dir-assistant 1.0.0

Chat with your current directory's files using a local or API LLM.

dir-assistant

Chat with your current directory's files using a local or API LLM.

Dir-assistant has local platform support for CPU (OpenBLAS), Cuda, ROCm, Metal, Vulkan, and SYCL.

Dir-assistant has API support for all major LLM APIs. More info in the LiteLLM Docs.

Dir-assistant uses a unique method for finding the most important files to include when submitting your prompt to an LLM called CGRAG (Contextually Guided Retrieval-Augmented Generation). You can read this blog post for more information about how it works.

This project runs local LLMs via the fantastic llama-cpp-python package and runs API LLMS using the also fantastic LiteLLM package.

New Features

• Now installable via pip
• Thorough CLI functionality including platform installation, model downloading, and config editing.
• User files have been moved to appropriate home hidden directories.
• Config now has llama.cpp completion options exposed (top_k, frequency_penalty, etc.)

Install

Install with pip:

pip install dir-assistant

The default configuration for dir-assistant is API-mode. If you download an LLM model with download-llm below, local-mode will automatically be set. To change from API-mode to local-mode, set the ACTIVE_MODEL_IS_LOCAL setting.

Embedding Model Download

You must download an embedding model regardless of whether you are running in local or API mode. You can download a good default embedding model with:

dir-assistant models download-embed

If you would like to use another embedding model, open the models directory with:

dir-assistant models

Note: The embedding model will be hardware accelerated after using the platform subcommand. To change whether it is hardware accelerated, change n_gpu_layers = -1 to n_gpu_layers = 0 in the config.

Select A Hardware Platform

By default dir-assistant is installed with CPU-only compute support. It will work properly without this step, but if you would like to hardware accelerate dir-assistant, use the command below to compile llama-cpp-python with your hardware's support.

dir-assistant platform cuda

Available options: cpu, cuda, rocm, metal, vulkan, sycl

For Platform Install Issues

If you have any issues building llama-cpp-python, reference the project's install instructions for more info: https://github.com/abetlen/llama-cpp-python

API Configuration

To configure which LLM API dir-assistant uses, you must edit LITELLM_MODEL and the appropriate API key in your configuration. To open your configuration file, enter:

dir-assistant config open

Once editing the file, change:

[DIR_ASSISTANT]
LITELLM_MODEL = "gemini/gemini-1.5-flash-latest"
LITELLM_CONTEXT_SIZE = 500000
...
[DIR_ASSISTANT.LITELLM_API_KEYS]
GEMINI_API_KEY = "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"

LiteLLM supports all major LLM APIs, including APIs hosted locally. View the available options in the LiteLLM providers list.

Local LLM Model Download

You can download a low requirements default local LLM model (Phi 3 128k) with:

dir-assistant models download-llm

If you would like to use another local LLM model, open the models directory with:

dir-assistant models

Note: The local LLM model will be hardware accelerated after using the platform subcommand. To change whether it is hardware accelerated, change n_gpu_layers = -1 to n_gpu_layers = 0 in the config.

Configure Settings

To print current configs:

dir-assistant config

To open the config file:

dir-assistant config open

Llama.cpp provides a large number of options to customize how your local model is run. Most of these options are exposed via llama-cpp-python. You can configure them with the [DIR_ASSISTANT.LLAMA_CPP_OPTIONS], [DIR_ASSISTANT.LLAMA_CPP_EMBED_OPTIONS], and [DIR_ASSISTANT.LLAMA_CPP_COMPLETION_OPTIONS] sections in the config file.

The options available for llama-cpp-python are documented in the Llama constructor documentation.

What the options do is also documented in the llama.cpp CLI documentation.

Upgrading

Some version upgrades may have incompatibility issues in the embedding index cache. Use this command to delete the index cache so it may be regenerated:

dir-assistant clear

Additional Help

Use the -h argument with any command or subcommand to view more information. If your problem is beyond the scope of the helptext, please report a github issue.

Contributors

We appreciate contributions from the community! For a list of contributors and how you can contribute, please see CONTRIBUTORS.md.

Limitations

• Only tested on Ubuntu 22.04. Please let us know if you run it successfully on other platforms by submitting an issue.
• Dir-assistant only detects and reads text files at this time.

Todos

• API LLMs
• RAG
• File caching (improve startup time)
• CGRAG (Contextually-Guided Retrieval-Augmented Generation)
• Multi-line input
• File watching (automatically reindex changed files)
• Single-step pip install
• Model download
• Web search
• API Embedding models
• Simple mode for better compatibility with external script automations