",
  "temperature": 0.7,
  "max_tokens": 4000,
  "auto_backup": true,
  "stream_responses": true,
  "typewriter_effect": false
}

Environment Variables

# API Keys (Required)
ANTHROPIC_API_KEY=your_anthropic_key
OPENAI_API_KEY=your_openai_key

# Optional settings  
COGNIX_DEBUG=true
DEFAULT_MODEL=gpt-4o
COGNIX_AUTO_SAVE=true

System Requirements

  • Python: 3.8 or higher
  • OS: Windows 10+, macOS 10.15+, Linux
  • Memory: 512MB minimum recommended
  • Internet: Required for API connections

๐Ÿ† Why Choose Cognix?

vs. GitHub Copilot

Feature Cognix Copilot
Multi-AI Support โœ… GPT-4o + Claude-4 โŒ OpenAI only
Session Persistence โœ… Full project memory โŒ No memory
Workflow Structure โœ… Thinkโ†’Planโ†’Write โŒ Code completion only
CLI Integration โœ… Native terminal โŒ Editor-dependent

vs. ChatGPT/Claude Web

Feature Cognix Web Interfaces
Development Integration โœ… Direct file operations โŒ Copy-paste workflow
Project Context โœ… Full codebase awareness โŒ Limited context
AI Model Switching โœ… Instant switching โŒ Separate applications
Session Management โœ… Auto-save everything โŒ Manual management

vs. Other AI Coding Tools

  • ๐Ÿง  Memory Persistence: Only Cognix remembers everything across sessions
  • ๐Ÿ”„ Multi-AI: Compare approaches from different models instantly
  • โšก Structured Workflow: Thinkโ†’Planโ†’Write methodology
  • ๐ŸŽฏ State Restoration: Resume work exactly where you left off

๐Ÿš€ Project-Specific Examples

Web Development

cognix> /think "Full-stack blog platform with Next.js"
cognix> /plan
cognix> /write --file blog-platform.js

Data Science

cognix> /think "Analyze customer churn with machine learning"
cognix> /plan  
cognix> /write --file churn_analysis.py

DevOps

cognix> /think "Docker containerization for my Python app"
cognix> /plan
cognix> /write --file Dockerfile

Mobile Development

cognix> /think "React Native app with offline sync"
cognix> /plan
cognix> /write --file OfflineSync.js

๐Ÿ› ๏ธ Advanced Features

Constraint Detection

cognix> /think "Todo app - brief"
๐ŸŽฏ Detected constraints: brief format
๐Ÿ’ญ Analysis Result:
**1) What needs to be built:** Basic CRUD operations...
**2) Key challenges:** Data persistence and user experience...  
**3) Success approach:** Start with MVP featuring essential functions...

Intelligent File Operations

# Edit with AI assistance
cognix> /edit src/api.py
๐Ÿ“ Editing: src/api.py
What changes would you like to make? Add rate limiting


๐Ÿค– Generating suggestions...
๐Ÿ’ก Suggestion: I'll add Express rate limiting middleware...

# Auto-fix specific functions
cognix> /fix utils.py --function calculate_total
๐Ÿ”ง Analyzing function: calculate_total
โœ… Fixed: Added null checking and proper error handling

Project-Aware Conversations

cognix> How can I improve the performance of my React components?

# AI automatically analyzes your React project structure
๐Ÿง  Analyzing your React project...
๐Ÿ“ Found: 15 components, 3 hooks, 2 contexts

๐Ÿ’ก Specific recommendations for your codebase:
1. UserProfile.jsx: Consider React.memo for expensive renders
2. DataTable.jsx: Implement virtualization for large datasets  
3. Global state: Your Redux store could benefit from RTK Query

๐Ÿค Contributing

We welcome contributions! Here's how to get started:

Development Setup

git clone https://github.com/cognix-dev/cognix.git
cd cognix
pip install -e ".[dev]"

Running Tests

pytest tests/

Code Style

black cognix/
flake8 cognix/

Contribution Guidelines


๐Ÿงฐ Troubleshooting

  • No LLM providers available โ†’ Set ANTHROPIC_API_KEY or OPENAI_API_KEY in your .env, then restart Cognix.
  • Patch apply failed โ†’ Restore the last backup with /backup restore.

๐Ÿ“„ License

MIT License - see LICENSE file for details.


๐ŸŒŸ Roadmap

v0.2.0 - Memory Management & Code Enhancement

  • ๐Ÿ“ Individual memory entry deletion
  • ๐Ÿ—‚๏ธ Automatic memory archiving
  • ๐Ÿ“Š Memory size management and cleanup
  • ๐ŸŽจ AI code enhancement (/refactor, /lint)
  • โšก Improved streaming output

v0.3.0 - Advanced Development Features

  • ๐ŸŽฏ Target file/function specification (@filename, #function)
  • ๐Ÿƒ File execution capabilities (/run)
  • ๐Ÿ“ฑ Browser-based GUI (beta)
  • ๐Ÿ” Advanced code analysis features

v0.4.0 - Team Collaboration

  • ๐Ÿ‘ฅ Shared sessions between team members
  • ๐Ÿ“‹ Code review workflows
  • ๐Ÿ”— Basic GitHub/GitLab integration

v0.5.0 - Enterprise

  • ๐Ÿข Self-hosted deployment options
  • ๐Ÿ”’ Advanced security features
  • ๐Ÿ“Š Usage analytics and metrics

๐Ÿ’ฌ Support

Need Help?

Stay Updated


๐Ÿง  Cognix - Where AI meets intelligent development workflows

Made with โค๏ธ by Individual Developer

โญ Star on GitHub โ€ข ๐Ÿš€ Get Started


Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

cognix-0.1.1.tar.gz (78.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

cognix-0.1.1-py3-none-any.whl (76.4 kB view details)

Uploaded Python 3

File details

Details for the file cognix-0.1.1.tar.gz.

File metadata

  • Download URL: cognix-0.1.1.tar.gz
  • Upload date:
  • Size: 78.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.3

File hashes

Hashes for cognix-0.1.1.tar.gz
Algorithm Hash digest
SHA256 ec35869cadf12b2500ddb59b2260f0ecb112fb2720979cad93e848f7f3a066d2
MD5 ca231a1a42b20a4f839da1a81ec2d151
BLAKE2b-256 fdb7dc5f4874ad02b2a4dbf4143ca624560db09780442d07937939b1e1f21b5f

See more details on using hashes here.

File details

Details for the file cognix-0.1.1-py3-none-any.whl.

File metadata

  • Download URL: cognix-0.1.1-py3-none-any.whl
  • Upload date:
  • Size: 76.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.3

File hashes

Hashes for cognix-0.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 378a4b6fa99da6417a60c09b0986096998ef889ce124221e2005eaaa977446a7
MD5 0d80f5a0e11a92b29166c53b024877a6
BLAKE2b-256 0913d73aedf3bf0149e0330450ac7bea43fd5f6158089e94071627e96591e170

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page