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Documentation Index

Fetch the complete documentation index at: https://codinitdev-mintlify-update-changelog-codinit-dev-90028.mintlify.app/llms.txt

Use this file to discover all available pages before exploring further.

Run models locally using Ollama for privacy, offline access, and control. Requires initial setup and sufficient hardware. Website: https://ollama.com/

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Setup

  1. Install Ollama: Download from ollama.com and install
  2. Start Ollama: Run ollama serve in terminal
  3. Download a model: 
    ollama pull qwen2.5-coder:32b
  4. Configure context window: 
    ollama run qwen2.5-coder:32b
/set parameter num_ctx 32768
/save your_custom_model_name

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Configuration in CodinIT

  1. Click the settings icon (⚙️) in CodinIT
  2. Select “ollama” as the API Provider
  3. Enter your saved model name
  4. (Optional) Set base URL if not using default http://localhost:11434
  • qwen2.5-coder:32b - Excellent for coding
  • codellama:34b-code - High quality, large size
  • deepseek-coder:6.7b-base - Effective for coding
  • llama3:8b-instruct-q5_1 - General tasks
See Ollama model library for full list.

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Notes

  • Context window: Minimum 12,000 tokens recommended, 32,000 ideal
  • Resource demands: Large models require significant system resources
  • Offline capability: Works without internet after model download
  • Performance: May be slow on average hardware