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Categorizer Module

The categorizer module provides LLM-powered categorization of mathematical concepts.

Setup

1. Install Required Dependencies

For FREE local models (recommended):

make install

For paid API models (optional):

For OpenAI:

pip install openai

For Anthropic Claude:

pip install anthropic

For Ollama (free local alternative):

  1. Install Ollama from https://ollama.ai
  2. Install langchain-community: pip install langchain-community
  3. Pull a model: ollama pull llama2

2. Configure API Keys (only for paid models)

Set the appropriate environment variable for your chosen LLM provider:

For OpenAI:

export OPENAI_API_KEY="your-openai-api-key-here"

For Anthropic Claude:

export ANTHROPIC_API_KEY="your-anthropic-api-key-here"

For Ollama (optional):

export OLLAMA_MODEL="llama2"  # Default is llama2

You can also add these to a .env file or your shell configuration file (.bashrc, .zshrc, etc.).

Usage

Basic Usage

Categorize all items using the default FREE LLM (HuggingFace FLAN-T5):

python manage.py categorize

With Options

Categorize a limited number of items:

python manage.py categorize --limit 10
make categorize
# OR

Use a specific LLM provider:

FREE models (run locally):

# Use HuggingFace FLAN-T5 (default, free, good for instruction following)
python manage.py categorize --llm huggingface_flan_t5

# Use HuggingFace GPT-2 (free, generative model)
python manage.py categorize --llm huggingface_gpt2

# Use HuggingFace DialoGPT (free, conversational model)
python manage.py categorize --llm huggingface_dialogpt

# Use Ollama (free, requires Ollama installed)
python manage.py categorize --llm ollama

Paid API models:

# Use OpenAI GPT-4 (requires API key)
python manage.py categorize --llm openai_gpt4

# Use OpenAI GPT-3.5 Turbo (requires API key)
python manage.py categorize --llm openai_gpt35

# Use Anthropic Claude (requires API key)
python manage.py categorize --llm anthropic_claude

Combine options:

python manage.py categorize --limit 5 --llm huggingface_flan_t5

Architecture

  • categorizer_service.py - Main service for categorizing items
  • llm_service.py - Service for calling various LLM APIs
  • management/commands/categorize.py - Django management command

Supported LLMs

Free Models (No API Key Required)

  1. HuggingFace FLAN-T5 - Google's instruction-following model (recommended for tasks)
  2. HuggingFace GPT-2 - OpenAI's classic generative model
  3. HuggingFace DialoGPT - Microsoft's conversational model
  4. Ollama - Run any Ollama model locally (llama2, mistral, etc.)

Paid API Models (Require API Key)

  1. OpenAI GPT-4 - Most capable, but expensive
  2. OpenAI GPT-3.5 Turbo - Fast and cheaper than GPT-4
  3. Anthropic Claude - High quality, good reasoning

Performance Notes

  • Free models run locally and don't require internet/API keys, but:

    • First run downloads the model (~1-3GB depending on model)
    • Requires sufficient RAM (4-8GB+ recommended)
    • Slower than API models (especially without GPU)

  • API models are faster but cost money per request

  • Ollama is a good middle ground - free, local, and supports many models

Extending

To add support for additional LLM providers:

  1. Add a new entry to the LLMType enum in llm_service.py
  2. Implement a new private method (e.g., _call_new_provider) in the LLMService class
  3. Add the new provider to the call_llm method's conditional logic
  4. Update the command choices in management/commands/categorize.py