Advanced Installation Intent Detection

[mikejmorgan-ai]

Description

Understand complex, multi-step installation requests and break them into actionable plans.

Requirements

• Parse complex natural language requests
• Identify multiple intents in single request
• Generate installation plan
• Handle ambiguous requests (ask clarifying questions)
• Context from previous interactions
• Suggest optimizations to user's request

Acceptance Criteria

• Parses multi-step requests
• Creates installation plan
• Asks clarifying questions when needed
• Uses context from previous commands
• Suggests better alternatives
• Integration with LLM
• Unit tests included (>80% coverage)
• Documentation with complex examples

Example Usage

$ cortex install "I need to run machine learning models on my gpu"
🧠 Understanding your request...

Installation Plan:
1. Detect GPU: NVIDIA RTX 4090 ✓
2. Install CUDA 12.3 + cuDNN
3. Install Python ML stack:
   - PyTorch 2.1.0 (GPU support)
   - TensorFlow 2.15.0 (GPU support)
   - Jupyter Lab
4. Verify GPU acceleration

💡 Optional additions:
   - Conda (recommended for ML environment management)
   - VS Code with Python extensions
   
Proceed with plan? [Y/n]:

Skills: Python, LangChain, prompt engineering, Claude API
Bounty: $25 upon merge
Priority: High

[pavanimanchala53]

Can you assign this to me

[mikejmorgan-ai]

🎯 Closing for MVP Focus

This issue is being closed to help the team focus on MVP-critical features (#1-45).

This is NOT abandoned - it's an important feature we'll revisit after MVP completion.

Timeline:

• Now (Nov-Dec 2024): Focus on MVP (Issues Build LLM integration layer for command interpretation #1-45)
• January 2025: Reopen post-MVP features
• February 2025: Seed funding round

Want to work on this anyway?
Comment below and we can discuss! We're always open to great contributions.

Tracking: Labeled as post-mvp for easy filtering when we reopen.

Thanks for understanding! 🚀

— Mike (@mikejmorgan-ai)