cllm - [C]ommand-line [LLM] usage

Installation

To install cllm:

1. Clone the repository:

   git clone https://github.com/m9e/cllm.git
   cd cllm

2. Install using pipx (recommended):

   pipx install .

   Or install with pip:

   pip install .

   For development:

   pip install -e .

Dependencies are managed through pyproject.toml and will be automatically installed.

Quickstart

To get started with cllm:

1. Clone the repository:

   git clone https://github.com/m9e/cllm.git
   cd cllm
   

2. Run the installation script:

   sudo ./install_cllm.sh
   

3. Set up your Azure OpenAI credentials:

   export AZURE_OPENAI_API_KEY=your_api_key_here
   export AZURE_OPENAI_ENDPOINT=your_azure_endpoint_here
   

4. You can now use the cllm command from anywhere on your system.

GPT o1 notes

For the o1 openai models:

• no system prompt is allowed
• we assume o1 if model name contains "o1" anywhere
• we swap max_tokens -> max_completion_tokens; param is the same
• update openai package (pip install -U openai) if you get an error about max_completion_tokens

Usage

See examples in Notebook form

Note: To run the example notebook, you'll need additional dependencies:

pip install jupyter

Or with conda:

conda install jupyter

Configuration

CLLM uses standard .env files for configuration. It will look for credentials in the following order:

1. .env file in the current directory
2. .env in parent directories (searching upwards)
3. ~/.env (global fallback)

Create a .env file with your Azure OpenAI credentials:

AZURE_OPENAI_API_KEY=your_api_key_here
AZURE_OPENAI_ENDPOINT=your_azure_endpoint_here

Getting Your Azure OpenAI Credentials

1. Go to the Azure Portal
2. Navigate to your Azure OpenAI resource
3. Find your API key:
   • Go to "Keys and Endpoint" in the left menu
   • Copy either "KEY 1" or "KEY 2"
4. Find your endpoint:
   • It will look like: https://<your-resource-name>.openai.azure.com/

Security Notes

• Never commit .env files to version control
• Add .env to your .gitignore
• Consider using a secrets manager for production environments
• Rotate your API keys periodically
• Use the minimum required permissions for your Azure OpenAI resource

Roadmap/TODO

• [] Test/fix the extend-prompt/summarizer functions
• [] Fix progress bar stuff

Immediate Improvement ideas

• [] Leverage non-OpenAI APIs
• [] File-In-File-Out (eg, input.txt -> input.txt.llm, input2.txt -> input2.txt.llm or something)
• [] Add some examples and add DSPy to "compile" prompts for flexibility?
• [] Allow user to pass more params to endpoint (eg, temperature)
• [] Allow user to specify certain params like BASE_URL via env vars (eg CLLM_BASE_URL)

mikoshi:cllm matt$ cllm -h
usage: cllm [-h] [-d DIRECTORY] [-p PROMPT] [-c CONTEXT_LENGTH] [-s SUMMARY] [-m MODEL] [--system SYSTEM] [-f FILTER] [--stats] [-v] [-e EXTENSIONS]
            [-l LIMIT] [-B BASE_URL] [--expand-prompt EXPAND_PROMPT] [-x] [-S] [-o OVERLAP] [-b] [--send-empty] [--tc] [-n MAX_INFERENCE_CALLS]
            [-I [INPUT ...]]
            ...

Composable command-line interactions with LLM APIs

positional arguments:
  inline_prompt         Unmatched arguments to be used as the prompt if -p is not provided

options:
  -h, --help            show this help message and exit
  -d DIRECTORY, --directory DIRECTORY
                        Directory to process
  -p PROMPT, --prompt PROMPT
                        User prompt
  -c CONTEXT_LENGTH, --context-length CONTEXT_LENGTH
                        Context length for splitting files/input
  -s SUMMARY, --summary SUMMARY
                        Summary prompt
  -m MODEL, --model MODEL
                        Model name
  --system SYSTEM       System message
  -f FILTER, --filter FILTER
                        Filter files by string in path
  --stats               Print statistics
  -v, --verbose         Print raw request, response, params to stderr
  -e EXTENSIONS, --extensions EXTENSIONS
                        Comma-separated list of file extensions to process
  -l LIMIT, --limit LIMIT
                        Limit output tokens
  -B BASE_URL, --base-url BASE_URL
                        (Optional) Base URL for OpenAI-compatible API, defaults to the standard OpenAI API endpoint
  --expand-prompt EXPAND_PROMPT
                        Prompt for prompt expansion, passed without the input to let the LLM craft a better prompt
  -x                    Expand the user prompt by pre-processing it with an LLM to try optimizing the result
  -S, --single-string-stdin
                        Treat all stdin as a single string instead of prompting with each line
  -o OVERLAP, --overlap OVERLAP
                        Number of bytes to include before the split if the chunk is larger than the context
  -b, --progress-bar    Display a progress bar based on the total bytes of the files processed
  --send-empty          Send empty lines with as empty context with the prompt instead of just emitting them back to stdout; no effect if -S is set
  --tc                  Token count mode: count tokens instead of processing prompts
  -n MAX_INFERENCE_CALLS, --max-inference-calls MAX_INFERENCE_CALLS
                        Maximum number of API calls to make
  -I [INPUT ...], --input [INPUT ...]
                        Input argument; usually read from stdin or provided as additional arguments