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Ollama Integration for semindex

This document explains how to use Ollama with semindex to leverage GPU-accelerated language models for enhanced code understanding and generation.

Prerequisites

  1. Install and run Ollama on your system:

    • Visit https://ollama.ai to download and install Ollama
    • Make sure Ollama is running (typically accessible at http://localhost:11434)

  2. Pull a model you'd like to use:

    ollama pull llama3
# or for code-specific models:
ollama pull codellama:7b
ollama pull deepseek-coder:6.7b

Using Ollama with semindex

Basic Query with Ollama

To perform a query and get an AI-generated response using Ollama:

semindex query "Explain how authentication works in this codebase" --ollama

Specify a Model

To use a specific Ollama model:

semindex query "How do I add a new user?" --ollama --ollama-model codellama:7b

Advanced Query with Context

You can combine Ollama with other features:

semindex query "Generate a test for the user authentication function" \
    --ollama \
    --ollama-model codellama:7b \
    --top-k 5 \
    --hybrid \
    --include-docs

Environment Variables

You can set these environment variables to customize Ollama behavior:

  • SEMINDEX_OLLAMA_MODEL: Default model to use (default: llama3)
  • SEMINDEX_OLLAMA_BASE_URL: Base URL for Ollama API (default: http://localhost:11434)

Example Use Cases

1. Code Explanation

semindex query "Explain the user management system" --ollama

2. Finding Implementation

semindex query "Show me how password hashing is implemented" --ollama

3. Generating Documentation

semindex query "Generate documentation for the API endpoints" --ollama

4. Code Suggestions

semindex query "How can I optimize the database queries in this module?" --ollama

Comparison with Standard Query

Without Ollama (just retrieves relevant code snippets):

semindex query "How does user authentication work?"

With Ollama (retrieves code + generates AI explanation):

semindex query "How does user authentication work?" --ollama

The Ollama-enhanced query will not only show relevant code snippets but also provide an AI-generated explanation of how the authentication system works, making it more similar to tools like Claude Code or GitHub Copilot.

Performance Tips

  1. Use code-specific models like codellama:7b or deepseek-coder:6.7b for better code understanding
  2. Adjust --top-k to control how many code snippets are provided as context (default is 10)
  3. Use --max-tokens to control the length of the Ollama response
  4. Consider using --hybrid and --include-docs for more comprehensive context