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https://github.com/paulrobello/par_gpt
CLI LLM tool
https://github.com/paulrobello/par_gpt
Last synced: about 2 months ago
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CLI LLM tool
- Host: GitHub
- URL: https://github.com/paulrobello/par_gpt
- Owner: paulrobello
- License: mit
- Created: 2024-11-04T22:11:44.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2024-12-04T23:24:27.000Z (about 2 months ago)
- Last Synced: 2024-12-05T00:24:56.644Z (about 2 months ago)
- Language: Python
- Size: 1020 KB
- Stars: 3
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# PAR GPT
## Description
A flexible command-line interface for interacting with various AI language models, supporting multiple providers and
customizable output formats.
**NOTE: This is a very work in progress project and may break at any time.**
## Features
* Can be run in basic LLM mode or agent mode that can use tools
* Shows pricing info when requested
* Support for multiple AI providers (OpenAI, Anthropic, Groq, Google, Ollama, Bedrock)
* Support for custom output formats Markdown, CSV, etc.
* Support for custom context sources stdin, file, url, and web search
## Technology
- Python 3.11+
- Rich for terminal output
- Typer for CLI interface
- Support for multiple AI providers (OpenAI, Ollama, Bedrock)
## Prerequisites
- Python 3.11 or higher
- UV package manager
- API keys for chosen AI provider (except for Ollama)
- OpenAI: Set OPENAI_API_KEY environment variable
- Other providers: See provider-specific documentation
## Installation
### Source
```shell
git clone https://github.com/paulrobello/par_gpt.git
cd par_gpt
uv tool install .
```
### GitHub
```shell
uv tool install git+https://github.com/paulrobello/par_gpt
```
## Update
### Source
```shell
cd par_gpt
git pull
uv tool install . -U --force
```
### GitHub
```shell
uv tool install -U --force git+https://github.com/paulrobello/par_gpt
```
## Usage
```shell
par_gpt [OPTIONS]
```
### CLI Options
```
--ai-provider -a [Ollama|OpenAI|Groq|Anthropic|Google|Bedrock|Github] AI provider to use for processing [default: OpenAI]
--model -m TEXT AI model to use for processing. If not specified, a default model will be used. [default: None]
--light-model -l Use a light model for processing. If not specified, a default model will be used.
--ai-base-url -b TEXT Override the base URL for the AI provider. [default: None]
--temperature -t FLOAT Temperature to use for processing. If not specified, a default temperature will be used. [default: 0.5]
--user-agent-appid -U TEXT Extra data to include in the User-Agent header for the AI provider. [default: None]
--pricing -p Enable pricing summary display
--display-output -d [none|plain|md|csv|json] Display output in terminal (none, plain, md, csv, or json) [default: md]
--context-location -f TEXT Location of context to use for processing. [default: None]
--system-prompt -s TEXT System prompt to use for processing. If not specified, a default system prompt will be used. [default: None]
--user-prompt -u TEXT User prompt to use for processing. If not specified, a default user prompt will be used. [default: None]
--agent-mode -g Enable agent mode.
--max-iterations -i INTEGER Maximum number of iterations to run when in agent mode. [default: 5]
--debug Enable debug mode [default: False]
--show-config Show config [default: False]
--yes-to-all -y Yes to all prompts [default: False]
--no-repl Disable use of REPL tool. [default: False]
--copy-to-clipboard Copy output to clipboard
--copy-from-clipboard Copy context or context location from clipboard
--version -v
--help Show this message and exit.
```
## Environment Variables
### Create a file ~/.par_gpt.env with the following content adjusted for your needs
```shell
# AI Providers
OPENAI_API_KEY=
ANTHROPIC_API_KEY=
GROQ_API_KEY=
GITHUB_TOKEN=
GOOGLE_API_KEY=
# Search
GOOGLE_CSE_ID=
GOOGLE_CSE_API_KEY=
TAVILY_API_KEY=
# Weather
WEATHERAPI_KEY=
### Tracing (optional)
LANGCHAIN_TRACING_V2=false
LANGCHAIN_ENDPOINT=https://api.smith.langchain.com
LANGCHAIN_API_KEY=
LANGCHAIN_PROJECT=par_gpt
# Application Options
PARGPT_AI_PROVIDER=OpenAI
PARGPT_MODEL=# if blank, strong model default will be used
PARGPT_PRICING=price
PARGPT_DISPLAY_OUTPUT=md
PARGPT_DEBUG=false
PARGPT_SHOW_CONFIG=false
PARGPT_AGENT_MODE=false
PARGPT_NO_REPL=false
PARGPT_MAX_ITERATIONS=5
PARGPT_YES_TO_ALL=false
```
* GROQ_API_KEY is required for Groq. Get a free key from https://console.groq.com/
* ANTHROPIC_API_KEY is required for Anthropic. Get a key from https://console.anthropic.com/
* OPENAI_API_KEY is required for OpenAI. Get a key from https://platform.openai.com/account/api-keys
* GITHUB_TOKEN is required for GitHub Models. Get a free key from https://github.com/marketplace/models
* GOOGLE_API_KEY is required for Google Models. Get a free key from https://console.cloud.google.com
* LANGCHAIN_API_KEY is required for Langchain Langsmith tracing. Get a free key from https://smith.langchain.com/settings
* AWS_PROFILE is used for Bedrock authentication. The environment must already be authenticated with AWS.
* No key required to use with Ollama models.
* TAVILY_API_KEY is required for Tavily AI search. Get a free key from https://tavily.com/. Tavily is much better than google and is the recommended search provider.
* GOOGLE_CSE_ID and GOOGLE_CSE_API_KEY are required for Google search.
* WEATHERAPI_KEY is required for weather. Get a free key from https://www.weatherapi.com/
## Agent mode
NOTE: Agent mode enables tool use one of which is a Python code REPL which allows the AI to write and execute code on your system.
If the REPL tool is used it will prompt you before executing the code. Unless you specify --yes-to-all.
## Example Usage
```shell
# Basic usage with stdin
echo "What is Python?" | par_gpt
# Use a the light model with custom temperature
par_gpt --light-model -t 0.7 "Explain quantum computing"
# Use Ollama with local models Note: you must have qwen2:latest pulled
par_gpt -a ollama -m qwen2:latest "Write a haiku"
# get 3d printer filament grade and properties from youtube then generate a sorted table and save to Obsidian vault.
# this example uses other commands that may not be available on your system however does showcase can it can be chainable
par_yt2text --transcript 'https://www.youtube.com/watch?v=weeG9yOp3i4' | \
par_gpt -p "use the transcript in the context and create a markdown table with 3 columns 'filament_name', 'properties' and 'grade' generate the table based on the feedback from the transcript" | \
par_gpt "sort the table by grade in the following order S,A,B,C,F" | \
save_vault fillament_grade_props
# get commit message for current changes
par_gpt 'display commit message for current changes'
# commit current changes with automatically generated commit message also show config and pricing
par_gpt --show-config --pricing 'commit current changes'
# copy commit message for current changes to clipboard using agent mode
par_gpt -t 0 --debug -g 'create a commit messages that would be relevant to the changes in the current repository and copy to clipboard'
# get details for new Macbook M4 Max (this will use web search and web scrape tools)
par_gpt -g 'get me the details for the new Macbook M4 Max'
# generate a csv file named data.csv filled with fake names and ages
par_gpt -g 'generate a csv file named data.csv filled with fake names and ages'
# read csv file named data.csv and generate a PNG format image graph with age on the x axis and count of age on y axis. open the PNG in a browser
par_gpt -g 'read csv file named data.csv and generate a PNG format image graph with age on the x axis and count of age on y axis. open the PNG in a browser'
# read csv file named data.csv and generate a graph with age on the x axis and count of age on y axis. display the image in the terminal
par_gpt -g 'read csv file named data.csv and generate a graph.png graph with age on the x axis and count of age on y axis. display the image in the terminal size large'
# display the current weather in Woodland CA
par_gpt -g 'current weather in Woodland CA and display the current conditions image / icon in the terminal'
par_gpt --pricing --debug -g -a OpenAI -d md 'what is the value of 4 times the ArcTangent of 1'
# tell me a joke using github model on azure
par_gpt --show-config --debug -p -a Github -m "Llama-3.2-90B-Vision-Instruct" "tell me a joke"
par_gpt --show-config --debug -p -a Github -m "gpt-4o" "tell me a joke"
# Groq vision model
par_gpt -a Groq -m 'llama-3.2-90b-vision-preview' -f PATH_TO_IMAGE "describe this image"
# get image from url and answer question
par_gpt -f "https://gratisography.com/wp-content/uploads/2024/10/gratisography-birthday-dog-sunglasses-1036x780.jpg" "describe the image"
# Get context from url and answer question about it. Note does not currently use RAG so can be token heavy
par_gpt --pricing -c url -f 'https://console.groq.com/docs/vision' "what model ids support vision"
# get image from url and answer question
par_gpt --pricing -c url -f 'https://freerangestock.com/sample/157314/mystical-glowing-mushrooms-in-a-magical-forest.jpg' "describe this image"
```
## What's New
- Version 0.2.1:
- Removed --context-source cli option as it is now auto-detected
- When working with images and model is not specified a suitable vision model will be selected
- added options to copy context from clipboard and results to clipboard
- Version 0.2.0:
- Added confirmation prompt for agent mode REPL tool
- Added yes-to-all flag to skip confirmation prompts
- Updated pricing data
- Version 0.1.0:
- Initial release
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request. Before contributing:
1. Ensure you have Python 3.11+
2. Use UV for dependency management
3. Follow the existing code style
4. Update documentation as needed
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Author
Paul Robello - [email protected]
GitHub: paulrobello